The Science of Rugby [2 ed.] 9780367492137, 9780367492113, 9781003045052

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THE SCIENCE OF RUGBY

Coaches, practitioners and medical staff working in the worldwide sport of rugby will frequently apply scientific principles to their programmes to inform the practice, performance, health, well-being and development of their athletes. This book explores the scientific principles underpinning the preparation and management of rugby players in both codes and modified versions of the sport. Applied examples are also provided throughout to understand the practical application of the material in a real-world context. This new edition of The Science of Rugby offers a significant contribution to the field of rugby science that will act as a useful resource to scientists, coaches, practitioners and students interested in rugby. New chapters and key topics include: • • • • • • • •

Physical and psychological preparation for rugby Planning and monitoring of training Managing fatigue, recovery and nutrition Effects of different environmental conditions and travel on performance The mechanics of rugby techniques and injury Young players and talent identification Considerations for training the female rugby player Modified rugby, including rugby sevens, touch, tag and wheelchair rugby

No other book bridges the gap between theory and applied practice in rugby, from grass roots to elite international standard, and therefore this is essential reading for any student, researcher, sport scientist, coach, physiotherapist or clinician with an interest in the game.

Craig Twist is Professor of Applied Sport & Exercise Science at Liverpool John Moores University, UK, and has primary research interests in the training and monitoring of rugby players. Craig is an accredited Sport and Exercise Scientist with the British Association of Sport and Exercise Sciences. Paul Worsfold is Head of Biomechanics at the UK Sports Institute and Professor in Sports Biomechanics and Performance Analysis at the University of Chester, UK. His applied and research interests are primarily focused on optimising athlete movement and technology to enhance performance and reduce injury.

THE SCIENCE OF RUGBY Second Edition

Edited by Craig Twist and Paul Worsfold

Designed cover image: peepo / Getty Images Second edition published 2023 by Routledge 605 Third Avenue, New York, NY 10158 and by Routledge 4 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN Routledge is an imprint of the Taylor & Francis Group, an informa business © 2023 Taylor & Francis The right of Craig Twist and Paul Worsfold to be identified as the authors of the editorial material, and of the authors for their individual chapters, has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification and explanation without intent to infringe. [First edition published by Routledge 2015] ISBN: 978-0-367-49213-7 (hbk) ISBN: 978-0-367-49211-3 (pbk) ISBN: 978-1-003-04505-2 (ebk) DOI: 10.4324/9781003045052 Typeset in Bembo by MPS Limited, Dehradun

For Alfie, Harry and Suzy. I love you all so very much. Craig Twist

To my family, for your continued love and support. Paul Worsfold

CONTENTS

List of Figures List of Tables About the Editors List of Contributors

x xii xiv xv

Introduction Craig Twist and Paul Worsfold

1

1 Physical Preparation for Rugby Tim J. Gabbett

2

2 Strength and Power Training for Rugby Daniel Travis McMaster, Michael R. McGuigan, and Nicholas D. Gill

15

3 Monitoring the Match and Training Demands of Rugby Mark Waldron, Erwan Izri, and Craig Twist

29

4 Monitoring Fatigue and Training Adaptations in Rugby Players Craig Twist and Jamie Highton

47

viii Contents

5 Match Day Strategies to Enhance the Physical and Technical Performance of Rugby Players Mark Russell, Samuel P. Hills, Christian J. Cook, and Liam P. Kilduff 6 Strategies to Enhance Recovery in Rugby Players Jamie Highton and Craig Twist 7 Nutrition for Rugby Graeme L. Close, Andreas M. Kasper, and James P. Morton

68

83

101

8 Training and Playing in the Heat: Strategies for the Rugby Player Rudi Meir, Neil Chapman, and Mike Climstein

126

9 Practical Considerations for Team Travel, the Lifestyle of Elite Athletes, Travel Fatigue, Infection and Coping with Jet Lag Ben J. Edwards, Tom Clark, Anna C. Fitzpatrick, Colin M. Robertson, and Neil P. Walsh

140

10 Psychological Preparation for Rugby Stephen D. Mellalieu and Rich Neil

159

11 Performance Analysis in Rugby Nimai Parmar, Nic James, and Wilbur Kraak

173

12 The Biomechanics of Rugby Neil E. Bezodis, Ezio Preatoni, Dario Cazzola, and Elena Seminati

186

13 Injury Epidemiology in Rugby Niki Gabb, Grant Trewartha, and Keith Stokes

207

14 Talent Identification, Development, and The Young Rugby Player Stephen Cobley and Kevin Till

222

Contents

ix

15 The Female Rugby Player Emma Ross

239

16 Modified Rugby Craig Twist

258

Index

275

FIGURES

1.1 Influence of physical qualities on rugby performance 2.1 Force-power-velocity continuum. (McMaster 2012, with permission.) 4.1 Factors influencing fatigue and recovery of players during and after rugby-related activity 5.1 A timeline profiling the typical practices used on match day by professional rugby players 5.2 Theoretical timeline of interventions for use on match day 7.1 Potential CHO periodisation strategy for a rugby player 7.2 Theoretical timeline of protein intake throughout the day for a 120 kg rugby player trying to achieve 2 g·kg-1 body mass per day of protein, performing resistance training in the morning and a field-based rugby session post lunch 8.1 Avenues of heat exchange for the rugby player 9.1 Mean circadian changes in core (rectal) temperature measured hourly in 8 subjects: living normally and sleeping from 24:00 to 08:00 h (solid line); and then woken at 04:00 h and spending the next 24 h on a “constant routine” (dashed line). (Based on Reilly et al., 1997.) 9.2 Circadian rhythm of rectal temperature with a cosine curve superimposed on 24 h of raw data 9.3 Schematic representation of advancing the circadian rhythm of rectal temperature by 10 h or delaying it by 14 h after an eastward flight across 10 time zones. Shading indicates night time 11.1 Example standardised performance profiles of opposing rugby league teams, based on their previous five matches, according

11 23 49 69 77 106

109 128

144 149

150

Figures

11.2 12.1 12.2 12.3 13.1 13.2 13.3 14.1 14.2

14.3

14.4

15.1

to score margin (defined as unbalanced when the team won or lost by more than 12 points (two tries) or balanced when less than 12 points) An example momentum graph of opposing rugby union teams from a competitive match Peak compression force at engagement A summary of the differences in key biomechanical features between tackle types A summary of the key biomechanical features associated with successful rugby place kicking performance Injury incidence by body region for men’s elite rugby Injury proportion by body region for community standard men’s rugby Comparison of the range of incidence rates recorded across the rugby playing population The biological and chronological age mismatch: maturity bias Relative age distribution of junior rugby league players (i.e., Under 13–15s combined) according to generic TID system stages. (Data from Till et al. (2010b) with permission.) Percentage change in anthropometric and fitness indices across a 2-year period according to maturity status in young rugby league players. (Data redrawn from Till et al., 2013.) Effect size changes and coefficient of variation (CV) in physical indices over a 4-year period in academy rugby league players. (Data redrawn from Till et al., 2015.) A typical menstrual cycle, showing fluctuations of oestrogen and progesterone, and the four points where hormone concentrations, and/or ratio of oestrogen and progesterone are distinctly different. (Published with permission from The WellHQ.)

xi

177 180 189 192 195 210 213 218 228

230

231

233

246

TABLES

1.1 Physiological and anthropometric qualities of high-performance rugby league players selected to start the first National Rugby League (NRL) game (i.e., professional ‘starters’), interchange players (i.e., professional ‘non-starters’), and those not selected (semi-professional players). (Data from Gabbett et al., 2011d.) 2.1 Dose-response guidelines for strength and power development in rugby code athletes (see McMaster et al., 2013b) 4.1 Typical tests for assessing the physical qualities of rugby players 4.2 An overview of tools for measuring fatigue and recovery status in rugby players 6.1 Types of cryotherapy used to enhance recovery of performance 7.1 Likely daily CHO requirements for rugby players during a typical week 7.2 Summary of the major non-prohibited supplements used by athletes 8.1 Strategies to assist players when training and playing in warm/ hot and humid environments 9.1 Circadian variation in various performance measures in males 9.2 Is there an optimal timing of performance after three-time-zone travel eastwards or westwards? 9.3 Recommendation for the use of bright light to adjust the body clock after time-zone transitions 9.4 Comments and considerations related to performance, timing of training and roles of naps and habit in time of training 9.5 Ten recommendations to avoid infection and maintain immune health in athletes (adapted from Walsh 2018) 13.1 Incidence and severity in community rugby literature

8 21 56 59 87 104 116 131 144 145 152 153 154 212

Tables xiii

13.2 13.3 14.1 15.1 16.1

Injury incidence in youth rugby Injury incidence and injury severity in women’s rugby A summary of England Rugby Union’s TID system Anthropometric characteristics of female rugby players Physical qualities of male and female representative sevens, touch and tag players. Values are mean ± SD 16.2 Summary of movement variables during a typical match quarter for national men’s wheelchair players. Values are mean ± SD

214 216 225 241 261 268

ABOUT THE EDITORS

Craig Twist is Professor of Applied Sport & Exercise Science at Liverpool John Moores University and has primary research interests in the training and monitoring of rugby players. Craig is an accredited Sport and Exercise Scientist with the British Association of Sport and Exercise Sciences. Paul Worsfold is Head of Biomechanics at the UK Sports Institute and Professor in Sports Biomechanics and Performance Analysis at the University of Chester, UK. His applied and research interests are primarily focused on optimising athlete movement and technology to enhance performance and reduce injury.

CONTRIBUTORS

Neil E. Bezodis, School of Engineering and Applied Sciences, Swansea University,

Swansea, UK. Dario Cazzola, Department for Health, University of Bath, UK. Neil Chapman, Faculty of Health, Sport and Exercise Science, Southern Cross

University, Australia; Faculty of Health Sciences and Medicine, Sport and Exercise Science, Bond University, Australia. Tom Clark, School of Sport and Exercise Sciences, Liverpool John Moores

University, UK. Mike Climstein, Faculty of Health, Sport and Exercise Science, Southern Cross

University, Australia. Graeme L. Close, School of Sport and Exercise Sciences, Liverpool John Moores

University, UK. Stephen Cobley, Faculty of Health Sciences, University of Sydney, Australia Christian J. Cook, School of Science and Technology, University of New

England, Australia. Ben J. Edwards, School of Sport and Exercise Sciences, Liverpool John Moores

University, UK. Anna C. Fitzpatrick, School of Health and Sport Sciences, University of Central

Lancashire, UK. Niki Gabb, Department for Health, University of Bath, UK. Tim J. Gabbett, Gabbett Performance, Australia.

xvi Contributors

Nicholas D. Gill, New Zealand Rugby Union, New Zealand, Sports Performance

Research Institute New Zealand (SPRINZ), Auckland University of Technology, New Zealand. Jamie Highton, Department of Sport and Exercise Sciences, University of

Chester, UK. Samuel Hills, Faculty of Science and Technology, Bournemouth University. Erwan Izri, School of Engineering and Applied Sciences, Swansea University,

Swansea, UK. Nic James, School of Science and Technology, Middlesex University, UK. Andreas M. Kasper, School of Sport and Exercise Sciences, Liverpool John

Moores University, UK. Liam P. Kilduff, School of Engineering and Applied Sciences, Swansea University,

Swansea, UK. Wilbur Kraak, Department of Sport Science, Stellenbosch University, Cape

Town, South Africa. Michael R. McGuigan, Sports Performance Research Institute New Zealand

(SPRINZ), Auckland University of Technology, New Zealand. Daniel T. McMaster, School of Health, Sport and Human Performance, The

University of Waikato, New Zealand. Rudi Meir, Faculty of Health, Sport and Exercise Science, Southern Cross

University, Australia. Stephen D. Mellieu, Cardiff School of Sport and Health Sciences, Cardiff, UK. James P. Morton, School of Sport and Exercise Sciences, Liverpool John Moores

University, UK. Rich Neil, Cardiff School of Sport and Health Sciences, Cardiff, UK. Nimai Parmar, School of Science and Technology, Middlesex University, UK. Ezio Preatoni, Department for Health, University of Bath, UK. Colin Robertson, Engineering, Sports and Sciences Academic Group, University

of Bolton, UK. Emma Ross, The WellHQ Mark Russell, School of Sport and Wellbeing, Leeds Trinity University, UK. Elena Seminati, Department for Health, University of Bath, UK. Keith Stokes, Department for Health, University of Bath, UK.

Contributors

xvii

Kevin Till, Institute for Sport, Physical Activity and Leisure, Leeds Beckett

University, UK. Grant Trewartha, Department for Health, University of Bath, UK. Craig Twist, School of Sport and Exercise Sciences, Liverpool John Moores

University, UK. Mark Waldron, School of Engineering and Applied Sciences, Swansea University,

Swansea, UK. Neil Walsh, School of Sport and Exercise Sciences, Liverpool John Moores

University, UK.

INTRODUCTION Craig Twist and Paul Worsfold

The application of science by coaches, practitioners and medical staff is now commonplace in most worldwide rugby programmes. Indeed, rugby science continues to be an evolving field of research that is used to inform the practice, performance, health, well-being and development of rugby players and coaches at all standards. This book examines the scientific principles underpinning the preparation and management of male and female rugby players in rugby union, league and modified versions of the game (e.g., sevens, touch, tag, wheelchair). The intention is to offer a contribution to the field of rugby science that will act as a useful resource to scientists, coaches, practitioners and students interested in rugby. Key topics include: • • • • • • •

Physical and psychological preparation for rugby Monitoring of rugby training and competition Managing fatigue, recovery and nutrition for rugby players Effects of environmental conditions and travel on rugby players’ performance and health The mechanics of rugby techniques and injury Young rugby players and talent identification The female rugby player

DOI: 10.4324/9781003045052-1

1 PHYSICAL PREPARATION FOR RUGBY Tim J. Gabbett

1.1 Introduction Rugby union and rugby league are two collision sports played worldwide. Although the sports are different in rules, history, and ‘culture’, the two codes share commonalities (e.g., running, carrying, and passing a football, highintensity collisions, tackling, wrestling, and grappling). Like most high-intensity, intermittent team sports, the rugby codes (i.e., rugby league and rugby union) are characterised by frequent bouts of high-intensity exercise (e.g., accelerations, decelerations, striding, and sprinting). However, the physical demands are unique in that rugby also requires players to regularly participate in collisions, tackling, wrestling, and grappling. These high-intensity activities are separated by periods of lower intensity activity (e.g., standing, walking, and jogging). During match-play, players will cover ~68 (rugby union) (Cahill et al., 2013) to ~100 m·min−1 (rugby league) (Austin & Kelly, 2014; Gabbett et al., 2012a; Waldron et al., 2011). Although these movement demands are considerably lower than that reported for Australian football (129 m·min−1) and soccer (104 m·min−1) (Varley et al., 2014), the demands of rugby are significantly increased through the large frequency of collisions and players are required to perform throughout a match. Indeed, rugby league players engage in a greater number of accelerations and collisions, and a greater frequency of repeated high-intensity effort bouts (involving sprinting and collisions) than both Australian football and soccer players (Varley et al., 2014). A critical component of strength and conditioning programmes is training players to perform these high-intensity movements and collisions, while also rapidly recovering from these activities. This chapter focuses primarily on the demands and physical preparation for male adult players. For movement characteristics and training of female and

DOI: 10.4324/9781003045052-2

Physical Preparation for Rugby

3

modified rugby players (e.g., sevens, touch, tag, and wheelchair), the reader is directed to Chapter 15 and Chapter 16, respectively.

1.2 Movement demands of rugby 1.2.1 Overall physical demands Early time-motion analyses of rugby union and rugby league match-play involved tracking of players using video technology (Duthie et al., 2005; Meir et al., 1993). Due to the time-intensive nature of coding activities performed, these studies relied on small sample sizes. Despite their limitations, these early studies provided important information for coaches and strength and conditioning staff on the physical demands of the rugby codes. A summary of these demands in male players includes the following. • • • •

Players covered approximately 6,500 m to 7,900 m during match-play, depending on playing position (Meir et al., 1993). The majority (88–95%) of time was spent in low-intensity activities (e.g., standing, walking, and jogging). Approximately 2.2–3.6% of time was spent in striding and sprinting activities (Duthie et al., 2005). High-intensity activities that included a combination of striding, sprinting, tackling, rucking/mauling, and static efforts were reported to account for 11.9%, 13.7%, 5.9%, and 4.1% of total match-play for front row, back row, inside backs, and outside backs, respectively (Duthie et al., 2005).

The introduction of wearable microtechnology (including global positioning system and inertial measurement sensor technology) has permitted practitioners to quantify both the locomotor (Cahill et al., 2013; Waldron et al., 2011) and collision (Hulin et al., 2017; Hulin & Gabbett, 2015) demands of match-play. Consequently, much data now exists on the physical demands of both rugby codes, providing strength and conditioning staff the opportunity to develop highly specific training programmes. Differences in movement demands have been reported between forwards and backs in international rugby union players, with front row (5,158 m; 62.3 m·min−1), second row (5,755 m; 64.7 m·min−1), and back row (6,038 m; 65.3 m·min−1) positions covering considerably less distance than the scrum half (7,098 m; 78.5 m·min−1), inside backs (6,545 m; 71.4 m·min−1), and outside backs (6,276 m; 66.9 m·min−1) positions (Cahill et al., 2013). Early studies reported no difference between hit-up forwards (3,569 m; 94 m·min−1), wide-running forwards (5,561 m; 96 m·min-1), adjustables (6,411 m; 101 m·min−1), and outside backs (6,819 m; 93 m·min−1) for the relative amount of distance covered in elite rugby league players (Gabbett et al., 2012a). However, the amount of high-speed running has been shown to differ between hit-up forwards (235 m; 6.2 m·min−1), wide-running forwards (418 m; 7.2 m·min−1),

4 Tim J. Gabbett

adjustables (436 m; 6.9 m·min−1), and outside backs (583 m; 8.0 m·min−1) (Gabbett et al., 2012a). In a meta-analysis of the demands of professional rugby league match-play, Glassbrook et al. (2019) reported no differences among forwards, adjustables, and backs when low-speed and high-speed distances were expressed relative to playing time.

1.2.2 Repeated-sprint, repeated high-intensity effort, collision, and peak movement demands Repeated-sprints, with short recovery between efforts, occur infrequently during competition (Gabbett, 2012b). On average, players performed one repeated-sprint bout (defined as three or more sprints with less than 21 s between sprints; Spencer et al., 2004) during match-play. While these findings suggest that repeated sprinting may be of low importance to rugby league physical performance, repeated-sprint training should still form part of the physical training programmes for rugby players. Indeed, it is likely that some repeated-sprint training might assist players to perform the high-speed running demands of match-play. The hit-up forwards and wide-running forwards perform a greater absolute amount of moderate and heavy collisions than the adjustables and outside backs and are consequently engaged in significantly more collisions per minute of match-play (Gabbett et al., 2011b; Gabbett et al., 2012a; Gissane et al., 2001a, 2001b). Hit-up forwards and wide-running forwards are involved in a collision approximately every minute, while the adjustables and outside backs are involved in a collision approximately every 2 min (Gabbett et al., 2012a). Hit-up forwards, wide-running forwards, adjustables, and outside backs perform a heavy collision every 2.5, 3.3, 5, and 5 min, respectively (Gabbett et al., 2012a). The repeated high-intensity effort demands of rugby match-play have also been investigated (Austin et al., 2011; Gabbett et al., 2012a) and are defined as ≥3 high speed, high acceleration, or contact efforts with less than 21 s between efforts (Gabbett et al., 2012a). While there are no differences among playing positions for the absolute number of repeated high-intensity effort bouts performed in a match, the hit-up forwards and wide-running forwards perform more repeated highintensity effort bouts per minute of match-play. Hit-up forwards complete on average, one repeated high-intensity effort bout every 4.8 min, while the widerunning forwards perform on average, one repeated high-intensity effort bout every 6.3 min. Conversely, repeated high-intensity effort bouts occur on average every 7.7 and 9.1 min for the adjustables and outside backs, respectively (Gabbett et al., 2012a). These repeated high-intensity effort bouts occur more frequently when defending the team’s own try-line and the opposition’s 30 m zone, as well as attacking the opposition’s try-line (Gabbett et al., 2014). Collisions and tackles are acknowledged as the most demanding aspect of rugby league match-play (Brewer & Davis, 1995). In addition, research from our laboratory has recently shown that repeated high-intensity effort exercise (sprinting and tackling) is associated with greater heart rate and perceived exertion and poorer sprint performance than

Physical Preparation for Rugby

5

repeated-sprint exercise alone (Johnston & Gabbett, 2011), demonstrating that the addition of tackling significantly increases the physiological response to repeatedsprint exercise and has the potential to reduce physical performance. These findings, coupled with the repeated high-intensity effort demands, suggest that repeated sprinting and physical collisions are necessary to adequately prepare hitup forwards for the demands of competition (Gabbett et al., 2010), while repeated high-speed sprinting is critical for outside backs (Gabbett, 2012). In rugby union, forwards are involved in 11–22 tackles per match compared to 10–16 for backs (Quarrie et al., 2013) and spend approximately three and half times longer in contact situations compared to inside (fly half and scrum half) and outside (wing, centre, and fullback) backs (Austin et al., 2011; Quarrie et al., 2013). Austin et al. (2011) have also reported that work to rest ratios are lower for forwards (~1:4) compared to inside (1:5) and outside backs (1:6). In a study of Super 14 rugby union competition, Austin et al. (2011) defined a repeated high-intensity effort bout as ≥3 sprints, and/or tackles, and/or scrum/ruck/maul activities within 21 s during the same passage of play. The number of repeated high-intensity effort bouts for front row forwards, back row forwards, inside backs, and outside backs was 15, 17, 16, and 7, respectively. The average duration of these repeated highintensity effort bouts was 45 to 52 s for forwards and 26 to 28 s for backs, although the individual longest repeated high-intensity effort bout for front row forwards (118 s), back row forwards (165 s), inside backs (64 s), and outside backs (53 s) was considerably greater. The shortest recovery duration between repeated highintensity effort bouts was 64, 25, 26, and 44 s for front row forwards, back row forwards, inside backs, and outside backs, respectively. Collectively, the findings of Austin et al. (2011) and (Gabbett et al. (2012a) demonstrate the extreme physical demands placed on rugby players, suggesting that training for the average demands of match-play will result in players being under-prepared for the most demanding passages of play. Several researchers have quantified the peak running intensities of rugby union (Delaney et al., 2017) and rugby league (Delaney et al., 2015). These studies typically employ a moving-average approach to identify the peak relative distance for a range of durations (typically 1–10 min). As one would expect, as the moving-average period increases, peak running intensity decreases. Depending on playing position, the peak running intensities of international rugby union match-play range from ~150 to 180 m·min−1 (Delaney et al., 2017). Halfbacks (184 m·min−1) and outside backs (175 m·min−1) have greater peak running intensities than the Tight 5 (154 m·min−1) and Loose Forwards (169 m·min−1). Sheppy et al. (2020) reported the peak running intensities of international women’s rugby union to be 154 m·min−1, with backs demonstrating higher peak intensities than forwards (157 m·min−1vs. 150 m·min−1). These peak running intensities include 50 m·min−1 of high-speed running, with backs performing greater volumes of high-speed running than forwards (63 m·min−1vs. 39 m·min−1). The peak running intensity of professional rugby league match-play is 156 m·min−1 (Delaney et al., 2015). Fullbacks were the

6 Tim J. Gabbett

only position that consistently showed higher peak running intensities (172 m·min−1) than other positions (154–161 m·min−1) (Delaney et al., 2015). Others have quantified the influence of collision frequency on peak running intensities (Johnston et al., 2019). The peak running intensities of professional rugby league ranged from (on average) 164 to 171 m·min−1 when no collisions were performed (Johnston et al., 2019). Increasing the duration of the window from 1 to 5 min decreased these running intensities to (on average) 101–116 m·min−1. Increasing the number of collisions performed per minute decreased the running intensities from ~155 (when one collision was performed per minute) to ~123 m·min−1 (when three collisions were performed per minute). Collectively, these findings extend our understanding of the most demanding passages of rugby match-play and can be used by practitioners to develop training drills that prepare players for these critical moments of play.

1.2.3 Activity and recovery cycles of match-play Examination of ball-in-play periods (i.e., match activity cycles) provides insight into the physical demands of rugby competition. The ball-in-play demands have been used by coaches to train the ability of players to compete for long passages of play. Colloquially, long ball-in-play periods might be perceived as an ‘arm wrestle’, as team’s battle for field position, in an attempt to force an error from their opponent. Gabbett (2012a) investigated the ball-in-play periods of senior elite and junior elite matches, coding time when the ball was continuously in play, and any recovery periods that occurred (e.g., for scrums, penalties, line drop-outs, tries, and video referee decisions). The total time the ball was in play was ~55 and ~50 min for senior elite and junior elite matches, respectively. In comparison to junior elite matches, senior elite matches had longer average activity cycles (81.2 ± 16.1 s vs. 72.0 ± 14.7 s). The average longest activity cycle was also higher in senior elite (318.3 ± 65.4 s) than junior elite (288.9 ± 57.5 s) matches. The longest activity cycle from any match was 667 and 701 s for senior elite and junior elite matches, respectively. Senior elite matches had a smaller proportion of short-duration (91–600 s) activity cycles. A novel aspect of this study was the inclusion of activity-recovery ratios. In order to gain an understanding of the longest activity periods and shortest recovery periods, and the potential influence these passages might have on the onset of fatigue and performance, rolling calculations of two sequential activity cycles, and the intervening recovery periods were performed. Using this definition, the activity-recovery ratio was 13:1. A wide range of activity-recovery cycles was found, with values as low as 1:1 and as demanding as 704:1 demonstrating the stochastic nature of professional rugby league. Collectively, these findings suggest that the ability to perform prolonged high-intensity exercise, coupled with the capacity to recover during brief stoppages in play, is a critical requirement of professional rugby league match-play. Furthermore, from a practical perspective, these findings could be used to develop game-specific testing protocols and

Physical Preparation for Rugby

7

training programmes to replicate the most demanding passages expected during professional rugby league competition. The ball-in-play time of professional rugby league competition (~55 min) is considerably greater than that reported for international rugby union, with reports that the ball is in play between 29 and 31 min (Eaves et al., 2005; McLean, 1992) during an 80-min rugby union match. Moreover, the average duration of work periods (81.2 s) and longest ball-in-play period (667 s) in professional rugby league is considerably greater than previously reported for international rugby union (19 and 70 s, respectively; McLean, 1992). The finding of longer ball-in-play periods in rugby league reflects the greater emphasis on stoppages (e.g., penalties, lineouts, and scrums) in rugby union. While similarities clearly exist between the codes, based on the findings from ball-in-play studies, it can be concluded that rugby league and rugby union are fundamentally different games, with markedly different physical demands placed on players. In comparison to matches involving lower standard teams, there was a greater proportion of long-duration (>91 s) and a smaller proportion of short-duration ( 0.91; CV < 4.5%) for assessing these respective capabilities. Strength and conditioning practitioners for rugby most often utilise the bench press, back squat, and clean to assess maximum strength (Argus et al., 2009; Baker & Newton, 2006; Comfort, 2012; Cronin & Hansen, 2005). The required squat depths (i.e., quarter, half, parallel, and full) and knee angles (70 to 110°) vary between investigators/practitioners, which in turn affects the 1RM result (Argus et al., 2009; Blazevich et al., 2002; Harris et al., 2000; McGuigan & Winchester, 2008). The technical requirements of the bench press are more consistent, as a barto-chest depth is generally used, as is required by the International Powerlifting Federation (IPF, 2012) and applied researchers (McGuigan & Winchester, 2008). The isometric mid-thigh pull and squat are also often implemented in the laboratory setting to assess maximum strength. Maximum isometric strength tests are less accessible and therefore less popular than the 1RM as a force measurement system, such as a force plate is required to assess strength qualities, such as peak force (Comfort et al., 2011; West et al., 2011). The isometric squat (90 to 140°) and isometric mid-thigh pull (120 to 145°) knee angles, contraction durations (3–6 s), inter-trial rest intervals (2–5 min), and force plate sampling frequencies (200 to 1000 Hz) vary between investigations (Blazevich et al., 2002; McGuigan & Winchester, 2008; West et al., 2011). These dynamic and isometric strength tests provide a non-specific measurement of rugby-specific strength, but may not

18

Daniel Travis McMaster et al.

necessarily provide a true representation of the required rugby-specific strength qualities (Comfort et al., 2011; Quarrie & Wilson, 2000). Scrummaging and tackling specific force have also been assessed in rugby (Pain et al., 2008; Preatoni et al., 2012; Preatoni et al., 2013; Quarrie & Wilson, 2000; Usman et al., 2010; Wu et al., 2007). Given the methodological differences, comparisons of the same strength measure between applied researchers and strength and conditioners are difficult. Strength and conditioning practitioners need to be aware of the benefits and limitations of the different assessment methodologies currently available, as these can potentially affect the outcome measures.

2.2.2 Power assessments The explosive qualities of rugby players are generally quantified and assessed via position transducer and force plate technologies during explosive squatting, jumping, pulling, pressing, and throwing movements (Argus et al., 2014; Baker et al., 2001b; Harris et al., 2007; McGuigan et al., 2009; McMaster et al., 2016; Nibali et al., 2013). Movement patterns with a flight phase such as jumping and throwing allow the athlete to accelerate throughout the entire range of motion resulting in greater velocity and power outputs than traditional non-ballistic movements (Baker & Newton, 2005; Cronin et al., 2001). Vertical jumps and bench throws have been implemented to create force–velocity–power profiles incorporating a variety of loads for the purpose of assessing and monitor ballistic performance (Argus et al., 2011; Baker, 2013; Bevan et al., 2010). When implementing vertical jump and bench throw profiling protocols, the sports scientist and strength and conditioning coach must carefully consider the measurement system being used (e.g., force plate, position transducer, jump mat, optical sensors, and accelerometer), testing apparatus (bar type [free vs. fixed]), movement patterns (i.e., countermovement, concentric-only, direction of movement, and depth), loading parameters (e.g., single load, incremental loading, absolute load, and relative load), warm-up strategy (e.g., dynamic, static, post-activation potentiation, and motivation), inter-trial rest periods, dependent variables of interest (e.g., displacement, velocity, force, and power), and processing techniques (e.g., sampling frequency, filtering, and smoothing options). A number of different vertical jump and bench throw testing protocols have been implemented to reliably (ICC ≥ 0.83; CV ≤ 8.5%) assess displacement, velocity, force, and power across the various absolute and relative loads using the previously mentioned measurement systems (Argus et al., 2014; Baker et al., 2001a, 2001b; Bevan et al., 2010; Cronin et al., 2004; Hansen et al., 2011a). It is clear that reliable and valid measures of the ballistic capacities of these athletes are important. Current physical performance assessments are utilised to create standards and develop athlete profiles to better inform programming. Athlete performance profiles can be further improved by assessing rugby-specific tasks covering the entire force–velocity–power spectrum such as passing, throwing, and kicking velocities, fending and tackling power outputs, and scrummaging, mauling, and blocking forces. A key purpose of any athlete

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assessment is to obtain insight into the training needs of the athlete. Therefore, all these factors need to be taken into consideration to ensure that any testing that is conducted provides information that can be of practical use and potentially improve the performance of the athletes.

2.3 Normative data 2.3.1 Maximum strength As with any athletic population, there is a wide range of maximal strength values, which is dependent on a number of factors including age, training history, playing position, and physical characteristics. The 1RM bench press, back squat, and power clean in highly trained rugby players can typically range from 110 to 190 kg, 140 to 250 kg, and 100 to 140 kg, respectively (Argus et al., 2014; Argus et al., 2009; Baker & Newton, 2008b; Comfort, 2012; Crewther et al., 2010; Harris et al., 2008a; Kilduff et al., 2007). In rugby union, forwards typically have superior maximum upper- and lower-body strength qualities in comparison to backs due to body mass and increased strength demands of scrummaging, mauling, and tackling from a stationary position (Crewther et al., 2009b). Mean and peak forces of 1400 to 2000 N and 2100 to 3500 N have been reported in rugby players during the isometric back squat and mid-thigh pull, respectively (Comfort et al., 2011; McGuigan & Winchester, 2008; West et al., 2011). The large ranges in maximum dynamic and isometric strength might be because of the various testing methods and large variations in somatotype within and between codes. The heterogeneity of these rugby-football code populations can be offset by normalising maximum strength to body mass and represented as a strength per kilogram of body mass ratio to allow for an unbiased comparison between players (Atkins, 2004; Crewther et al., 2009a; Crewther et al., 2011). Allometric scaling has also been used to consider the body size of individuals (Crewther et al., 2011). The isometric and dynamic strength tests can be used to assess and monitor maximum strength adaptations as well as effectively inform weight-room-specific programming. However, these might not necessarily provide a true representation of the required rugby-specific isometric/dynamic strength qualities (Comfort et al., 2011; Quarrie & Wilson, 2000). Rugby-specific strength tests have been developed to quantify individual tackling capabilities (Usman, 2010) and scrum forces (Quarrie & Wilson, 2000; Wu et al., 2007); however, their diagnostic value to strength and conditioning practice remains inconclusive.

2.3.2 Power capabilities Maximal peak power has been reported across a range of bench throws (20–60% 1RM; 35–70 kg) (Argus et al., 2014; Baker et al., 2001b; Baker & Newton, 2006; Bevan et al., 2010; McMaster et al., 2016) and vertical jump loads (0–45% 1RM) (Argus et al., 2011; Bevan et al., 2010; Cronin et al., 2004), which is dependent on

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the measurement system and the group or individual being assessed. The maximal peak power in highly trained rugby players can range between 800 and 1500 W during the bench throw using relative loads between 20 and 60% 1RM (40–80 kg) (Argus et al., 2014; Baker & Newton, 2008b; Bevan et al., 2010; Crewther et al., 2010; McMaster et al., 2016) and between 5000 and 9000 W during the vertical jump using loads between zero/body mass and 45% 1RM (0–100 kg) (Argus et al., 2011; Baker et al., 2001b; Bevan et al., 2010; Comfort et al., 2011; McGuigan et al., 2009). Large variations in peak power can be attributed to the wide range of physical characteristics between the various rugby position-specific demands. Individual tackling forces from 1400 (non-dominant shoulder) to 2100 N (dominant shoulder) and scrum forces between 1000 and 1700 N have been reported in highly trained rugby union players (Preatoni et al., 2012; Preatoni et al., 2013; Quarrie & Wilson, 2000; Usman, 2010; Wu et al., 2007). It is important for practitioners to establish their own normative data/benchmarks for the group of athletes they are working with due to the large effect of different measurement methods and other factors that can influence the results in any test of power capacities.

2.4 Training applications: development, retention, decay The training volume (dose) required to develop, retain, and decay strength and ballistic/power capabilities can be classified as high, moderate, and low, respectively (Cormie et al., 2011; Cronin & Sleivert, 2005; McMaster et al., 2013). The literature currently recommends that three to five sets of two to six repetitions at 85 to 98% 1RM be prescribed to improve strength, and three to five sets of two to six repetitions at 0 to 60% of 1RM to improve ballistic (power) capacities (Baker & Newton, 2007; Baker & Newton, 2005; McMaster et al., 2013b). Numerous periodised loading schemes, such as linear, non-linear, undulating, conjugate, and block training, have been prescribed to continually develop strength and power over time (Baker, 2001b; Issurin, 2008; Prestes et al., 2009). Strength and power maintenance have been investigated to a lesser extent in rugby, but generally, the intensity and session volume are held constant and the weekly training frequency is reduced by 33 to 66% (Baker, 2001b; Tan, 1999). In rugby, the demands of a match and lengthy competition can have acute and accumulative effects on strength and power (Argus et al., 2009; McLean et al., 2010). This accumulation of fatigue might lead to performance decrements if suitable monitoring methods and recovery modalities are not in place (see Chapter 4). Training programmes have been implemented successfully to prevent decay and even improve strength and power performance throughout the competitive season in elite rugby players (Baker, 2001b). During detraining, the weekly rates of decay in power and strength are of great interest, as they allow practitioners to determine the minimum and maximum durations that training can be ceased before another training stimulus is required. This, in turn, might allow practitioners to periodise training programmes more effectively. A residual effect is the maximum detraining duration in which an athlete

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TABLE 2.1 Dose-response guidelines for strength and power development in rugby code

athletes (see McMaster et al., 2013b) Volume and intensity

Percent increase per session (s)

Quality

MP per session

Sets per MP

Reps

% 1RM 1

5

10

20

Strength Power (force) Power (velocity)

2–5 2–5

3–6 3–6

1–6 2–6

80–100 85–98

0.5 0.1

2.5 0.5

5.0 1.0

10.0 2.0

2–5

3–6

2–6

˗20–60

0.2

1.0

2.0

4.0

MP = movement pattern; Reps = repetitions; % 1RM = percentage of one-repetition maximum utilised.

can retain their strength or power, whereas the decay rate is a measure of the speed at which power and strength are lost over time. It has also been suggested that maximal strength can be retained for up to 30 ± 5 days post-training and that maximal speed can only be retained for 5 ± 3 days post-training (Issurin, 2008). This highlights the need to reconsider current periodisation strategies in the rugby context (Issurin, 2008). Maximal speed and maximal power production utilise similar energy requirements and neuromuscular activation processes (e.g., motor unit recruitment/ firing frequencies); therefore, they should have similar adaptations to detraining. Currently, there is limited research investigating these aspects in elite rugby union players. Table 2.1 shows the proposed dose-response guidelines for power and strength development in contact sports such as rugby.

2.4.1 Maximum strength The dosage required to develop maximal strength is described as high frequency (two to four weekly sessions per muscle group), moderate volume (three to five movement patterns per session [three to six sets of one to six repetitions per movement pattern]), and high intensity (80–100% 1RM) (McMaster et al., 2013b; Peterson et al., 2005). Rugby players that resistance train each muscle group two to three times per week should expect monthly strength increment of 4 to 8% if periodised correctly, although there will be large individual differences (Appleby et al., 2012; Argus et al., 2010; Hansen et al., 2011b; Harris et al., 2000; McMaster et al., 2013). Strength and conditioning researchers and practitioners often implement a range of different hypertrophy, strength, and power loading schemes to increase maximum strength qualities including the conjugate-mixed method (Argus et al., 2010; Harris et al., 2000; Hoffman et al., 2009), stepwise blocks (Stone et al., 1999), linear (Coutts et al., 2007), non-linear (Hoffman et al., 2009), cluster sets (Hansen et al., 2011b), heavy load high force (Harris et al., 2000; Harris et al., 2008b), and power-specific training (Harris et al., 2000; Harris et al., 2008b; McBride et al., 2002). Regardless of the method of periodisation utilised, it appears

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that maximum strength can be improved with as little as 10–20 strength training sessions (Argus et al., 2010; Hansen et al., 2011b). If volume and intensity are constant, then the magnitude of change in strength is dependent on the total number of training sessions (duration × frequency) performed (Tan, 1999). Strength adaptation rates are also dependent on training age and experience because, as these two variables increase, strength adaptation rates diminish (Baker & Newton, 2006; Folland & Williams, 2007; Issurin, 2008; Rhea & Alderman, 2004). The magnitude of strength improvement tends to be greater in weaker less experienced players (Appleby et al., 2012; Baker & Newton, 2008a; Baker, 2013). Longitudinal studies tracking changes in strength in elite rugby players have found moderate improvements during the first 12 months and diminished returns thereafter (Appleby et al., 2012; Baker, 2013; Baker & Newton, 2006). The retention of strength qualities is of great importance for preventing injuries and maintaining consistent performance throughout the season, particularly where the competition periods are lengthy (18 to 24 weeks). Based on the current research, it appears that maximum strength can be maintained with as little as one resistance training session per week if session intensity and volume are maintained (Argus et al., 2009; Hoffman & Kang, 2003). There is little detraining data on elite rugby, but researchers studying other elite athletes and resistance-trained individuals have reported that maximum strength can be maintained for up to 4 weeks with more substantial losses occurring thereafter (Mujika & Padilla, 2001). Strength also plays an important role in increasing ballistic (power) capabilities regardless of somatotype, as stronger athletes often have more developed morphological qualities and potentially greater neuromuscular capacity (Argus et al., 2009; Baker & Newton, 2008b; Cormie et al., 2010; Crewther et al., 2009b).

2.4.2 Power capabilities The required dose to develop power can be described as high frequency (three to five weekly sessions per muscle group), low volume (e.g., three to five movement patterns per session [three to six sets of two to six repetitions per movement pattern]), and low-moderate intensity (0–60% 1RM) (Baker et al., 2001b; Baker & Newton, 2006; Cormie et al., 2011; McMaster, 2012). Although substantial individual differences exist, power increases between 3 and 12% have been reported after 4 to 8 weeks of ballistic training and maximum strength combined with ballistic training (Hansen et al., 2011b; Harris et al., 2000; Hoffman et al., 2005; Lockie et al., 2012; McBride et al., 2002). These low volume–low intensity training loads are utilised to optimise upper- and lower-body power due to the high movement velocities and high-power outputs generated with these training loads (Baker & Newton, 2007; Baker & Newton, 2005). It should be noted that a number of researchers recommend using hypertrophy (three to five movement patterns per session [three to four sets of six to ten repetitions at 70–85% 1RM per movement pattern]) and/or maximum strength training loads to improve power

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Maximum Strength (90-100% 1RM)

Force (N)

Power-Force (75-90 % 1RM)

Power (30-60 % 1RM) Power-Velocity (< 30 % 1RM)

0.5

FIGURE 2.1

1.0 1.5 Velocity (m/s)

2.0

2.5

Force–power–velocity continuum. ( McMaster 2012, with permission.)

through an increase in the force component (Folland & Williams, 2007; Harris et al., 2008b; McBride et al., 2002; Wilson et al., 1993). To a lesser extent, power improvements ranging from 1 to 5% have also been reported after 4 to 12 weeks of hypertrophy/maximum strength training (Hansen et al., 2011b; Hoffman et al., 2004; Hoffman et al., 2009; Hoffman et al., 2005). The basis for the prescription of heavy loads is related to hypertrophic adaptations and motor unit recruitment in that near-maximal force production is needed to recruit and fully activate the Type II muscle fibres (Wilson et al., 1993). Current ballistic intensity prescription guidelines span the entire loading spectrum (0–98% 1RM), depending on the performance variable of interest (e.g., force, power, or velocity) (Figure 2.1). Long-term power adaptations are also affected by training age and experience following the concept of diminishing returns (Baker & Newton, 2006; Folland & Williams, 2007; Issurin, 2008). The longitudinal tracking of power in elite rugby league players showed a large increase in power (15%) after the first 2 years and a small decrease in power between the second and fourth year (˗3%), which supports the concept of diminishing returns in elite athletes (Baker & Newton, 2006). Similar to maximal strength, power retention in rugby players can be achieved with as little as one to two weekly training sessions providing session intensity and volume that are maintained over time (Appleby et al., 2012; Baker, 2001a, 2001b; Baker, 2013). Muscular power can be maintained and under the right training stimulus even improved throughout a competitive rugby season (Argus et al., 2009; Baker, 2001b). The detraining effects on ballistic (power) capabilities in rugby are scarce. However, some inferences can be drawn from previous research using elite athletes. Vertical jump performance can be maintained for up to 8 weeks of resistance detraining if a ballistic stimulus (e.g., a field session, plyometrics, and sprint training) is provided as part of the training dosage (Gabbett, 2006). It is believed that a training stimulus must be provided every 5 to 8 days to retain power capabilities (Issurin, 2008). There is also evidence to suggest that high-velocity qualities (body weight/ unloaded ballistic movements e.g., jump squats) may decrease at a greater rate than

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high-force qualities (loaded ballistic movements e.g., loaded jump squats) based on the purported neuromuscular and morphological adaptations due to detraining (Folland & Williams, 2007; Hakkinen, 1994; Issurin, 2008; McMaster et al., 2013). Further investigations looking at weekly/biweekly strength, speed, and ballistic performance changes over these off-season/detraining periods are recommended to effectively quantify decay rates and residual effects in rugby.

2.5 Summary Strength and power assessment, development, and retention in elite rugby athletes are crucial considerations for practitioners. The strength and conditioning practitioner must carefully consider the benefits and limitations of the various measurement systems, testing apparatus, movement patterns, loading parameters, warm-up strategies, rest periods, and the performance variables of interest currently available. Assessment selections must reflect the required rugby strength and power demands and be of practical/meaningful benefit to the athlete’s development. The dosage required to develop strength is described as high frequency, moderate volume, and high intensity, whereas the required dose to develop ballistic-power capabilities can be described as high frequency, low volume, and low-moderate intensity. Maximum strength training loads can also be employed to improve power through an increase in force production.

References Appleby, B., Newton, R., & Cormie, P. (2012). Changes in strength over a 2-year period in professional rugby union players. Journal of Strength and Conditioning Research, 26(9), 2538–2546. Argus, C. K., Gill, N. D., Keogh, J. W., & Hopkins, W. G. (2014). Assessing the variation in the load that produces maximal upper-body power. Journal of Strength and Conditioning Research, 28(1), 240–244. Argus, C. K., Gill, N., Keogh, J., Hopkins, W. G., & Beaven, C. M. (2010). Effects of a shortterm pre-season training programme on the body composition and anaerobic performance of professional rugby union players. Journal of Sports Sciences, 28(6), 679–686. Argus, C. K., Gill, N. D., Keogh, J. W., & Hopkins, W. G. (2011). Assessing lower body peak power in elite rugby-union players. Journal of Strength and Conditioning Research, 25(6), 1616–1621. Argus, C. K., Gill, N. D., Keogh, J. W., Hopkins, W. G., & Beaven, C. M. (2009). Changes in strength, power, and steroid hormones during a professional rugby union competition. Journal of Strength and Conditioning Research, 23(5), 1583–1592. Atkins, S. J. (2004). Normalizing expressions of strength in elite rugby league players. Journal of Strength and Conditioning Research, 18(1), 53–58. Baker, D. (2001a). Acute and long-term power responses to power training: observations on the training of an elite power athlete. Strength and Conditioning Journal, 23(1), 47–56. Baker, D. (2001b). The effects of an in-season of concurrent training on the maintenance of maximal strength and power in professional and college aged rugby league football players. Journal of Strength and Conditioning Research, 15(2), 172–177.

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Baker, D., Nance, S., & Moore, M. (2001a). The load that maximizes the average mechanical power output during explosive bench press throws in highly trained athletes. Journal of Strength and Conditioning Research, 15(1), 20–24. Baker, D., Nance, S., & Moore, M. (2001b). The load that maximizes the average mechanical power output during jump squats in power-trained athletes. Journal of Strength and Conditioning Research, 15(1), 92–97. Baker, D., & Newton, R. (2007). Change in power output across a high-repetition set of bench throws and jump squats in highly trained athletes. Journal of Strength and Conditioning Research, 21(4), 1007–1011. Baker, D. G., & Newton, R. U. (2008a). Comparison of lower body strength, power, acceleration, speed, agility, and sprint momentum to describe and compare playing rank among professional rugby league players. Journal of Strength and Conditioning Research, 22(1), 153–158. Baker, D., & Newton, R. (2008b). Observation of 4-year adaptations in lower body maximal strength and power output in professional rugby league players. Journal of Australian Strength and Conditioning, 16(1), 3–10. Baker, D., & Newton, R. U. (2005). Methods to increase the effectiveness of maximal power training for the upper body. Strength and Conditioning Journal, 27(6), 24–32. Baker, D. G. (2013). 10-year changes in upper body strength and power in elite professional rugby league players--the effect of training age, stage, and content. Journal of Strength and Conditioning Research, 27(2), 285–292. Baker, D. G., & Newton, R. U. (2006). Adaptations in upper-body maximal strength and power output resulting from long-term resistance training in experienced strengthpower athletes. Journal of Strength and Conditioning Research, 20(3), 541–546. Bevan, H. R., Bunce, P. J., Owen, N. J., Bennett, M. A., Cook, C. J., Cunningham, D. J., & Kilduff, L. P. (2010). Optimal loading for the development of peak power output in professional rugby players. Journal of Strength and Conditioning Research, 24(1), 43–47. Blazevich, A. J., Gill, N., & Newton, R. U. (2002). Reliability and validity of two isometric squat tests. Journal of Strength and Conditioning Research, 16(2), 298–304. Blazevich, A. J., & Sharp, N. C. (2005). Understanding muscle architectural adaptation: macro and micro level research. Cells Tissues Organs, 181, 1–10. Comfort, P. (2012). Within and between session reliability of power, force and rate of force development during the power clean. Journal of Strength and Conditioning Research, 27(5), 1210–1214. Comfort, P., Graham-Smith, P., Matthews, M. J., & Bamber, C. (2011). Strength and power characteristics in English elite rugby league players. Journal of Strength and Conditioning Research, 25(5), 1374–1384. Corcoran, G. (2010). Analysis of the anatomical, functional, physiological and morphological requirements of athlete’s in rugby union. Journal of Australian Strength and Conditioning, 18(1), 24–28. Cormie, P., McGuigan, M., & Newton, R. (2011). Developing maximal neuromuscular power part 2 - training considerations for improving maximal power production. Sports Medicine, 41(2), 125–146. Cormie, P., McGuigan, M. R., & Newton, R. U. (2010). Influence of strength on magnitude and mechanisms of adaptation to power training. Medicine and Science in Sports and Exercise, 42(8), 1566–1581. Coutts, A., Reaburn, P., Piva, T. J., & Murphy, A. (2007). Changes in selected biochemical, muscular strength, power, and endurance measures during deliberate overreaching and tapering in rugby league players. International Journal of Sports Medicine, 28(2), 116–124.

26

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Crewther, B. T., Cook, C. J., Lowe, T. E., Weatherby, R. P., & Gill, N. (2010). The effects of short-cycle sprints on power, strength, and salivary hormones in elite rugby players. Journal of Strength and Conditioning Research, 25(1), 32–39. Crewther, B. T., Gill, N., Weatherby, R. P., & Lowe, T. (2009a). A comparison of ratio and allometric scaling methods for normalizing power and strength in elite rugby union players. Journal of Sports Sciences, 27(14), 1575–1580. Crewther, B. T., Lowe, T., Weatherby, R. P., Gill, N., & Keogh, J. (2009b). Neuromuscular performance of elite rugby union players and relationships with salivary hormones. Journal of Strength and Conditioning Research, 23(7), 2046–2053. Crewther, B. T., McGuigan, M. R., & Gill, N. D. (2011). The ratio and allometric scaling of speed, power, and strength in elite male rugby union players. Journal of Strength and Conditioning Research, 25(7), 1968–1975. Cronin, J., McNair, P., & Marshall, R. (2001). Developing explosive power: a comparison of technique and training. Journal of Science and Medicine in Sport, 4(1), 59–70. Cronin, J., & Sleivert, G. (2005). Challenges in understanding the influence of maximal power training on improving athletic performance. Sports Medicine, 35(3), 213–234. Cronin, J. B., & Hansen, K. T. (2005). Strength and power predictors of sports speed. Journal of Strength and Conditioning Research, 19(2), 349–357. Cronin, J. B., Hing, R. D., & McNair, P. J. (2004). Reliability and validity of a linear position transducer for measuring jump performance. Journal of Strength and Conditioning Research, 18(3), 590–593. Folland, J., & Williams, A. (2007). The adaptations to strength training: morphological and neurological contributions to increased strength. Sports Medicine, 37(2), 145–168. Fry, A. C. (2004). The role of resistance exercise intensity on muscle fibre adaptations. Sports Medicine, 34(10), 663–679. Gabbett, T. (2006). Performance changes following a field conditioning program in junior and senior rugby league players. Journal of Strength and Conditioning Research, 20(1), 215–221. Hakkinen, K. (1994). Neuromuscular adaptation during strength training, aging, detraining and immobilization. Physical and Rehabilitation Medicine, 6(3), 161–198. Hansen, K., Cronin, J., & Newton, M. (2011a). The reliability of linear position transducer and force plate measurement of explosive force-time variables during a loaded jump squat in elite athletes. Journal of Strength and Conditioning Research, 25(5), 1447–1456. Hansen, K., Cronin, J., Pickering, S., & Newton, M. (2011b). Does cluster loading enhance lower body power development in preseason preparation of elite rugby union players. Journal of Strength and Conditioning Research, 25(8), 2118–2126. Harris, G. R., Stone, M. H., O’Bryant, H. S., Proulx, C. M., & Johnson, R. L. (2000). Short-term performance effects of high power, high force, or combined weight-training methods. Journal of Strength and Conditioning Research, 14(1), 14–20. Harris, N. K., Cronin, J. B., & Hopkins, W. G. (2007). Power outputs of a machine squat-jump across a spectrum of loads. Journal of Strength and Conditioning Research, 21(4), 1260–1264. Harris, N. K., Cronin, J. B., Hopkins, W. G., & Hansen, K. T. (2008a). Relationship between sprint times and the strength/power outputs of a machine squat jump. Journal of Strength and Conditioning Research, 22(3), 691–698. Harris, N. K., Cronin, J. B., Hopkins, W. G., & Hansen, K. T. (2008b). Squat jump training at maximal power loads vs. heavy loads: effect on sprint ability. Journal of Strength and Conditioning Research, 22(6), 1742–1749. Hoffman, J., Cooper, J., Wendell, M., & Kang, J. (2004). Comparison of Olympic vs traditional power lifting training programs in football players. Journal of Strength and Conditioning Research, 18(1), 129–135.

Strength and Power Training for Rugby

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Hoffman, J., Ratamess, N., Klatt, M., Faigenbaum, A., Ross, D., Tranchina, N., & Kraemer, W. (2009). Comparison between different off-season resistance training programs in division III American college football players. Journal of Strength and Conditioning Research, 23(1), 11–19. Hoffman, J. R., & Kang, J. (2003). Strength changes during an in-season resistance-training program for football. Journal of Strength and Conditioning Research, 17(1), 109–114. Hoffman, J. R., Ratamess, N. A., Cooper, J. J., Kang, J., Chilakos, A., & Faigenbaum, A. D. (2005). Comparison of loaded and unloaded jump squat training on strength/power performance in college football players. Journal of Strength and Conditioning Research, 19(4), 810–815. IPF. (2012). International Powerlifting Federation: Technical Rules Book. In (Vol. January, pp. 35). Issurin, V. (2008). Block periodization versus traditional training theory: a review. Journal of Sports Medicine and Physical Fitness, 48(1), 65–75. Kilduff, L. P., Bevan, H., Owen, N., Kingsley, M. I., Bunce, P., Bennett, M., & Cunningham, D. (2007). Optimal loading for peak power output during the hang power clean in professional rugby players. International Journal of Sports Physiology and Performance, 2(3), 260–269. Lockie, R. G., Murphy, A. J., Schultz, A. B., Knight, T. J., & Janse de Jonge, X. A. (2012). The effects of different speed training protocols on sprint acceleration kinematics and muscle strength and power in field sport athletes. Journal of Strength and Conditioning Research, 26(6), 1539–1550. McBride, J. M., Triplett-McBride, T., Davie, A., & Newton, R. U. (2002). The effect of heavy vs. light-load jump squats on the development of strength, power and speed. Journal of Strength and Conditioning Research, 16, 75–82. McGuigan, M., & Winchester, J. (2008). The relationship between isometric and dynamic strength in college football players. Journal of Sports Science and Medicine, 7, 101–105. McGuigan, M. R., Cormack, S., & Newton, R. U. (2009). Long-term power performance of elite Australian rules football players. Journal of Strength and Conditioning Research, 23(1), 26–32. McLean, B. D., Coutts, A. J., Kelly, V., McGuigan, M. R., & Cormack, S. J. (2010). Neuromuscular, endocrine, and perceptual fatigue responses during different length between-match microcycles in professional rugby league players. International Journal of Sports Physiology and Performance, 5(3), 367–383. McMaster, D. T., Gill, N. D., Cronin, J. B., & McGuigan, M. R. (2016). Force-velocitypower assessment in semiprofessional rugby union players. The Journal of Strength & Conditioning Research, 30(4), 1118–1126. McMaster, D. T., Gill, N. D., Cronin, J., & McGuigan, M. (2013). The development, retention and decay rates of strength and power in elite rugby union, rugby league and American Football. Sports Medicine, 43(5), 367–384. McMaster, T. (2012). Hot topic: supplementing bands and chains into training. National Strength and Conditioining Association Hot Topics, August. Mujika, I., & Padilla, S. (2001). Muscular characteristics of detraining in humans. Medicine and Science in Sport and Exercise, 33(8), 1297–1303. Nibali, M. L., Chapman, D. W., Robergs, R. A., & Drinkwater, E. J. (2013). A rationale for assessing the lower-body power profile in team sport athletes. Journal of Strength and Conditioning Research, 27(2), 388–397. Pain, M. T., Tsui, F., & Cove, S. (2008). In vivo determination of the effect of shoulder pads on tackling forces in rugby. Journal of Sports Sciences, 26(8), 855–862.

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Peterson, M. D., Rhea, M. R., & Alvar, B. A. (2005). Applications of the dose-response for muscular strength development: a review of meta-analytic efficacy and reliability for designing training prescription. Journal of Strength and Conditioning Research, 19(4), 950–958. Preatoni, E., Stokes, K., England, M., & Trewartha, G. (2012). Forces generated in rugby union machine scrummaging at various playing levels. Paper presented at the International Research Council on the Biomechanics of Injury Conference Proceedings, Dublin. Preatoni, E., Stokes, K. A., England, M. E., & Trewartha, G. (2013). The influence of playing level on the biomechanical demands experienced by rugby union forwards during machine scrummaging. Scandinavian Journal of Medicine and Science in Sports, 23(3), e178–e184. Prestes, J., De Lima, C., Frollini, A. B., Donatto, F. F., & Conte, M. (2009). Comparison of linear and reverse linear periodization effects on maximal strength and body composition. Journal of Strength and Conditioning Research, 23(1), 266–274. Quarrie, K. L., Hopkins, W. G., Anthony, M. J., & Gill, N. D. (2013). Positional demands of international rugby union: evaluation of player actions and movements. Journal of Science and Medicine in Sport, 16(4), 353–359. Quarrie, K. L., & Wilson, B. D. (2000). Force production in the rugby union scrum. Journal of Sports Science, 18(4), 237–246. Rhea, M. R., & Alderman, B. L. (2004). A meta-analysis of periodized versus nonperiodized strength and power training programs. Research Quarterly, 75(4), 413–422. Sapega, A., & Drillings, G. (1983). The definition and assessment of muscular power. Journal of Orthopaedic and Sports Physical Therapy, 5(1), 7–9. Stone, M., Sanborn, K., Smith, L., O’Bryant, H., Hoke, T., Utter, A., …Garner, B. (1999). Effects of in-season (5 weeks) creatine and pyruvate supplementation on anaerobic performance and body composition in American football players. International Journal of Sport Nutrition, 9, 146–165. Tan, B. (1999). Manipulating resistance training program variables to optimize maximum strength in men: a review. Journal of Strength and Conditioning Research, 13(3), 289–304. Usman, J., McIntosh, A., & Best, J. (2010). The investigation of shoulder forces in rugby union. Journal of Science and Medicine in Sport, 13(S1), 63. West, D. J., Owen, N. J., Jones, M. R., Bracken, R. M., Cook, C. J., Cunningham, D. J., & Kilduff, L. P. (2011). Relationships between force-time characteristics of the isometric midthigh pull and dynamic performance in professional rugby league players. Journal of Strength and Conditioning Research, 25(11), 3070–3075. Wilson, G. J., Newton, R. U., Murphy, A. J., & Humphries, B. J. (1993). The optimal training load for the development of dynamic athletic performance. Medicine and Science in Sport and Exercise, 25(11), 1279–1286. Wu, W. L., Chang, J. J., Wu, J. H., & Guo, L. Y. (2007). An investigation of rugby scrummaging posture and individual maximum pushing force. Journal of Strength and Conditioning Research, 21(1), 251–258.

3 MONITORING THE MATCH AND TRAINING DEMANDS OF RUGBY Mark Waldron, Erwan Izri, and Craig Twist

3.1 Introduction Quantification of both internal and external load enables rugby practitioners to modify the demands of training in accordance with their periodized programmes. In addition, load measurements enable prescription of exercise thresholds to avoid injury (Gabbett, 2004a, b). Heart rate (HR) and rating of perceived exertion (RPE) have prevailed for monitoring internal training load in the field, owing to their low cost and practicality. Such methods include sessionRPE (sRPE; Foster et al., 2001) and the summated HR method (Edwards, 1993), which are now commonplace in rugby research and applied practice. The introduction of video and wearable micro-technology, such as inertial measurement units (IMUs) and Global Positioning systems (GPS) (also referred to as Global Navigation Satellite System; GNSS) in elite team sport, has also advanced our understanding of training load, turning attention to the external demands of rugby players. It is the aim of this chapter is to provide critical review of such methods, with reference to their relationship with training practices in rugby league and union.

3.2 Monitoring the external demands of training and competition in rugby The temporal running patterns of rugby match play are intermittent in nature, whereby clustered periods of repeated maximal exertions such as tackling, accelerating and sprinting, separate prolonged periods of low intensity activity (Austin et al., 2011b; Gabbett et al., 2012; Cahill et al., 2013; Tee et al., 2017; Delaney et al., 2017; Reardon et al., 2017; Read et al., 2018). Rugby is also a ‘collision sport’, which describes the coming together of players from opposing sides either DOI: 10.4324/9781003045052-4

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as the ‘tackling’ or the ‘tackled’ counterpart. Such demands place stress on both aerobic and anaerobic metabolism (Coutts et al., 2003), as well as increasing the risk of muscle damage and injury (Smart et al., 2008; Twist et al., 2012; Oxendale et al., 2016; Fitzpatrick et al., 2018). Accordingly, to prepare players for competition, it has become increasingly important to understand the external demands of the training and match environment.

3.2.1 The use of time-motional analysis in rugby Manual Time-Motion Analysis (TMA) requires visual interpretation of the player’s gait pattern, sub-categorized into incremental movement classifications of standing, walking, jogging, striding, sprinting, backward and lateral movements (McLean, 1992; Deutsch et al., 2007; King et al., 2009; Austin et al., 2011a, b). The player’s movement is then manually timed, with speed (and thus distance) estimated based upon pre-determined values associated with each movement classification (see Reilly & Thomas, 1976). Alternatively, the distance of the player can be estimated based on their movement between pre-identified visual cues around the pitch side and timed with a stopwatch (with speed = distance/time). Quantifying movement can be incorporated into conditioning practices, enabling rugby coaches to prepare players for the external demands that they are likely to experience in a match. While such methods are cost-effective and can be reliably administered, they are labour-intensive for the user and generate relatively simplistic data.

3.2.2 The use of multiple camera systems in rugby Semi-automated computerized tracking (via multiple camera systems) of players is one approach used to capture time-motion characteristics in rugby. Semiautomated tracking uses visual image recognition software to identify features unique to an individual (Carling et al., 2008; Di Salvo et al., 2007). Examples of such features might be colour, shape or size of the participant (Carling et al., 2008). Cameras are situated in specific areas around the perimeter of the playing surface and synchronously digitized in order to calculate the distance and speed of players’ movements. The use of such systems is apparent only within elite sporting contexts, largely owing to the high cost and logistical impracticality, therefore limiting their use in training scenarios. Multiple camera systems, are thought to provide a valid measurement of distance and speed in team sports, with reports of only 0.4% error in comparison to running speeds assessed using timing gates (Bradley et al., 2007; Di Salvo et al., 2006). However, Randers et al. (2010) reported disparity between GPS (5 Hz and 1 Hz) and a multiple camera system, with coefficient of variation (CV) values ranging from 7 to 12% for total distance covered during the match. Interestingly, there were large differences between systems with regards to distance covered in separate locomotive categories. For example, the multiple camera systems recorded a greater distance in

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high-speed running compared to the GPS (5 Hz) by 0.63 km and the manual gait TMA by 0.81 km. Such findings prohibit comparisons between studies using different modes of TMA. Figueroa et al. (2006) highlighted issues with lighting of the playing surface and sharp changes in motion velocity, which cause difficulty in using multiple camera systems in sports where players maintain close proximity (i.e., collisions). Consequently, such systems require frequent (3% to 42% of the time) human intervention to reconfigure the tracking of players (Di Salvo et al., 2009). Whilst the limitations of multiple camera systems should be recognized, the sampling rate of 7.5 to 25 Hz (with the option to increase) remains far superior to alternative measures of TMA. This has important implications for the recognition of accelerations/decelerations in team sport that impose a large metabolic demand on players (Osgnach et al., 2010). Sykes and colleagues were the first to use a multiple camera system to monitor movement characteristics of rugby league (Sykes et al., 2009) and show signs of fatigue via variations in the running performance of rugby players across progressive match periods (Sykes et al., 2011). In rugby union, multiple camera systems have been used to quantify differences in the match running patterns of positional groups (Roberts et al., 2008; Lacome et al., 2014). Lacome et al. (2014) reported ~ 65% of exercise periods during the match lasted 5 time zone differences from their home country have a 2–3-fold increased risk of illness. British Journal of Sports Medicine, 46(11), 816–821. Silva, A. C., Silva, A., Edwards, B. J., Tod, D., Amaral, A. S., de Alcântara Borba, D., … & de Mello, M. T. (2021). Sleep extension in athletes: what we know so far–a systematic review. Sleep Medicine, 77, 128–135. Smith, C. S., Reilly, C., & Midkiff, K. (1989). Evaluation of three circadian rhythm questionnaires with suggestions for an improved measure of morningness. Journal of Applied Psychology, 74(5), 728. Smithies, T. D., Eastwood, P. R., Walsh, J., Murray, K., Markwick, W., & Dunican, I. C. (2021). Around the world in 16 days: the effect of long-distance transmeridian travel on the sleep habits and behaviours of a professional Super Rugby team. Journal of Sports Sciences, 39(22), 2596–2602. Straub, W. F., Spino, M. P., Alattar, M. M., Pfleger, B., Downes, J. W., Belizaire, M. A., … & Vasankari, T. (2001). The effect of chiropractic care on jet lag of Finnish junior elite athletes. Journal of Manipulative and Physiological Therapeutics, 24(3), 191–198. Svendsen, I. S., Taylor, I. M., Tønnessen, E., Bahr, R., & Gleeson, M. (2016). Trainingrelated and competition-related risk factors for respiratory tract and gastrointestinal infections in elite cross-country skiers. British Journal of Sports Medicine, 50(13), 809–815. Van Rensburg, D. C. C. J., Van Rensburg, A. J., Fowler, P., Fullagar, H., Stevens, D., Halson, S., … & Cronje, T. (2020). How to manage travel fatigue and jet lag in athletes? A systematic review of interventions. British Journal of Sports Medicine, 54(16), 960–968.

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Walsh, N. P. (2018). Recommendations to maintain immune health in athletes. European Journal of Sport Science, 18(6), 820–831. Walsh, N. P. (2019). Nutrition and athlete immune health: new perspectives on an old paradigm. Sports Medicine, 49(2), 153–168. Walsh, N. P., Halson, S. L., Sargent, C., Roach, G. D., Nédélec, M., Gupta, L., … & Samuels, C. H. (2021). Sleep and the athlete: narrative review and 2021 expert consensus recommendations. British Journal of Sports Medicine, 55(7), 356–368. Waterhouse, J., Nevill, A., Finnegan, J., Williams, P., Edwards, B., Kao, S. Y., & Reilly, T. (2005). Further assessments of the relationship between jet lag and some of its symptoms. Chronobiology International, 22(1), 121–136. Waterhouse, J., Reilly, T., Atkinson, G., & Edwards, B. (2007). Jet lag: trends and coping strategies. The Lancet, 369(9567), 1117–1129. Waterhouse, J., Edwards, B., Nevill, A., Atkinson, G., Reilly, T., Davies, P., & Godfrey, R. (2003). Do subjective symptoms predict our perception of jet-lag? In Reilly, T., & Greeves, J. (Eds.). Advances in sport, leisure and ergonomics (pp. 81–94). London: Routledge. Waterhouse, J. A., Edwards, B., Nevill, A., Carvalho, S., Atkinson, G., Buckley, P., … & Ramsay, R. (2002). Identifying some determinants of “jet lag” and its symptoms: a study of athletes and other travellers. British Journal of Sports Medicine, 36(1), 54–60. Waterhouse, J., Minors, D., Folkard, S., Owens, D., Atkinson, G., Macdonald, I., … & Tucker, P. (1998). Light of domestic intensity produces phase shifts of the circadian oscillator in humans. Neuroscience Letters, 245(2), 97–100. Wegmann, H. M., Klein, K. E., Conrad, B., & Esser, P. (1983). A model for prediction of resynchronization after time-zone flights. Aviation, Space, and Environmental Medicine, 54, 524–527. Wilder-Smith, A., Mustafa, F. B., Peng, C. M., Earnest, A., Koh, D., Lin, G., … & MacAry, P. A. (2012). Transient immune impairment after a simulated long-haul flight. Aviation, Space, and Environmental Medicine, 83(4), 418–423. Wright, K., Badia, P. & Myers, B. (1997). Combination of bright light and caffeine as a countermeasure for impaired alertness and performance during extended sleep deprivation. Journal of Sleep Research, 6(1), 26–35. Youngstedt, S., Elliott, J., Kripke, D. (2019). Human circadian phase‐response curves for exercise. Journal of Physiology, 597(8), 2253–2268. Zubac, D., Buoite Stella, A., & Morrison, S. A. (2020). Up in the air: Evidence of dehydration risk and long-haul flight on athletic performance. Nutrients, 12(9), 2574.

10 PSYCHOLOGICAL PREPARATION FOR RUGBY Stephen D. Mellalieu and Rich Neil

10.1 Introduction The intermittent high-intensity, collision-based, decision-making nature of rugby means that in addition to its physical challenges, it is also cognitively and emotionally demanding (Campo et al., 2012). Elite players need to possess a range of psychological qualities and deploy several psychological skills to manage these demands and perform successfully (Taylor & Collins, 2019). Fundamental to the deployment of these skills is suitable psychological preparation for performance. The development of the professional codes of rugby over the past two decades has seen increased investment directed into preparing teams for performance, resulting in the growth of sports science and medicine support, and increased psychological service provision to national governing bodies and teams. Although not commonplace (Green et al., 2012), most professional teams will have worked with, or had access to, some form of consultant or associated service to assist with psychological preparation for performance (Mellalieu, 2017). Considering the psychological demands of competing at the elite level the purpose of this chapter is to discuss the scientific evidence regarding psychological preparation for rugby. First, this chapter describes the psychological demands rugby players encounter at the elite level and the psychological qualities that characterise successful rugby performance. This chapter then considers the mental strategies rugby players can adopt to psychologically prepare for performance, including goal setting, imagery, self-talk and activation management. Considerations regarding the psychological dynamics of the team are then discussed before this chapter concludes with a summary of the key elements underpinning psychological preparation for rugby.

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10.2 Psychological demands of rugby While the physiological requirements of rugby at the elite level are well understood, in contrast there have been few empirical attempts to comprehend the psychological demands associated with competing in the game (Quarrie et al., 2017). This is despite the potential impact that the failure to manage such demands can have on upon performance and well-being (Mellalieu et al., 2021). The psychological demands (sometimes referred to as ‘psychological load’) that elite performers face in sport can be classified according to their experiences in relation to training and competition, and emanate from three sources: organisation, performance and personal (Mellalieu et al., 2009). Organization demands are associated primarily and directly with the sports organisation within which the performer operates (e.g., wages, finance). Performance demands are associated primarily and directly with competitive performance (e.g., opponents, injury). Personal demands are associated primarily and directly with non-sporting life events away from the work/sport environment (family, social lives, study). Within rugby, several performance-related psychological demands have been reported including making mental errors, making a physical error, opponent behaviour (cheating), referee decisions, injury concerns and experiencing pain (Anshel, 2001; Nicholls et al., 2006, 2009). Away from rugby, personal demands reported by elite players include diet, home life and sleep (Nicholls et al., 2009).

10.3 Psychological characteristics of successful rugby performance Understanding how players cope with the demands encountered within and away from rugby and perform successfully centres around the ability to draw upon available psychological resources. One such resource is coping, an ongoing process including conscious and deliberately executed attempts to manage demands appraised as being stressful, that could, without coping, cause emotional distress and poor performance (Lazarus, 1999). Coping strategies seek to regulate emotional distress (i.e., mental and/or behavioural withdrawal, denial, relaxation, self-blame, avoidance, acceptance, and wishful thinking), solve the problem causing the distress (i.e., through planning, information seeking, suppression of competing behaviour, or increasing efforts), or avoid the stressful situation altogether (e.g., walking away or mentally blocking it). The limited research examining coping strategy use in rugby suggests players adopt a variety of different techniques to manage the demands experienced, and the subsequent effectiveness of their coping attempts can vary. The most frequently cited strategies used to cope with performing include increased concentration, blocking out the thought of the demand, positive re-appraisal of the demand faced, and being focused on the task, while the most effective coping strategies reported include focusing on the task and increasing effort (Nicholls et al., 2006). Understanding and developing the psychological qualities that will assist a player’s ability to cope with the demands of professional rugby is fundamental to

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effective preparation for performance. Several differences have been identified in psychological qualities between elite and non-elite players, with elite players displaying greater attentional focus, self-confidence, hardiness, and mental toughness than their non-elite counterparts (Andrew et al., 2007; Golby & Sheard, 2004; Tanaka & Gould, 2015). Elite players also use mental strategies (mental imagery, cognitive self-talk, and activation management) more effectively than non-elite players (Di Corrado et al., 2014; Neil et al., 2006). Collectively, these findings suggest that elite rugby players use their mental skills more effectively to develop certain psychological qualities that positively influence preparation for competition (Hardy et al., 2017). The mental techniques associated with the psychological qualities of successful rugby performance are three of the four most commonly cited strategies in applied sport psychology research and practice: goal setting, mental imagery, self-talk and activation management1 (Hardy et al., 1996). The process by which rugby players practice these techniques with a view to maximise psychological preparation for performance is referred to as psychological skills training (Weinberg, 2019). Psychological skills training is a proactive, systematic and consistent approach with evidence provided for its effectiveness in developing psychological preparation in rugby (Edwards & Edwards, 2012) and solid empirical support documenting its overall ability to enhance athletic performance (see Barker et al., 2020). The remainder of this chapter now considers each of the four psychological strategies and their use in psychological preparation for rugby.

10.4 Goal setting A goal is described as the object, behaviour, standard or aim of an action, which a player tries to accomplish (Locke & Latham, 2002). Setting goals influences performance by: (a) directing a player’s behaviour to focus on a specific task or action, (b) enhancing the effort and intensity invested, (c) increasing persistence despite likelihood of failure or adversity and (d) allowing players to engage in problem-solving behaviours that help them develop new strategies to achieve their goals (Kingston & Wilson, 2009). Goal setting is a fundamental psychological preparation strategy that is effective for the enhancement of specific individual performance behaviours in rugby and overall team performance (Mellalieu et al., 2006). Setting goals can also reduce the anxiety symptoms associated with performing and enhance feelings of confidence to successfully execute a task (Kingston & Hardy, 1997). Typically, recommendations for goal setting to enhance preparation for performance are made in relation to setting multiple types of goals across different time periods, and in specific ways to maximise effectiveness. Rugby players can be taught to set three different goals to maximise preparation for performance. Outcome goals refer to a specific desired result or outcome in a rugby match (e.g., win next match, gain promotion, finish top of the league or conference). Performance goals involve players focusing on achieving certain

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standards of performance. For example, a player may seek to improve their tackle completion success rate from 75–90%. Process goals encourage players to focus on actions associated with successful performance (e.g., arms tight to the chest, chase feet/short steps, focus on ball carrier’s hips, drop body height into the tackle). Players should be encouraged to set all three types of goals in preparation for performance, as, although outcome goals ultimately provide the focus for matches and achievement in a player’s career (trophies, international honours), they are only partially within a player’s control (i.e., match outcome is dependent on match officials, opposition behaviour, and the behaviours of the player’s own team as well as that of the player themselves). In addition to setting multiple goal types, players should also have a time emphasis to their goal setting. Outcome, performance and process goals should be set in combination across the short- (match to match), medium- (phase of competition/playing season) and long-term (season to season). To maximise the effectiveness of each goal set players can adopt SMART principles (Doran, 1981), namely: Specific, Measurable, Adjustable, Realistic and Time-orientated. Players should therefore ensure the goals they set: are specific to what they want to achieve (e.g., a kicker might wish to improve their penalty goal kicking success rate); can be measured or assessed so that a player is able to determine the extent to which the goal set has been achieved (e.g., penalty kick success can be assessed through a percentage rate of successful versus total kicks attempted); are adjustable in relation to individual or contextual changes (e.g., a target of an 85% penalty goal kick success rate may need to be lowered if playing in difficult weather conditions); are realistic in order to allow the player a chance to achieve their goal (e.g., a kicker with a 50% penalty goal success rate is unlikely to achieve a new goal of 100% without a significant investment of time, practice and coaching); and, have a temporal element so that the player seeks to achieve the goal within specific time frames (e.g., a kicker may set a goal at the start of the season of improving their penalty goal kick success rate by 10% by the mid-season, and 20% by the end of season).

10.5 Mental imagery Mental imagery is a technique that can benefit rugby performance by enhancing the learning and execution of the motor skills that underpin the physical, technical, and tactical demands of the sport. It can also enhance rugby performance through its indirect effects (Mellalieu et al., 2009), for example, on the modification of cognitions (e.g., enhanced confidence in role execution), regulation of mental and physical activation states (e.g., optimising pre-match arousal), and behaviour change through increasing motivation-related persistence and maintenance of effort (e.g., continuing to work at a high intensity during a long phase of defensive sets in a match). Imagery is a mental process involving multisensory experiences in the absence of actual perception (Murphy et al., 2008). Imagery differs subtly from related techniques such as visualisation, whereby visualisation

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refers to a specific sensory modality, in this case vision. In contrast, imagery comprises all the senses (e.g., the smell of the turf as the ball is placed ready for the penalty goal kick attempt, the feel and the sound of the contact of the boot with the ball during the kick, and the sight of the ball subsequently moving towards the goal posts). When using imagery, the player should decide on the desired outcome or function to be achieved (cognitive or motivational) and base the content (i.e., what they image) on this outcome. Content can be specific in nature (e.g., a player wishing to improve their confidence on a penalty goal kick should imagine themselves performing a penalty goal kick competently and successfully) or general (e.g., imaging how a set move or team play will run). To maximise the overall effectiveness of imagery, players can adopt the principles of the PETTLEP model (Holmes & Collins, 2001). The PETTLEP model is grounded in the notion that a functional equivalence exists between imagery and motor performance. Essentially, the brain areas responsible for coordinating overt physical movements are also activated when players image the same actions. Engaging in practice of imagery of that action results in neural activity which regulates subsequent motor and sports performance (cf. Cumming & Ramsey, 2009). PETTLEP stands for Physical, Environment, Task, Timing, Learning, Emotion and Perspective and is based on the premise that a player needs to engage in imagery that resembles the actual performance as closely as possible. Specifically: •

•

•

•

•

•

Physical refers to the congruency between the physical nature of the imagery undertaken and the actual performance (e.g., a player imaging themselves undertaking a successful penalty kick should wear clothing like that as if they were performing that task and assume the starting position of a penalty kick as if they were going to physically undertake the action). Environment refers to the physical environment in which the imagery is being undertaken. For example, a player should be at the training ground or match venue if they are imaging actions that will be performed on the field. Task suggests the image should mimic the actual task as closely as possible (e.g., the image of the completion of a successful tackle or a player’s role in an attacking play should replicate the exact components of that action). Timing suggests the image should be in ‘real-time’ - matched to that actual speed of the execution of the task. For example, an attacking play or move should be imaged at the same speed as which it is executed ‘live’ on the training field or during the match. Learning indicates that the image should correspond with the individual’s specific stage of learning and develop as their actual skill level improves (e.g., expert or elite players will be able to image execution of complex and refined movements or skills than their less skilled counterparts). Emotion represents the extent to which the image encapsulates all the emotions of the actual performance of the task. For example, a kicker imaging a penalty kick at goal may focus on experiencing an emotional state comprising

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feelings of calmness, composure and confidence before, and during, the execution of the kick. Perspective describes how the image should take the viewpoint of the player during the actual performance; either from an internal (in your own body making the tackle) or external (seeing yourself on film or DVD making the tackle) perspective in relation to the player.

10.6 Self-talk Self-talk refers to the automatic statements reflective of the deliberate techniques (e.g., thought stopping), players use to direct their sports-related thinking (Hardy et al., 2009). Self-talk can be external (expressed out loud) or internal (in one’s head) and enhance rugby performance through its instructional or motivational properties. Specifically, players can use self-talk in the form of brief cue words/ triggers or statements to enhance the performance of motor skills by producing greater concentration and attention on the task at hand, increasing motivation and confidence to undertake the task or action, improving movement kinematics, and reducing task-related anxiety (Tod et al., 2011). To use the content of their thoughts effectively, rugby players must know when and how to talk to themselves (Zinsser et al., 2006). This begins with identifying what thoughts are helpful/harmful and what situations are associated with this talk. Players can identify their self-talk use through retrospective means, by recalling or re-creating the thoughts and feelings that occurred before and during a good or bad performance and the specific circumstances that led to the thoughts and resulting performance. Alternatively, players can keep a logbook to record the type, intensity and frequency of thought content before, during, or after successful/unsuccessful performances. Similar to the guidance for using mental imagery, when considering the content of the self-talk players use, it is critical that the self-talk is congruent with the desired goal/outcome of the action or skill, and that it contains the most appropriate information within the cue. For example, employment of motivational types of self-talk (e.g., ‘stay alert,’ ‘calm,’ ‘relax’) should be most beneficial for psyching-up or relaxation outcomes (before a penalty goal kick or after a skill error or mistake), whereas instructional (skillspecific) self-talk should most strongly assist skill execution (‘follow through the ball’). However, it is possible that a self-talk phrase may serve more than one function, and players should therefore be clear on the intended outcome before creating the content/type of self-talk. Players can also use several other mental training techniques associated with self-talk to prepare for rugby including thought stopping, thought replacement, countering, reframing, and affirming (Zinsser et al., 2006). Thought stopping is a method for eliminating counterproductive thoughts. Once players are aware of unwanted performance thoughts, they can learn to use a trigger to interrupt or stop the undesirable thoughts. Some players may find it difficult to suppress unwanted thoughts; indeed focusing on suppressing unwanted thoughts may even

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increase them. When thought stopping does not work players can learn to replace any negative thought (‘I’m not going to make this kick’) with a positive thought (‘I’m going to make this kick’) that provides motivational and/or instructional support or appropriately redirects attention. Here, the aim for the player is to switch to a positive thought as soon as they become aware of a dysfunctional selftalk. This technique can be combined with relaxation, so that the player stops the negative thought, takes a deep breath, slowly exhales, and substitutes the positive thought as the body relaxes. Countering is a form of self-talk via an internal dialogue that uses facts and reasons to contest the underlying beliefs and assumptions that lead to negative thinking. Players should be guided to identify and build a case against the negative self-statements by drawing upon past evidence and future possibilities to refute underlying beliefs that cause the dysfunctional thoughts (‘I have been in this situation before and executed the successful play’). Reframing is the process of creating alternative frames of reference or different ways of looking at the world, such as interpreting situations in a more positive way. For example, a player can learn to transform weakness/difficulty (e.g., dropped pass, missed tackle) into a strength/possibility (e.g., focus on making a correct pass/tackle execution in the next play) rather than denying or ignoring the experience. Affirmations are a form of self-talk that take the form of a positive action-oriented affirmation statement reflecting positive attitudes or thoughts about oneself (e.g., ‘I am ready for this match,’ ‘I am good enough to play in this team’). To be effective players must develop affirmations that are both believable and vivid. Players should state affirmations in present tense and avoid perfectionistic demands. Affirmations need to be written or repeated many times and once the affirmation is achieved (comes true), the player can choose another and begin the process again.

10.7 Activation management Activation management strategies focus on coping with the stress experienced when preparing for, or during, competition, and comprise three approaches: reduction, restructuring and energizing (see Baldock et al., 2020). Where elevated arousal and anxiety can have a detrimental effect on performance (e.g., before taking a penalty goal kick), a reduction approach (i.e., relaxation) can be adopted to reduce the intensity of the symptoms experienced. Players can engage in either muscle-to-mind or mind-to-muscle approaches. Muscle-to-mind techniques focus on the bodily aspects to aid relaxation and include strategies such as breathing exercises and progressive relaxation (PR). Breathing exercises typically include learning a general meditative technique that focuses on controlled breathing and the use of a mantra to calm the player (Neil & Thomas, 2014). Players can introduce a mantra word on each breath out (e.g., ‘relax,’ ‘exhale’), and once relaxed, count down from, for example, 10 to 1 on each exhalation and upwards from 1 to 7 on inhalation. The goal of PR is for players to progress through a series of logical, progressive stages working towards being able to achieve a relaxed physical state rapidly in response to any stressful situation. Players can seek to consciously tense and relax different gross

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muscle groups within the body and focus their attention on the difference between a tense (anxious) state and a relaxed (less anxious) one, progressing to using a cue (mental or physical) that acts as an association trigger to activate the relaxed state in the desired muscle group. Mind-to-muscle strategies focus on reducing activation via efferent nerve control, or the stimulation from the brain to the muscles and include transcendental meditation, visualization, and autogenic training. With transcendental mediation, the goal for the player is to learn the skill of relaxation through a series of steps designed to change their mental state from one of anxious to one of being calm. Players progress through stages to a desired outcome where they can lower anxiety levels associated with performing in a matter of seconds. Typically, players first learn a general meditative technique that focuses on breathing (e.g., counting down from 5 to 1 on exhalation, counting up from 1 to 3 on inhalation) together with the use of a mantra, with the goal of shortening the time taken to achieve mental relaxation. Players can then look to transfer the skill into more realistic stressful settings (before or during training) to reduce anxiety experienced in these situations, and then finally integrate the skill into the rugby match environment. Visualization can be used by players to provide a sense of calm and relaxation, by picturing being in a place conducive to relaxation. For example, lying on a beach feeling the warm sand and sun on the body while listening to the continuous rhythm of breaking waves and smelling the salt air. Autogenic training is a form of relaxation training combined with visualization using self-suggestion. Players can learn to associate a series of verbal cues and visual images with feelings of warmth and cold in different parts of the body. At the same time, players practice regulation of several physiological activities (e.g., heart rate) in response to these cues and images. Once players have acquired these skills, they are then able to generate these responses to reduce symptoms as desired before or during performance. The second approach to activation management considers the viewpoint that high anxiety and arousal associated with preparing for, and performing in, rugby need not be detrimental and can be viewed in a positive way that benefits performance (Mellalieu et al., 2004). Players can therefore be taught to gain control over their anxiety experienced by restructuring interpretation of symptoms from a negative to a positive viewpoint (i.e., debilitative to facilitative) for optimal performance. First, players can use imagery to recreate symptoms associated with anxious thoughts and feelings related to performance. For example, a player can identify stressful situations where the images have been experienced, and then recall experiences of these symptoms, possibly with the aid of video footage or a competition diary. Once players recreate the anxious thoughts and feelings, they can be taught to rationalise and restructure symptoms by identifying, disputing, and then replacing negative interpretations of anxiety symptoms (Neil et al., 2013). Players can be educated to change their view of their symptoms experienced by questioning whether the symptoms reported are always detrimental to performance and then replacing these thoughts with ones suggesting that the worries experienced highlight the personal importance of the match – such

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thoughts can help the player increase effort and have a more focused and concentrated performance state. When players have an insufficient activation state (i.e., under aroused) an energizing approach (‘psyching-up’) can be adopted to enhance performance. ‘Psyching-up’ is an umbrella term describing sequences of cognitive, emotional and physical actions performed just before, or even during, movement to enhance performance (Tod et al., 2003), often because players lack a sufficient stimulus to create the optimum mental and physical activation state for performance. A variety of techniques exist, many of which are the reverse of the interventions outlined in the reduction approach (i.e., they become energizing rather than calming). For example, players can engage in breathing exercises whereby they consciously deepen and increase their breathing rate and imagine that with each inhalation they are increasing energy to reach an optimum activation state. A supply of energizing images and verbal cues can also be developed that work for players in various situations encountered, such as during the warm-up or breaks in play. Players can also learn to ‘transfer’ energy from other sources, such as feelings of anger, frustration (or some other emotion that tends to interfere with performance), or spectators, opponents, and convert it into positive energy to accomplish goals or upcoming actions. The activation management strategies described so far fall under an ‘emotionfocused’ coping umbrella, reflecting a player’s efforts to regulate responses (e.g., anxiety and arousal) that emanate from the problem causing the stress (i.e., the demands of preparing for, and competing in, rugby). A further approach for managing activation is to adopt a problem-focused approach which seeks to remove or more likely reduce the stressor causing the symptoms (the demands of preparing for, and playing, rugby) to bring relief (Baldock et al., 2020). Examples include advice seeking (e.g., speaking to coaches for input around technical/tactical aspects of preparation), information gathering (undertaking opposition analysis), planning (tactical plays or moves for the upcoming match), problem solving (resolving technical/tactical weaknesses), and proactive behaviour (e.g., working on potential areas of their game where improvement is needed). Problem-focused strategies work, however, only when the player can exert some control over eradicating the demand. When not possible, emotion-focused coping strategies are more appropriate treatments. Adopting a range of emotion- and problem-focused strategies is therefore recommended to help players to prepare to cope effectively with the demands of rugby performance.

10.8 Psychological preparation for rugby competition Limited empirical research exists to date regarding how to specifically psychologically prepare rugby players for competition. In a study of international players, Mellalieu et al. (2008) identified use of specific psychological strategies to manage mental and physical activation across distinct phases of psychological preparation in the lead up to matches, including the build-up to match day (days leading up to the match) and the time before the kick-off on match day (morning of the match,

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travel to the venue, time in changing rooms, warm-up, time directly before kickoff). Early in the preparation period (build up to the day of the match) players sought to reduce or regulate activation states to avoid any unnecessary demands incurred, while nearer to the match (team warm-up, directly before kick-off) strategies focused upon enhancing or maximizing mental and physical activation states in preparation for performance. Mental imagery is an important strategy to help assist players with their psychological preparation in the lead up to competition (Mellalieu et al., 2009). Players can use mental rehearsal of the successful execution of specific individual roles, team plays or performance plans in order to assist with building clarity and confidence in the time leading up to the day of the match (e.g., a 10–25 minute virtual ‘captain’s run’ the night before the game). Closer to kick-off, imagery with more motivational properties (feelings associated with successful execution of match-related roles and tasks) can be used to enhance psychological and physiological activation (30 s visualizing a successful tackle, high ball catch, or scrum engagement). In addition to preparation before kick-off, opportunities also exist for players to engage in psychological preparation at intervals throughout the match, such as during breaks in play or at half-time (Nicholls & Callard, 2012). During breaks in play, players can engage in strategies to regulate activation states and focus on successful skill execution in the next play (winning set piece, penalty kick, goal line defence). Half-time also offers a window for players to psychologically prepare by: modulating mental and physical activation (i.e., reduce, restructure, or energise); reviewing first half performance (individual and team); using mental imagery to rehearsing intended tactical strategies; and focusing on the desired actions (roles, tasks) to be completed to achieve successful performance for the remainder of the match. A key element of any psychological preparation for rugby whether before, or during, the match, is the need to ensure mental strategies are deployed consistently within an established routine (e.g., rehearsal of team plays the day before a match). To maximise effectiveness, where appropriate, mental preparation should be embedded within existing physical and technical preparation for performance (e.g., pre-match plans, individual warm-up routines). The use of pre-performance routines (Jackson & Baker, 2001), for example, before taking a penalty goal kick, scrum engagement, defensive read, also provide simple yet effective tools for players to build consistent mental, technical, and physical performance preparation and execution.

10.9 Team dynamics When developing psychological preparation for rugby performance, consideration should also be given to the importance of the psychological dynamics of the team, specifically how to bring players to together to perform in a team environment. For a rugby team to be effective, individual team members need to perform role-specific actions whilst interacting effectively with other members of the team, placing importance on both individual- and team-functioning. In considering the impact of the team on performance, team cohesion and collective efficacy are key aspects in

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psychological preparation for rugby (Shearer, 2015). Team cohesion represents a dynamic process reflected in a group’s tendency to stick together and remain united in pursuit of its instrumental objectives and/or for the satisfaction of member affective needs (Carron et al., 1998). In sport settings positive relationships have been demonstrated between team cohesion and performance, and a range of factors associated with team functioning including cooperation, communication, and management of conflict (McEwan & Beauchamp, 2014). Collective efficacy is a group’s shared belief in its collective ability to organise and execute courses of action required to produce given standards of attainment (Bandura, 1997), and has been found to be positively related to measures of team performance, athlete satisfaction and team resilience in sport (McEwan & Beauchamp, 2014). While a detailed discussion of the science and practice of team building in sport is beyond the scope of this chapter (for details see Beauchamp et al., 2017), a rugby player’s beliefs about their ability, and that of the team, to perform effectively in upcoming competition, their perceptions of team cohesion, and subsequent team performance can be enhanced through observational learning (Bruton et al., 2019). Specifically, the act of observing (typically undertaken by watching video footage, but also by using mental imagery) your own team working together effectively or another team achieving success over the upcoming opponents, provide opportunities to learn individual- and team-level social behaviours which can enhance a player’s individual and collective efficacy beliefs. Practitioners can therefore help players to foster greater perceptions of team cohesion and collective efficacy in preparing for performance using individual and group video-based observation sessions that contain both team and individual content (e.g., individual actions or team plays or strategies that demonstrate mastery over an opponent).

10.10 Conclusion The research to date indicates that rugby players face a wide range of demands, on and off the field, upon their ability to perform successfully. Effective psychological preparation for rugby to cope with these demands therefore requires possession of a range of psychological characteristics using methods developed through systematic psychological skills training. Goal setting, mental imagery, self-talk and activation management are core strategies and skills which enable effective psychological preparation, successful coping and performance. When preparing for performance, consideration should also be given to team dynamics and strategies to enhance perceptions of cohesion and collective efficacy.

Note 1 For this chapter ‘psyching-up’ and ‘relaxation’ (commonly associated with ‘psychingdown’) are viewed on opposite ends on the continuum of the techniques associated with the psychological skill of activation management (i.e., managing one’s physical and mental readiness for competition; Hardy et al., 1996).

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References Andrew, M., Grobbelaar, H. W., & Potgieter, J. C. (2007). Sport psychological skill levels and related psychosocial factors that distinguish between rugby union players of different participation levels. South African Journal for Research in Sport Physical Education and Recreation, 29, 1–14. Anshel, M. H. (2001). Qualitative validation of a model for coping with acute stress in sport. Journal of Sport Behaviour, 24, 223–246. Baldock, L., Hanton, S., Mellalieu, S. D., ＆ Williams, J. M. (2020). Understanding and managing stress in sport. In J. Williams ＆ V. Krane (eds.), Applied sport psychology: Personal growth to peak performance (8th ed., pp. 210–243). United States: McGraw Hill. Bandura, A. (1997). Efficacy: The exercise of control. United States: Freeman. Barker, J. B., Slater, M. J., Pugh, G., Mellalieu, S. D., McCarthy, P. J., Jones, M. V., & Moran, A. (2020). The effectiveness of psychological skills training and behavioural interventions in sport using single-case designs: A meta regression analysis of the peerreviewed studies. Psychology of Sport and Exercise, 51, 101746. Beauchamp, M. R., McEwan, D., & Waldhauser, K. J. (2017). Team building: Conceptual, methodological, and applied considerations. Current Opinion in Psychology, 16, 114–117. Bruton, A. M., Shearer, D. A., & Mellalieu, S. D. (2019). Who said “there is no ‘I’ in team”? The effects of observational learning content level on efficacy beliefs in groups. Psychology of Sport and Exercise, 45, 101563. Campo, M., Mellalieu, S. D., Ferrand, C., Martinent, G., & Rosnet, E. (2012). Emotions in team contact sports: A systematic review. The Sport Psychologist, 26, 62–97. Carron, A. V., Brawley, L. R., & Widmeyer, W. N. (1998). The measurement of cohesiveness in sport groups. In J. L. Duda (ed.), Advances in sport and exercise psychology measurement (pp. 213–226). Morgantown, WV: Fitness Information Technology. Cumming, J., & Ramsey, R. (2009). Imagery interventions in sport. In S. D. Mellalieu & S. Hanton (eds.), Advances in applied sport psychology: A review (pp. 5–36). London: Routledge. Di Corrado, D., Murgia, M., & Freda, A. (2014). Attentional focus and mental skills in senior and junior professional rugby union players. Sport Sciences for Health, 10, 79–83. Doran, G. T. (1981). There’s a SMART way to write management’s goals and objectives. Management Review, 70, 35–36. Edwards, D. J., & Edwards, S. D. (2012). The evaluation of a psychological skills training programme for rugby players. African Journal for Physical Health Education, Recreation and Dance, 18, 525–534. Golby, J., & Sheard, M. (2004). Mental toughness and hardiness at different levels of rugby league. Personality and Individual Differences, 37, 933–942. Green, M., Morgan, G., & Manley, A. (2012). Elite rugby league players’ attitudes towards sport psychology consulting. Sport & Exercise Psychology Review, 8, 32–44. Hardy, J., Oliver, E., & Tod, D. (2009). A framework for the study and application of selftalk within sport. In S. D. Mellalieu & S. Hanton (eds.), Advances in applied sport psychology: A review (pp. 47–84). United Kingdom: Routledge. Hardy, L., Barlow, M., Evans, L., Rees, T., Woodman, T., & Warr, C. (2017). Great British medallists: Psychosocial biographies of super-elite and elite athletes from Olympic sports. Progress in Brain Research, 232, 11–19. Hardy, L., Jones, J. G., & Gould, D. (1996). Understanding psychological preparation for sport: Theory and practice of elite performers. United States: Wiley. Holmes, P. S., & Collins, D. J. (2001). The PETTLEP approach to motor imagery: A functional equivalence model for sport psychologists. Journal of Applied Sport Psychology, 13, 60–83.

Psychological Preparation for Rugby

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Jackson, R. C., & Baker, J. S. (2001). Routines, rituals, and rugby: Case study of a world class goal kicker. The Sport Psychologist, 15, 48–65. Kingston, K. M., & Hardy, L. (1997). Effects of different types of goals on processes that support performance. The Sport Psychologist, 11, 277–293. Kingston, K. M., & Wilson, K. M. (2009). The application of goal setting in sport. In S. D. Mellalieu & S. Hanton (eds.), Advances in applied sport psychology: A review (pp. 85–133). United Kingdom: Routledge. Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57, 705–717. Lazarus, R. S. (1999). Stress and emotion: A new synthesis. United Kingdom: Free Association Books. McEwan, D., & Beauchamp, M. R. (2014). Teamwork in sport: A theoretical and integrative review. International Review of Sport and Exercise Psychology, 7, 229–250. Mellalieu, S. D. (2017). Sport psychology consulting in professional rugby union in the United Kingdom. Journal of Sport Psychology in Action, 8, 109–120. Mellalieu, S. D., Hanton, S., & O’Brien, M. (2004). Intensity and direction of competitive anxiety as a function of sport type and experience. Scandinavian Journal of Medicine & Science in Sports, 14, 326–334. Mellalieu, S. D., Hanton, S., & O’Brien, M. (2006). Performance behaviour modification as a function of goal setting strategies: A single-case design. Journal of Applied Behaviour Analysis, 39, 257–261. Mellalieu, S. D., & Hanton, S., & Shearer, D. (2008). The temporal patterning of the precompetitive psychological experience in elite rugby union. Journal of Sports Sciences, 25, 26–37. Mellalieu, S. D., Hanton, S., & Thomas, O. (2009). The effects of a motivational generalarousal imagery intervention upon preperformance symptoms in male rugby union players. Psychology of Sport and Exercise, 10, 175–185. Mellalieu, S., Jones, C., Wagstaff, C., Kemp, S., & Cross, M. J. (2021). Measuring psychological load in sport. International Journal of Sports Medicine, 42, 782–788. Mellalieu, S. D., Neil, R., Hanton, S., & Fletcher, D. (2009). Competition stress in sport performers: Stressors experienced in the competition environment. Journal of Sports Sciences, 27, 729–744. Murphy, S., Nordin, S. M., & Cumming, J. (2008). Imagery in sport, exercise and dance. In T. Horn (ed.), Advances in sport and exercise psychology (3rd ed., pp. 297–324). United States: Human Kinetics. Neil, R., Mellalieu, S. D., & Hanton, S. (2006). Psychological skills usage and the competitive anxiety response as a function of skill level in rugby union. Journal of Sports Science and Medicine, 5, 415–423. Neil, R., Hanton, S., & Mellalieu, S. D. (2013). Seeing things in a different light: Assessing the effects of a cognitive-behavioural intervention upon the further appraisals and performance of golfers. Journal of Applied Sport Psychology, 25, 106–130. Neil, R., & Thomas, O. (2014). Relaxation. In R. C. Eklund & G. Tenenbaum (eds.), Encyclopedia of Sport and Exercise Psychology (pp. 588–591). United States: Sage. Nicholls, A. R., Backhouse, S. H., Polman, R. C., & McKenna, J. (2009). Stressors and affective states among professional rugby union players. Scandinavian Journal of Medicine & Science in Sports, 19, 121–128. Nicholls, A. R., & Callard, J. (2012). Focused for rugby. United States: Human Kinetics. Nicholls, A. R., Holt, N. L., Polman, R. C. J., & Bloomfield, J. (2006). Stressors, coping and coping effectiveness among professional rugby union players. The Sport Psychologist, 20, 314–329.

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Nicholls, A. R., Jones, C. R., Polman, R. C., & Borkoles, E. (2009). Acute sport-related stressors, coping, and emotion among professional rugby union players during training and matches. Scandinavian Journal of Medicine & Science in Sports, 19, 113–120. Quarrie, K. L., Raftery, M., Blackie, J., Cook, C. J., Fuller, C. W., Gabbett, T. J., … & Lambert, M. (2017). Managing player load in professional rugby union: a review of current knowledge and practices. British Journal of Sports Medicine, 51, 421–427. Shearer, D. A. (2015). Collective efficacy at the Rugby World Cup 2015–The role of imagery and observation. European Journal of Sport Science, 15, 530–535. Tanaka, S., & Gould, D. (2015). Psychological skills usage among Japanese rugby players. International Journal of Sport and Exercise Psychology, 13, 309–319. Taylor, J., & Collins, D. (2019). Shoulda, Coulda, Didnae—Why don’t high-potential players make it? The Sport Psychologist, 33, 85–96. Tod, D., Hardy, J., & Oliver, E. (2011). Effects of self-talk: A systematic review. Journal of Sport and Exercise Psychology, 33, 666–687. Tod, D., Iredale, F., & Gill, N. (2003). ‘Psyching-up’ and muscular force production. Sports Medicine, 33, 47–58. Weinberg, R. S. (2019). Psychological skills training. In D. Hackfort, R. J. Schinke, & B. Strauss (Eds.). Dictionary of sport psychology: Sport, exercise and performing arts (pp. 230–231). Elsevier. Zinsser, N., Bunker, L. K., & Williams, J. M. (2006). Cognitive techniques for building confidence and enhancing performance. In J. Williams (Ed.), Applied sport psychology: Personal growth to peak performance (5th ed., pp. 349–381). United States: McGraw Hill.

11 PERFORMANCE ANALYSIS IN RUGBY Nimai Parmar, Nic James, and Wilbur Kraak

11.1 Introduction The popularity of performance analysis of sport can be observed through the proliferation of full-time positions within professional sport. Many professional and semi-professional team now employ performance analysts on a full-time basis and in a variety of roles that involve the use of video and/or data. These performance analysts work closely with coaching staff and other departments (for example the specialist skills coaches and strength and conditioning coaches) to provide insights into training, match, and opponent performances. Voluntary analysis positions are widespread for community clubs with some coaches undertaking some form of analysis themselves. Further to this, there has also been a development of analysts working in recruitment and scouting departments, supporting the processes for monitoring and acquiring players. This expansion within the applied sphere has also been mirrored within academic circles with the development of Sport Performance Analysis short courses, workshops, modules, and degrees. This growth has led to more academic performance analysis positions and thus there has been an increase in the quantity and quality of performance analysis research evidenced through publications, both in academic journals, conference proceedings, and book formats. Alongside this, sport performance data are widely integrated into media outlets, namely through television broadcasters, newspapers, magazines, and online sports related websites and blogs. These outlets are typically supported by third party data collection companies like Opta and Statsbomb who employ performance analysts to collect data on a variety of sports, resulting in agreements to access their data with clubs, leagues, sporting organisations, and other related industries like media and gambling. Sports science related research in rugby has historically focused on the anthropometric and physiological characteristics of players, with the basic premise being DOI: 10.4324/9781003045052-12

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that the bigger, stronger, and faster players are, the more likely they are to succeed. Whilst this can certainly play a factor in physical contact sports like rugby union and rugby league, the emergence of tactical and technical analysis of team and player performance has opened several research themes, which can provide useful insights into factors affecting rugby performance. Performance analysis is a subdiscipline of sports science and has been used to objectively audit and describe behaviours of players and teams during different facets of play in training and match-play, providing additional information for practitioners to improve future sports performance (McGarry et al., 2013; Vilar et al., 2012). This chapter therefore aims to explore the various key themes relating to performance analysis in both codes of rugby, whilst identifying emerging areas of interest which future research could focus on.

11.2 Performance indicators A study by Hendricks et al. (2020) developed a framework to improve the consistency of performance analysis data collection in rugby union, with an overarching aim of enhancing the quality of future research in the sport. This framework of performance indicator (PI) descriptors and definitions should be developed further for other rugby football codes such as rugby sevens and rugby league. PIs are “a selection, or combination, of action variables that aim to define some aspects of sports performance” (Hughes & Bartlett, 2002, p. 739). Therefore, these PIs help to quantify performance in sport (Vogelbein et al., 2014). To be informative, these performance indicators should be presented with context to allow for meaningful interpretations of performance to be made, for example, with opponent, peer, or past performances (Hughes & Bartlett, 2002) and/or accounting for independent variables like match venue, team, opposition quality, and match status where possible. PI research in rugby has had the general aim of exploring PIs that influence rugby performance and to try and gain a better understanding of how teams perform, both generally and in specific contexts. In rugby union, PIs have been identified at team level, namely effective kicking, lineout success on opposition ball, line breaks, tackle breaks, tackles completed, and turnovers won (Bennett et al., 2019; Jones et al., 2004; Ortega et al., 2009; Schoeman & Schall, 2019a; 2019b). In rugby league, teams had a higher chance of winning and gained more points when they scored first, gained more metres, offloaded the ball, and increased completed sets, whilst it was also identified that teams who increased PIs associated with “amount of possession” and “making quick ground” improved their chances of winning and scoring more points (Parmar et al., 2017; Parmar et al., 2018; Woods et al., 2017). These findings can be useful for coaches and practitioners to help plan training sessions and develop tactics and can also be used to build performance profiles of opponents. Readers should, however, interpret findings with caution and pay particular attention to the methods presented. For example, the competition that was analysed, when and how the data was collected including the operational definitions used and, finally, the context provided. Small differences in how these variables are categorised can have large impacts on subsequent results.

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A key limitation of performance analysis research to date has been the focus on outcome variables like set completion or possession, which is not useful for informing the processes that enable these to successfully take place (James, 2009). Rather, it is suggested for studies to look at process variables like passes, carries, metres gained, line breaks that are likely to lead to a completed set which will provide coaches with actionable insights to impact performance (Parmar et al., 2017). Typical techniques to identify PIs involve the comparison of performance variables between winning and losing teams or identifying variables that best predict match outcome/points difference. However, this approach can provide some limitations, namely that analysing these variables in isolation can be misleading. For example, saying performing one more completed set will result in an increased chance of winning or gaining points, as rugby union and rugby league are multifaceted the relationship between variables are often complex in nature and interdependent of each other. Parmar et al. (2018) utilised principal component analysis to group variables that were explaining similar variances in the dataset. For example, by improving performances on a collection of variables that formed the component “making quick ground,” like supported breaks, breaks, tackles busts, and support carries, teams were more likely to succeed. In addition, when investigating factors that lead to success, variables relating to match outcome should be excluded to allow for more meaningful insights to be gained from the resultant analysis. There are several areas for future research directions to be explored, investigations should focus on identifying PIs according to the different playing positions found in rugby teams and extend research to cover women’s rugby competitions. Future research should take these considerations into account, whilst providing context to their data and findings. In addition, research should also build upon clustering methods to identify patterns according to match outcome in rugby union (Coughlan et al., 2019; Croft et al., 2015) and dimension reduction techniques in rugby league (Parmar et al., 2018) which help to reduce substantial datasets with a large number of variables into smaller components, making it easier to understand and interpret performance. Finally, research could be undertaken to assess team performances according to whether a team has come back from being in a losing position to a winning position (Gomez et al., 2020).

11.3 Performance profiling Performance profiles are a collection of action variables and or PIs that are used to represent typical teams and or athlete’s performance (Hughes et al., 2001; Liu et al., 2015; O’Donoghue, 2005). These profiles are usually visual representations of sports performance and are often used in applied settings, for example, by coaching staff and performance analysts to inform training session design, training activities, and match tactics for a specific opponent or official. This information is often used to prepare reports for a specific opponent in an upcoming match and identify strengths and weaknesses in team’s own performances. Therefore, it is important that the methods employed provide the end-users with confidence in

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the data and story that is told. The two main methods used to create these profiles have been to calculate confidence intervals of medians (James et al., 2005) and quantiles (O’Donoghue, 2005). James et al. (2005) utilised medians and their confidence intervals to develop position specific profiles of rugby union performance on an intra- and inter-positional basis, with players only included if they had played more than five matches. The techniques utilised enabled the development of individual player performance profiles and enabled intra-positional comparisons, with differences evident between individuals within all the playing positions investigated. These included passing, ball carries and tackling for the forwards, and passing, carrying, tackling, and kicking for the backs. James et al. (2005) highlighted future profiles should include the effects of independent variables such as team and opposition quality, therefore alluding to the fact that one profile may be inadequate. Despite the importance of performance profiles in understanding team and positional performances, little research has been undertaken in both codes of rugby, especially in rugby league. As such, this remains an area that should be developed further, as the game continues to evolve over time. Methods of profiling should include the use of confidence intervals (a range of values that we expect performance to fall within), z-scores (describe a value’s relationship to the average), and percentiles (a value that falls within a percentage of scores) to help analysts in the applied world to have confidence in the story that they are giving to coaches and players. Previous research (Hughes et al., 2001) suggested that an evolving mean and tolerable percentages of the mean could be used to determine how many matches are sufficient to create “stable” profiles. However, O’Donoghue (2005) suggested that meaningful differences could be lost using this method. There is yet to be sufficient guidance on how many matches are suitable for representative profiles, and it is questionable to expect performances to ever stabilise due to the unpredictable nature of sport (James et al., 2005) whilst also retaining the important between match variability that is lost with larger sample sizes. It is therefore important that authors utilise sufficient context when creating profiles (see Figure 11.1), for example, score margin (i.e., points differential), match venue, team and opposition quality, past performances, etc. and utilise standardised techniques to achieve this (Jones et al., 2008). Finally, ideographic approaches to profiling performance may be more relevant for practitioners compared to analysing large datasets where detailed and meaningful information on performances can sometimes be lost.

11.4 Technique analysis Rugby union and league are both physical sports, with players having to make contact with opponents to prevent them from scoring points, typically through performing tackles on players with possession of the ball. Therefore, it is no surprise that rugby, and in particular rugby union, has the highest incidence of overall injuries sustained compared to other team sports (Brooks & Kemp, 2008). This higher incidence could be attributed to the more physical contact between

Example standardised performance profiles of opposing rugby league teams, based on their previous five matches, according to score margin (defined as unbalanced when the team won or lost by more than 12 points (two tries) or balanced when less than 12 points).

FIGURE 11.1

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players, more specifically, tackling accounts for more than 61% of injuries in rugby league (Hopkinson et al., 2022a) and 50% of injuries in rugby union (Quarrie & Hopkins, 2008). This has led to the use of video-based performance analysis methods to assess tackling techniques by scoring the technique of the players, with research being undertaken to better understand the contributing factors to tacklerelated injuries. This research has revealed that there is a decreased risk of injury when performance improves during tackling events (Burger et al., 2016; Davidow et al., 2018; Hendricks et al., 2016) highlighting the benefits of using video-based performance analysis to assess technique. This has led on to the development of video analysis frameworks in rugby union (Hendricks et al., 2020) and in rugby league (Hopkinson et al., 2022b) allowing for the classification of complex tackle events. The framework proposed by Hendricks et al. (2020) divided the tackle event into three phases: pre-contact (preparation), contact (action), and postcontact (follow through). Each of these phases have assessment points for both the tackler and ball-carrier allowing for an in-depth analysis of the tackle event. The framework also includes the tackle outcomes like tackle result, injury, territorial dominance, and infringements whilst accounting for contextual factors like match period, match status and field position. As the gameplay in rugby league differs from rugby union, in particular, the fact there are six tackles before a turnover which promotes actions and strategies that keep the ball alive, like offloading the ball, Hopkinson et al. (2021) argued the need for a separate framework and variables to assess the rugby league tackle event due to the different behaviours exhibited. This framework assessed the phases as follows: (1) tackle event, (2) defensive start point, (3) pre-contact phase, (4) initial contact phase, (5) postcontact phase, and (6) play the ball phase. Both of these rugby league and rugby union video analysis frameworks for assessing tackling, will facilitate the expansion of future rugby research to be conducted in a consistent approach allowing for fair comparisons to be made between studies. Future research should also consider the inclusion of the analysis of the spatial and temporal interactions between players, both within and between teams, based on their locations on the pitch. This information should provide an increased understanding of injuries sustained in rugby. Furthermore, research can be extended to assess whether law changes can reduce incidences of injury, with some research being undertaken already. For example, Stokes et al. (2021) assessed whether reducing the height of the tackle through law changes reduced the incidence of concussion in elite men’s rugby union which included the assessment of tackle videos, finding that the lower tackle height resulted in 30% less contacts with the ball carriers head and neck in the tackle by defenders. Surprisingly, they found that this did not influence concussion incidence rates and tacklers suffered more concussions in the lowered tackle height setting compared to the standard height setting. Tackle and ruck events are the most common phases of play, with the ruck occurring ~116 times during an 80minute match (Hendricks et al., 2014). The second highest proportion of injuries (6–17%) at a professional level occur during the ruck (Fuller et al., 2007; Hendricks & Lambert, 2010; Posthumus & Viljoen, 2008; Roberts et al., 2015).

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Kraak et al. (2019) analysed a total of 22,281 ruck cleanouts during the 2018 Super Rugby competition of which 2,111 (9.0%) were deemed illegal. Of the illegal cleanouts (n = 2,111), 93.0% (n = 1,953) were not sanctioned by the on-field referee although 51.0% (n = 1,087) were considered dangerous. The ruck and the tackle are the most frequently occurring events in rugby union. More video-based performance analysis research is needed in these areas to increase our understanding of injury risks and the effectiveness of law changes in reducing injuries.

11.5 Considerations for future research areas This section suggests areas which future research could focus on and be of interest to practitioners and academics that work in both codes of rugby. This includes momentum, dynamical systems theory, and linking tracking data more closely to PIs.

11.5.1 Momentum Momentum is a word regularly used in sport, and in particular the media, to describe a pattern of repeated advantageous events and or outcomes. In rugby, this could be linked to possession and phase outcomes like successive positive outcomes from events like territorial gain, penalties won and tries scored to name a few. Momentum theory has been researched in psychology, initially by Adler (1981, p. 29) who defined momentum as “a state of dynamic intensity marked by an elevated or depressed rate in motion, grace and success.” More recently, Cotterill (2013) described psychological momentum as the positive or negative perception of a team or individual working towards/away from a successful outcome. In contrast, behavioural momentum, considers the observable actions and how these may contribute towards progress towards/away from a successful outcome (Wanzek et al., 2012) and seems more appropriate for performance analysis research. Momentum from this behavioural perspective has been under-researched due to the inherent problems with defining momentum and therefore reliable ways to code and interpret it. Despite these challenges, some momentum research has been undertaken in a variety of sports such as handball (Mortimer & Burt, 2014), basketball (Morgulev et al., 2020), and tennis (Den Hartigh & Gernigon, 2018). However, in both codes of rugby, little to no research has been published, leaving a big gap in the literature. Momentum could be linked to phase and possession outcomes, with events being weighted and scored based on whether they are deemed to be positive. For example, tries scored, territorial gain, penalties won, possession retained etc. On the other hand, they could be considered negative and scored accordingly, like territory loss, tries conceded, penalties conceded, turnovers, and possession loss. This information can be utilised to create momentum charts (Figure 11.2) and assess the impact that this has on performance. Further detail can be added by examining the factors that affect these events. For example, ruck speed in rugby union or play the ball speed in rugby league, both in relation

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TEAM A

TEAM B

An example momentum graph of opposing rugby union teams from a competitive match.

FIGURE 11.2

to possession being retained, as an indicator of success. Furthermore, weighting scores according to the complexity of the event is practical as it can allow for differentiation between positive and negative outcomes.

11.5.2 Dynamical systems theory It has been suggested that performance analysis, as a research and coaching tool, should have a sound theoretical rationale to explain performance behaviours and not just to describe them (Vilar et al., 2012). The dynamical systems theory can be used to conceptualise stability and variability in team sport by considering the complex temporal patterns that characterise performance (McGarry et al., 2002). It considers how sport performance fluctuates through stable and unstable states and the resultant self-organisation in response to these changes in system states. This allows for the detection of emergent patterns in data through the analysis of interactions between players and teams. This analysis advances the more traditional descriptive based analysis of isolated variables and can help gather useful insights to sports performance. However, dynamical systems theory in rugby union, and in particular rugby league, remains largely unexplored, this is partly due to the limitations in XY coordinate data being collected presently. Passos et al. (2008) assessed interpersonal distances and how relative velocity affected attacker-defender dyads occurring in youth rugby union. The authors observed that relative velocity increased its influence on the organisation of dyads when players changed their running line direction, increasing speed or both; however, this work has not been extended to adult elite rugby union. Correia et al. (2011) utilised distance gained (distance between initial ball position and ball current

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position over time) as a potential coordination variable, using this measure to describe the coordination between players and teams, finding that successful attacking phases had lower distances of positional retreat. There was evidence of less regularity and more complexity in unsuccessful phases of play. This analysis provided some insight into collective behaviour patterns in team sports like rugby union where there are multiple players and attack and defences systems. Future research could expand this work by identifying control parameters that might provide context and by also accounting for the influence of ball location on behaviour patterns. There are many opportunities for research to be undertaken utilising dynamical systems theory to assess team dispersion, interpersonal distances, and co-ordination networks to better understand sport performance and how this relates to player and team behaviours/ organisation. This may provide meaningful insights into how certain successful events occur like how teams gain territory, make line breaks, and score tries.

11.5.3 Perturbations Considered as part of dynamical systems theory, a perturbation was defined by Hughes et al. (1998) in soccer as an incident that changed the rhythmic flow of attacking and defending leading to a shooting opportunity or “critical incident.” In squash, experts were able to consistently identify shots that gave players a clear advantage over their opponents, i.e., events that changed the match state from stable to unstable or vice versa and therefore be considered to be perturbations (McGarry et al., 1999). Perturbations are therefore an attempt to change the state from a stable situation to an unstable situation. Kim et al. (2019a) identified that previous perturbation research in soccer did not provide satisfactory definitions of either stable or unstable events or perturbations. The authors consequently aimed to produce robust definitions for unstable events to help aid the identification of perturbations in forthcoming research. Future rugby union and rugby league research into perturbations should take these principles into consideration since if unstable and stable situations can be reliably differentiated, it would aid the identification of perturbations. It can lead on to the development of frameworks for categorising the attacking process in rugby, like those that have been created for soccer (Kim et al., 2019b). Limited research exists on perturbations in rugby, with Barkell et al. (2017) investigating perturbation effects in men’s and women’s international sevens, finding that winning teams created more perturbations and had a higher proportion of those perturbations resulting in tries compared to losing teams, with no differences between sexes. Therefore, there is scope for research to be undertaken in both codes of rugby, which can eventually be extended to create a try scoring threat value by utilising player and ball positions.

11.5.4 Tracking data There has been a recent expansion of research undertaken using tracking data in soccer (Goes et al., 2021) and other sports like basketball (Sampaio et al., 2015),

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with player tracking technology providing opportunities to gain new insights into sport performance through spatiotemporal analysis. This expansion has occurred due to data collection companies employing various methods to collect this spatiotemporal data, including global navigation satellite systems (GNSS), radio-based local positioning systems (LPS) and video/optical tracking systems, with most the world’s top soccer leagues utilising optical tracking systems (Buchheit & Simpson, 2017). These optical tracking systems are popular as they are the only nonintrusive solution that can track both the ball and players simultaneously using video footage and therefore less prone to data loss (i.e., sensor failures) as experienced when using physical equipment and accuracy issues faced with GNSS systems in stadiums (Linke et al., 2020). However, these systems are not being widely used within rugby union or rugby league competitions, thus there is a distinct lack of research being undertaken. Opportunities to better understand playing styles and patterns, formations, ball possessions, defensive pressure, how space is created, and line breaks are all possible avenues for future research. Tracking data can be merged with technical data to provide greater insights into performance than seen before in rugby union and could mark an exciting step forward in gaining better understanding of sport performance in both codes of rugby for both academics and practitioners alike. Lessons learned from soccer (Low et al., 2020) should be considered such as contextualising positional data, whilst understanding and integrating needs of practitioners and coaching staff when designing future research to better bridge the research-practice gap.

11.6 Conclusion This chapter has outlined research that has been undertaken in both codes of rugby whilst also presenting avenues for future research to be undertaken. Whilst research has primarily focused on PIs in isolation using a largely reductionist approach, there are opportunities to gain more meaningful insights into performance through analysing collections of variables, e.g., process variables. Most exciting is the opportunities to further develop our understanding of rugby through modelling momentum, utilising dynamical systems theory, identifying perturbations and exploring tracking data. Research needs to bridge the theory to practice gap as faced in other sports like soccer (Mackenzie & Cushion, 2013) and produce research that has practical relevance. Research needs to consider providing adequate context, e.g., match venue, team and opposition quality, match status, and ensure that sufficient sample sizes are utilised. On the other hand, practitioners need to balance their expectations of becoming experts in all areas and methods (as mentioned in this chapter) within performance analysis. Striking this balance will ensure consistent and appropriate approaches to performance analysis are used in both applied and academic settings. Finally, the majority of research undertaken to date has focused on the men’s rather than women’s game and should therefore be a focus for future work given the growing popularity of the sport.

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References Adler, P. (1981). Momentum: A theory of social action. Beverly Hills, CA: SAGE Publications. Barkell, J. F., O’Connor, D., & Cotton, W. G. (2017). Perturbation effects in men’s and women’s international sevens. International Journal of Performance Analysis in Sport, 17(1-2), 17–33. Bennett, M., Bezodis, N., Shearer, D. A., Locke, D., & Kilduff, L. P. (2019). Descriptive conversion of performance indicators in rugby union. Journal of Science and Medicine in Sport, 22(3), 330–334. Brooks, J., & Kemp S. (2008). Recent trends in rugby union injuries. Clinics in Sports Medicine, 27(1), 51–73. Buchheit, M., & Simpson, B. M. (2017). Player-tracking technology: Half-full or halfempty glass? International Journal of Sports Physiology and Performance, 12(s2), S235–S241. Burger, N., Lambert, M. I., Viljoen, W., Brown, J. C., Readhead, C., & Hendricks, S. (2016). Tackle technique and tackle-related injuries in high-level South African Rugby Union under-18 players: Real-match video analysis. British Journal of Sports Medicine, 50(15), 932–938. Correia, V., Araújo, D., Davids, K., Fernandes, O., & Fonseca, S. (2011). Territorial gain dynamics regulates success in attacking sub-phases of team sports. Psychology of Sport and Exercise, 12(6), 662–669. Cotterill, S. (2013). Team psychology in sports: Theory and practice. Abingdon: Routledge. Coughlan, M., Mountifield, C., Sharpe, S., & Mara, J. K. (2019). How they scored the tries: Applying cluster analysis to identify playing patterns that lead to tries in super rugby. International Journal of Performance Analysis in Sport, 19(3), 435–451. Croft, H., Lamb, P., & Middlemas, S. (2015). The application of self-organising maps to performance analysis data in rugby union. International Journal of Performance Analysis in Sport, 15(3), 1037–1046. Davidow, D., Quarrie, K., Viljoen, W., Burger, N., Readhead, C., Lambert, M., Jones, B., & Hendricks, S. (2018). Tackle technique of rugby union players during head impact tackles compared to injury free tackles. Journal of Science and Medicine in Sport, 21(10), 1025–1031. Den Hartigh, R. J., & Gernigon, C. (2018). Time-out! How psychological momentum builds up and breaks down in table tennis. Journal of Sports Sciences, 36(23), 2732–2737. Fuller, C., Brooks, J., Cancea, R., Hall, J., & Kemp, S. (2007). Contact events in rugby union and their propensity to cause injury. British Journal of Sports Medicine, 41(12), 862–867. Goes, F. R., Meerhoff, L. A., Bueno, M. J. O., Rodrigues, D. M., Moura, F. A., Brink, M. S., … & Lemmink, K. A. P. M. (2021). Unlocking the potential of big data to support tactical performance analysis in professional soccer: A systematic review. European Journal of Sport Science, 21(4), 481–496. Gomez, M. A., Reus, M., Parmar, N., & Travassos, B. (2020). Exploring elite soccer teams’ performances during different match-status periods of close matches’ comebacks. Chaos, Solitons & Fractals, 132, 109566. Hendricks, S., & Lambert, M. (2010). Tackling in rugby: Coaching strategies for effective technique and injury prevention. International Journal of Sports Science and Coaching, 5(1), 117–136. Hendricks, S., Matthews, B., Roode, B., & Lambert, M. (2014). Tackler characteristics associated with tackle performance in rugby union. European Journal of Sport Science, 14(8), 753–762. Hendricks, S., O’Connor, S., Lambert, M., Brown, J. C., Burger, N., Mc Fie, S., … & Viljoen, W. (2016). Video analysis of concussion injury mechanism in under-18 rugby. BMJ Open Sport and Exercise Medicine, 2(1), e000053. Hendricks, S., Till, K., Den Hollander, S., Savage, T. N., Roberts, S. P., Tierney, G., … & Jones, B. (2020). Consensus on a video analysis framework of descriptors and definitions

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by the Rugby Union Video Analysis Consensus group. British Journal of Sports Medicine, 54(10), 566–572. Hopkinson, M., Nicholson, G., Weaving, D., Hendricks, S., Fitzpatrick, A., Naylor, A., … & Jones, B. (2022a). Rugby league ball carrier injuries: The relative importance of tackle characteristics during the European Super League. European Journal of Sport Science, 22(2), 269–278. Hopkinson, M., Bissas, A., Nicholson, G., Beggs, C., Scantlebury, S., Hendricks, S., & Jones, B. (2022b). A video analysis framework for the rugby league tackle. Science and Medicine in Football, 6(1), 15–28. Hughes, M. D., & Bartlett, R. M. (2002). The use of performance indicators in performance analysis. Journal of Sports Sciences, 20(10), 739–754. Hughes, M., Dawkins, N., David, R., & Mills, J. (1998). The perturbation effect and goal opportunities in soccer. Journal of Sports Sciences, 16(1), 20. Hughes, M., Evans, S., & Wells, J. (2001). Establishing normative profiles in performance analysis. International Journal of Performance Analysis in Sport, 1(1), 1–26. James, N. (2009). Performance analysis of golf: Reflections on the past and a vision of the future. International Journal of Performance Analysis in Sport, 9(2), 188–209. James, N., Mellalieu, S., & Jones, N. (2005). The development of position-specific performance indicators in professional rugby union. Journal of Sports Sciences, 23(1), 63–72. Jones, N. M., James, N., & Mellalieu, S. D. (2008). An objective method for depicting team performance in elite professional rugby union. Journal of Sports Sciences, 26(7), 691–700. Jones, N. M., Mellalieu, S. D., & James, N. (2004). Team performance indicators as a function of winning and losing in rugby union. International Journal of Performance Analysis in Sport, 4(1), 61–71. Kim, J., James, N., Parmar, N., Ali, B., & Vučković, G. (2019a). Determining unstable game states to aid the identification of perturbations in football. International Journal of Performance Analysis in Sport, 19(3), 302–312. Kim, J., James, N., Parmar, N., Ali, B., & Vučković, G. (2019b). The attacking process in football: A taxonomy for classifying how teams create goal scoring opportunities using a case study of Crystal Palace FC. Frontiers in Psychology, 10, 2202. Kraak, W., Bam, J., Kruger, S., Henderson, S., Josias, U., & Stokes, K. (2019). Sanctioning of illegal and dangerous ruck cleanouts during the 2018 super rugby competition. Frontiers Psychology, 10, 803. Linke, D., Link, D., & Lames, M. (2020). Football-specific validity of TRACAB’s optical video tracking systems. PloS one, 15(3), e0230179. Liu, H., Yi, Q., Giménez, J. V., Gómez, M. A., & Lago-Peñas, C. (2015). Performance profiles of football teams in the UEFA Champions League considering situational efficiency. International Journal of Performance Analysis in Sport, 15(1), 371–390. Low, B., Coutinho, D., Gonçalves, B., Rein, R., Memmert, D., & Sampaio, J. (2020). A systematic review of collective tactical behaviours in football using positional data. Sports Medicine, 50(2), 343–385. Mackenzie, R., & Cushion, C. (2013). Performance analysis in football: A critical review and implications for future research, Journal of Sports Sciences, 31(6), 639–676. McGarry, T., Anderson, D. I., Wallace, S. A., Hughes, M. D., & Franks, I. M. (2002). Sport competition as a dynamical self-organizing system. Journal of Sports Sciences, 20(10), 771–781. McGarry, T., Khan, M. A., & Franks, I. M. (1999). On the presence and absence of behavioural traits in sport: An example from championship squash match-play. Journal of Sports Sciences, 17(4), 297–311.

Performance Analysis in Rugby

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McGarry, T., O’Donoghue, P., Sampaio, J., & de Eira Sampaio, A. J. (eds.). (2013). Routledge handbook of sports performance analysis. Routledge. Morgulev, E., Azar, O. H., & Bar-Eli, M. (2020). Searching for momentum in NBA triplets of free throws. Journal of Sports Sciences, 38(4), 390–398. Mortimer, P., & Burt, W. E. (2014). Does momentum exist in elite handball? International Journal of Performance Analysis in Sport, 14(3), 788–800. O’Donoghue, P. (2005). Normative profiles of sports performance. International Journal of Performance Analysis in Sport, 5(1), 104–119. Ortega, E., Villarejo, D., & Palao, J. M. (2009). Differences in game statistics between winning and losing rugby teams in the Six Nations Tournament. Journal of Sports Science and Medicine, 8(4), 523. Parmar, N., James, N., Hearne, G., & Jones, B. (2018). Using principal component analysis to develop performance indicators in professional rugby league. International Journal of Performance Analysis in Sport, 18(6), 938–949. Parmar, N., James, N., Hughes, M., Jones, H., & Hearne, G. (2017). Team performance indicators that predict match outcome and points difference in professional rugby league. International Journal of Performance Analysis in Sport, 17(6), 1044–1056. Passos, P., Araújo, D., Davids, K., Gouveia, L., Milho, J., & Serpa, S. (2008). Informationgoverning dynamics of attacker–defender interactions in youth rugby union. Journal of Sports Sciences, 26(13), 1421–1429. Posthumus, M., & Viljoen, W. (2008). BokSmart: Safe and effective techniques in rugby union. South African Journal of Sports Medicine, 20(3), 64–68. Quarrie, K. L., & Hopkins, W. G. (2008). Tackle injuries in professional rugby union. The American Journal of Sports Medicine, 36(9), 1705–1716. Roberts, S., Trewartha, G., England, M., & Stokes, K. (2015). Collapsed scrums and collision tackles: What is the injury risk? British Journal of Sports Medicine, 49(8), 536–540. Sampaio, J., McGarry, T., Calleja-González, J., Jiménez Sáiz, S., Schelling i del Alcázar, X., & Balciunas, M. (2015). Exploring game performance in the National Basketball Association using player tracking data. PloS One, 10(7), e0132894. Schoeman, R., & Schall, R. (2019a). Comparison of match-related performance indicators between major professional rugby competitions. International Journal of Sports Science and Coaching, 14(3), 344–354. Schoeman, R., & Schall, R. (2019b). Team performance indicators as predictors of final log position and team success in Aviva Premiership, Guinness Pro 14, French Top 14 and Super Rugby. International Journal of Performance Analysis in Sport, 19(5), 763–777. Stokes, K. A., Locke, D., Roberts, S., Henderson, L., Tucker, R., Ryan, D., & Kemp, S. (2021). Does reducing the height of the tackle through law change in elite men’s rugby union (The Championship, England) reduce the incidence of concussion? A controlled study in 126 games. British Journal of Sports Medicine, 55(4), 220–225. Vilar, L., Araújo, D., Davids, K., & Button, C. (2012). The role of ecological dynamics in analysing performance in team sports. Sports Medicine, 42(1), 1–10. Vogelbein, M., Nopp, S., & Hökelmann, A. (2014). Defensive transition in soccer—are prompt possession regains a measure of success? A quantitative analysis of German Fußball-Bundesliga 2010/2011. Journal of Sports Sciences, 32(11), 1076–1083. Wanzek, J. S., Houlihan, D. D., & Homan, K. J. (2012). An examination of behavioral momentum in girl’s high school volleyball. Journal of Sport Behavior, 35(1), 94–107. Woods, C. T., Sinclair, W., & Robertson, S. (2017). Explaining match outcome and ladder position in the National Rugby League using team performance indicators. Journal of Science and Medicine in Sport, 20(12), 1107–1111.

12 THE BIOMECHANICS OF RUGBY Neil E. Bezodis, Ezio Preatoni, Dario Cazzola, and Elena Seminati

12.1 Introduction Rugby players and practitioners deal with biomechanical principles daily. A sound understanding of biomechanics can be beneficial for player performance and player welfare. When applied to sporting techniques, biomechanics is “the science concerned with the internal and external forces acting on a human body and the effects produced by these forces” (Hay, 1985, p. 2). Biomechanics can be divided in to two branches: kinetics, which studies the forces causing motion, and kinematics, which describes the movements caused by these forces. Practitioners cannot directly “see” kinetic quantities such as forces or torques, although players frequently feel the effects of forces applied to their bodies by external factors (e.g., gravity, the ground, other players) and transferred through the body. Kinematic descriptors of motion (displacement, velocity, acceleration) are directly determined by kinetic quantities and are often highly evident. However, there are other situations where players could be subjected to high forces without much visible motion. For example, a prop in a stationary scrum is a situation where many large forces are acting on a player but are approximately equal and opposite, and thus no movement is generated in this quasi-static system. Rugby comprises numerous activities ranging from static through to highly dynamic and it is often the ability of a player to accelerate or decelerate themselves, an opponent, or the ball – or to resist such motion – which will determine the outcome of a phase of play. This chapter aims to provide an overview of the current scientific evidence relating to the biomechanics of different rugby activities, primarily from research in rugby union, with the intention of making this information applicable for the practitioner who may previously only have a limited knowledge of biomechanics. DOI: 10.4324/9781003045052-13

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12.2 Biomechanical analyses of rugby activities Numerous rugby union activities play an important role in determining match outcome. For example, it has been shown that teams who perform more line breaks, kick more, miss fewer tackles, and win more set piece ball, amongst a range of other indicators, have a greater likelihood of winning in international and domestic competitions (Bennett et al., 2019, 2021; Coughlan et al., 2019; Ortega et al., 2009; Vaz et al., 2010; Watson et al., 2017). Clearly there is a wealth of coaching expertise regarding the techniques used which is not captured in the scientific literature for various reasons, not least the challenges of accurately quantifying biomechanics in a realistic environment. This chapter does not intend to replace this important coaching knowledge, but to supplement it with scientific evidence to support and challenge existing coaching philosophies, ideas, and approaches, as well as to identify areas which scientific research should seek to support in the future.

12.3 Lineout The lineout restarts play after the ball, or a player carrying the ball, crosses the touchline. A successful lineout requires the coordination of multiple players with different roles including throwing, lifting, and catching, and lineouts can be used tactically to set up other match activities such as a maul. Like many activities discussed throughout this chapter, there is not a single lineout throwing technique for all (Trewartha et al., 2008) but certain technical features are associated with successful lineout throwing performance. Like most target skills, the thrower’s accuracy decreases as throw distance increases. This is potentially due to them being less stable to achieve the greater release velocities and higher release angles required (Kneblewski et al., 2020). Greater release velocities are typically achieved from a more “cocked” (retracted) arm and upper trunk position at the top of the backswing, followed by increased extension of the legs, particularly from the knee (Sayers, 2011; Trewartha et al., 2008). Ball release typically occurs from a relatively consistent upper body configuration irrespective of throw distance as arm movements appear highly repeatable during the throwing action, helping the thrower to control torso position which minimises head movements (Sayers, 2011). The greater leg extension therefore enables longer distances to be achieved without any discernible increase to the shoulder or elbow angular velocities, particularly in accurate throwers, whilst knee extension also appears to play a role controlling throw trajectory (e.g., flat versus lob; Trewartha et al., 2008). Relatively little is known about the biomechanics of lineout lifting, although by maintaining their support of the jumper until landing, lifters reduce the external force loading rates which jumpers experience upon landing (Sinclair et al., 2017a). Simple models have revealed that the jumper’s attempted jump height, the point of force application from the lifters, and the magnitude of the forces they apply all influence the time to peak height, the quickness of jump initiation and/or the

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potential for a deception strategy (Smith et al., 2018). These factors therefore all need careful consideration depending on the purpose of a particular line-out call.

12.4 Scrum The scrum restarts play after a minor infringement or stoppage. Three main phases of the scrum can be identified from the referee’s calls. Firstly, during the scrum formation, players bind with their teammates, face the opponents at no more than an arm’s length, adopt a stable crouched position with no contact between teams at the “crouch” call, and then each prop grabs their opponent’s jersey at the “bind” call. Secondly, the engagement then happens when the referee calls “set” and the two front rows come together, leaving a tunnel for ball entry, and creating a platform for the pushing contest. Finally, the sustained push is characterised by intense pushing between the two teams (World Rugby, 2022). From a simple biomechanical perspective, scrum performance could be assessed through two main measures: the amount of force generated and sustained, and the ability to maintain the correct shape despite the forces applied by the opponents (i.e., stability). However, the scrum is an extremely complex system with many interactions between players, and multiple kinematic and kinetic factors affect both performance and injury outcomes. Owing to the lack of measurement technologies that can be used under realistic, match-type conditions, most biomechanical studies have used simplified scenarios (e.g., fewer players, machine scrummaging, synthetic turf; Martin & Beckham, 2020). Injury risk, player safety, and global changes to the scrum laws in 2007 (“crouch-touch-pause-engage”) and 2013 (“crouch-bind-set”; World Rugby, 2022) have sparked more recent interest in scrum biomechanics, which only a few authors (e.g., Du Toit et al., 2004, 2005; Milburn, 1990, 1993, 1994; Milburn & O’Shea, 1994; Quarrie & Wilson, 2000; Rodano & Tosoni, 1992) had previously analysed. The engagement and sustained push phase have been the focus, and biomechanical studies were used to inform the regulatory changes introduced (Cazzola et al., 2015a; Preatoni et al., 2013, 2015, 2016; Trewartha et al., 2015). The replacement of the “… touch-pause-engage” with “… bind-set” calls has (1) decreased the distance between the two front rows at scrum formation by ~0.13 m (~27%), (2) lowered the maximum closing speed between teams at the engagement by ~0.41 m·s−1 (~17%) which consequently (3) reduced peak impact forces by 2 kN on average (~24%), and (4) caused fewer scrum disruptions and improved stability (Cazzola et al., 2015a; Preatoni et al., 2016). The effects of the new rules on the mechanical load experienced by players have been observed across all playing standards (Martin & Beckham, 2020; Preatoni et al., 2013, 2015, 2016; Figure 12.1) and observational studies from the seasons after the introduction of the new engagement calls have reported a general trend towards fewer collapses, resets and infringements (e.g., early engagement, pulling down; Bradley et al., 2018), together with a decline in catastrophic injuries (Hendricks et al., 2014; Reboursiere et al., 2018). However, Preatoni et al. (2015) reported larger upward

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FIGURE 12.1

forces during the sustained push in machine scrummaging with the newer calls which could generate increased spinal stresses if carried over to contested scrums, and Swaminathan et al. (2016a) observed no changes in spinal movements for the hooker in live scrummaging. Law changes have also reduced the focus on the initial impact for tactical dominance, and teams have shifted their attention to the sustained push (Bradley et al., 2018; Martin & Beckham, 2020). De-emphasizing the high-energy engagement has not affected the ability of teams to generate propulsive force during and after the introduction of the ball. An increase in playing standard corresponds

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to higher forces in the sustained push during machine scrummaging, with this trend becoming less clear in live scrums, where measured forces are about half of those measured with instrumented scrum machines (Martin & Beckham, 2020; Preatoni et al., 2016), and range between ~4.1 kN (~47% of the combined pack weight) for international teams and 2.8 kN (~35% of the pack weight) for community standard packs (Preatoni et al., 2016; Figure 12.1). Also, the scrum contact phase appears to be lasting longer (from an average of 7.5 s in 2013 to 10.8 s in 2016; Bradley et al., 2018), which could raise issues related to muscle conditioning and fatigue. Neck and trunk muscle activation has been studied in both machine (Cazzola et al., 2015b; Sharp et al., 2014) and live (Cazzola et al., 2015b) scrummaging, with the latter eliciting a higher response during the sustained push phase, most likely because of more unstable conditions (Cazzola et al., 2015b). Machine scrummaging also facilitates more synchronous leg muscle activation than live scrummaging, with professional players showing improved ability to recruit muscle faster and more synchronously than players from lower standards (Yaghoubi et al., 2019). These findings suggest that training should incorporate live scrummaging sessions to better prepare players’ back and neck musculature for match situations. In the “crouchbind-set” call, muscles of the neck and upper trunk are more active than during the “crouch-touch-pause-engage” sequence, which may be to better prepare the cervical area to receive the engagement load given that these are activated before contact (Cazzola et al., 2015b; Wang et al., 2018). Contrasting results have been reported on the effect of fatigue on scrummaging technique and performance. Some authors have not found clear evidence that multiple scrum executions or simulated match efforts significantly affect player performance (Cochrane et al., 2017; Green et al., 2017a). Conversely, other studies have shown repeated scrummaging to induce greater muscle fatigue in knee extensors (~21% reduction in muscle activation) and performance (~23% less pushing force) than other rugby-related tasks such mauls and sprints (Morel et al., 2015). This could be an important aspect to consider and explore further for tactical (e.g., replacements during a match) and recovery (active versus passive) choices, and player-specific training (Bradley et al., 2018; Morel & Hautier, 2016; Morel et al., 2015). Many authors have tried to identify what factors are most influential for improving overall scrum performance. The tight-five players are the primary contributors to the scrum, generating up to ~80% of the total force (Du Toit et al., 2004, 2005; Martin & Beckham, 2020; Milburn, 1993; Preatoni et al., 2015), and between-player coordination appears to be a key factor for performance, outweighing individual force generating capabilities in isolation (Milburn, 1993; Quarrie & Wilson, 2000). Although body mass was a key factor in determining peak compression forces during old engagement sequences (Du Toit et al., 2005; Martin & Beckham, 2020; Preatoni et al., 2016; Quarrie & Wilson, 2000), it is only moderately associated with sustained push abilities – technique seems to play a bigger role (Du Toit et al., 2005; Green et al., 2017b; Martin & Beckham, 2020; Preatoni et al., 2016; Quarrie & Wilson, 2000).

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Several studies have analysed the effect of body position and have found a wider stance width (parallel feet), a lower back and pelvis height (~49% and 42% of player height, respectively; Green et al., 2017b; Wu et al., 2007), a straighter back (Green et al., 2017b) and more extended hips and knees (Bayne & Kat, 2018) to be associated with higher force production. However, much of the available research on body position has analysed single players pushing against an instrumented scrum machine (e.g., Green et al., 2017b; Wu et al., 2007) and focused on compression forces exclusively, whereas shear components (i.e., vertical and lateral forces) may be equally important for performance and injury prevention issues (Bayne & Kat, 2018; Milburn, 1993; Preatoni et al., 2015, 2016). The few studies examining contested scrummaging with two full forward packs (Cazzola et al., 2015a; Du Toit et al., 2005; Preatoni et al., 2016) have mainly compared movement behaviour of players from different playing standards when performing under different engagement rules, or the effect of the playing surface on spinal kinematics of the hooker (Swaminathan et al., 2016b). When following the “crouch-bind-set” calls compared with the previous “crouch-touch-pause-engage”, both props show (1) a more “shoulder above hips” position in the set-up phase, (2) less hip range of movement, reduced vertical movement of the shoulders, and greater stability during the engagement, and (3) no consistent differences in the sustained push phase. Scrummaging on artificial pitches appears to reduce spinal rotations for the hooker (Swaminathan et al., 2016b), suggesting that there is more stability when scrummaging on synthetic pitches compared to natural turf. Overall, there are contrasting scrummaging technique findings between studies (Martin & Beckham, 2020), thus yielding a current lack of clear evidence regarding technique and the interaction between players in live scrummaging.

12.5 Tackling Tackling is a fundamental defensive movement used in open play to stop the opposition gaining territory. Research is mainly focused on kinematics to provide benchmark technique descriptors and identify potential risk factors, rather than focusing on performance applications. However, accurate kinematic measurements are challenging to obtain due to the highly dynamic nature of tackling, even in “controlled” laboratory protocols. The tackler, rather than the ball carrier, has typically been the focus of analysis, and the trunk, head, and upper limbs have been most frequently investigated. This section provides an overview of the biomechanical features associated with tackle technique (Figure 12.2). A range of different tackling scenarios have been studied to encompass the main tackle types performed during a match, including front-on and side-on with different impact angles, as well as tackles performed with dominant and nondominant shoulders. Tackle bags have been used to replicate the ball carrier in some studies (e.g., Kawasaki et al., 2018; Seminati et al., 2017b) whereas in others 1-on-1 tackles have been performed (e.g., Tanabe et al., 2019; Tierney et al., 2018). In potentially injurious tackles where players placed the head on the

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A summary of the differences in key biomechanical features between tackle types. Please see Section 12.5 for the specific studies which have informed this summary. n.s. denotes not significant.

FIGURE 12.2

“wrong side” (i.e., head-in-front tackle), significant decreases in neck extension (from 28° to 13°, where 0° is neutral) and increases in neck rotation (by ~80%) were found (Tanabe et al., 2019). The neck has also been found to be ~20% more flexed for non-dominant than dominant side tackles in both front-on and side-on conditions (Seminati et al., 2017b, 2017c), highlighting the importance of monitoring head position in non-dominant side tackles where technique appears less compliant with current coaching recommendations. The detailed analysis of head kinematics during tackling has become of great interest given the role of tackling as a mechanism for concussion injuries (Gardner et al., 2014; King et al., 2017). The measurement of head kinematics is challenging and, whilst computer models offer one potential approach, current models based on those used for pedestrian accidents are not yet suitable for tackling scenarios (Tierney & Simms, 2019). Experimental approaches require accurate wearables and, in the last decade, several research groups have developed instrumented mouthguards to measure accelerations. Although not solely restricted to tackle events, King et al. (2015) observed 20,687 head impacts >10 g in senior amateur rugby union players over a season, the majority of which were categorised as mild impact severity (7 days

Roberts et al. (2013)

34∗

Unable to recalculate for >24 h time-loss only

52 injuries per 1000 player hours

16.9 per 1000 player hours #

Mean no. of matches missed

No. of days lost: Slight - 0–1 days Minimal - 2–3 days Mild - 4–7 days Moderate - 8–28 days Severe - >28 days

No. of days lost: Minor ≤1 week Intermediate = 1 to 3 weeks Serious >3 weeks Transient - 24 h time-loss only

Medical attention only and time-loss injuries Medical attention only and time-loss injuries

Bird et al. (1998)

9.9 injuries per 100 player games

Unable to recalculate for >24 h time-loss only

14 injuries per 1000 player hours

Garraway et al. (1999)

Unable to recalculate for >24 h time-loss only

1 injury per 16.7 player-games (time-loss only)

Medical attention only and time-loss injuries Included injuries 24 h) Injuries per 1000 player hours ( ∗recalculated where required)

Injury incidence (using published data)

Author

TABLE 13.1 Incidence and severity in community rugby literature

% of Injuries classified as: Slight = 35% Mild = 17% Moderate = 30% Severe = 7% Season Ending = 8% Career Ending = 4% 6.6 per injury

% of Injuries classified as: Minor = 59% Intermediate = 29% Serious = 13% Transient = 22% Mild = 38% Moderate = 24% Severe = 16% Not reported

Injury severity

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Head/Neck Roberts et al (2013) = 16% Schneiders et al (2009) = 34% Bird et al (1998) = 25% Huhes & Fricker (1995) = 23% Upper Limb Roberts et al (2013) = 25% Schneiders et al (2009) =19% Bird et al (1998) = 24% Huhes & Fricker (1995) = 17%

Trunk Roberts et al (2013) = 7% Schneiders et al (2009) = 11% Bird et al (1998) = 8% Huhes & Fricker (1995) = 12%

Lower Limb Roberts et al (2013) = 51% Schneiders et al (2009) = 36% Bird et al (1998) = 43% Huhes & Fricker (1995) = 48% FIGURE 13.2

Injury proportion by body region for community standard men’s rugby.

(Chadwick et al., 2010). The risk of injury is reported to be higher for those young people exposed to high standard sports participation compared with their peers (Caine et al., 2003) and injuries may have a significant effect on the health of these young athletes (Caine et al., 2006). There is currently a broad array of injury surveillance literature concentrating on youth rugby; unfortunately there is very little consistency in terms of the injury definitions and data collection methods, and consequently it is difficult to make meaningful comparisons (Bleakley et al., 2011). Concentrating on those studies that have reported injury incidence rates for time-loss injuries sustained throughout the season (i.e., not during an International tournament), incidence ranges from 16 to 49 injuries per 1000 player hours (Table 13.2) (Kerr et al., 2008; Haseler et al., 2010; PalmerGreen et al., 2013). Despite using similar injury definitions, there are a number of contextual differences between the published youth rugby studies, which might in part explain the variation in injury incidence figures. These factors include different standards of play, with significant differences found between tier one and tier two nations at the respective Junior Rugby World Championship/Trophy tournaments (Fuller & Taylor, 2012a, 2012b) and between school and English Premiership academy rugby cohorts (Palmer-Green et al., 2013). Age must also be considered as it has been found that the risk of injury increases with age through youth rugby (Haseler et al., 2010). As with both elite and community senior rugby, the tackle is the most common match event associated with injury in the youth game (Garraway et al., 1999;

Injury incidence time-loss (per 1000 player hours)

47 to 87 ⌘ 20 to 50 ⌘ Team medic

England Premiership Academies (16–18) U20 Tier 1 nations (International Tournament) U20 Tier 2 nations (International Tournament)

IRB Consensus statement definition – time-loss injuries (≥24 h absence) IRB Consensus statement definition – time-loss injuries (≥24 h absence) IRB Consensus statement definition – time-loss injuries (≥24 h absence)

35

29

25

Team medic

Team reported to tournament medic Team reported to tournament medic School medic

U18 – Academy (South Africa Tournament) U18 (Craven) (South Africa Tournament) English Schools (16–18)

20

47

Team reported to tournament medic

U16 (South Africa -Tournament)

49

Academy team physio

Team coach/first aider

English Clubs U17

40

Medics/ team coaches/ 16 ∗ identified player Team coach/first aider

USA collegiate ~17–21 y

Collection method

English Clubs U16 - U17

Notes ∗ Re-calculated to report time-loss incidence rate only. ⌘ Range of injury incidence rates observed from 2008–2012.

Brown et al. (2013) Brown et al. (2013) Palmer-Green et al. (2013) Palmer-Green et al. (2013) Fuller & Taylor (2012a) Fuller & Taylor (2012b)

Haseler et al. (2010) Haseler et al. (2010) Brown et al. (2013)

Kerr et al. (2008)

Age range

Requiring medical attention. Resulting in any restriction of the player’s participation for ≥1 day beyond the injury event. IRB Consensus statement definition – time-loss injuries (≥24 h absence) IRB Consensus statement definition – time-loss injuries (≥24 h absence) Time-loss Injuries – absence from more than one match in tournament or one day of normal/ planned activity after the tournament. Time-loss Injuries – absence from more than one match in tournament or one day of normal/ planned activity after the tournament. IRB Consensus statement definition – time-loss injuries (≥24 h absence)

Injury definition

Author

TABLE 13.2 Injury incidence in youth rugby

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Kerr et al., 2008; Collins et al., 2008; Palmer-Green et al., 2013), with between 50 and 58% of all injuries occurring in the tackle (Haseler et al., 2010; Palmer-Green et al., 2013). There does not, however, appear to be consensus when reviewing which body region has the highest incidence of injury. This is an area that needs further investigation to inform comprehensive injury reduction strategies for this rugby population.

13.3.4 Women’s rugby Despite the growth in the women’s game, relatively little evidence is available from this population as to the incidence, causes or severity of injuries sustained during match play or practice. Indeed, a search of current literature yields only seven injury surveillance papers examining the incidence of injuries in the women’s game (Bird et al., 1998; Carson et al., 1999; Doyle & George, 2004; Kerr et al., 2008; Schick et al., 2008; Taylor et al., 2011). Unfortunately, similar to other populations, the ability to generalize and make cross-study comparisons is restricted due to the variability in the methodologies adopted within these papers (Table 13.3). The incidence rate for injuries sustained in women’s rugby in studies complying with the IRB consensus document ranges from 16 to 38 injuries per 1000 h, which is lower than elite men’s rugby but is very similar to the range for both community men’s rugby and youth rugby (Kerr et al., 2008; Taylor et al., 2011). The only reported mean severity of injuries within the women’s game is 55 days per injury sustained, based on injuries sustained at the 2010 Women’s RWC (Taylor et al., 2011). Unfortunately, other studies have not reported mean injury severity with many not reporting severity at all (Table 13.3). Women’s rugby remains, for the most part, amateur and consequently the level of medical cover and rehabilitation opportunities might hamper the time it takes a player to return to play. Thus, it is perhaps not a surprise that the mean severity reported for the 2010 women’s RWC was significantly higher than that reported for the 2007 men’s RWC (Fuller et al., 2008; Taylor et al., 2011). Similar to the men’s game, the tackle is responsible for the greatest proportion of injuries, with figures ranging from 38 to 66% (Kerr et al., 2008; Schick et al., 2008; Taylor et al., 2011). Closer study of the tackle event shows that being tackled (33–36% of all injuries) accounts for proportionally more injuries compared with tackling (5–21%) (Kerr et al., 2008; Schick et al., 2008; Taylor et al., 2011). Further description of injury causation is limited in women’s rugby. The lower limbs are again the region of the body sustaining the greatest proportion of injuries, with a range from 41 to 67% (Bird et al., 1998; Carson et al., 1999; Doyle & George, 2004; Kerr et al., 2008; Schick et al., 2008; Taylor et al., 2011). Again, these studies utilize various injury definitions and cover a range of playing standards (collegiate, school, international).

Competitive standard

Community/School

National and Regional (Canadian)

National (England)

Collegiate

Author

Bird et al. (1998)

Carson et al. (1999)

Doyle & George (2004)

Kerr et al. (2008)

Rugby-related event that kept a player out of practice or competition for >24 h or required attention of a physician. Requiring medical attention. Resulting in any restriction of the player’s participation for ≥1 day beyond the injury event.

Rugby-related event that kept a player out of practice or competition for >24 h or required attention of a physician.

Medical attention or causing the player to miss at least one schedule match or practice.

Injury definition

TABLE 13.3 Injury incidence and injury severity in women’s rugby

Time-loss injury Severity incidence (>24 h) Injuries per 1000 player h

6.1 per 100 playergames

Unable to recalculate for % of Injuries per severity AIS ∗ category: >24 h time-loss only AIS-1 – minor = 76.7% AIS-2 – moderate = 22.8% AIS-3 – serious = 0.5% 21 per 1000 playerUnable to recalculate for % of Injuries per severity game hours >24 h time-loss only category: NTO = 4% 1 day = 7.2% 2-3 days = 17.1% 4–7 days = 20.7% >7days = 51% 3.6 per 1000 playing Unable to recalculate for % of Injuries per severity hours (Match and >24 h time-loss only category: training injuries 3 weeks – 37% 17.1 per 1000 player- 16.4 % of Injuries per severity game hours category: No time-loss – 11% 1 week absence – 37% 2 week absence – 7% >2 week absence – 44%

Incidence

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World Cup

Military Collegiate

Taylor et al (2011)

Peck et al. (2013)

Note ∗ AIS – Abbreviated Injury Scale.

World Cup

Schick et al. (2008)

IRB Consensus statement 37.5 per 1000 player- 37.5 definition – Time-loss game hours injuries (≥ 24 h absence) IRB Consensus statement 35.5 per 1000 player- 35.5 definition – Time-loss game hours injuries (≥ 24 h absence) Unable to recalculate for Any new event occurring 29.1 per 10,000 Athletic-Exposures >24 h time-loss only during rugby practice or match that required medical attention. No. of days lost from play: Mean = 55 days per injury Median = 9 days per injury Severity not reported

Severity not reported due to incomplete data.

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13.4 Conclusion Rugby union is a sport played worldwide by a diverse population of men, women, and youth players. Injury definitions, reporting measures, and general methodologies vary greatly across the existing rugby injury surveillance literature making cross-study comparisons difficult to perform. The publication of a consensus statement for reporting injuries in rugby union goes some way to alleviate some of these challenges, although comparisons with past studies may remain challenging. Importantly, the injury surveillance process is not static, and as the game/population evolves so should the definitions/methodologies used for injury surveillance, and thus regular reviews of the consensus statement would be prudent. Rugby union is played at varying standards from amateur through to fully professional. Injury incidence varies greatly between playing standards, with the highest reported in the elite men’s game and the lowest reported in the women’s game (Figure 13.3). In the youth population, the risk of injury increases with age (Haseler et al., 2010) and with the standard of rugby being played (Palmer-Green et al., 2013). Although the incidence of injuries are important, the severity of injuries, or the time a player is unable to play or fully train, also has a large impact on the individual and indeed the team. Whilst the incidence of injuries increases at higher playing standards, it appears that severity increases as the playing standard decreases, which may be indicative of a number of factors including the amount of medical support, time given to rehabilitation, player and club priorities. 120

Injuries per 1000 player hours

100

80

60

40

20

0 Elite men’s

Community men’s

Youth (Non-international)

Women’s

Comparison of the range of incidence rates recorded across the rugby playing population. The data are for injuries sustained across at least one season (i.e., not during a tournament) and the injury definition used is that of time-loss with >24 h lost from training or match play.

FIGURE 13.3

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References Bird, Y. N., Waller, A. E., Marshall, S. W., Alsop, J. C., Chalmers, D. J., & Gerrard, D. F. (1998). The New Zealand Rugby Injury and Performance Project: V. Epidemiology of a season of rugby injury. British Journal of Sports Medicine, 32(4), 319–325. Bohu, Y., Julia, M., Bagate, C., Peyrin, J. C., Colonna, J. P., Thoreux, P., & PascalMoussellard, H. (2009). Declining Incidence of Catastrophic Cervical Spine Injuries in French Rugby: 1996-2006. The American Journal of Sports Medicine, 37(2), 319–323. Bleakley, C., Tully, M., & O’Connor, S. (2011). Epidemiology of adolescent rugby injuries: a systematic review. Journal of Athletic Training, 46(5), 555–565. Brooks, J. H., & Fuller, C. W. (2006). The influence of methodological issues on the results and conclusions from epidemiological studies of sports injuries. Sports Medicine, 36(6), 459–472. Brooks, J. H., Fuller, C. W., Kemp, S. P. T., & Reddin, D. B. (2005). Epidemiology of injuries in English professional rugby union: part 1 match injuries. British Journal of Sports Medicine, 39(10), 757–766. Brooks, J. H., & Kemp, S. P. T. (2011). Injury-prevention priorities according to playing position in professional rugby union players. British Journal of Sports Medicine, 45(10), 765–775. Brown, J. C., Lambert, M. I., Verhagen, E., Readhead, C., van Mechelen, W., & Viljoen, W. (2013). The incidence of rugby-related catastrophic injuries (including cardiac events) in South Africa from 2008 to 2011: A cohort study. British Medical Journal Open, 3, e002475. Caine, D. J., Caine, C. G., & Lindner, K. J. (1996). Epidemiology of sports injuries. The Nurse Practitioner, 21(9), 142. Caine, D., DiFiori, J., & Maffulli, N. (2006). Physeal injuries in children’s and youth sports: reasons for concern? British Journal of Sports Medicine, 40(9), 749–760. Caine, D., Knutzen, K., Howe, W., Keeler, L., Sheppard, L., Henrichs, D., & Fast, J. (2003). A three-year epidemiological study of injuries affecting young female gymnasts. Physical Therapy in Sport, 4(1), 10–23. Carson, J. D., Roberts, M. A., & White, A. L. (1999). The epidemiology of women’s rugby injuries. Clinical Journal of Sport Medicine: Official Journal of The Canadian Academy of Sport Medicine, 9(2), 75–78. Chadwick, S., Semens, A., Schwarz, E. C., Schwarz, E., & Zhang, D. (2010). Economic impact report on global rugby. Part III: Strategic and emerging markets. http://www. irb.com/mm/document/newsmedia/mediazone/02/04/22/88/2042288_pdf.pdf, (Accessed 31 Aug 2012). Chalmers, D. J., Samaranayaka, A., Gulliver, P., & McNoe, B. (2012). Risk factors for injury in rugby union football in New Zealand: a cohort study. British Journal of Sports Medicine, 46(2), 95–102. Collins, C. L., Micheli, L. J., Yard, E. E., & Comstock, R. D. (2008). Injuries sustained by high school rugby players in the United States, 2005-2006. Archives of Pediatrics and Adolescent Medicine, 162(1), 49–54. Doyle, C., & George, K. (2004). Injuries associated with elite participation in women’s rugby over a competitive season: an initial investigation. Physical Therapy in Sport, 5(1), 44–50. Drawer, S., & Fuller, C. W. (2001). Propensity for osteoarthritis and lower limb joint pain in retired professional soccer players. British Journal of Sports Medicine, 35(6), 402–408. Estell, J., Shenstone, B., & Barnsley, L. (1995). Frequency of injuries in different age-groups in an elite rugby league club. Australian Journal of Science and Medicine in Sport, 27(4), 95–97.

220

Niki Gabb et al.

Fuller, C. & Taylor, A. (2012a). Junior World Championship, Injury Epidemiology Results: 2008 to 2012. International Rugby Board, Injury Surveillance Studies. Fuller, C. & Taylor, A. (2012b). Junior World Championship, Injury Epidemiology Results: 2008 to 2012. International Rugby Board, Injury Surveillance Studies Fuller, C. W., Brooks, J. H., Cancea, R. J., Hall, J., & Kemp, S. P. (2007a). Contact events in rugby union and their propensity to cause injury. British Journal of Sports Medicine, 41(12), 862–867. Fuller, C. W., Laborde, F., Leather, R. J., & Molloy, M. G. (2008). International Rugby Board Rugby World Cup 2007 injury surveillance study. British Journal of Sports Medicine, 42(6), 452–459. Fuller, C. W., Molloy, M. G., Bagate, C., Bahr, R., Brooks, J. H., Donson, H., … & Wiley, P. (2007b). Consensus statement on injury definitions and data collection procedures for studies of injuries in rugby union. British Journal of Sports Medicine, 41(5), 328–331. Fuller, C. W., Raftery, M., Readhead, C., Targett, S. G., & Molloy, M. G. (2009). Match injuries in Southern Hemisphere professional rugby union: Impact of the International Rugby Board’s Experimental Law Variations. South African Medical Journal, 99(4), 232. Fuller, C. W., Sheerin, K., & Targett, S. (2013). Rugby World Cup 2011: International Rugby Board injury surveillance study. British Journal of Sports Medicine, 47(18), 1184–1191. Gabbett, T., King, T., & Jenkins, D. (2008). Applied physiology of rugby league. Sports Medicine, 38(2), 119–138. Gabbett, T. J. (2003). Incidence of injury in semi-professional rugby league players. British Journal of Sports Medicine, 37(1), 36–44. Gabbett, T. J. (2004a). Incidence of injury in junior and senior rugby league players. Sports Medicine, 34(12), 849–859. Gabbett, T. J. (2004b). Influence of training and match intensity on injuries in rugby league. Journal of Sports Sciences, 22(5), 409–417. Garraway, W. M., Lee, A. J., Macleod, D. A., Telfer, J. W., Deary, I. J., & Murray, G. D. (1999). Factors influencing tackle injuries in rugby union football. British Journal of Sports Medicine, 33(1), 37–41. Haseler, C. M., Carmont, M. R., & England, M. (2010). The epidemiology of injuries in English youth community rugby union. British Journal of Sports Medicine, 44(15), 1093–1099. Hodgson, L., Gissane, C., Gabbett, T. J., & King, D. A. (2007). For debate: consensus injury definitions in team sports should focus on encompassing all injuries. Clinical Journal of Sport Medicine, 17(3), 188–191. Hughes, D. C., & Fricker, P. A. (1994). A prospective survey of injuries to first-grade rugby union players. Clinical Journal of Sport Medicine, 4(4), 249–256. Kemp, S., Brooks, J., Fuller, C., Anstiss, T., Smith, A., Taylor, A., … & Stokes, K. (2013). England Professional Rugby Injury Surveillance Project 2011-2012 Season Report. RFU. Kerr, H. A., Curtis, C., Micheli, L. J., Kocher, M. S., Zurakowski, D., Kemp, S. P. T., & Brooks, J. H. M. (2008). Collegiate rugby union injury patterns in New England: A prospective cohort study. British Journal of Sports Medicine, 42(7), 595–603. King, D. A., & Gabbett, T. J. (2009). Injuries in the New Zealand semi-professional rugby league competition. New Zealand Journal of Sports Medicine, 36(1), 6–15. King, D. A., Gabbett, T. J., Gissane, C., & Hodgson, L. (2009). Epidemiological studies of injuries in rugby league: Suggestions for definitions, data collection and reporting methods. Journal of Science and Medicine in Sport, 12(1), 12–19.

Injury Epidemiology in Rugby

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King, D. A., & Gissane, C. (2009). Injuries in amateur rugby league matches in New Zealand: A comparison between a division 1 and a division 2 premier grade team. Clinical Journal of Sport Medicine, 19(4), 277–281. King, D. A., Hume, P. A., Milburn, P. D., & Guttenbeil, D. (2010). Match and training injuries in rugby league. Sports Medicine, 40(2), 163–178. Lorentzon, R., Wedren, H., Pietilä, T., & Gustavsson, B. (1988). Injuries in international ice hockey: A prospective, comparative study of injury incidence and injury types in international and Swedish elite ice hockey. The American Journal of Sports Medicine, 16(4), 389–391. Meyers, M. C., & Barnhill, B. S. (2004). Incidence, causes, and severity of high school football injuries on FieldTurf versus natural grass: a 5-year prospective study. The American journal of Sports Medicine, 32(7), 1626–1638. O’Connell, T. C. (1954). Rugby football injuries and their prevention; a review of 600 cases. Journal of the Irish Medical Association, 34(199), 20–26. Orchard, J. and Hoskins, W. (1997). Rugby league injuries at State of Origin level [online]. Available from URL: http://www.injuryupdate.com.au/images/research/Origininjuries 20002006.pdf, [Accessed 7 Oct 2013]. Orchard, J., & Seward, H. (2002). Epidemiology of injuries in the Australian Football League, seasons 1997–2000. British Journal of Sports Medicine, 36(1), 39–44. Palmer-Green, D. S., Stokes, K. A., Fuller, C. W., England, M., Kemp, S. P., & Trewartha, G. (2013). Match injuries in English youth academy and schools rugby union: An epidemiological study. The American Journal of Sports Medicine, 41(4), 749–755. Peck, K. Y., Johnston, D. A., Owens, B. D., & Cameron, K. L. (2013). The Incidence of injury among male and female intercollegiate rugby players. Sports Health: A Multidisciplinary Approach, 5, 327–333. RFU, 2012. Rugby participation up by 26,000 in England. http://www.rfu.com/news/ 2012/june/newsarticles/220612_participation_grainger, Accessed 4 October 2013. Roberts, S. P., Trewartha, G., England, M., Shaddick, G., & Stokes, K. A. (2013). Epidemiology of time-loss injuries in English community-level rugby union. BMJ Open, 3(11), e003998. Roberts, S. P., Trewartha, G., Higgitt, R. J., El-Abd, J., & Stokes, K. A. (2008). The physical demands of elite English rugby union. Journal of Sports Sciences, 26(8), 825–833. Schick, D. M., Molloy, M. G., & Wiley, J. P. (2008). Injuries during the 2006 women’s rugby world cup. British Journal of Sports Medicine, 42(6), 447–451. Schneiders, A. G., Takemura, M., & Wassinger, C. A. (2009). A prospective epidemiological study of injuries to New Zealand premier club rugby union players. Physical Therapy in Sport, 10(3), 85–90. Stephenson, S., Gissane, C., & Jennings, D. (1996). Injury in rugby league: A four year prospective survey. British Journal of Sports Medicine, 30, 331–334. Taylor, A. E., Fuller, C. W., & Molloy, M. G. (2011). Injury surveillance during the 2010 IRB women’s rugby world cup. British Journal of Sports Medicine, 45(15), 1243–1245. Walker, R. D. (1985). Sports injuries: Rugby league may be less dangerous than union. The Practitioner, 229(1401), 205–206. Williams, S., Trewartha, G., Kemp, S., & Stokes, K. (2013). A meta-analysis of injuries in senior men’s professional Rugby Union. Sports Medicine, 43(10), 1043–1055.

14 TALENT IDENTIFICATION, DEVELOPMENT, AND THE YOUNG RUGBY PLAYER Stephen Cobley and Kevin Till

14.1 Introduction Over the last 20–30 years, both rugby league and union have become synonymously associated with professionalisation, (inter-)national media coverage, and commercialism. As a consequence, the emergence of ‘top-down’ economic and competition demands as well as ‘bottom-up’ growth in social demands have occurred. Related to the latter, an inherent demand to watch and participate from early-age ‘grass-roots’ standards has grown across and within rugby. For many young players, their aspirations are to follow in the footsteps of iconic players (e.g., Beauden Barrett & Owen Farrell in Rugby Union; Cameron Smith & Cooper Cronk in Rugby League; Sonny Bill-Williams & Sam Burgess – who have successfully traversed both codes). Meanwhile, connected to ‘top-down’ demand, national sporting systems and localised professional clubs have progressively expanded their activities related to systematically identifying, training, and developing future players. Across sports, this process is more popularly known as talent identification and development (TID). In this chapter, we begin by defining the slippery concept of talent. With reference to England Rugby’s TID system, we then summarise the common structural features of TID systems including selection and tiers of representation at player developmental time points. Interacting with TID systems, we consider the growing young player – characterised by unstable timing and tempo of maturation – relative to other players within or outside the TID system. Here we highlight the problematic and changing relationship between advanced maturity and facets of rugby performance, which makes the capability to accurately identify who are genuinely talented youth players and who will become exceptional players in adulthood challenging. To help illustrate complexity in the TID process, we evaluate studies which longitudinally tracked player development – retrospectively and DOI: 10.4324/9781003045052-15

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prospectively – in rugby league TID. Based on such knowledge and with rugby TID practitioners in mind, the final sub-section provides some key practical recommendations.

14.2 Talent defined? Whether a researcher or practitioner (e.g., coach), the concept of talent is a hotly contested term. Talent is a difficult term to define and measure, has been operationalised in different ways, and has been associated with different underpinning explanations accounting for exceptionality in sports as well as other domains (e.g., education, art, and music; Cobley et al., 2012; 2020). Such challenges, thus, might also explain why talent, as a term, is applied in different ways, in different settings, and with different meanings. For instance, popular media consistently associate talent with innate, ‘in-born’ pre-dispositions or ‘giftedness’ – referring to an apparent capability to perform without prior practice – which all provide a stable basis of advantage [relative to others] over time. Media sporting commentary is littered with pre-depositional talent being associated with either physical presence/dominance, ‘in-game decision-making intelligence’, or moments of individual skill exceptionality which are difficult to explain ‘in the moment’. By contrast in other sporting circles, practitioners (e.g., physical educators; coaches) often apply the term ‘blanketly’ and interchangeably, characterising an athlete who has either a broad range of movement coordination capabilities (i.e., not necessarily specific to a sport context), a higher standard of performance relative to others in a given age group or competition, or someone who performs a specific skill (within performance) exceptionally. These applications are not necessarily linked to a pre-depositional view of talent and may more generally align with developmental and nurturist explanations. Nonetheless, these applications have not helped to provide conceptual consistency, clarity in defining talent, or better understanding on the origins of sporting talent. Given the unique movement skill coordination, physiological, and psychological demands required within the rugby codes and the fact that many of these capabilities are influenced by extensive training, more recent developmental and ecological explanations (Araújo et al., 2010; Lerner & Castellino, 2002) provide more encompassing explanations of talent. While acknowledging the genetic and biological processes remain at the root of human adaptability and change, these explanations collectively describe how talent can emanate from multiple causal pathways. The explanations highlight how reciprocal (i.e., two-way) relationships influence the development of attributes and capabilities underpinning talent (i.e., the behaviour or skill under question). Pathways and relationships refer to the favourable alignment of sport task demands with individual psychological (e.g., intent and motivation to learn; resilience to adversity), social (e.g., communication skill), and physical (e.g., upper- and lower-body aerobic endurance and anaerobic strength) characteristics; qualities of the social environment (e.g., coaching knowledge and expertise; family social support mechanisms; athletic development programmes); as well as wider social policy and culture (e.g., society value of a

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sport, state and sporting TID system infrastructure). As such, a multitude of individual, social, and ecological factors are described as combining to determine sporting talent development. It is then the activities undertaken (e.g., training structure) deployed by practitioners (e.g., coaches) within developmental environments which together generate interactions and individual psycho-socialneuro-physiological responses. These interactions determine the direction and intensity of athlete development over time. Developmental and ecological explanations also emphasise how (forms of) rugby talent should be viewed as highly transient (not fixed; Cobley et al., 2020). Implicitly, suggesting how talent can be a temporary state or form of status relative to others (whoever the reference group may be). While rugby-related talent can be said to emerge, surge, or accelerate over time, if underpinning capabilities of performance are optimally developed (i.e., via individual–social–environment and activity alignment). Similarly, talent can plateau, decelerate, and regress via several processes, specifically, from sub-optimal or malalignment among individual, social, and environmental context characteristics. For example, these might include changing individual interests, poor coaching interactions and relationships, under/ overexposure to physical training and competition load, and training activities not targeting skill or performance weaknesses (Davids et al., 2013; Ericsson et al., 1993). Given anthropometric, physiological, and other constraints (e.g., injury; biological ageing processes; Cobley, 2016), talent loss might occur due to ‘performance ceilings’ and/or due to the evolving nature of performance environments (e.g., age-group standards and increasing pace and tempo of the game according to representative standard). Based on such dynamic possibilities, talent can emerge or regress at different ages and developmental stages via different processes within developmental environments (see e.g., Den Hartigh et al., 2018).

14.3 TID systems In professionalised sport contexts, it is common for both national governing bodies and professional clubs to have TID systems. Sporting TID systems typically reflect the social structures and environments where youthful athletic talent interacts with practitioners to maximise competitive performance or the facets of development. However, TID systems between and within a sport may vary in structure and policy, design sophistication, transitional steps within ages and across age spans, as well as the progressiveness of programme content. Despite TID feature variability, two fundamental processes remain similar. First, being able to recognise and identify youthful talent who demonstrate potential to become elite players (Williams & Reilly, 2000). Second, to accelerate their learning and performance via the provision of optimal training conditions and environments (Abbott & Collins, 2004) with the aim of developing elite players. To illustrate an example of a modern TID system within rugby, Table 14.1 summarises the structure and characteristics of England Rugby Football Union’s (RFU) TID system. England RFU’s pathway has evolved from a single to dual

Over 18s

Senior Academy

~40–50 players

Under 18s

Under 18s

~40–45 players

Under 16s

England Academy Players

~35–45 players

Under 15s

Player Developing Group (PDG)

~20 players

~12 players

Dependent upon academy but ~100–150 per age category

6–18 years 14–16 years

Age-grade Rugby Developing Player Programme (DPP)

Number of players

Ages

Stage

TABLE 14.1 A summary of England Rugby Union’s TID system

20 sessions per year

Once per month

Training time

Inter-satellite competitions – up to 3 per year

Competition

3 playing opportunities in April/May Weekly delivery 4 playing opportunities across season resulting in weeklong Festival (now moving to U17 in 2021) Delivered at Regional 1–3 sessions per week RFU organised festivals, Academy base Academy League (8 fixtures) & friendlies. Delivered at Regional 1–3 sessions per week RFU organised festivals, Academy base and in situ Academy League (8 at school/college fixtures) & friendlies. International fixtures. Dual career focus with full- Part-time or full time Play within University, time rugby & Reserve Grade or Loan education/job. Club. International fixtures.

Schools and clubs Training & competition delivered within satellite centres within Regional Academies. Delivered at Regional Academy base Delivered at Regional Academy base

Delivery

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pathway approach to permit both a narrow and focused development of youth rugby players as well as a wide and emergent pathway (see Till et al., 2020, for an overview). The emergent pathway tries to capture players who undertake a nonlinear, less structured, developmental path (Cupples et al., 2018). This pathway acknowledges players that might not necessarily be participating competitively in rugby at an early age, might not be identified at an early age, and might accelerate their playing skill as well as biological and physical development at a later age compared to those identified on the linear path. England RFU’s TID system is implemented via 14 Regional Academies, with each academy having designated areas of geographical responsibility. Regionality aims to help encourage ‘homegrown’ player development, whilst minimising player and parental travel/resource demands alongside other necessary developmental activities (e.g., education). The RFU system’s foundational base is ‘age-grade rugby’. Age-grade rugby is a framework for 6–18-year-old players in clubs, schools, and colleges. The framework aims to ensure every player – regardless of ability – can enjoy rugby in a safe environment while simultaneously developing an array of transferable multi-sport skills. Competition rules progress from small-sided games (e.g., 6 a-side at Under 8s) to more representative versions of the adult game (e.g., 15 a-side with uncontested lineouts at Under 14s). Recent initiatives have also been mandated within age-grade rugby (i.e., 6–16 years) to maximise participation opportunities, including the ‘halfgame’ regulation in 2019, ensuring all players within a matchday squad play at least half a match (England Rugby, 2019). As rugby union is characterised as a late-age specialisation sport (Baker et al., 2009), referring to peak performance ages coinciding with adulthood (e.g., 18–30 years), the RFU’s TID pathways are intentionally delayed until ~14–15 years, but still adheres to a pyramidalisation model (Güllich & Emrich, 2012) from age-grade rugby onward. At the Developing Player Programme (DPP) stage, players can be identified to participate at regional satellite centres which aim to ‘provide a first opportunity to identify those players with the greatest potential to enter the pathway towards the professional game and England’ (Till et al., 2020). Here approximately 5,500–7,000 players, at under 14–16 age groups, are identified nationally. Identified players train once per month whilst continuing participation in their normal playing environments. The DPP also permits players to enter and leave the programme throughout the season, dependent upon their potential and progression. Such practice aligns with research recommendations associated with delayed identification and emergent selection opportunities (e.g., Cobley, 2017; Till & Baker, 2020). By 15 years of age, tiers of TID involvement begin to expand as the Player Development Group (PDG) is introduced, continuing until Under 18s. This programme aims to increase selection and player development while still promoting a wide degree of participatory involvement, unlike other sports TID systems where participation often begins to narrow post-16 years of age. The PDG involves the selection of ~40–50 players per age category with players training at a central regional academy venue. With PDG progression, training and competition requirements also increase (up to 1–3 training sessions per week and up to 8 match

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fixtures). At Under 18s, PDG-selected players can undertake a Diploma in Sporting Excellence (DiSE), involving a partnership between a Regional Rugby Academy and the players’ schools/colleges. The aim is to help talented players engage in both outstanding education and rugby development programme. DiSE benefits include a higher quality combination of academic and rugby development, a minimum of 12 h of week of rugby-related activity, access to off-field support (e.g., physiotherapy, strength, & conditioning), and potential access to higher rugby competition and education post-18 years of age. After the Under 18 programmes, players can be offered a senior academy contract with the academy representing a transition between the TID system (Under 18s and below) to full-time professional rugby. Despite societal popularity, when reflecting holistically across TID research, preexisting TID systems and practices (not referring to England the RFU’s pathways) have been met with criticism. For instance, the efficacy of TID systems has been questioned on grounds of ineffectiveness, with low percentages of youth athletes being retained or maintaining TID programme involvement across developmental stages (see Güllich & Emrich, 2012; Vaeyens et al., 2008). TID systems have shown a limited capability to accurately forecast who will attain higher sporting echelons, questioning the necessity for early-age TID selection and specialisation (Güllich & Cobley, 2017), as well as the rationale for preferential treatment (i.e., access to TID resources) for selected athletes. Perhaps more worrying, TID systems have been questioned on health grounds (Rongen et al., 2018), with physiological overexposure and increased competition associated with injury (see e.g., Bergeron et al., 2015). Detrimental psychological outcomes such as burnout (e.g., Gustafsson et al., 2017), narrow identity development (Rongen et al., 2020), and exposure to toxic psychological high-performance environments (Cobley, 2016) have all been identified. Inter-individual variability in growth and maturation is also one key concern, but it is also (partially) connected to those listed previously. Specifically, TID systems often implement forms of identification and selection at chronological age time points coinciding with substantial growth and maturational variability (i.e., 12–16 years in males; 11–14 years in females). Research evidence suggests that markers of rugby athleticism – such as body size (e.g., height, body mass, and limb length) and physiological indices (e.g., upper- and lower-body strength) are substantially related to the timing and tempo of growth and maturation (see e.g., Till et al., 2010a). Thus, inter-individual variability in growth and maturation makes the capability to accurately differentiate genuine rugby talent from advanced biological development exceedingly difficult.

14.4 Biological age: growth and maturational variability As children develop from birth to adulthood, growth and maturation occur. Although these processes are interrelated, they have fundamental differences (Baxter-Jones & Sherar, 2007). Growth is predominantly genetically determined and refers to changes in size or proportions of the body including height, body

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mass, fat tissue, and organ size (Malina et al., 2004). Height and body mass are the most rudimentary and common growth measurements. As an indicator of health status during years of growth, individuals are compared against large databases of chronologically aged-matched healthy children using growth charts or reference data (see e.g., RCPCH, 2013). Growth charts allow individuals to be compared against reference percentiles, such as the 50th = average, 75th = top 25%, and 25th = lowest 25% at specific chronological age points (e.g., 4–18 years of age), helping determine relative growth progress. At around 12–15 years of age for males (11–14 years for females), a rapid growth spurt occurs, typified by a period of dynamic anthropometric and physical change known as maturation (Baxter-Jones et al., 2005). Maturation is regarded as growth towards the mature adult state (Malina, 1994) and has two well-known components, timing and tempo. Timing refers to the age when specific maturational events occur such as the appearance of pubic hair or age at maximum growth in height, while tempo refers to the rate at which maturation progresses. Within maturation, there is the period of maximal growth rate, also known as peak height velocity (PHV), with males and females accumulating height markedly (e.g., 10–30 cm and 10–25 cm; Barnes, 1975), before subsiding with progression to final adult height. The chronological age time point of PHV (and distance from it) is a common way to determine an individual’s biological maturity status. Age at PHV usually occurs around 14 years of age in adolescent boys in Caucasian populations (e.g., 14.2 ± 0.9 years, Bell, 1993; 13.8 ± 0.8 years, Philippaerts et al., 2006). However, due to variability in maturation onset, age at PHV can occur anywhere between 12.0–15.8 for boys and 10.0–14.0 years of age for girls (based on UK and US data; Malina et al., 2004; Kelly et al., 2014). To illustrate maturational variation in rugby players of similar chronological age see Figure 14.1. On the left half are hypothetical examples from Tanner (1962) showing how three males of similar chronological age (i.e., 14.75 years) differ substantially in terms of maturational stage. On the right half, a practical comparison of three male rugby league players of differing maturational stages (i.e., pre, mid,

FIGURE 14.1

The biological and chronological age mismatch: maturity bias.

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post-PHV), but residing within the same chronological age category (i.e., Under 15s). Within a physically demanding sport like rugby, it is these inter-player variations that can significantly influence performance and TID opportunities. Sport governing bodies and TID systems routinely allocate players into chronological (bi)annual age categories. For example, across rugby codes in the UK (and akin to education age grouping), 1st September is used as the ‘cut-off date’ to divide participants into chronological age groups (e.g., Under 13s). While attempting to minimise developmental differences, unfortunately, the categorisation still permits up to nearly 1 year (i.e., 1st September to 31st August) of inter-individual development differences to occur. However, during the maturation years, growth and developmental differences can be markedly exacerbated (Musch & Grondin, 2001) when comparing across age-group peers as Figure 14.1 illustrates. For instance, ‘earlier maturers’ experience anthropometric (e.g., height and weight) and physical advantages (e.g., strength, speed, and endurance; Baxter-Jones et al., 1995) and are more likely to outperform ‘later maturers’ when comparing results across chronological aged-matched norms (Armstrong et al., 1998). The result, which consistently occurs in team sports, is that ‘earlier maturing boys’ have increased participation and selection opportunities in TID systems at youth stages, as they are more likely to be perceived as talented (Towlson et al., 2017). In a study of youth rugby league players, Till et al. (2010a) examined a TID system sample of male 13–16 years olds (n = 683), comparing their growth and maturation status against UK reference percentiles (Freeman et al., 1995). On height, 92.4% of players were taller than the age-matched 50th percentile (or average) and 33.3% were above the 97th percentile (top 3% of the UK). On weight, 96.0% and 30.3% of players resided above the 50th and 97th percentiles, respectively. In terms of maturational status, players had a mean PHV age of 13.61 (±0.58) years, indicating earlier maturation timing when referenced against the average age of PHV in European boys that occurs between 13.8 and 14.2 years (Malina et al., 2004). Together, these figures highlight a maturity bias, with growth benefits occurring when set against the age-matched UK normal population. Studies in other sports contexts also generically replicate these trends (e.g., soccer; Malina et al., 2004; Lovell et al., 2015).

14.4.1 The biological and chronological age mismatch: relative age bias In addition to maturity bias, relative age biases (or relative age effects; Wattie et al., 2008) are also evident. Relative age refers to the coincidental interaction between a player’s ‘birth date’ and the dates used for chronological age grouping. Thus, a ‘relatively older’ player is an individual born within the 1st quartile after a cut-off date (e.g., UK – September–November), while a ‘relatively younger’ player is an individual born in the last quartile (e.g., UK – June–August). Assuming two individual players are following a similar, normative, maturational trajectory, then it is possible that age-based growth differences may still exist (i.e., up to potentially

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Percentage of Players (%)

60

Quartile 1

Quartile 2

Quartile 3

Quartile 4

50 40 30 20 10 0 Community

Service Area

Regional

National Carnival

National

Relative age distribution of junior rugby league players (i.e., Under 13–15s combined) according to generic TID system stages. (Data from Till et al. (2010b) with permission.)

FIGURE 14.2

364 days’ worth; Cobley et al., 2020). At a group or cohort level, age-based differences lead to relative age biases, where the relatively older are more likely to participate in local junior community, representative, and national standard rugby. To illustrate, Figure 14.2 shows relative age bias within UK junior rugby league (Till et al., 2010b). From the local community (n = 4,829; aged 13–15) to the national standard (n = 88; aged 13–15), participation and selection inequalities are evident, with relative age biases increasing across the TID system. Other studies by Lewis et al. (2015) and Cobley & Till (2017b) also confirm relative age biases in rugby at junior, adult professional, and international standards. Considered together, maturity and relative age biases in youth rugby highlight the need to acknowledge, understand, and be responsive to inter-player development variability. Youth participation and TID systems are potentially placing greater emphasis on current performance as opposed to longer term participation and development. In doing so, the confounding influences of growth and maturation on performance are not being considered. These points become extremely poignant when considering that the anthropometric and physiological ‘gaps’ between junior players are transient, reduced post-maturation, and can potentially become nonexistent (or even reversed by early adulthood; Till et al., 2014). To illustrate, and to identify transiency in development, the next section summarises studies which longitudinally tracked (i.e., over years) a TID sample of rugby league players.

14.5 Retrospective and prospective longitudinal player tracking in rugby league Longitudinal research designs can track change on multiple indices using repeated observations over an extended time period (e.g., > 6 months; see Cobley & Till, 2017a for a review). Retrospective studies aim to compare an athlete’s earlier

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adolescent characteristics with a future career-related outcome (i.e., professional vs. non-professional) to understand which qualities may contribute towards future successful performance. Johnston and colleagues (2017) illustrated there was no clear consensus on which characteristics could distinguish between future career outcomes across multiple sports due to the following: • • • •

the the the the

sport-specific nature of talent identification metrics; varying ages of athletes at initial assessments (i.e., 6 to 19 years); length of time to assess future career outcome (i.e., 1 to 10 years); and wide-ranging, uni- and multi-dimensional testing batteries employed.

However, multiple research studies (e.g., Till et al., 2013; 2015; 2017) conducted in rugby league players who were involved in Rugby Football League’s (RFL) player performance pathway and players aged 16–20 years from a professional rugby league academy provide useful insight.

14.5.1 Player development – 13–15 years Youth rugby league players selected to the RFL’s national TID programme were longitudinally monitored over three consecutive years (Under 13s, 14s, and 15s) between 2005 and 2008. Expectedly, Till et al. (2013) identified significant improvements in several anthropometric and fitness indices across 13–15 years of age. Interestingly though, with players classified as ‘later’, ‘average’, or ‘earlier’ on maturation timing based on age at PHV, maturation status was a key factor impacting longitudinal change. Greater anthropometric and physical indices improvements were apparent in later maturing players (see Figure 14.3). For instance, later maturing 60 m Sprint 20 m Sprint Med Ball Throw Vertical Jump Body Mass Height 0.0

5.0

10.0 Earlier

15.0 % Change

20.0

Average

Later

25.0

30.0

Percentage change in anthropometric and fitness indices across a 2-year period according to maturity status in young rugby league players. (Data redrawn from Till et al., 2013.)

FIGURE 14.3

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players improved 60 m sprint performance by ˗0.85 s over the 2-year period compared to ˗0.46 s in earlier maturing players. These findings identify how later maturing players can catch up (and overtake) on physical performance indices, questioning the validity of early TID identification and selection policies using crosssectional approaches. Using longitudinal retrospective designs, the players involved in the RFL TID programme in 2005–2008 were also tracked to 2014–2015 (some 6–7 years later; see Till et al., 2016a; 2017). These studies examined whether anthropometric and fitness qualities at 13–15 years influenced future career attainment outcomes. Specifically, whether they became professional academy players at 16 years (1–3 years post-TID involvement) and/or senior professional players (7–10 years postTID involvement). Findings demonstrated that physical fitness, and importantly the change in physical fitness, contributed to the attainment of becoming an academy and adult professional player. Interestingly, body size characteristics and maturity status at 13–15 years were not associated with future career outcomes, a finding supported in other sports (e.g., soccer; Ostojic et al., 2014). These findings highlight how factors influencing performance during adolescence (e.g., enhanced size and maturity) are poor indicators for future career attainment, while physical fitness indices and systematic training at younger ages were a contributor toward longer term outcomes.

14.5.2 Player development – 16–20 years Within a professional club academy setting, Till and colleagues (2015) prospectively monitored a sample of 15 rugby league players, 16–20 years of age, over a 4-year period. Annual changes in height, body mass, power, strength, and aerobic capacity were greater in younger (e.g., Under 16s) compared to older (e.g., Under 19s) players, probably due to a combination of factors, including training age as well as the continuation of growth and maturation. However, changes in sprint speed were inconsistent between age categories. This is because increases in body mass impact sprint speed development; therefore, monitoring variables that combine anthropometric and fitness performance (e.g., sprint momentum) are recommended. Figure 14.4 shows the magnitude of change (i.e., effect sizes) for physical performance indices across the 4-year period. Moderate to large changes are apparent in physical indices (except skinfolds and 20 m sprint), suggesting physical capabilities require a long-term developmental process. Large coefficients of variation (CVs) were also apparent in the sample, highlighting inter-individual variability in physical development changes. Such variability likely indicates how multiple factors, and processes over time, may account for greater or lesser developmental change. Findings promote the need for longitudinal and individualised monitoring to better understand what is involved in more optimally accelerated development, and how sub-optimal development can be prevented or remedied. Based on their career attainment outcome (i.e., professional vs. nonprofessional), Till et al. (2016b) then retrospectively examined their development

TID and Young Rugby Player

Height

233

CV= 45.0%

Body Mass

CV= 56.2%

Sum 4 Skinfolds

CV= 2700%

20 m Sprint

CV= 164.5%

10 m Momentum

CV= 45.7%

Yo-Yo IR1

CV= 142.5%

Vertical Jump

CV= 52.2%

1RM Bench Press

CV= 42.9%

1RM Squat

CV= 53.9%

1RM Prone Row

CV= 27.8% 0

0.5

1

1.5 2 Cohen's d Effect Size

2.5

3

3.5

Effect size changes and coefficient of variation (CV) in physical indices over a 4-year period in academy rugby league players. (Data redrawn from Till et al., 2015.)

FIGURE 14.4

(16–20) characteristics. Based on the sample, professional players were taller and had scored higher on upper- and lower-body strength indies at 17–19 years of age, relative to those not achieving professional status. Whilst perhaps obvious given sporting demands, it is somewhat surprising that indices were still related to selection at the sub-elite–elite standard. Thus, size and strength remain important, but are independent to size and strength advantages associated with growth and maturation (i.e., 13–15 years). When player physical development change was monitored according to career attainment, body mass and 10 m momentum were greater in future professional vs. non-professional players. Thus, the development of (lean) body mass is also important and differentiating. Overall, findings suggest that player development programmes should focus on the development of physical qualities post-maturation, particularly as size, strength, and associated body mass are required for the physical contact, high-performance demands made of rugby league players.

14.6 Conclusion This chapter has been written from a dual (researcher and coach practitioner) perspective where key issues within TID and youth rugby player development have been summarised. In our dual roles, our aims are to utilise the most up to date research evidence (i.e., evidence-based knowledge) along with applied knowledge (i.e., practical-based knowledge) to best implement evidence-based practice within TID systems. We acknowledge, sport TID systems – like other skill development systems (e.g., medical and educational training) – work within dayto-day real-world constraints and therefore might have difficulty implementing practice or culture change. Nonetheless, like maturing players, systems and practices possess strengths and weaknesses which can evolve. On the assumption that evolving practice occurs – whether fast or slow – we now provide three key

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(although not exhaustive) recommendations for governing bodies, clubs, coaches, and associated practitioners. For anyone working with young rugby players, our first recommendation is to acknowledge, recognise, and understand the relationships between growth, maturation, and performance development. Unstable developmental variability, particularly during the maturational years, affects physical performance in youth rugby. This challenges the capability to accurately assess talent (i.e., potential) relative to peers and predict future performance. One-off assessments (e.g., coaching/scouting judgements) predominantly reliant upon subjective physical assessment could be inaccurate in identifying talent. So, what might be deemed as exceptional at one age and stage might not remain the same (and thus the same individual) at a later time point. On the foundations of knowledge and understanding, our second recommendation is to monitor young rugby players over time, particularly during adolescence. Monitoring individual growth and maturational change relative to others will help identify current stages of biological development, observe the varying developmental trajectories which can occur, inform training programming (e.g., training/competition loadings), and inform player evaluation processes. For instance, while a ‘later maturing’ 15-year old may not be performing equivalently to an age-matched ‘early maturing’ individual, their progress and trajectory could be reviewed at a later time point (e.g., when maturity status is matched), and where they have likely benefitted from their maturation-related growth spurt. By contrast, the trajectory of an ‘earlier maturing’ player may need to be carefully evaluated relative to players of similar maturation status. Careful evaluation may help maintain their ‘progressive trajectory’ as opposed to plateauing or attaining a ‘performance ceiling’. Potential manipulation of rugbyspecific training (e.g., technical skills; volume and intensity of endurance), ‘offfield but performance-related’ training (e.g., strength and conditioning), and other supportive behaviours (e.g., nutritional management) may all be necessary, given their developmental stage, and considerate of performance demands at the next level of the TID system. Based on research summarised, our third recommendation is to develop and implement initiatives which provide as many participation and developmental opportunities to as many junior players as possible up to 16–18 years of age. Rugby could better emphasise participation, inclusion, and personal and team development, as opposed to winning and competition alone. For longer term benefits of all stakeholders, practitioners should adopt a long-term inclusive player development mindset instead of an emphasis on immediate performance success. England Rugby’s TID system presents a dual pathway that consists of both a narrowed and focussed as well as wide and emergent approach to try and help enable more developmental opportunities for players. On current understanding, such pathways would not detrimentally affect the likelihood of developing elite adult rugby players and is less likely to miss out on ‘later emerging’ players via early assessment, differentiation, and deselection.

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TID systems are tasked with achieving the ‘top-down demands’ of developing future athletes. However, through our discussion of only biological growth and maturation, we hopefully have demonstrated how optimal rugby development is a complex, multi-faceted, developmental process which TID systems and practitioners need to recognise. Alongside growth and maturation, other performance facets (e.g., movement and technical skills; psychological skills) with their corresponding developmental paths must also be successfully navigated. Together, this highlights the necessity of multi-disciplinary understanding to inform beneficial, valid, and effective player development.

References Abbott, A., & Collins, D. (2004). Eliminating the dichotomy between theory and practice in talent identification and development: considering the role of psychology. Journal of Sports Sciences, 22(5), 395–408. Araújo, D., Fonseca, C., Davids, K. W., Garganta, J., Volossovitch, A., Brandão, R., & Krebs, R. (2010). The role of ecological constraints on expertise development. Talent Development & Excellence, 2(2), 165–179. Armstrong, N., Welsman, J. R., & Kirby, B. J. (1998). Peak oxygen uptake and maturation in 12 year olds. Medicine and Science in Sports and Exercise, 30(1), 165–169. Baker, J., Cobley, S., & Fraser-Thomas, J. (2009). What do we know about early sport specialisation? Not much! High Ability Studies, 20(1), 77–89. Barnes, H. V. (1975). Physical growth and development during puberty. Medical Clinics of North America, 59(6), 1305–1317. Baxter-Jones, A., Eisenmann, J., & Sherar, L. (2005). Controlling for maturation in pediatric exercise science. Pediatric Exercise Science, 17(1), 18–30. Baxter-Jones, A., Helms, P., Maffulli, N., Baines-Preece, J. C., & Preece, M. (1995). Growth and development of male gymnasts, swimmers, soccer and tennis players: A longitudinal study. Annals of Human Biology, 22(5), 381–394. Baxter-Jones, A., & Sherar, L. (2007). Growth and maturation. Philadelphia: Elsevier Limited. Bell, W. (1993). Body size and shape: A longitudinal investigation of active and sedentary boys during adolescence. Journal of Sports Sciences, 11(2), 127–138. Bergeron, M. F., Mountjoy, M., Armstrong, N., Chia, M., Côté, J., Emery, C. A., … & Malina, R. M. (2015). International Olympic Committee consensus statement on youth athletic development. British Journal of Sports Medicine, 49(13), 843–851. Cobley, S. (2016). Talent identification and development in youth sport. In: K. Green & A. Smith (eds.), Routledge handbook of youth sport (pp. 476–491). Abingdon: Routledge. (Taylor and Francis). Cobley, S. (2017). Growth and maturation in athlete development: An educational resource for sporting organisations (pp. 1 –29). Canberra: Australian Institute of Sport. Cobley, S., Abbott, S., Moulds, K., Hogan, C., & Romann, M. (2020). Re-balancing the relative age effect scales: Meta-analytical trends, mechanisms and corrective adjustment procedures as a solution. In: J. Dixon, S. Horton, L. Chittle, & J. Baker (eds.), Relative age effects in sport international perspectives (pp. 136–153). United States: Routledge (Taylor and Francis). Cobley, S., Baker, J., & Schorer, J. (2012). Identification and development of sport talent: A brief introduction to a growing field of research and practice. In: J. Baker, S. Cobley, & J. Schorer (eds.), Talent identification and development in sport: International perspectives (pp. 1–10). London: Routledge (Taylor and Francis).

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Cobley, S., Baker, J., & Schorer, J. (2020). Talent identification and development in sport: An introduction to a field of expanding research and practice. In: J. Baker, S. Cobley, & Schorer (eds.), Talent identification and development in sport: International perspectives (2nd ed., pp. 1–15). United States: Routledge (Taylor and Francis). Cobley, S., & Till, K. (2017a). Longitudinal studies of athlete development: Their importance, methods and future considerations. In: J. Baker, S. Cobley, J. Schorer, & N. Wattie (eds.), Routledge handbook of talent identification and development in sport (pp. 250–268). Abingdon: Routledge (Taylor and Francis). Cobley, S., & Till, K. (2017b). Participation trends according to relative age across youth UK Rugby League. International Journal of Sports Science & Coaching, 12(3), 339–343. Cupples, B., O’Connor, D., & Cobley, S. (2018). Distinct trajectories of athlete development: A retrospective analysis of professional rugby league players. Journal of Sports Sciences, 36(22), 2558–2566. Davids, K., Araújo, D., Vilar, L., Renshaw, I., & Pinder, R. (2013). An ecological dynamics approach to skill acquisition: Implications for development of talent in sport. Talent Development and Excellence, 5(1), 21–34. Den Hartigh, R. J., Hill, Y., & Van Geert, P. L. (2018). The development of talent in sports: A dynamic network approach. Complexity, 2018, 10.1155/2018/9280154. England Rugby. (2019). Half Game. Retrieved from https://www.englandrugby.com/ participation/coaching/age-grade-rugby/half-game. Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3), 363–406. Freeman, J. V., Cole, T. J., Chinn, S., Jones, P., White, E. M., and Preece, M. A. (1995). Cross sectional stature and weight reference curves for the UK, 1990. Archives of Disease in Childhood, 73(1), 17–24. Güllich, A., & Cobley, S. (2017). On the efficacy of talent identification and talent development programmes. In: J. Baker, S. Cobley, J. Schorer, & N. Wattie (eds.), Routledge handbook of talent identification and development in sport (pp. 80–98). Abingdon: Routledge (Taylor and Francis). Güllich, A., & Emrich, E. (2012). Individualistic and collectivistic approach in athlete support programmes in the German high-performance sport system. European Journal of Sport and Society, 9(4), 243–268. Gustafsson, H., DeFreese, J. D., & Madigan, D. J. (2017). Athlete burnout: Review and recommendations. Current Opinion in Psychology, 16, 109–113. Johnston, K., Wattie, N., Schorer, J., & Baker, J. (2017). Talent identification in sport: a systematic review. Sports Medicine, 48(1), 97–109. Kelly, A., Winer, K. K., Kalkwarf, H., Oberfield, S. E., Lappe, J., Gilsanz, V., & Zemel, B. S. (2014). Age-based reference ranges for annual height velocity in US children. Journal of Clinical Endocrinology and Metabolism, 99(6), 2104–2112. Lerner, R. M., & Castellino, D. R. (2002). Contemporary developmental theory and adolescence: Developmental systems and applied developmental science. Journal of Adolescent Health, 31(6), 122–135. Lewis, J., Morgan, K., & Cooper, S. M. (2015). Relative age effects in Welsh age grade rugby union. International Journal of Sports Science & Coaching, 10(5), 797–813. Lovell, R., Towlson, C., Parkin, G., Portas, M., Vaeyens, R., & Cobley, S. (2015). Soccer player characteristics in English lower-league development programmes: The relationships between relative age, maturation, anthropometry and physical fitness. PloS One, 10(9), e0137238.

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Malina, R. M. (1994). Physical growth and biological maturation of young athletes. Exercise and Sport Sciences Reviews, 22(1), 280–284. Malina, R. M., Bouchard, C., & Bar-Or, O. (2004). Growth, maturation, and physical activity. Human Kinetics Publishers. Musch, J., & Grondin, S. (2001). Unequal competition as an impediment to personal development: A review of the relative age effect in sport. Developmental Review, 21(2), 147–167. Ostojic, S. M., Castagna, C., Calleja-González, J., Jukic, I., Idrizovic, K., & Stojanovic, M. (2014). The biological age of 14-year-old boys and success in adult soccer: Do early maturers predominate in the top-level game? Research in Sports Medicine, 22(4), 398–407. Philippaerts, R. M., Vaeyens, R., Janssens, M., Van Renterghem, B., Matthys, D., Craen, R., & Malina, R. M. (2006). The relationship between peak height velocity and physical performance in youth soccer players. Journal of Sports Sciences, 24(3), 221–230. Royal College of Paediatrics and Child Health (RCPCH) (2013). UK 2-18 years growth chart resources. Retrieved 15th of July, 2013, from http://www.rcpch.ac.uk/growthcharts. Rongen, F., McKenna, J., Cobley, S., Tee, J. C., & Till, K. (2020). Psychosocial outcomes associated with soccer academy involvement: Longitudinal comparisons against agedmatched school pupils. Journal of Sports Sciences, 38(11-12), 1387–1398. Rongen, F., McKenna, J., Cobley, S., & Till, K. (2018). Are youth sport talent identification and development systems necessary and healthy? Sports Medicine Open, 4(1), 1–4. Tanner, J. (1962). Growth at adolescence. Oxford: Blackwell Scientific Publications. Till, K., & Baker, J. (2020). Challenges and [possible] solutions to optimizing talent identification and development in sport. Frontiers in Psychology, 11, 664. Till, K., Barrell, D., Lawn, J., Lazenby, B., Rock, A., & Cobley, S. (2020). Wide and emergent - Narrow and focussed: A dual pathway approach to talent identification and development in English Rugby Union. In: J. Baker, S. Cobley, & J. Schorer (eds.), Talent identification and development in sport: International perspectives (2nd ed., pp. 170–183). United States: Routledge (Taylor and Francis). Till, K., Cobley, S., Morley, D., O’Hara, J., Chapman, C., & Cooke, C. (2016a). The influence of age, playing position, anthropometry and fitness on career attainment outcomes in rugby league. Journal of Sports Science, 34(13), 1240–1245. Till, K., Cobley, S., O’Hara, J., Chapman, C., & Cooke, C. (2010a). Anthropometric, physiological and selection characteristics in high performance UK Junior Rugby League players. Talent Development and Excellence, 2, 193–207. Till, K., Cobley, S., O’Hara, J., Chapman, C., & Cooke, C. (2013). A longitudinal evaluation of anthropometric and fitness characteristics in junior rugby league players considering playing position and selection level. Journal of Science and Medicine in Sport, 16(5), 438–443. Till, K., Cobley, S., O’Hara, J., Cooke, C., & Chapman, C. (2014). Considering maturation status and relative age in the longitudinal evaluation of junior rugby league players. Scandinavian Journal of Medicine and Science in Sports, 24(3), 569–576. Till, K., Cobley, S., Wattie, N., O’Hara, J., Cooke, C., & Chapman, C. (2010b). The prevalence, influential factors and mechanisms of relative age effects in UK Rugby League. Scandinavian Journal of Medicine and Science in Sports, 20(2), 320–329. Till, K., Jones, B., Darrall-Jones, J., Emmonds, S., & Cooke, C. (2015). The longitudinal development of anthropometric and physical characteristics in academy rugby league players. Journal of Strength and Conditioning Research. 29(6), 1713–1722. Till, K., Jones, B., & Geeson-Brown, T. (2016b). Do physical qualities influence the attainment of professional status within elite 16–19-year-old rugby league players? Journal of Science and Medicine in Sport, 19(7), 585–589.

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Till, K., Morley, D., O’Hara, J., Jones, B., Chapman, C., Beggs, C., Cooke, C., & Cobley S. (2017). A retrospective longitudinal analysis of anthropometric and physical qualities that associate with adult career attainment in junior rugby league players. Journal of Science and Medicine in Sport, 20(11), 1029–1033. Towlson, C., Cobley, S., Midgley, A. W., Garrett, A., Parkin, G., & Lovell, R. (2017). Relative age, maturation and physical biases on position allocation in elite-youth soccer. International Journal of Sports Medicine, 38(3), 201–209. Vaeyens, R., Lenoir, M., Williams, A. M., & Philippaerts, R. M. (2008). Talent identification and development programmes in sport. Sports Medicine, 38(9), 703–714. Wattie, N., Cobley, S., & Baker, J. (2008). Towards a unified understanding of relative age effects. Journal of Sports Sciences, 26(13), 1403–1409. Williams, A., & Reilly, T. (2000). Talent identification and development in soccer. Journal of Sports Sciences, 18(9), 657–667.

15 THE FEMALE RUGBY PLAYER Emma Ross

15.1 Introduction Despite a dramatic rise in participation and professionalism of Women’s Rugby (Rugby England, 2019), the infrastructure, sports science research, and applied practise for the women’s game still lags sorely behind their male counterparts. In rugby, women join a sport that has been, for so long, dominated by men, playing, coaching, supporting, and administrating the game. This has led to training approaches and preparing players for peak performance that have previously been successful for males or based on research that has been carried out exclusively on males. For example, there is a paucity of published research about physical preparation of female rugby players (Heyward et al., 2020; Cummins et al., 2020), and more broadly, only 6% of sports science and medicine research is conducted exclusively on women (Cowley et al., 2021). This tends to mean that training methods are transposed from men to women without due consideration for the fact that men and women differ biomechanically, physiologically, and psychologically. In women’s rugby, there are marked sex differences in anthropometric and physiological characteristics (Sella et al., 2019; Sheel, 2016), match-play demands (Ball et al., 2019), and physical performance (Sella et al., 2019). In addition to sex differences, there are also female-specific factors which are commonly overlooked in sports. Women have periods and menstrual cycles, many use hormonal contraception (Martin et al., 2018), they might go through pregnancy, they have breasts and require breast support (Brown et al., 2020), they are far more likely to have pelvic floor dysfunction (Casey & Temme, 2017), they have a higher risk of injury (Zumwalt, 2018), they manage emotions and derive confidence differently from men (Hays et al., 2009). As women continue to pursue optimal performance, from participation DOI: 10.4324/9781003045052-16

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to podium, we must explore the science behind what it takes to allow them to fulfil their potential, because it is not always the same things that have worked for men. Despite having little research, we do have enough well-established knowledge of female physiology, practise-based evidence from working with female athletes, and emerging evidence from research, to begin to understand the important considerations for supporting female athlete health and performance. For a comprehensive review of the exercising female, readers are directed to ‘The Exercising Female: Science and its Application’ (Forsyth & Roberts, 2018), and ‘Strength and Conditioning for Female Athletes’ (Barker & Sargent, 2018). However, it is the author’s ambition within this chapter to draw attention to where the women’s game and female players are different from what we conventionally understand from the men’s game, and to encourage a new approach.

15.2 The women’s game The first reported positional characteristics of English female rugby league players found backs were more agile, quicker, and had greater relative power compared to forwards (Jones et al., 2016). Similar findings were suggested in female rugby union players (Posthumus et al., 2020) rugby 7s players (Misseldine et al., 2021), and Super League players, where backs had greater acceleration over 10 and 20 m and forwards had higher momentum as a result of greater body mass (Heyward et al., 2019). In a study of female English national rugby union players, speeds reached by backs and forwards were 23.2 km·h−1 and 20.5 km·h−1, respectively. The total distance covered during match-play was 4982 m with a mean relative distance of 54.8 m·min−1 (Bradley et al., 2020). These distances are lower than those covered by international Spanish rugby players (5820 m or 68.5 m·min−1, respectively; Suarez-Arrones et al., 2014), with differences possibly attributed to greater match intensity, different tactical approaches, and greater player quality at the international standard (Jones et al., 2015). Interestingly, despite the transition from amateur to professional codes, a 5-year longitudinal analysis evaluating the changes in rugby union physical match characteristics over this period of evolution suggests that match demands have stayed largely consistent, relative to playing position (Woodhouse et al., 2021). Match-play data from the women’s game is also different to the men’s game. For example, distance travelled in men’s rugby union is between ~5000 m by front row players to ~7000 m by the scrum half (Cahill et al., 2013) and maximum running speeds of ~28 km·h−1 in backs (Cunniffe et al., 2009). This disparity with female players is potentially due to sex differences in both physical make-up, which contributes to differences in force production and subsequently disparities in velocity and impact intensity (Clarke et al., 2017), and physical capacities. Correlational analysis suggests that, for females, superior physical fitness is beneficial for onfield performance (Clarke et al., 2017).

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15.3 The female player As in the men’s game, specific anthropometric (height, body mass, skinfold) and body composition (lean mass, fat mass, bone mass) characteristics are required for successful performance in specific playing positions in order to meet the physical demands of the sport (Posthumus et al., 2020). In a sport such as rugby, body composition should be optimised so that the player can physically withstand the frequency and intensity of collisions during and match-play (Zemski, et al., 2015), but so that it also supports the development of power, speed, and aerobic fitness (Smart et al., 2014). Despite limited research examining body composition of elite female rugby union players, consistent findings are that forwards demonstrate greater values across all anthropometric measures compared to backs (Hene et al., 2011; Posthumus et al., 2020). Anthropometric characteristics of female rugby union players are summarised in Table 15.1 (Posthumus et al., 2020). The greater body mass and lower skinfolds reported by Posthumus and colleagues compared to previous studies on female players (e.g., Hene et al., 2011; Nyberg & Penpraze, 2016) might reflect the evolution of the game into a professional era. When positional difference within forwards and backs are examined, only forward positional groups demonstrate significant anthropometric differences, whereas backs are more homogenous in body size and composition (Posthumus et al., 2020). In the forwards, the tight five possess greater body mass, total lean mass, fat mass, and fat percentage compared to the loose forwards. They also have a greater trunk lean mass, trunk fat mass, and arm fat mass compared to the loose forwards (Posthumus et al., 2020). These findings suggest that individualised training and nutrition programmes might be of greater importance for forwards, who have more position-specific physicality than backs (Posthumus et al., 2020). It is unknown whether the additional fat mass in the tight five players is a requirement of the demands on the position. A greater fat mass might enable these players to cope with the greater number and impact of collisions that their positions demand (Suarez-Arrones et al., 2014). However, non-essential additional fat mass can impair power to body mass ratio and acceleration capability (Zemski et al., 2018), so, it is important to better understand how much is optimal across playing positions in women’s rugby. TABLE 15.1 Anthropometric characteristics of female rugby players (see Posthumus et al.,

2020) Characteristic Height (cm) Body mass (kg) Lean mass (kg) Fat mass (kg) Fat (%)

All players 171.3 83.5 60.9 20.3 23.6

± ± ± ± ±

7.7 13.9 7.8 6.6 4.2

Note ∗ difference compared to backs (p ≤ 0.05).

Forwards 175.6 93.7 66.2 25.3 26.5

± ± ± ± ±

Backs ∗

6.3 10.9 ∗ 6.3 ∗ 5.4 ∗ 3.1 ∗

167.0 73.3 55.6 15.4 20.8

± ± ± ± ±

6.6 7.5 5.3 3.1 3.0

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15.4 Physical preparation 15.4.1 Physical performance testing Heyward and colleagues (2020) were the first group to describe the physical preparation characteristics in female rugby. Testing of important determinants of performance across the season seems to mirror practises in the men’s game, with aerobic capacity and muscular strength assessed in pre-season, and acceleration and muscular strength prioritised for testing in-season. Training programmes for female players comprise resistance training (prescribed ~3 days per week preseason and 2 days per week in-season), cardiovascular training (often integrated within rugby training sessions), sprint training (up to 2 times per week pre-season and in-season), plyometric training (usually integrated within resistance training sessions), and recovery sessions (predominantly on non-rugby training days and post-match-play) (Heyward et al., 2020).

15.4.2 Resistance training Women have a similar array of muscle fibre types (type I slow twitch, type II fast twitch and all their subtypes), but a sex difference does exist in untrained individuals, where 75% of untrained women have larger slow twitch than fast twitch muscle fibres (Zatsiorsky & Kraemer, 2006). The cause of such a sex difference is unknown but could, along with the fact that females tend to enter sport less conditioned and with a lower training age, be turned into a potential advantage, with females having a greater potential to see superior results from strength training when they begin their athletic development (Zatsiorsky & Kraemer, 2006). Muscle hypertrophy (i.e., an increase in muscle fibre number and size) is similar between the sexes, as well as muscle synthesis rates after exercise and rate of gain of cross-sectional area (CSA) per day (Hunter, 1985; Wernbom et al., 2007), meaning that males and females make similar strength gains in response to a welldesigned training programme (Triplett & Stone, 2016). If exercises are performed at the same relative percentage of 1RM, females develop strength equally to males, although in women changes in strength depend less on increases in muscle CSA and more on better neuromuscular activation of the muscle. When strength improvements are tested at the same absolute load and are normalised for the entire volume of trained musculature (i.e., absolute muscle power quality), one study showed women’s strength improved by 9% but no change in men’s strength (Delmonico et al., 2005). It is thought that improvements in muscle function with strength training result from non-muscle mass adaptations to a greater extent in women than men, possibly down to better coordination of all the muscles involved in the movement and better signalling from the brain to activate the muscle(s) in question. In practise, the prioritised use of compound (multi-muscle, multi-joint), coordinated, sports-specific exercises might take advantage of these superior neuromuscular gains in female athletes.

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Performing muscular contractions with loads ~50–80% 1RM, women seem less fatigable (Hunter, 2016; Ansdell et al., 2017). Interestingly, contractile fatigue at task failure is the same in male and females across a number of muscle groups, except females perform more muscular work before they reach task-failure (Hunter, 2009; Hunter, 2016). Recovery of maximal strength and power from fatigue is also quicker in females (Ansdell et al., 2019). It is important to build these concepts into training programmes for female athletes so that both programming parameters such as sets, repetitions, tempos, rest periods and load not only suit the desired adaptation, but also take these female-specific neuromuscular factors into consideration in order to elicit optimal adaptations for rugby performance.

15.5 Injury risk and prevention Injury rates in women’s rugby 15s varies from 3.6 per 1000 playing hours (Doyle & George, 2004) to 37.5 per 1000 playing hours (Schick et al., 2008) during the Women’s World Cup competition. In the few studies examining player position and injury risk, the prop and the centre are the most injured positions (Doyle & George, 2004; Kerr et al., 2008). After the head and face, the knee, ankle, and cervical spine are the most common injury sites (King et al., 2019), with the lower limb being the most common injury region reported (King et al., 2019). The tackle is the cause of most injuries, with the ball carrier recording more injuries than the tackler in the women’s game (Schick et al., 2008; Kerr et al., 2008).

15.5.1 Joint injuries Females are more likely to suffer injury to connective tissue, meaning they are more at risk of joint injury than men (Crossley et al., 2020). The ankle joint is injured twice as frequently in female athletes and shoulder injuries are more common in women than in men (Wolf et al., 2015). Most notable, females are 4.5 times more likely to suffer a non-contact anterior cruciate ligament (ACL) injury than men (Adachi, et al., 2008; Chidi-Ogbolu & Baar, 2019; Zumwalt, 2018). For female athletes who suffer an ACL injury, 45% never compete again, 35% do not meet their previous standard of athleticism and up to half show signs of osteoarthritis just a decade later (Queen, 2017). Because of the clearly devastating impact of joint injury for women’s shortterm performance, and their life-long participation in sports, awareness of and protection against this injury risk should become an important consideration in coaching and training women. The increased risk in females is thought only to occur after puberty, since equal numbers of ligament sprains occur in girls and boys before adolescence but girls have higher rates immediately after their growth spurt and into maturity (Zumwalt, 2018). Although the reasons why are not entirely clear, there are some important factors that might contribute. For example, the Q angle (the angle from the hip to the knee) is wider in women due to their wider pelvis. This has been linked to increased knee pain in women and to the greater

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risk of ACL injury because of the risks of increased valgus during landing and changes of direction whilst running (Zumwalt, 2018). Further risk factors for joint injury in females are inadequate muscle strength and muscle imbalance. Importantly, these factors are modifiable, and as such can be targeted to reduce injury risk in players. Female athletes demonstrate greater strength in the quadriceps muscles and preferential activation of this muscle group at the expense of force generation from gluteal and hamstring muscles exacerbates the issue (Huston & Wojtys, 1996). In sporting tasks such as running, crosscutting, and side-cutting, women activate their knee extensors more, and flexors less when compared to men, across all the tasks (Malinzak et al., 2001). During movements like running, particularly high-speed running, stable knees require strong quadriceps to straighten the knee and help to flex the foot forward, and strong hamstrings to bend the knee and help to pull the leg backward. Muscle weakness, imbalance and poor coordination of muscle recruitment around the knee joint increases the risk of injury (Kim & Hong, 2011; Myer et al., 2005), and might explain why poor agility and reduced speed are postulated as predictors of severe injuries in female rugby players (Rizi et al., 2017). The menstrual cycle phase may also be an additional risk factor for injury in women, since oestrogen decreases stiffness in tendons and ligaments and at times of the cycle when oestrogen concentrations are high, joints may become laxer or less stable (Chidi-Ogbolu & Baar, 2019). When a joint is laxer it is more likely to become injured (Myer et al., 2004). Since oestrogen has been linked to increased knee laxity, and increased knee laxity linked to increased risk of injury, studies have examined how injury risk in women changes across their cycle, as oestrogen fluctuates (Deie et al., 2002). However, there remains no consensus on whether time of the cycle poses a significant risk and more research is needed to fully understand just how important the menstrual cycle is in influencing injury in athletes. Rather than focusing solely on physical and physiological determinants of injury risk in females, Fox et al. (2020) have suggested that confining women’s injury risk to biological causes (e.g., hormones, anatomy, physiology) fundamentally misrepresents the root cause of ACL injury, which is likely to be strongly influenced by gendered environmental disparities including access to and experiences with sport and training. For example, in rugby, these psycho-social factors might include women’s teams often being allocated artificial surfaces or poorer grass surfaces which increase ACL injury rates (Dragoo et al., 2013). In addition, exposure to different experiences during childhood requires and develops differential physical skill sets in girls and boys, and exposure to rugby via school sport is less likely in girls and as such they arrive at the sport with less skill and physical development than their male counterparts (Parsons et al., 2021). In an attempt to reduce injury risk in female athletes, various sports-specific multi-component conditioning programmes have been developed, such as the ‘RugbySmart’ programme, the ‘FIFA 11+ Workbook’ in Football, and the ‘Jump High, Land Strong’ programme from England Netball. Evidence from a systematic

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review and meta-analysis using a large cohort of female team sport athletes (soccer) provides low-level evidence that these multi-component, exercise-focused interventions reduce overall injuries by 27% and ACL injury rates by 45% (Crossley et al., 2020).

15.5.2 Concussion Across sports, rugby has the highest risk of concussion (Prien et al., 2018; Van Pelt et al., 2021). The head/face is reported as the most common injury site for female rugby players, and female rugby 7s players are reported to have a higher number of incidences of concussion compared to rugby 15s (King et al., 2019). Female athletes, across sports, are also more susceptible to sport-related concussions, and when they experience a concussion, they have more severe and prolonged symptoms and take longer to return to sport when compared to male athletes (Zuckerman et al., 2014). Reasons for these sex differences in severity of concussion remain unclear, with emerging hypotheses regarding poor neck strength, lower head–neck segment mass, brain anatomy, and sex hormones’ potential contributing factors (La Tierney et al., 2005; La Fountaine et al., 2019). However, it is likely that these different explanations are not mutually exclusive and, like any other injury, some of the risk factors combine to create the ‘perfect storm’ (Covassin et al., 2016). Female athletes are also more forthcoming in reporting concussion-related symptoms, and this may influence the prevalence and recovery data when compared to men who underreport (McGroarty et al., 2020). Females experiencing concussion in the luteal phase of the menstrual cycle (when progesterone is elevated), experienced poorer outcomes in a one month follow up (Wunderle et al., 2014). The researchers postulated that because progesterone has neuroprotective qualities, when women are injured during the phase of the cycle when hormone concentrations are high, the stress of the concussion causes progesterone to decline exponentially and there may exist a withdrawal effect from the progesterone that impacts recovery. A blood test or, at least, information about the date of a woman’s last period to identify where she is in her cycle is important for medical practitioners to consider when a female athlete presents with concussion. Knowing if an athlete was in a high progesterone phase of her cycle might indicate that she is at risk for poorer long-term outcomes and requires more vigilant monitoring or return to play support.

15.6 Female-specific considerations for health and performance of rugby players 15.6.1 Menstrual cycle The fluctuating hormone concentrations across the menstrual cycle delineate four ‘phases’ of the cycle where sex hormones and ratios are distinctly different from one another (see Figure 15.1). The first day of the cycle is the first day of the period.

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A typical menstrual cycle, showing fluctuations of oestrogen and progesterone, and the four points where hormone concentrations, and/or ratio of oestrogen and progesterone are distinctly different. (Published with permission from The WellHQ.)

FIGURE 15.1

During the period, both hormones are at their lowest, after which oestrogen rises to its peak in the late follicular phase. In the second half of the cycle both hormones rise, with progesterone peaking in the mid luteal phase, before both hormones are reduced, assuming again the cycle has not resulted in pregnancy. The hormonal fluctuations, and their influence on physiology, affect how women feel physically and emotionally (Dam et al., 2022). This can differ tremendously amongst women, and every female athlete’s lived experience of her cycle, in relation to her wellbeing, training, recovery, and performance, will be different. Importantly for rugby players, determinants of performance, such as V O2max, speed, and power, are not affected across the menstrual cycle (McNulty et al., 2020). However, 88% of active women report that their symptoms make sports performance worse at some point of their cycle (Bruinvels et al., 2021). Although tracking of wellness, match, and training loads are popular practise in women’s’ rugby, menstrual cycle monitoring has been reported in only 22% of participants (Heyward et al., 2020). Therefore, given the emerging evidence that menstrual cycle phase has the potential to impact players’ ability to train and perform, it is recommended that cycle tracking is utilised as a standard approach to supporting female athletes (Pitchers & Elliott-Sale, 2019). When females are being negatively impacted by their cycle symptoms, there are numerous strategies that can be explored to alleviate these symptoms, including diet, lifestyle, exercise, rest, and recovery and stress management through to pharmacological interventions (Panay, 2011). Whilst determinants of performance might be unaffected across the cycle, adaptations to training might be. Oestrogen creates an ‘anabolic’ environment – one where muscle repair and growth is supported, through influences on antioxidative processes, cell membrane stability, and satellite cell proliferation (Mangan et al., 2014).

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Accordingly, researchers have sought to explore whether performing more resistance training in the first half of the cycle, when oestrogen peaks, affects adaptation to resistance training regimes (Reis et al., 1995; Sung et al., 2014). When women performed strength training sessions every other day in the first two weeks of the cycle, and then only twice in the second half of the cycle, participants reported a 33% increase in muscular strength, compared to a 14% increase when training was scheduled evenly across the cycle (Reis et al., 1995) and a 40% vs. 28% increase when strength training was performed more frequently in the first half or the second half of the cycle, respectively (Sung et al., 2014). Consensus in this area is still emerging, and whilst working with individual athletes makes training mapped to the menstrual cycle a feasible approach it is not always pragmatic when training in squads or around tournament and travel schedules. However, training with the menstrual cycle in mind does not have to include training that is synchronised to the cycle. It could be ensuring that each player understands how she feels across her cycle and develops strategies to capitalise or cope with her physical and emotional state at that time, to optimise readiness to train and perform. Menstrual cycle monitoring is a powerful tool for athletes, coaches, and support staff. It allows an athlete to capture her own experience of the cycle, and how it influences her in the context of her life and her sport. At the very least it can help explain why some days feel better than others; at best it can produce patterns that can be anticipated, exploited, or overcome to optimise training, recovery, and performance (Elliott-Sale et al., 2020a). Physical and emotional changes should be monitored across the cycle, as well as sleep, muscle soreness, motivation to train and any injury or illness. Monitoring the cycle requires recording the first day of the period, which indicates day one of the cycle, and over time, tracks cycle length. Athletes should note how heavy their flow is during their period, which can help identify heavy menstrual bleeding. Players with heavy periods are more likely to suffer from iron deficiency (Bruinvels et al., 2016) which can compromise aerobic fitness via reductions in total haemoglobin mass and therefore oxygen carrying capacity (Hinton, 2014). Cycle monitoring also allows players and their support team to recognise when the cycle is unhealthy. The period is a vital sign of health, and loss of periods (amenorrhea) needs to be investigated. In athletes, this is commonly a sign of underfuelling or low-energy availability, and it increases the risk of injury and illness and long-term poor health (Mountjoy et al., 2014; Mountjoy et al., 2018). Amenorrhea in athletes is often indicative of Relative Energy Deficiency in Sport (RED-S). RED-S still remains poorly recognised by health professionals, coaches, and athletes (Curry et al., 2015) despite the significant impact it can have on athlete’s health. Left untreated, RED-S can impact healthy bone mineral density, and in turn athletes can develop a lower peak bone mass, recurrent bony injuries and, at worse, osteoporosis (Papageorgiou et al., 2018). However, participation in sports like rugby that convey a high mechanical loading and impact may attenuate the negative influence of reduced energy availability on bone (Papageorgiou et al., 2018). Education on RED-S within coaching qualifications is vital, yet researchers have identified that

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deficiencies exist in current coach development programmes, and these serve to undermine adequate support of female athlete health and performance (Hamer et al., 2021). For detailed reviews of low energy availability and RED-S in athletes, its impact and management, readers are directed towards Logue et al. (2020) and Mountjoy et al. (2018) and for special considerations in adolescent female athletes, to Brown et al. (2017).

15.6.2 Hormonal contraception and female athletes About 50% of 18–30-year old athletes use hormonal contraception, although for active women in their 20s this can be as high as 66%, dropping to about 11% in the mid-40s (Elflein, 2020). Like the menstrual cycle, the physiological effects of the synthetic hormones delivered by the pill or other hormonal contraceptives do not just influence the reproductive system but can have consequences throughout the body, which can have both a positive and negative influence on health and performance of sportswomen both acutely and chronically. In addition to its primary purpose of preventing unwanted pregnancies, many sportswomen report using hormonal contraception to counteract the debilitating influences of their symptoms on their training and performance such as heavy periods, debilitating period pains (e.g., endometriosis), or to treat conditions like acne or polycystic ovarian syndrome (Martin et al., 2018). However, women who use hormonal contraception do not have a period to rely on as a window into their health. The bleed that women experience on contraceptives like the pill (called a ‘withdrawal bleed’) is not the same as that caused by the shedding of the uterine lining, as occurs in a normal menstrual cycle. For players using hormonal contraception there is a risk that this masks RED-S, because, unlike periods which stop, withdrawal bleeds will still occur, even in the presence of prolonged low energy availability (Dudgeon, 2019). As such, greater attention to fuelling which matches the energy requirements for training and playing is needed in players using hormonal contraceptives. While there is now evidence that the pill could be counter-productive for sportswomen, the research in this area is still emerging (Elliott-Sale et al., 2020b). Absolute strength is not affected by hormonal contraceptive use (Pitchers & Elliott-Sale, 2019), but comparing hormonal contraception athletes vs. athletes with a natural menstrual cycle found a potentially negative influence of oral contraceptive pill use on performance (Elliot-Sale et al., 2020a). In particular, women whose V O2max was not changed across their natural menstrual cycle, saw an 11% decrease when they started taking the pill and peak power during a cycle ergometer test decreased concomitantly by 8% (Casazza et al., 2002). Better quality research is required to examine whether the effect of the pill on test parameters such as V O2max or peak power translate meaningfully into an impact on performance in rugby (Martin & Elliott-Sale, 2016). Using hormonal contraception is a very individual decision, yet female athletes are often not counselled well enough to make an informed choice which weighs

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up the risk to benefits ratio and best suits them, in the context of their relationships, their sport, and their life (Martin & Elliott-Sale, 2016).

15.6.3 Breast support and breast injury Breast tissue is predominantly comprised fat and has limited internal anatomical support. This causes breast tissue to move, over the chest wall, when our body moves (Haake & Scurr, 2010). Breast movement is linked with increased breast pain, tissue strain, and embarrassment for participants, as well as negatively impacting exercise performance (McGhee & Steele, 2020). Breast pain is often, but not always, experienced by female athletes as a symptom of the menstrual cycle and can prevent or negatively impact upon exercise training (Brown et al., 2014). Inadequate breast support during running also impacts gait mechanics, notably stride length, such that the distance covered decreased and energy cost increased in a low-breast support condition (Milligan et al., 2015). Further, vertical ground reaction forces decrease in runners with low breast support (Shivitz, 2001) causing them to change technique to reduce breast displacement, sacrificing performance (White et al., 2009). Thus, the importance of wearing a well-fitted and supportive bra, to reduce breast movement during physical activity, is well established (Nolte et al., 2016) despite many women wearing incorrectly fitting breast support for sport (Wood et al., 2008). The effects of changes in breast support on female rugby players remains unclear; however, improvements in breast support could not only have significant impact on performance, but also comfort and enjoyment. In addition to providing breast support, sports bras for female rugby players might warrant the addition of breast protection properties. In a study, 58% of female Australian football, rugby league, rugby union, and rugby 7s players (n = 297) reported experiencing contact injuries to their breasts, with almost half perceiving breast injuries to negatively affect their sporting performance (Brisbine et al., 2019). It is also reported that very few rugby union or 7s players used breast protective equipment (Brisbine et al., 2020b) despite the specific regulation drafted by World Rugby allowing females to wear appropriate breast padding. Of the players that used protective equipment (23 of 35 players), padding was perceived effective in protecting their breast from contact injuries and therefore a strategy to decrease breast injury occurrence (Brisbine et al., 2020a).

15.6.4 Pelvic floor health Dysfunction of the pelvic floor muscles can lead to urinary incontinence which is defined as any involuntary leakage of urine (Bø & Nygaard, 2020). Believed to be mainly a problem of the elderly and post-natal women, female athletes are up to three times more likely to suffer with urinary incontinence than the general population (Bø & Nygaard, 2020; Almeida et al., 2016). In collegiate rugby players, 54% suffered urinary incontinence doing their sport of whom 90% leaked urine when competing in a match and 88% leaked when being tackled or hit (Sandwith & Robert, 2021).

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The cause for urinary incontinence in athletes is unclear. Young female athletes often experience significant and sudden intra-abdominal pressure increases, especially during high-impact activities such as running and jumping, during a Valsalva manoeuvre during strength training or during contact in rugby, which may play a role in urinary incontinence. In addition, the cause might be related to female athletes having very strong pelvic floor muscles from continued training of the abdominal musculature. The pelvic floor muscles become overactive and unable to relax or coordinate effectively (Carvalhais et al., 2018). Studies have shown up to 70% improvement in symptoms of stress incontinence after appropriately performed pelvic floor exercise, with evidence that women perform better with exercise regimes supervised by specialist physiotherapists or trainers, as opposed to unsupervised or leaflet-based care (Price et al., 2010). Athletes with good knowledge about pelvic floor training are less likely to develop symptoms of dysfunction such as urinary incontinence (Cardoso et al., 2018). Importantly, urinary incontinence in female rugby players is seriously underreported, and as such, undertreated (Sandwith & Robert, 2021). Practitioners must not normalise incontinence as ‘just a part of doing sport’, but instead work to encourage athletes to seek advice and support if they are experiencing urine leakage at any time. Women’s health physiotherapists are experienced at identifying and treating pelvic floor dysfunction and should be part of a science and medical team’s referral network for female players.

15.7 Conclusion As women’s rugby continues to grow globally, the infrastructure and support for female players need to evolve and improve. There are important differences between male and female athletes that mean we cannot simply apply the evidence derived from research in male players to inform practice in female players. The female game is played differently to the men’s, and female players have different determinants of health and peak performance than their male counterparts. This has implications for practise of sports scientists and coaches of women’s teams, particularly those who have only previously experienced working in the men’s game. Rugby is still a male-dominated sport, and coach–athlete relationships are often male–female. In fact, the inability of male coaches to understand how best to engage with female athletes is recognized as a key barrier to participation, engagement, and progression in girls and women in sport (Norman & French, 2013). This dynamic also makes the consideration of important female-specific factors such as the menstrual cycle, hormonal contraceptive use, breast health, and pelvic health more challenging because male coaches do not have personal experience of, will have had little, or no education or training in, and are often topics that carry stigma or embarrassment. In addition to the physical and physiological consideration of the female game that has been outlined in this chapter, in practice it is also important to acknowledge that the science and craft of coaching need to be adapted in a male

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coach–female player environment, when compared to a male coach working with male players. Whereas male coaches prefer an autocratic style of coaching, female players tend to prefer a more democratic approach, where decisions are made together and the rationale for decisions is explored (Norman & French, 2013). Female athletes also place more value on being supported as a person, as well as a performer, wanting a good quality personal relationship with their coach. Whilst male athletes tend to derive confidence from comparing themselves to others and winning, female athletes tend to derive confidence from their coach’s encouragement and positive feedback, and from mastering skills and achieving personal goals (Hays et al., 2007). This chapter has provided evidence that female players will benefit from an increase in sex-specific research, and improved awareness and education about how the science of the women’s game can be translated into practise to support female players in fulfilling their performance potential, stay healthy, and remain engaged in the sport of rugby across their life. With thanks to Fiona Scott (Hartpury College), Claire Edwards, Lewis Clarke, Tim Exell, Joanna Wakefield-Scurr (University of Portsmouth), and Baz Moffat (The WellHQ) for their help preparing this manuscript.

References Adachi, N., Nawata, K., Maeta, M., & Kurozawa, Y. (2008). Relationship of the menstrual cycle phase to anterior cruciate ligament injuries in teenaged female athletes. Archives of Orthopaedic and Trauma Surgery, 128(5), 473–478. Almeida, M. B. A., Barra, A. A., Saltiel, F., Silva‐Filho, A. L., Fonseca, A. M. R. M., & Figueiredo, E. M. (2016). Urinary incontinence and other pelvic floor dysfunctions in female athletes in Brazil: A cross‐sectional study. Scandinavian Journal of Medicine & Science in Sports, 26(9), 1109–1116. Ansdell, P., Brownstein, C. G., Škarabot, J., Hicks, K. M., Howatson, G., Thomas, K., … & Goodall, S. (2019). Sex differences in fatigability and recovery relative to the intensity–duration relationship. Journal of Physiology, 597(23), 5577–5595. Ansdell, P., Thomas, K., Howatson, G., Hunter, S., & Goodall, S. (2017). Contraction intensity and sex differences in knee-extensor fatigability. Journal of Electromyography and Kinesiology, 37, 68–74. Ball, S., Halaki, M., & Orr, R. (2019). Movement demands of rugby sevens in men and women: a systematic review and meta-analysis. Journal of Strength & Conditioning Research, 33(12), 3475–3490. Barker, K., & Sargent, D. (2018). Strength and Conditioning for Female Athletes. Wiltshire: Crowood. Bø, K., & Nygaard, I. E. (2020). Is physical activity good or bad for the female pelvic floor? A narrative review. Sports Medicine, 50(3), 471–484. Bradley, E. J., Board, L., Hogg, B., & Archer, D. T. (2020). Quantification of movement characteristics in women’s English premier elite domestic rugby union. Journal of Human Kinetics, 72(1), 185–194. Brisbine, B. R., Steele, J. R., Phillips, E. J., & McGhee, D. E. (2019). The occurrence, causes and perceived performance effects of breast injuries in elite female athletes. Journal of Sports Science & Medicine, 18(3), 569.

252

Emma Ross

Brisbine, B. R., Steele, J. R., Phillips, E. J., & McGhee, D. E. (2020a). Breast and torso characteristics of female contact football players: Implications for the design of sports bras and breast protection. Ergonomics, 63(7), 850–863. Brisbine, B. R., Steele, J. R., Phillips, E., & McGhee, D. E. (2020b). Breast injuries reported by female contact football players based on football code, player position and competition level. Science and Medicine in Football, 4(2), 148–155. Brown, K. A., Dewoolkar, A. V., Baker, N., & Dodich, C. (2017). The female athlete triad: special considerations for adolescent female athletes. Translational Pediatrics, 6(3), 144. Brown, N., Burbage, J., & Wakefield-Scurr, J. (2020). Sports bra use, preferences and fit issues among exercising females in the US, the UK and China. Journal of Fashion Marketing and Management: An International Journal, 25(3). Brown, N., White, J., Brasher, A., & Scurr, J. (2014). The experience of breast pain (mastalgia) in female runners of the 2012 London Marathon and its effect on exercise behaviour. British Journal of Sports Medicine, 48(4), 320–325. Bruinvels, G., Burden, R., Brown, N., Richards, T., & Pedlar, C. (2016). The prevalence and impact of heavy menstrual bleeding (menorrhagia) in elite and non-elite athletes. PLoS One, 11(2), e0149881. Bruinvels, G., Goldsmith, E., Blagrove, R., Simpkin, A., Lewis, N., Morton, K., … & Pedlar, C. (2021). Prevalence and frequency of menstrual cycle symptoms are associated with availability to train and compete: a study of 6812 exercising women recruited using the Strava exercise app. British Journal of Sports Medicine, 55(8), 438–443. Cahill, N., Lamb, K., Worsfold, P., Headey, R., & Murray, S. (2013). The movement characteristics of English Premiership rugby union players. Journal of Sports Sciences, 31(3), 229–237. Cardoso, A. M. B., Lima, C. R., & Ferreira, C. W. (2018). Prevalence of urinary incontinence in high-impact sports athletes and their association with knowledge, attitude and practice about this dysfunction. European Journal of Sport Science, 18(10), 1405–1412. Carvalhais, A., Jorge, R. N., & Bø, K. (2018). Performing high-level sport is strongly associated with urinary incontinence in elite athletes: a comparative study of 372 elite female athletes and 372 controls. British Journal of Sports Medicine, 52(24), 1586–1590. Casazza, G. A., Suh, S. H., Miller, B. F., Navazio, F. M., & Brooks, G. A. (2002). Effects of oral contraceptives on peak exercise capacity. Journal of Applied Physiology, 93(5), 1698–1702. Casey, E. K., & Temme, K. (2017). Pelvic floor muscle function and urinary incontinence in the female athlete. The Physician and Sportsmedicine, 45(4), 399–407. Chidi-Ogbolu, N., & Baar, K. (2019). Effect of estrogen on musculoskeletal performance and injury risk. Frontiers in Physiology, 1834. Clarke, A. C., Anson, J. M., & Pyne, D. B. (2017). Game movement demands and physical profiles of junior, senior and elite male and female rugby sevens players. Journal of Sports Sciences, 35(8), 727–733. Covassin, T., Moran, R., & Elbin, R. J. (2016). Sex differences in reported concussion injury rates and time loss from participation: an update of the National Collegiate Athletic Association Injury Surveillance Program from 2004–2005 through 2008–2009. Journal of Athletic Training, 51(3), 189–194. Cowley, E. S., Olenick, A. A., McNulty, K. L., & Ross, E. Z. (2021). “Invisible sportswomen”: The sex data gap in sport and exercise science research. Women in Sport and Physical Activity Journal, 29(2), 146–151.

The Female Rugby Player

253

Crossley, K. M., Patterson, B. E., Culvenor, A. G., Bruder, A. M., Mosler, A. B., & Mentiplay, B. F. (2020). Making football safer for women: a systematic review and meta-analysis of injury prevention programmes in 11 773 female football (soccer) players. British Journal of Sports Medicine, 54(18), 1089–1098. Cummins, C., Melinz, J., King, D., Sanctuary, C., & Murphy, A. (2020). Call to action: a collaborative framework to better support female rugby league players. British Journal of Sports Medicine, 54(9), 501–502. Cunniffe, B., Proctor, W., Baker, J. S., & Davies, B. (2009). An evaluation of the physiological demands of elite rugby union using global positioning system tracking software. Journal of Strength and Conditioning Research, 23(4), 1195–1203. Curry, E. J., Logan, C., Ackerman, K., McInnis, K. C., & Matzkin, E. G. (2015). Female athlete triad awareness among multispecialty physicians. Sports Medicine-Open, 1(1), 1–7. Deie, M., Sakamaki, Y., Sumen, Y., Urabe, Y., & Ikuta, Y. (2002). Anterior knee laxity in young women varies with their menstrual cycle. International Orthopaedics, 26(3), 154–156. Dam, T.V., Dalgaard, L.B., Sevdalis, V., Bibby, B.M., Janse, D.E. Jonge, X., Gravholt, C. H., & Hansen, M. (2022). Muscle performance during the menstrual cycle correlates with psychological well-being, but not fluctuations in sex hormones. Medicine & Science in Sports & Exercise, 54(10), 1678–1689. Delmonico, M. J., Kostek, M. C., Doldo, N. A., Hand, B. D., Bailey, J. A., Rabon-Stith, K. M., … & Hurley, B. F. (2005). Effects of moderate-velocity strength training on peak muscle power and movement velocity: do women respond differently than men? Journal of Applied Physiology, 99(5), 1712–1718. Doyle, C., & George, K. (2004). Injuries associated with elite participation in womenas rugby over a competitive season: an initial investigation. Physical Therapy in Sport, 5(1), 44–50. Dragoo, J. L., Braun, H. J., & Harris, A. H. (2013). The effect of playing surface on the incidence of ACL injuries in National Collegiate Athletic Association American Football. The Knee, 20(3), 191–195. Dudgeon, E. (2019). Relative energy deficiency in sport (RED-S): recognition and next steps. [Online]. British Journal of Sports Medicine Blog: Available at: https://blogs.bmj.com/bjsm/ 2019/04/22/relative-energy-deficiency-in-sport-red-s-recognition-and-next-steps/ [Accessed June 2020]. Elflein, J. (2020). Contraceptive use among women in England 2019/20, by type and age. Avalible at: https://www.statista.com/statistics/1233817/contraceptive‐use‐women‐ worldwide‐region/. Elliott-Sale, K. J., McNulty, K. L., Ansdell, P., Goodall, S., Hicks, K. M., Thomas, K., … & Dolan, E. (2020a). The effects of oral contraceptives on exercise performance in women: a systematic review and meta-analysis. Sports Medicine, 50(10), 1785–1812. Elliott-Sale, K., Ross, E., Burden, R., & Hicks, K. (2020b). The BASES expert statement on conducting and implementing female athlete based research. The Sport and Exercise Scientist, (65), 6–7. Forsyth, J., & Roberts, C. M. (eds.). (2018). The exercising female: Science and its application. Routledge. Fox, A., Bonacci, J., Hoffmann, S., Nimphius, S., & Saunders, N. (2020). Anterior cruciate ligament injuries in Australian football: should women and girls be playing? You’re asking the wrong question. BMJ Open Sport & Exercise Medicine, 6(1), e000778. Haake, S., & Scurr, J. (2010). A dynamic model of the breast during exercise. Sports Engineering, 12(4), 189–197. Hamer, J., Desbrow, B., & Irwin, C. (2021). Are coaches of female athletes informed of relative energy deficiency in sport? A scoping review. Women in Sport and Physical Activity Journal, 29(1), 38–46.

254

Emma Ross

Hays, K., Thomas, I., Maynard, I. & Bawden, M. (2009). The role of confidence in worldclass sport performance. Journal of Sports Sciences, 27(11), 1185–1199. Hays, K., Thomas, O., Maynard, I. & Bawden, M. (2007). The role of confidence in world-class sport performance. Journal of Applied Sport Psyhcology, 19(4), 424–456. Hene, N. M., Bassett, S. H., & Andrews, B. S. (2011). Physical fitness profiles of elite women’s rugby union players: physical fitness and training programme. African Journal for Physical Health Education, Recreation and Dance, 17(sup-1), 1–8. Heyward, O., McCormack, S., Emmonds, S., Roe, G., Till, K., & Jones, B. (2019). Strength and Speed Characteristics of Women’s Super League Players. In: NSCA National Conference, 10 July 2019 ‐ 13 July 2019, Washington D.C. USA. Heyward, O., Nicholson, B., Emmonds, S., Roe, G., & Jones, B. (2020). Physical preparation in female rugby codes: An investigation of current practices. Frontiers in Sports and Active Living, 2, 584194. Hinton, P. S. (2014). Iron and the endurance athlete. Applied Physiology, Nutrition, and Metabolism, 39(9), 1012–1018. Hunter, G. R. (1985). Changes in body composition, body build and performance associated with different weight training frequencies in males and females. Strength and Conditioning Journal, 7(1), 26–28. Hunter, S. K. (2009). Sex differences and mechanisms of task-specific muscle fatigue. Exercise and Sport Sciences Reviews, 37(3), 113. Hunter, S. K. (2016). Sex differences in fatigability of dynamic contractions. Experimental physiology, 101(2), 250–255. Huston, L. J., & Wojtys, E. M. (1996). Neuromuscular performance characteristics in elite female athletes. American Journal Sports Medicine, 24(4), 427–436. Jones, B., Emmonds, S., Hind, K., Nicholson, G., Rutherford, Z., & Till, K. (2016). Physical qualities of international female rugby league players by playing position. Journal of Strength and Conditioning Research, 30(5), 1333–1340. Jones, M. R., West, D. J., Crewther, B. T., Cook, C. J., & Kilduff, L. P. (2015). Quantifying positional and temporal movement patterns in professional rugby union using global positioning system. European Journal of Sport Science, 15(6), 488–496. Kerr, H. A., Curtis, C., Micheli, L. J., Kocher, M. S., Zurakowski, D., Kemp, S. P. T., & Brooks, J. H. M. (2008). Collegiate rugby union injury patterns in New England: a prospective cohort study. British Journal of Sports Medicine, 42(7), 595–603. Kim, D., & Hong, J. (2011). Hamstring to quadriceps strength ratio and non-contact leg injuries: A prospective study during one season. Isokinetics and Exercise Science, 19, 1–6. King, D., Hume, P., Cummins, C., Pearce, A., Clark, T., Foskett, A., & Barnes, M. (2019). Match and training injuries in women’s rugby union: a systematic review of published studies. Sports Medicine, 49(10), 1559–1574. La Fountaine, M. F., Hill-Lombardi, V., Hohn, A. N., Leahy, C. L., & Testa, A. J. (2019). Preliminary evidence for a window of increased vulnerability to sustain a concussion in females: a brief report. Frontiers in Neurology, 10, 691. Logue, D. M., Madigan, S. M., Melin, A., Delahunt, E., Heinen, M., Donnell, S. J. M., & Corish, C. A. (2020). Low energy availability in athletes 2020: an updated narrative review of prevalence, risk, within-day energy balance, knowledge, and impact on sports performance. Nutrients, 12(3), 835. Malinzak, R. A., Colby, S. M., Kirkendall, D. T., Yu, B., & Garrett, W. E. (2001). A comparison of knee joint motion patterns between men and women in selected athletic tasks. Clinical Biomechanics, 16(5), 438–445.

The Female Rugby Player

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Mangan, G., Bombardier, E., Mitchell, A. S., Quadrilatero, J., & Tiidus, P. M. (2014). Oestrogen‐dependent satellite cell activation and proliferation following a running exercise occurs via the PI 3K signalling pathway and not IGF‐1. Acta Physiologica, 212(1), 75–85. Martin, D., Sale, C., Cooper, S. B., & Elliott-Sale, K. J. (2018). Period prevalence and perceived side effects of hormonal contraceptive use and the menstrual cycle in elite athletes. International Journal of Sports Physiology and Performance, 13(7), 926–932. Martin, D., & Elliott-Sale, K. (2016). A perspective on current research investigating the effects of hormonal contraceptives on determinants of female athlete performance. Revista Brasileira de Educação Física e Esporte, 30, 1087–1096. McGhee, D. E., & Steele, J. R. (2020). Breast biomechanics: What do we really know?. Physiology, 35(2), 144–156. McGroarty, N. K., Brown, S. M., & Mulcahey, M. K. (2020). Sport-related concussion in female athletes: A systematic review. Orthopaedic Journal of Sports Medicine, 8(7), 2325967120932306. McNulty, K. L., Elliott-Sale, K. J., Dolan, E., Swinton, P. A., Ansdell, P., Goodall, S., … & Hicks, K. M. (2020). The effects of menstrual cycle phase on exercise performance in eumenorrheic women: a systematic review and meta-analysis. Sports Medicine, 50(10), 1813–1827. Milligan, A., Mills, C., Corbett, J., & Scurr, J. (2015). The influence of breast support on torso, pelvis and arm kinematics during a five kilometer treadmill run. Human Movement Science, 42, 246–260. Misseldine, N. D., Blagrove, R. C., & Goodwin, J. E. (2021). Speed demands of women’s rugby sevens match play. Journal of Strength and Conditioning Research, 35(1), 183–189. Mountjoy, M., Sundgot-Borgen, J., Burke, L., Ackerman, K. E., Blauwet, C., Constantini, N., … & Budgett, R. (2018). International Olympic Committee (IOC) consensus statement on relative energy deficiency in sport (RED-S): 2018 update. International journal of Sport Nutrition and Exercise Metabolism, 28(4), 316–331. Mountjoy, M., Sundgot-Borgen, J., Burke, L., Carter, S., Constantini, N., Lebrun, C., … & Ljungqvist, A. (2014). The IOC consensus statement: beyond the female athlete triad—relative energy deficiency in sport (RED-S). British Journal of Sports Medicine, 48(7), 491–497. Myer, G. D., Ford, K. R., & Hewett, T. E. (2004). Rationale and clinical techniques for anterior cruciate ligament injury prevention among female athletes. Journal of Athletic Training, 39(4), 352. Myer, G. D., Ford, K. R., & Hewett, T. E. (2005). The effects of gender on quadriceps muscle activation strategies during a maneuver that mimics a high ACL injury risk position. Journal of Electromyography and Kinesiology, 15(2), 181–189. Nolte, K., Burgoyne, S., Nolte, H., Van der Meulen, J., & Fletcher, L. (2016). The effectiveness of a range of sports bras in reducing breast displacement during treadmill running and two step star jump. Jurnal of Sports Medicine and Physical Fitness, 56(11), 1311–1317. Norman, L. & French, J. (2013). Understanding how high performance women athletes experience the coach-athlete relationship. International Journal of Coaching Science, 7(1), 3–24. Nyberg, C. C., & Penpraze, V. (2016). Determination of anthropometric and physiological performance measures in elite Scottish female rugby union players. International Journal of Research in Exercise Physiology, 12(1), 10–16. Panay, N. (2011). Management of premenstrual syndrome: evidence-based guidelines. Obstetrics, Gynaecology & Reproductive Medicine, 21(8), 221–228.

256

Emma Ross

Papageorgiou, M., Dolan, E., Elliott-Sale, K. J., & Sale, C. (2018). Reduced energy availability: implications for bone health in physically active populations. European Journal of Nutrition, 57(3), 847–859. Parsons, J. L., Coen, S. E., & Bekker, S. (2021). Anterior cruciate ligament injury: towards a gendered environmental approach. British Journal of Sports Medicine, 55(17), 984–990. Pitchers, G. & Elliott-Sale, K. (2019). Considerations for coaches training female athletes. Professional Strength and Conditioning, 55, 19–30. Posthumus, L., Macgregor, C., Winwood, P., Darry, K., Driller, M., & Gill, N. (2020). Physical and fitness characteristics of elite professional rugby union players. Sports, 8(6), 85. Price, N., Dawood, R., & Jackson, S. R. (2010). Pelvic floor exercise for urinary incontinence: a systematic literature review. Maturitas, 67(4), 309–315. Prien, A., Grafe, A., Rössler, R., Junge, A., & Verhagen, E. (2018). Epidemiology of head injuries focusing on concussions in team contact sports: a systematic review. Sports Medicine, 48(4), 953–969. Queen, R. M. (2017). Infographic: ACL injury reconstruction and recovery. Bone & Joint Research, 6(11), 621–622. Reis, E., Frick, U., & Schmidtbleicher, D. (1995). Frequency variations of strength training sessions triggered by the phases of the menstrual cycle. International Journal of Sports Medicine, 16(08), 545–550. Rizi, R. M., Yeung, S. S., Stewart, N. J., & Yeung, E. W. (2017). Risk factors that predict severe injuries in university rugby sevens players. Journal of Science and Medicine in Sport, 20(7), 648–652. Rugby England (2019). World Rugby Launch Women’s Campaign. [Online] Available at: https://www.englandrugby.com/news/article/world-rugby-launch-womens-campaign. [Accessed November 2020]. Sandwith, E., & Robert, M. (2021). Rug-pee study: the prevalence of urinary incontinence among female university rugby players. International Urogynecology Journal, 32(2), 281–285. Schick, D. M., Molloy, M. G., & Wiley, J. P. (2008). Injuries during the 2006 women’s rugby world cup. British Journal of Sports Medicine, 42(6), 447–451. Sella, F. S., McMaster, D. T., Beaven, C. M., Gill, N. D., & Hébert-Losier, K. (2019). Match demands, anthropometric characteristics, and physical qualities of female rugby sevens athletes: a systematic review. Journal of Strength and Conditioning Research, 33(12), 3463–3474. Sheel, A. W. (2016). Sex differences in the physiology of exercise: an integrative perspective. Experimental Physiology, 101(2), 211–212. Shivitz, N. (2001). Adaptation of vertical ground reactionforce due to changes in breast support in running. Eugene(Oregon): Microform Publications. Smart, D., Hopkins, W. G., Quarrie, K. L., & Gill, N. (2014). The relationship between physical fitness and game behaviours in rugby union players. European Journal of Sport Science, 14(sup1), S8–S17. Suarez-Arrones, L., Portillo, J., Pareja-Blanco, F., de Villareal, E. S., Sánchez-Medina, L., & Munguía-Izquierdo, D. (2014). Match-play activity profile in elite women’s rugby union players. Journal of Strength and Conditioning Research, 28(2), 452–458. Sung, E., Han, A., Hinrichs, T., Vorgerd, M., Manchado, C., & Platen, P. (2014). Effects of follicular versus luteal phase-based strength training in young women. Springerplus, 3(1), 1–10. Tierney, R. T., Sitler, M. R., Swanik, C. B., Swanik, K. A., Higgins, M., & Torg, J. (2005). Gender differences in head-neck segment dynamic stabilization during head acceleration. Medicine and Science in Sports and Exercise, 37(2), 272–279.

The Female Rugby Player

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Triplett, N. T. & Stone, M. (2016). The female athlete. In: Sport injury prevention and rehabilitation. Abington: Routledge, pp. 429–435. Van Pelt, K. L., Puetz, T., Swallow, J., Lapointe, A. P., & Broglio, S. P. (2021). Datadriven risk classification of concussion rates: a systematic review and meta-analysis. Sports Medicine, 51(6), 1227–1244. Wernbom, M., Augustsson, J., & Thomeé, R. (2007). The influence of frequency, intensity, volume and mode of strength training on whole muscle cross-sectional area in humans. Sports Medicine, 37(3), 225–264. White, J. L., Scurr, J. C., & Smith, N. A. (2009). The effect of breast support on kinetics during overground running performance. Ergonomics, 52(4), 492–498. Wolf, J. M., Cannada, L., Van Heest, A. E., O’Connor, M. I., & Ladd, A. L. (2015). Male and female differences in musculoskeletal disease. JAAOS-Journal of the American Academy of Orthopaedic Surgeons, 23(6), 339–347. Woodhouse, L. N., Tallent, J., Patterson, S. D., & Waldron, M. (2021). Elite international female rugby union physical match demands: A five-year longitudinal analysis by position and opposition quality. Journal of Science and Medicine in Sport, 24(11), 1173–1179. Wood, K., Cameron, M., & Fitzgerald, K. (2008). Breast size, bra fit and thoracic pain in young women: a correlational study. Chiropractic & Osteopathy, 16(1), 1–7. Wunderle, M. K., Hoeger, K. M., Wasserman, M. E., & Bazarian, J. J. (2014). Menstrual phase as predictor of outcome after mild traumatic brain injury in women. Journal of Head Trauma Rehabilitation, 29(5), E1. Zatsiorsky, V. M. & Kraemer, W. J. (2006). Science and practice of strength training. Leeds: Human Kinetics. Zemski, A. J., Broad, E. M., & Slater, G. J. (2018). Skinfold prediction equations fail to provide an accurate estimate of body composition in elite rugby union athletes of Caucasian and Polynesian ethnicity. International Journal of Sport Nutrition and Exercise Metabolism, 28(1), 90–99. Zemski, A. J., Slater, G. J., & Broad, E. M. (2015). Body composition characteristics of elite Australian rugby union athletes according to playing position and ethnicity. Journal of Sports Sciences, 33(9), 970–978. Zuckerman, S. L., Apple, R. P., Odom, M. J., Lee, Y. M., Solomon, G. S., & Sills, A. K. (2014). Effect of sex on symptoms and return to baseline in sport-related concussion. Journal of Neurosurgery: Pediatrics, 13(1), 72–81. Zumwalt, M. (2018). Musculoskeletal injury and the exercising female. In: The Exercising Female (pp. 142–159). Routledge.

16 MODIFIED RUGBY Craig Twist

16.1 Introduction Modified versions of the rugby, such as sevens, touch, tag and wheelchair rugby have increased in popularity. For example, rugby sevens has a higher profile because of tournaments such as HSBC Sevens, Women’s Sevens and its introduction to the 2016 Olympic Games. Non-contact versions of touch and tag have become increasingly popular as part of the school curriculum, competitively and have also emerged as viable modes to promote physical activity. Wheelchair rugby is played to international standards and enables disabled athletes to participate in the sport. This chapter offers a summary of the current science of modified rugby formats.

16.2 Rugby sevens 16.2.1 Competition demands of rugby sevens Rugby sevens is played as 2 × 7 min halves (2 × 10 min in cup finals) with a 2-minute half time, contested by seven players (three forwards and four backs) using the same rules and same size playing area as 15-a-side rugby. The game is typically played as a two- to three-day tournament comprising two to three matches per day. In male and female players, overall distance covered (~1200–1500 m) in a match is lower than 15-a-side because of the shorter playing time (Higham et al., 2012; Vescovi & Goodale 2015). However, mean speed (86–130 m·min−1; Higham et al., 2012; Ross et al., 2015b; Higham et al., 2016; Clarke et al., 2017), high-speed running (120 and 201 m for females and males respectively; Clarke et al., 2017) and work to rest ratios (1:0.3 and 1:0.5 for females and males, respectively; Portillo et al., 2014) are higher because reduced player numbers allow DOI: 10.4324/9781003045052-17

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increased movement. Players of both sexes have mean heart rates of ~170 b·min−1 (80–90% maximum) during a match (Suarez-Arrones et al., 2012; Granatelli et al., 2014; Portillo et al., 2014; Vescovi & Goodale, 2015; Higham et al., 2016). Small differences are reported in total distance, high- and low-intensity activities between positions during international match play, yet backs perform more highspeed running of longer distance and involvements with the ball and forwards are involved in more contacts (Ross et al., 2015a, 2015b; Higham et al., 2016). Male players cover more distance (~1200 m cf. ~1000 m), more relative distance (~100 cf. ~90 m·min−1) more high-speed running (~200 cf. ~120 m), more sprinting (~220 m cf. ~150 m) and perform more impacts (~25 cf. ~13) than female players (Clarke et al., 2017). Sex-related physiology (Hunter et al., 2016) and the use of the same arbitrary thresholds for quantifying movement characteristics will explain some of these differences. Differences in match characteristics between playing standards for male sevens players come from more distance at high speeds, more sprints, involvement in more rucks, a greater number of impacts and greater ballin-play time for higher (i.e., international) compared to lower standard players (Ross et al., 2015a; Clarke et al., 2017). There is more variability in movement characteristics between playing standards in female sevens players; notably higher peak speeds, more high-speed running, greater sprint distance and more impacts in elite players (Portillo et al., 2014; Vescovi & Goodale, 2015; Clarke et al., 2017). A complete overview of movement demands of women’s and men’s sevens can be found in a systematic review by Ball et al. (2019). Small to moderate reductions in running in the second half of matches suggest that players of both sexes demonstrate cumulative fatigue within a single match (Higham et al., 2012; Granatelli et al., 2014; Suarez-Arrones et al., 2014; Furlan et al., 2015; Ross et al., 2015a; Goodale et al., 2017; Malone et al., 2020). Furlan et al. (2015) have also reported transient fatigue in elite male sevens players during matches where 2-min peak periods were immediately followed by reductions in movement intensity. These transient fluctuations in movement intensity indicate players adopt a pacing strategy in an effort to optimize performance (Waldron & Highton, 2014). However, players seem capable of maintaining similar running characteristics across a multi-day tournament (Higham et al., 2012; Ross et al., 2015b). Match running performance is also influenced by contextual factors, such as match score, opposition quality and environmental temperature (Goodale et al., 2017; Henderson et al., 2020). There are often short periods of time (~5–7 days) between tournaments that involve flights across multiple time zones, meaning players might be subject to symptoms of travel-related fatigue (West et al., 2014).

16.2.2 Training demands of rugby sevens During a 3-week preparation period, the average duration for training sessions was between 35 and 50 minutes with players covering distances ~3000 m, mean speeds of ~80–90 m·min−1 and ~10–12 m·min−1 of high-speed running (Gibson et al., 2016). Higham et al. (2016) reported the on-field training demands of an international sevens

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team were lower than those observed in matches, with forwards exposed to lower physiological demands yet more accelerations and high speed (>6 m·s−1) running than backs. Low-intensity skill sessions offered the poorest representation of physiological and movement match demands (Higham et al., 2016), which is to be expected given the emphasis of these drills. However, game-simulation drills did not replicate the physiological and physical loads associated with match play (Higham et al., 2016). Griffin et al. (2017) examined training demands of international women’s sevens players across seven multi-day training camps (2–4 d) structured around four two-day tournaments. On average, training sessions lasted ~90 min with distances of ~3800 m (~44 m·min−1), ~240 m (~2.8 m·min−1) of sprinting from ~41 (~0.5 per minute) sprints. Women’s training reflected a technical and tactical focus by coaches to prepare players for competition and minimize residual fatigue. Training has a number of different purposes and is influenced by multiple factors such as season phase, recovery, travel, environment and individual differences. A true representation of the match environment is compounded by difficulties in replicating the contextual factors that influence running (e.g., crowd, score line, environmental conditions; Goodale et al., 2017; Henderson et al., 2020), the accompanying psychological stress associated with match play, the desire to enable coaching and minimizing residual fatigue between tournaments. However, a failure to replicate match loads in game-specific drills might under prepare players and impair the development of skills and decision-making at high intensities.

16.2.3 Physical qualities of sevens players Different movement demands (e.g., ~45% more relative running volume and ~135% more high velocity running; Higham et al., 2012) require sevens players of both sexes to have lower body mass and higher lean mass than 15-a-side players (Table 16.1). Male players are typically heavier and taller than female players (Clarke et al., 2017), with male sevens players possessing ~40% more lean mass and ~40% lower skinfold thickness than female players (Pyne et al., 2012). Other than forwards being heavier than backs for scrummaging (Fuller et al., 2010; Agar-Newman et al., 2017), differences in physical qualities between positions for both sexes (Pyne et al., 2012; Ross et al., 2015b; Agar-Newman et al., 2017) are typically small given the homogeneity in activity profiles between forwards and backs. Specific conditioning training for positional groups in sevens remains debatable (Clarke et al., 2017) and suggests why few studies report data for positional groups. In female players, physical qualities discriminate better between playing standards and hold stronger associations with match characteristics (Vescovi & Goodale, 2015; Clarke et al., 2017). For example, female athletes who played the most minutes of international competition were older, had greater training experience, better upper body maximum strength and a higher aerobic fitness (Goodale et al., 2017). Female players’ high-intensity running capacity (i.e., distance achieved in the YoYo IR1) also explained ~30–40% of the variance in high-intensity

Touch rugby O’Connor (1997) Ogden (2010)

Goodale et al. (2017)

Higham et al. (2012) Ross et al. (2015a)

Clarke et al. (2017)

Rugby Sevens Elloumi et al. (2012) Agar-Newman et al. (2017)

Reference

Int

Prov

M

M

All

All

F

F (mixed)

All

All

Nat

M

All

All

All

All

24.9 ± 4.8

23.2 ± 2.4

23.3 ± 4.0

23.5 ± 3.9

22.1 ± 3.2

24.3 ± 3.3

21.2 ± 3.4

24.0 ± 3.7

– 21.9 ± 2.0

–

Forward All

All All

22.8 ± 4.0

23.8 ± 3.1

Age (y)

Back

All

Position

M (mixed)

Int

F

Int

Nat

F M

F

Nat

Nat

F

M

Nat

Group

M

Sex

62.6 ± 4.8

64.9 ± 6.3

75.5 ± 9.0

75.1 ± 7.6

56.8 ± 4.2

70.0 ± 4.9

89.1 ± 9.5

95.7 ± 7.1

68.6 ± 4.4 89.7 ± 7.6

72.9 ± 4.8 92.0 ± 6.9

66.4 ± 3.5

87.3 ± 7.4

Body mass (kg)

166 ± 6

166 ± 5

173 ± 5

177 ± 7

163 ± 8

168 ± 7

182 ± 5

186 ± 6

169 ± 2 183 ± 6

171 ± 4 184 ± 7

166 ± 6

183 ± 1

Stature (cm)

–

–

–

–

71.3 ± 11.8

86.8 ± 11.2

73.8 ± 15.5

61.6 ± 10.5

67 ± 14 52.2 ± 11.5

95.0 ± 12.3 48 ± 6

84.4 ± 26.1

–

Σ7 skinfolds (mm)

1.86 ± 0.09

1.85 ± 0.05

1.72 ± 0.11

1.70 ± 0.06

1.82 ± 0.09

1.83 ± 0.05

1.73 ± 0.08

1.68 ± 0.05

1.76 ± 0.05 1.74 ± 0.06

1.84 ± 0.04 1.76 ± 0.06

1.81 ± 0.03

1.80 ± 0.07

10 m sprint (s)

–

–

–

–

5.71 ± 0.22

5.66 ± 0.11

5.23 ± 0.18

4.99 ± 0.11

5.50 ± 0.16 5.11 ± 0.15

5.72 ± 0.12 5.14 ± 0.16

5.60 ± 0.06

–

40 m sprint (s)

–

–

–

–

–

–

–

–

49.6 ± 3.8 66.3 ± 72

– 65.8 ± 9.3

–

–

CMJ (cm) ∗

TABLE 16.1 Physical qualities of male and female representative sevens, touch and tag players. Values are mean ± SD

(Continued)

Predicted V O2max: 50.8 ± 3.2 ml·kg−1·min−1 Predicted V O2max: 55.8 ± 3.7 ml·kg−1·min−1 Predicted V O2max: 54.7 ± 4.8 ml·kg−1·min−1 Predicted V O2max: 49.1 ± 2.8 ml·kg−1·min−1 Predicted V O2max: 50.2 ± 6.3 ml·kg−1·min−1

20 m multistage fitness test: 2563 ± 197 m 20 m multistage fitness test: 2164 ± 288 m 1.6 km time-trial: 370 ± 25 s

Yo-Yo IR1: 1702 ± 329 m Yo-Yo IR1: 2256 ± 268 m

1.6 km time-trial: 370 ± 25 s Yo-Yo IR1: 2351 ± 371 m

1.6 km time-trial: 390 ± 28 s

Yo-Yo IR2: 1925 ± 333 m

Endurance

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Nat

Int

Group

24 ± 4 26 ± 3 22 ± 2

Inside Outside

25.4 ± 5.2

25.5 ± 5.4

Age (y)

All

All

All

Position

76.7 ± 9.7 75.2 ± 9.7

75.9 ± 9.4

76.5 ± 7.9

60.5 ± 6.1

Body mass (kg)

175 ± 3 181 ± 7

178 ± 6

178 ± 6

163 ± 5

Stature (cm)

– –

–

–

–

Σ7 skinfolds (mm)

1.69 ± 0.08 1.60 ± 0.07

1.65 ± 0.08

1.88 ± 0.10

2.09 ± 0.16

10 m sprint (s)

– –

–

–

–

40 m sprint (s)

51.3 ± 3.2 56.1 ± 5.4

53.7 ± 5.0

36.3 ± 5.0

26.3 ± 3.1

CMJ (cm) ∗

Yo-Yo IR2: 1115 ± 406 m Yo-Yo IR2: 930 ± 269 m

YoYo-IR2: 1023 ± 346 m

YoYo-IR1: 1846 ± 528 m

YoYo-IR1: 884 ± 312 m

Endurance

∗

Note different apparatus was used to measure vertical jump, i.e., Vertec device for 7s and Tag vs. force platform for Touch.

Abbreviations: F/M – female/male; Nat/Int – national/international; CMJ – countermovement jump; Yo-Yo IR1 – Yo-Yo Intermittent recovery test Level 1; Yo-Yo IR2 – Yo-Yo Intermittent recovery test Level 2. Predicted V O2max from 20 m multistage fitness test.

M

M

F

Dobbin et al. (2022)

Tag rugby Hogarth et al. (2015a)

Sex

Reference

TABLE 16.1 (Continued)

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movements during match play (Vescovi & Goodale, 2015). Although other factors will clearly contribute to match performance, training and improved physical qualities are likely to be beneficial given the apparent heterogeneity in physical fitness characteristics reported in female players. As specific research into females and training practices evolve, players are likely to share similar physical qualities and other rugby-centric determinants will influence performance and selection at higher standards. Moderate to large associations between physical qualities and match performance have been reported in male sevens players, albeit ‘fitness’ accounted for only ~35% of variations in match activities (Ross et al., 2015c). Sprint and jumping ability held the strongest associations with several attack- and defence-orientated match activities (e.g., line breaks, defenders beaten, tackle performance dominant tackles), whereas associations between match activities and measures of maximum strength and aerobic power were lower in magnitude (Ross et al., 2015c). Clarke et al. (2017) reported that strength, power, technical and tactical ability were more likely to influence selection to higher standards in male sevens players. Already well-developed physical qualities that are more homogenous between players means other qualities are likely to explain the variations in performance at the higher standards in male sevens.

16.3 Touch and tag rugby 16.3.1 Competition demands of touch rugby Touch (rugby) comprises six players on the pitch at one time, with another eight players used as unlimited ‘rolling’ substitutes. Touch has no tackling or scrummaging with each team having six touches to progress the ball down the field until the ball is handed over to the opposing team. Teams comprise either single or mixed-sex formations that are categorized by player age. International tournaments involve matches lasting 40 minutes (2 × 20-minute halves), with a maximum of three matches played in one day over successive days (typically 3–5 days). In domestic tournaments, teams normally play a minimum of 5 × 20-minute matches (maximum 6 matches) over one day. Movement data on touch players is typically based on individual teams using small sample sizes. Ogden (2010) reported only differences in maximum speed between elite New Zealand male and female players (~12%), with similar distances of 2000–3000 m and mean speeds of 150–166 m·min−1 reported during matches. UK International and regional male touch players (Men’s Open) covered mean speeds during a match of ~140 and ~125 m·min−1, respectively (Beaven et al., 2014), which are partly explained by greater high speed running (>14 km·h−1) for international compared to regional players (~40 cf. ~25 m·min−1; Beaven et al., 2014). In international female touch players (Women’s Open, UK), mean speed during matches was ~120 m·min−1 that comprises ~25 m·min−1 of high-speed running (Marsh et al., 2017). Differences in movement characteristics between

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males and females support observations that the composition of the team, i.e., single vs. mixed-sex, influences the movement characteristics (Ogden, 2010; Vickery & Harkness, 2017; Prather et al., 2021; Dobbin et al., 2022). Differences in movement characteristics between players within a team are also likely to be influenced by playing position (i.e., middles, links and wing). Players in the middle and link positions perform more multidirectional running and a greater number of attacking and defending involvements (Vickery & Harkness, 2017; Chow, 2020; Dobbin et al., 2022). Compared to wingers, middles and link positions make greater use of interchanges during a match that leads to a reduced playing time for these positions (Chow, 2020). With a longer playing time, wingers tend to cover greater distance and with more linear movements reach greater peak speeds than middles and links but also perform more walking and running at slower speeds (Vickery & Harkness, 2017; Chow, 2020). Only two studies have examined movement characteristics between the first and second half of matches, reporting only trivial to small differences for male and female players (Prather et al., 2021; Zaragoza et al., 2022). As such, the occurrence of fatigue during a touch match seems unlikely and different to the changes in movement characteristics observed in other rugby codes, e.g., Waldron et al. (2013). Shorter match durations (i.e., 2 × 20 min or 1 × 20 m for international and regional, respectively) will contribute to less fatigue as will the use of unlimited interchange that enables players to play multiple playing bouts of short duration. For example, Vickery & Harkness (2017) reported mixed team players to perform ~3–5 bouts per match with mean durations of ~90–360 s depending on playing position; links and middles playing more bouts (~4–5) of shorter duration (~90–120 s) compared to wings playing fewer bouts (~3) but longer duration (~360 s). Players will work in small (2–3 players) positionally arranged groups (or Pods) to self-determine when they interchange, removing themselves from the field of play to rotate with a partner. This strategy is an example of players pacing to distribute their energy resources and maintain match running performance (Waldron & Highton, 2014). Mean speed and high-speed running fluctuate between days during a tournament for both male and female touch players (Marsh et al., 2017; Dobbin et al., 2020a; Dobbin et al., 2022), suggesting a combination of both exercise-induced fatigue and pacing.

16.3.2 Competition demands of tag rugby Tag, or flag rugby, is non-contact with players wearing a belt or shorts with two Velcro tags attached. Tag requires players to remove a Velcro tag (i.e., tagging) from the ball carrier to initiate the ‘tackle’ and restart play, with five ‘plays’ before the ball is handed over to the opponents. Teams comprise eight on-field players at one time and can be of single or mixed-sex, with mixed teams having a maximum of four male players per team and tries scored by females accruing two rather than one point. Matches are 20 minutes per half played on a field of 70 × 50 m. Unlike touch, players can kick the ball in general play, albeit this must be below the referee’s shoulder height and after the fourth tag. Tag rugby is played worldwide

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in several guises, such as Try Tag Rugby (UK), OzTag, and Mini Tag (children). Tag is also used as part of the school sport/PE curriculum due to inclusivity (e.g., mixed-sex teams), team work, development of fundamental movement skills, encouraging moderate-to-vigorous activity, while no-contact avoids issues that might discourage participation (Pugh & Alford, 2004). Tag players of both sexes perform multiple on-field efforts comprising ~5–6 field rotations lasting ~4–5 min with the interchange rule allowing players to have ~4–6 interchanges lasting ~2.5–3.5 min (Hogarth et al., 2014; Hogarth et al., 2015d). Total playing times in tag are shorter for males (~20–26 min) compared to females (~19–35 min), with mean speeds of ~80–105 m·min−1 and ~71–97 m·min−1 for males and females, respectively (Hogarth et al., 2014; Hogarth et al., 2015a; Hogarth et al., 2015d). High-speed running accounts for ~13% (females) and ~15% (males) of the overall mean speed, performed intermittently throughout a match at a rate of one high-speed effort every ~45–60 s (Hogarth et al., 2014). Regardless of sex, higher-standard tag players perform more high-speed running efforts, cover greater distance at very high-intensity (>18 km·h−1) and possess higher maximum running speeds during match play (Hogarth et al., 2014; Hogarth et al., 2015d). Mean heart rates of ~170 b·min−1 (86% peak heart rate) and mean RPE (Borg’s CR-10) of ~4.7 AU have also been reported in male players during match play (Hogarth et al., 2015a). Movement characteristics in tag are influenced by playing position. Despite similar playing times, interchanges and field rotation times, relative high-speed running during male tag match play is greater for outside players (i.e., links and wings) because these positions often have more space allowing higher running speeds (Hogarth et al., 2014; Hogarth et al., 2015a). Wings, however, appear to have greater recovery between work efforts than middles and links (Hogarth et al., 2014) and have fewer maximal acceleration and deceleration efforts (Hogarth et al., 2014; Hogarth et al., 2015a). Female middles and links have greater high-speed running compared to wings yet wingers typically played for longer (~31 min) than middles (~23 min) and links (~21 min), and performed fewer interchanges (~3) compared to other positions (~6) (Hogarth et al., 2014). Tactical strategies in females might increase the risk of fatigue in wider positions that results in different positional movement characteristics compared to males. Changes in distance covered and high-speed running between the first and second halves of matches are reported to be trivial and small for male and female players, respectively (Hogarth et al., 2014). As with touch, male players adopt suitable pacing strategies to limit fatigue during a match using consistent interchanges (~2 per half) of similar duration (~5 min). Conversely, female players adopt more interchanges in the first vs. second half (~3 vs. 2) with bouts in the second half lasting longer (~4.3 vs. 5.4 min). Longer field rotations in the second half for females might promote fatigue that manifests as a reduction in high-intensity movements in the latter stages of a match. During multi-day tournaments, male players show progressive declines in match running performance within and between days and accumulation of fatigue as the tournament progresses (Hogarth et al., 2015c).

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16.3.3 Physical qualities of touch and tag players The physical qualities of touch and tag players remain relatively unexplored compared to other rugby codes, with data largely based on small sample sizes of representative teams. Touch and tag players demonstrate lower body mass than those players from contact versions of the game, with fast times over short distances (5–10 m) and superior V O2max and high-intensity intermittent running capacity (O’Connor, 1997; Ogden, 2010; Hogarth et al., 2015a; Hogarth et al., 2015d; Dobbin et al., 2022). There are differences in physical qualities between sexes for both tag and touch (Ogden, 2010; Dobbin et al., 2022), between playing positions (Hogarth et al., 2015a; Dobbin et al., 2022) and playing standards (Hogarth et al., 2015d). Data on physical qualities for touch and tag players is provided in Table 16.1. Distance covered during Yo-Yo IR1 and IR2 tests influences a number of movement characteristics (total dance, distance per minute, high-speed running, repeated high-intensity efforts) and internal responses (heart rate and perceived effort) during touch and tag match play (Hogarth et al., 2015a; Hogarth et al., 2015d; Dobbin et al., 2022). A superior intermittent high-speed running capability is also associated with reduced fatiguability despite greater activity and internal load during multi-day tournaments (Hogarth et al., 2015b). Other qualities such as sprint speed, change of direction and lower body muscle power also influence match performance in touch (Dobbin et al., 2022) and tag (Hogarth et al., 2015a). These data provide guidelines for practitioners conditioning touch and tag players.

16.4 Modified rugby for health Tag and touch offer ways of providing moderate to vigorous physical activity (Griffin et al., 2021), with data in children suggesting mean metabolic equivalent of task (MET) values of ~6 METS (Moy et al., 2006) and mean heart rate in adults exceeding 80% maximum (Beaven et al., 2014; Filliau et al., 2015; Hogarth et al., 2015a; Vickery & Harkness, 2017). Modified rugby enables a range of groups to participate in recognizable sporting activities that are focused on promoting enjoyment, exercise adherence as well as physical, social and psychological well-being (Griffin et al., 2021). Training interventions (≤12 weeks) using touch have shown positive effects on markers of cardiovascular health. Dobbin et al. (2020b) reported similar reductions in resting heart rate (~3–4 b·min−1) but greater reductions in systolic blood pressure (~6 cf. ~2 mmHg) in active men playing one touch session per week for 4 weeks compared to a similar group using traditional interval running. Mendham and colleagues reported improved submaximal power and V O2 in sedentary men after 8 weeks of touch (Mendham et al., 2014) and increased aerobic capacity, power output and time to exhaustion in previously inactive males after training 3 d·week−1 for 8 weeks playing touch (Mendham et al., 2015a). Increases in aerobic capacity were comparable to a group of inactive males who performed duration matched cycling over the same period but greater than a control group (Mendham et al., 2015a). Twelve weeks of a single 90 min touch training session

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per week in sedentary adults reported moderate to large reductions in resting heart rate, systolic and diastolic blood pressure, alongside small increases in maximal oxygen uptake and maximal aerobic speed (Filliau et al., 2015). Changes were attributed to training-induced decreases in resting sympathetic activity and improved parasympathetic modulation (Filliau et al., 2015), although data should be interpreted with caution because the study did not use a control group. A single bout of modified rugby has also been shown to stimulate intracellular signalling pathways associated with mitochondrial biogenesis in sedentary, middle-aged males (Mendham et al., 2016). However, training 3 d·week−1 for 8 weeks using touch resulted in no changes in the content of skeletal muscle proteins associated with glucose regulation and mitochondrial biogenesis (Mendham et al., 2015a). A single bout of touch with middle-aged men (Mendham et al., 2015b) and Indigenous Australian men (Mendham et al., 2012) with a high risk of metabolic disease induced immediate increases in acute inflammatory markers (e.g., IL-6, IL-1ra) that remained elevated above pre-exercise values for 240 min afterwards. This exercise-induced anti-inflammatory response alongside elevated cortisol appeared to impose an inhibitory effect on pro-inflammatory cytokines (e.g., TNF-α, IL-1β) that along with C-reactive protein remained unchanged in the 240 min after modified rugby (Mendham et al., 2012; Mendham et al., 2015b). These inflammatory responses immediately after modified rugby occurred alongside a greater reduction in blood glucose and delayed insulin response, that are like the inflammatory and glucose responses observed after stationary cycling matched for intensity and duration (Mendham et al., 2012; Mendham et al., 2015). Chronic reductions in inflammatory markers have also been reported alongside reductions in total and regional fat mass and increases in muscle mass after touch interventions lasting 4–8 weeks in both sedentary and active men (Mendham et al., 2014; Mendham et al., 2015a; Dobbin et al., 2020b). Modified rugby offers a strategy to improve chronic inflammation and protection against disease in less active males, albeit these effects might be influenced by other population-specific factors and work in females and younger sedentary groups is required. While the intensity of modified team sports is high, Mendham et al. (2012) reported those participating in touch rugby perceived the activity to be less challenging (6.6 ± 2.0 cf. 7.4 ± 1.8 AU) and to be more ‘fun’ (6.6 ± 0.5 cf. 5.2 ± 1.3 AU) when compared to cycle ergometry. In contrast, Dobbin et al. (2020b) reported similar positive well-being, psychological distress and perceived fatigue between two groups who performed 4 weeks of touch and interval training, respectively. Incorporating modified rugby as part of an overall strategy to promote physical activity and psychological well-being might therefore help encourage participation and adherence to appropriate exercise, particularly in groups that are attracted to such team sports. However, the adoption of modified rugby in normally sedentary populations should consider potential implications for injury, physiological complications, technical proficiency and resulting muscle soreness when compared against more traditional exercise (e.g., cycling) that can induce similar adaptations.

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16.5 Wheelchair rugby 16.5.1 Competition demands of wheelchair rugby Wheelchair rugby comprises 4 × 8 min quarters played indoors on the preferred surface of hardwood and adheres to the same measurements as a regulation basketball court (15 × 28 m). Teams have 40 s in possession of the ball to score, after which the ball is passed to the opposition. The majority of wheelchair rugby athletes have a spinal cord injury, although tetraequivalent athletes (i.e., non-spinal cord injury) such as cerebral palsy, forms of muscular dystrophy and multiple amputations also compete. Wheelchair rugby players are classified using one of seven classifications depending on functional ability (0.5 = least function to 3.5 = most function; International Wheelchair Rugby Federation), which have subsequently been used to group players into defensive (Groups I [0.5] and II [1.0–1.5]) and offensive players (Groups III [2.0–2.5] and IV [3.0–3.5) (Rhodes et al., 2015a; Rhodes et al., 2015b). Upper body function and wheelchair manoeuvrability differentiate between on-court roles, with lower and higher-function players typically assigned to defensive and offensive roles, respectively (Molik et al., 2008). Each team compromises four on-court players at a time, with the total number of points not exceeding 8 points (Molik et al., 2008; Rhodes et al., 2015a). Depending on classification, wheelchair rugby players cover between 3500 and 5500 m per match at mean speeds of 60–90 m·min−1 (Sarro et al., 2010; Rhodes et al., 2015b). Typical movement characteristics across match quarters are shown in Table 16.2. Movement characteristics of wheelchair rugby players during competition are influenced by multiple factors, including classification, player role and team rank. For example, lower-function players typically exhibit less total distance, lower peak TABLE 16.2 Summary of movement variables during a typical match quarter for national

men’s wheelchair players. Values are mean ± SD IWRF classification I (n= 38)

II (n = 138)

III (n = 122)

IV (n = 108)

Total distance (m) Relative distance (m·min−1) Peak speed (m·s−1)

881 ± 137 60 ± 7 2.99 ± 0.28

1011 ± 142 70 ± 8 3.44 ± 0.26

1155 ± 196 77 ± 7 3.67 ± 0.32

1153 ± 172 78 ± 10 3.82 ± 0.31

High-intensity activities ∗ Number (n) Mean duration (s) Maximum duration (s) Mean distance (m) Maximum distance (m)

13 1.7 4.3 4.7 11.7

11 1.7 4.2 5.4 13.5

9 1.8 4.4 6.3 15.4

9 1.9 4.0 6.4 14.8

± ± ± ± ±

7 0.8 2.3 2.3 5.2

± ± ± ± ±

6 0.7 1.9 2.1 6.2

± ± ± ± ±

5 0.8 2.3 2.6 8.4

± ± ± ± ±

6 0.8 1.8 2.8 6.6

Data adapted from Rhodes et al. (2015b); IWRF = International Wheelchair Rugby Federation Note ∗ High-intensity defined as >81% peak speed.

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speeds and greater fatiguability, i.e., reductions in high-intensity activity between the first and second half of a match (Sarro et al., 2010; Rhodes et al., 2015a; Rhodes et al., 2015b). Players with a higher functional classification are likely to possess higher aerobic capacity, which might contribute to reduced fatigue during a match (Sarro et al., 2010). Similarly, players with a higher classification are superior in points scored, interceptions and passes made/received (Molik et al., 2008). Defensive players perform more low-speed activities and more high-intensity bouts compared to offensive players (Rhodes et al., 2015a). Other classification-related factors will influence wheelchair rugby players’ movements during match play. For example, players with a spinal cord injury (i.e., lower classification) possess reduced heat loss capacity and experience greater thermal strain during wheelchair rugby match play compared to those players without (i.e., higher classification) (Griggs et al., 2017). Finally, more successful wheelchair rugby teams performed more high-speed movements and had highest peak speeds (Rhodes et al., 2015a). Lower-ranked teams had players on the court for less time, which has been attributed to poorer fitness in these teams (Rhodes et al., 2015a).

16.5.2 Physical qualities of wheelchair rugby players Wheelchair rugby players have body mass values of ~65–72 kg that comprise a lean mass of ~46–52 kg and fat mass of ~16–17 kg (Goosey-Tolfrey et al., 2016; Griggs et al. 2017; Flueck, 2020). Regional fat-free mass of ~7 kg in the arms, ~14 kg in the legs and 26 kg in the trunk compares to fat mass of ~2 kg, 6 kg and 8 kg in the arms, legs and trunk, respectively (Flueck, 2020). Percentage body fat measured using dual-energy x-ray absorptiometry show values of ~24–26% in wheelchair rugby players (Goosey-Tolfrey et al., 2016; Griggs et al., 2017), which are higher than when percent fat values have been predicted using a range of skinfold equations (~12–19%; Goosey-Tolfrey et al., 2016). Body composition using the sum of 4 skinfolds (biceps, triceps, subscapular and suprailiac) has values of ~57 mm and ~51 mm for rugby players with a spinal cord injury and those without, respectively (Griggs et al., 2017). V O2peak values of ~1.50–1.80 L·min−1 or ~28 ml·kg−1·min−1 have been reported for wheelchair rugby players using treadmill ergometry and modified multistage fitness test (Morgulec-Adamowicz et al., 2011; Griggs et al., 2015; Weissland et al., 2016; Goosey-Tolfrey et al., 2021) or ~1.1 L·min−1 or ~16 ml·kg−1·min−1 using arm ergometry (Barfield et al., 2010). V O2peak in wheelchair rugby players with a spinal cord injury (~1.4–1.6 L·min−1, classification 0.5–2.5) is lower compared to those with non-spinal cord-related physical impairments (~2.4 L·min−1, classification 1.5–3.5) (Morgulec-Adamowicz et al., 2011; Griggs et al., 2017). Using a more game-specific test, Kelly and colleagues reported peak speeds of 10.7 ± 1.7 km·h−1 using a modified intermittent 30–15 intermittent fitness test performed over a 28 m (30–15IFT-28 m) on an indoor court (Kelly et al., 2018). Performance in the 30-15IFT-28 m was also dependant of classification, with higher peak speeds achieved by those with higher functional ability (Kelly et al., 2018). Using a one-mile mile

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push conducted on a 200 m indoor track, moderate differences in time were reported between those players selected (~7.7 min) and non-selected (~8.7 min) for a national team (Barfield & Malone, 2012). Sprint and repeat sprint ability are important qualities for wheelchair rugby players given these replicate the demands of match play (Gee et al., 2018). Fastest times of ~1.4 s, ~4.0 s and ~6.3 s are reported for 5, 10 and 20 m sprints, respectively (West et al., 2014; Gee et al., 2018) with peak speeds greater in higher (~3.98 m·s−1) compared to lower (~3.31 m·s−1) classification players (Gee et al., 2018). Small differences in sprint, sprint endurance and agility performance have also been reported between selected and non-selected national representative wheelchair rugby players (Barfield & Malone, 2012). Upper body 30 s Wingate performance in wheelchair rugby players again reveals differences between players of different classifications, with peak power outputs of ~227 W, ~199 W, ~137 W and 83 W for groups 4, 3, 2 and 1, respectively (Morgulec-Adamowicz et al., 2011).

16.6 Conclusion Modified rugby formats possess different movement characteristics and physical qualities compared to the 13 and 15-a-side versions of the game. The match demands can be influenced by factors such as sex, playing position, tournament format, travel and in the case of wheelchair rugby functional classification. Physical qualities also influence player performance and should be an important consideration alongside technical and tactical preparation. Modified rugby might also be part of a broad range of physical activities to promote moderate to vigorous physical activity in healthy and sedentary groups to improve cardiovascular, metabolic and psychological health.

References Agar-Newman, D. J., Goodale, T. L., & Klimstra, M. D. (2017). Anthropometric and physical qualities of international level female rugby sevens athletes based on playing position. Journal of Strength and Conditioning Research, 31(5), 1346–1352. Ball, S., Halaki, M., & Orr, R. (2019). Movement demands of rugby sevens in men and women: a systematic review and meta-analysis. Journal of Strength and Conditioning Research, 33(12), 3475–3490. Barfield, J. P., & Malone, L. A. (2012). Performance test differences and paralympic team selection: Pilot study of the United States national wheelchair rugby team. International Journal of Sports Science & Coaching, 7(4), 715–720. Barfield, J. P., Malone, L. A., Arbo, C., & Jung, A. P. (2010). Exercise intensity during wheelchair rugby training. Journal of Sports Sciences, 28(4), 389–398. Beaven, R. P., Highton, J. M., Thorpe, M. C., Knott, E. V., & Twist, C. (2014). Movement and physiological demands of international and regional men’s touch rugby matches. Journal of Strength and Conditioning Research, 28(11), 3274–3279.

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Chow, C. C. G. (2020). Global positioning system activity profile in touch rugby: does training meet the match-play intensity in a two-day international test match series? Journal of Sports Science & Medicine, 19(3), 613–619. Clarke, A. C., Anson, J. M., & Pyne, D. B. (2017). Game movement demands and physical profiles of junior, senior and elite male and female rugby sevens players. Journal of Sports Sciences, 35(8), 727–733. Dobbin, N., Thorpe, C., Highton, J., & Twist, C. (2020a). Sex-related changes in physical performance, well-being, and neuromuscular function of elite touch players during a 4-day international tournament. International Journal of Sports Physiology and Performance, 1(15(8)), 1138–1146. Dobbin, N., Bloyce, D., Hughes, S. F., & Twist, C. (2020b). Effects of a 4-week touch rugby and self-paced interval running intervention on health markers in active young men. Sport Sciences for Health, 16(4), 635–643. Dobbin, N., Thorpe, C., Highton, J., & Twist, C. (2022). Individual and situational factors affecting the movement characteristics and internal responses to Touch match-play during an international tournament. Science and Medicine in Football, doi: 10.1080/24733 938.2022.2107232 Elloumi, M., Makni, E., Moalla, W., Bouaziz, T., Tabka, Z., Lac, G., & Chamari, K. (2012). Monitoring training load and fatigue in rugby sevens players. Asian journal of sports medicine, 3(3), 175. Filliau, C., Younes, M., Blanchard, A. L., Piscione, J., Van de Louw, A., Seguret, C., … & Cottin, F. (2015). Effect of “touch rugby” training on the cardiovascular autonomic control in sedentary subjects. International Journal of Sports Medicine, 36(07), 567–572. Flueck, J. L. (2020). Body composition in swiss elite wheelchair athletes. Frontiers in Nutrition, 7, 1. Fuller, C. W., Taylor, A., & Molloy, M. G. (2010). Epidemiological study of injuries in international rugby sevens. Clinical Journal of Sport Medicine, 20(3), 179–184. Furlan, N., Waldron, M., Shorter, K., Gabbett, T. J., Mitchell, J., Fitzgerald, E., & Gray, A. J. (2015). Running-intensity fluctuations in elite rugby sevens performance. International Journal of Sports Physiology and Performance, 10(6), 802–807. Gee, C. M., Lacroix, M. A., & West, C. R. (2018). A 20× 20 m repeated sprint field test replicates the demands of wheelchair rugby. Journal of Science and Medicine in Sport, 21(7), 753–757. Gibson, N. E., Boyd, A. J., & Murray, A. M. (2016). Countermovement jump is not affected during final competition preparation periods in elite rugby sevens players. Journal of Strength and Conditioning Research, 30(3), 777–783. Goodale, T. L., Gabbett, T. J., Tsai, M. C., Stellingwerff, T., & Sheppard, J. (2017). The effect of contextual factors on physiological and activity profiles in international women’s rugby sevens. International Journal of Sports Physiology and Performance, 12(3), 370–376. Goosey-Tolfrey, V. L., de Groot, S., Tolfrey, K., & Paulson, T. A. (2021). Criterion validity of a field-based assessment of aerobic capacity in wheelchair rugby athletes. International Journal of Sports Physiology and Performance, 16(9), 1341–1346. Goosey-Tolfrey, V., Keil, M., Brooke-Wavell, K., & de Groot, S. (2016). A comparison of methods for the estimation of body composition in highly trained wheelchair games players. International Journal of Sports Medicine, 37(10), 799–806. Granatelli, G., Gabbett, T. J., Briotti, G., Padulo, J., Buglione, A., D’Ottavio, S., & Ruscello, B. M. (2014). Match analysis and temporal patterns of fatigue in rugby sevens. Journal of Strength and Conditioning Research, 28(3), 728–734.

272

Craig Twist

Griffin, J. A., McLellan, C. P., Presland, J., Rathbone, E., & Keogh, J. W. (2017). Quantifying the movement patterns of international women’s rugby sevens preparation training camp sessions. International Journal of Sports Science & Coaching, 12(5), 677–684. Griffin, S. A., Perera, N. K. P., Murray, A., Hartley, C., Fawkner, S. G., Kemp, S. P., … & Kelly, P. (2021). The relationships between rugby union, and health and well-being: a scoping review. British Journal of Sports Medicine, 55(6), 319–326. Griggs, K. E., Havenith, G., Price, M. J., Mason, B. S., & Goosey-Tolfrey, V. L. (2017). Thermoregulatory responses during competitive wheelchair rugby match play. International Journal of Sports Medicine, 38(3), 177–183. Griggs, K. E., Leicht, C. A., Price, M. J., & Goosey-Tolfrey, V. L. (2015). Thermoregulation during intermittent exercise in athletes with a spinal-cord injury. International Journal of Sports Physiology and Performance, 10(4), 469–475. Henderson, M. J., Chrismas, B. C., Stevens, C. J., Coutts, A. J., & Taylor, L. (2020). Changes in core temperature during an elite female rugby Sevens tournament. International Journal of Sports Physiology and Performance, 15(4), 571–580. Higham, D. G., Pyne, D. B., Anson, J. M., & Eddy, A. (2012). Movement patterns in rugby sevens: effects of tournament level, fatigue and substitute players. Journal of Science and Medicine in Sport, 15(3), 277–282. Higham, D. G., Pyne, D. B., Anson, J. M., Hopkins, W. G., & Eddy, A. (2016). Comparison of activity profiles and physiological demands between international rugby sevens matches and training. Journal of Strength and Conditioning Research, 30(5), 1287–1294. Hogarth, W. L., Burkett, J. B., & McKean, R. M. (2014). Movement patterns in tag football: influence of playing position, representative selection and fatigue. International Journal of Performance Analysis in Sport, 14(2), 367–383. Hogarth, L. W., Burkett, B. J., & McKean, M. R. (2015a). Activity profiles and physiological responses of representative tag football players in relation to playing position and physical fitness. PLoS One, 10(12), e0144554. Hogarth, L. W., Burkett, B. J., & McKean, M. R. (2015b). Influence of Yo-Yo IR2 scores on internal and external workloads and fatigue responses of tag football players during tournament competition. PLoS One, 10(10), e0140547. Hogarth, L. W., Burkett, B. J., & McKean, M. R. (2015c). Neuromuscular and perceptual fatigue responses to consecutive tag football matches. International Journal of Sports Physiology and Performance, 10(5), 559–565. Hogarth, W. L., Burkett, J. B., & McKean, R. M. (2015d). The relationship between physical capacity and match running performance in men’s tag football. International Journal of Performance Analysis in Sport, 15(1), 147–158. Hunter, S. K. (2016). The relevance of sex differences in performance fatigability. Medicine and Science in Sports and Exercise, 48(11), 2247. Kelly, V. G., Chen, K. K., & Oyewale, M. (2018). Reliability of the 30-15 intermittent fitness test for elite wheelchair rugby players. Science and Medicine in Football, 2(3), 191–195. Malone, S., Earls, M., Shovlin, A., Eddy, A., & Winkelman, N. (2020). Match-play running performance and exercise intensity in elite international women’s rugby sevens. Journal of Strength and Conditioning Research, 34(6), 1741–1749. Marsh, N., Dobbin, N., Twist, C., & Curtis, C. (2017). Estimates of energy intake and expenditure in elite female touch players during an international tournament. International Journal of Sport Nutrition and Exercise Metabolism, 27(6), 499–506. Mendham, A. E., Coutts, A. J., & Duffield, R. (2012). The acute effects of aerobic exercise and modified rugby on inflammation and glucose homeostasis within Indigenous Australians. European Journal of Applied Physiology, 112(11), 3787–3795.

Modified Rugby

273

Mendham, A. E., Duffield, R., Marino, F., & Coutts, A. J. (2014). Small-sided games training reduces CRP, IL-6 and leptin in sedentary, middle-aged men. European Journal of Applied Physiology, 114(11), 2289–2297. Mendham, A. E., Duffield, R., Coutts, A. J., Marino, F., Boyko, A., & Bishop, D. J. (2015a). Rugby-specific small-sided games training is an effective alternative to stationary cycling at reducing clinical risk factors associated with the development of type 2 diabetes: a randomized, controlled trial. PloS One, 10(6), e0127548. Mendham, A. E., Duffield, R., Coutts, A. J., Marino, F. E., Boyko, A., McAinch, A. J., & Bishop, D. J. (2016). Similar mitochondrial signaling responses to a single bout of continuous or small-sided-games-based exercise in sedentary men. Journal of Applied Physiology, 121(6), 1326–1334. Mendham, A. E., Duffield, R., Marino, F., & Coutts, A. J. (2015b). Differences in the acute inflammatory and glucose regulatory responses between small-sided games and cycling in sedentary, middle-aged men. Journal of Science and Medicine in Sport, 18(6), 714–719. Molik, B., Lubelska, E., Kosmol, A., Bogdan, M., Yilla, A., & Hyla, E. (2008). An examination of the international wheelchair rugby federation classification system utilizing parameters of offensive game efficiency. Adapted Physical Activity Quarterly, 25, 335–351. Morgulec-Adamowicz, N., Kosmol, A., Molik, B., Yilla, A. B., & Laskin, J. J. (2011). Aerobic, anaerobic, and skill performance with regard to classification in wheelchair rugby athletes. Research Quarterly for Exercise and Sport, 82(1), 61–69. Moy, K., Scragg, R., McLean, G., & Carr, H. (2006). Metabolic equivalent (MET) intensities of culturally-specific physical activities performed by New Zealanders. New Zealand Medical Journal, 119, 6. O’Connor, D. (1997). Profile of elite female touch football players. In: Science and Football III, 22, pp. 7–10. London: E & FN Spon Ogden, T. M. (2010). Time-Motion analysis and physiological profile of elite New Zealand touch players during competition (Doctoral dissertation, Auckland University of Technology). Pugh, S. F., & Alford, A. (2004). Teaching touch rugby in physical education classes. Strategies, 17(5), 7–10. Prather, J. M., Zaragoza, J. A., Harrison, C. M., Goonan, J., Tinnin, M., Secrest, A., … & Taylor IV, L. W. (2021). Within game and between gender comparisons of match demands in men’s and women’s international Touch Rugby World Cup. In International Journal of Exercise Science: Conference Proceedings, 2, 42. Portillo, J., Gonz lez-Rav‚, J. M., Ju rez, D., Garc¡a, J. M., Su rez-Arrones, L., & Newton, R. U. (2014). Comparison of running characteristics and heart rate response of international and national female rugby sevens players during competitive matches. Journal of Strength & Conditioning Research, 28(8), 2281–2289. Pyne, D. B., Higham, D. G., Clarke, A., Mitchell, J. A., & Eddy, A. (2012). Comparison of fitness characteristics between men’s and women’s rugby sevens players. Medicine and Science in Sports and Exercise, 44, 572–573. Rhodes, J. M., Mason, B. S., Malone, L. A., & Goosey-Tolfrey, V. L. (2015a). Effect of team rank and player classification on activity profiles of elite wheelchair rugby players. Journal of Sports Sciences, 33(19), 2070–2078. Rhodes, J. M., Mason, B. S., Perrat, B., Smith, M. J., Malone, L. A., & Goosey-Tolfrey, V. L. (2015b). Activity profiles of elite wheelchair rugby players during competition. International Journal of Sports Physiology and Performance, 10(3), 318–324. Ross, A., Gill, N. D., & Cronin, J. B. (2015a). A comparison of the match demands of international and provincial rugby sevens. International Journal of Sports Physiology and Performance, 10(6), 786–790.

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Craig Twist

Ross, A., Gill, N., & Cronin, J. (2015b). The match demands of international rugby sevens. Journal of Sports Sciences, 33(10), 1035–1041. Ross, A., Gill, N., Cronin, J., & Malcata, R. (2015c). The relationship between physical characteristics and match performance in rugby sevens. European Journal of Sport Science, 15(6), 565–571. Sarro, K. J., Misuta, M. S., Burkett, B., Malone, L. A., & Barros, R. M. (2010). Tracking of wheelchair rugby players in the 2008 Demolition Derby final. Journal of Sports Sciences, 28(2), 193–200. Suarez-Arrones, L., Arenas, C., López, G., Requena, B., Terrill, O., & MendezVillanueva, A. (2014). Positional differences in match running performance and physical collisions in men rugby sevens. International Journal of Sports Physiology and Performance, 9(2), 316–323. Suarez-Arrones, L. J., Nuñez, F. J., Portillo, J., & Mendez-Villanueva, A. (2012). Running demands and heart rate responses in mens rugby sevens. Journal of Strength and Conditioning Research, 26(11), 3155–3159. Vescovi, J. D., & Goodale, T. (2015). Physical demands of women’s rugby sevens matches: female athletes in motion (FAiM) study. International Journal of Sports Medicine, 94(11), 887–892. Waldron, M., & Highton, J. (2014). Fatigue and pacing in high-intensity intermittent team sport: an update. Sports Medicine, 44(12), 1645–1658. Vickery, W., & Harkness, A. (2017). Physical, physiological and perceptual match demands of amateur mixed gender touch players. Journal of Sports Science & Medicine, 16(4), 589. Waldron, M., Highton, J., Daniels, M., & Twist, C. (2013). Preliminary evidence of transient fatigue and pacing during interchanges in rugby league. International Journal of Sports Physiology and Performance, 8(2), 157–164. Weissland, T., Leprêtre, P. M., Bruere, S., Troadec, G., & Terrefond, M. (2016). Prediction of peak oxygen consumption from the multistage field test in elite wheelchair rugby players. Annals of Physical and Rehabilitation Medicine, 59, e54. West, C. R., Campbell, I. G., Goosey-Tolfrey, V. L., Mason, B. S., & Romer, L. M. (2014). Effects of abdominal binding on field-based exercise responses in Paralympic athletes with cervical spinal cord injury. Journal of Science and Medicine in Sport, 17(4), 351–355. Zaragoza, J. A., Prather, J., Florez, C. M., Goonan, J., Tinnin, M. R., Secrest, A. H., … & Dalbo, V. J. (2022). 2019 International touch rugby world Cup: An analysis of movement demands by half and gender. International Journal of Sports Science and Coaching, 17479541221100185.

INDEX

activation management strategies 165–167 active pre-match warm-up 68–70 active recovery 84, 91, 94 Adler, P. 179 age-grade rugby 226 Algafly, A. A. 85 assessment strategies 17; maximum strength assessments 17–18; power assessments 18–19 athletes 18–20, 50, 107–110, 112–115, 141, 145–148, 151, 247, 250 Austin, D. 5 autogenic training 166 Ball, S. 259 ball carrying 198–199 ballistic training 16, 22 Bandelow, S. 133 Bannister, E. W. 37 Barkell, J. F. 181 Beaven, C. M. 93 behavioural advice 145–146; after arrival 147–152; during flight 146–147; training schedules, advice 152–153 biological age 227–229; relative age bias 229–230 biomechanical analyses 187 biomechanics 186–199 Bleakley, C. 84 body clock 142, 143, 145–153 body mass 9, 19, 132–135, 228, 232, 233, 240, 241

body temperature regulation 126–128; heat exchange and 128–129 Brade, C. 132 breathing exercises 165, 167 Brooks, J. H. 209 Brown, F. 89, 90 Brown, K. A. 248 Buscemi, N. 147 caffeine 75 carbohydrate requirements 76, 102; during exercise 105; loading phase 103–104; post-exercise 105–106; pre-exercise meal 104; total carbohydrate 102–103; types, carbohydrate 103 Cian, C. 133 Clarke, A. C. 263 Cobley, S. 230 cold-water immersion 83–86, 88, 93, 94, 131 collective efficacy 168, 169 community rugby 210, 211 compression 88; mechanisms and practical considerations 88–89; performance and recovery 89–90 compression garments 84, 88–90, 94 Cook, C. J. 93 core temperature 69, 126–130, 132, 143; rising, impacts 129–130 Correia, V. 180 Cotterill, S. 179 creatine 76

276

Index

Cross, R. 49 cryotherapy 83–86, 88, 93, 94; and functional recovery 83–84; timing, duration and temperature 88; type administered 86–88; working 85–86 Cunniffe, B. 52 Dawson, B. 91 Di Prampero, P. E. 39 Dobbin, N. 266, 267 Duffield, R. 84, 90 Duthie, G. 31 dynamical systems theory 179–180 Edmonds, R. C. 51 Ekstrand, L. 74 electrolytes 110, 111, 134 elite athletes 22, 23, 92, 114, 115, 140, 153 elite players 159–161, 163, 224, 259 elite rugby league players 3, 10, 23, 141 elite rugby union athletes 84 Elloumi, M. 52 ergogenic aids 114–115 fatigue 9, 47, 48, 50–55, 58, 130, 140, 141, 190, 264, 265 fatigue, monitoring 49; athlete-reported outcome measures 50; blood, salivary and urine-borne markers 51–52; heart rate variability (HRV) 50–51; neuromuscular function 53–54; performance tests 54–55 fat requirements 109; total fat 109–110; types, dietary fat 110 female athletes 240, 242–246, 248–251, 260 female players 240–242, 250, 251, 258–260, 263–265 female rugby player 239–251; breast support and breast injury 249; hormonal contraception 248–249; joint injuries 243–245; menstrual cycle 245–248; pelvic floor health 249–250; physical performance testing 242; resistance training 242–243 female rugby union players 240, 241 Figueroa, P. J. 31 fitness-fatigue response 47–49 fitness response, monitoring 55–57; interpretation, data 57–58; players’ and coaches’ engagement 58 Foster, C. 38 Fox, A. 244 Fuller, C. 210 Furlan, N. 259

Gabbett, T. J. 6, 9–10, 32 George, K. P. 85 Gill, N. D. 84 Gissane, C. 208 Glassbrook, D. J. 4 goal setting 159, 161–162, 169 GPS devices 31, 32, 34–36, 39 GPS devices, training 31–37; accelerations and decelerations 34–35; body load and collisions, measurement 35–37; movement activity, speed zones 34; relative distance, measurements 33; repeated efforts, measurement 35; validity and reliability, measurements 32–33 Griffin, J. A. 260 Hamlin, M. J. 90 heat-induced reductions: fluid loss and replacement 132–135; pre-cooling strategies 131–132; strategies to counter 130–131 heat maintenance strategies 70–71 heat stress 131, 135 Hendricks, S. 174, 178, 193 Heyward, O. 242 Higham, D. G. 259 Hopkinson, M. 178 hormonal priming 74–75 Hughes, M. 181 hydration 110; fluid requirements 111 Impey, S. G. 103 injury epidemiology 207–218 international rugby union 5, 7, 195 ischemic preconditioning (IPC) 73 James, N. 175–176 Johnston, K. 231 Johnston, R. D. 10 Kemp S. 209 kicking 194–195; place kicking 195–197; punt kicking 197 Kim, J. 181 King, D. A. 192, 208 Kraak, W. 179 Lacome, M. 31 Leeder, J. D. 84, 92 Lewis, J. 230 lineout 187–188 Lisboa, F. D. 73 Logue, D. M. 248

Index

long-haul travel, elite athletes 153–154 longitudinal player tracking 230–231; player development - 13-15 years 231–232; player development - 16-20 years 232–233 low-intensity exercise 91 male players 3, 250, 251, 259, 260, 264, 265 Marrier, B. 55 massage 90 match-related injuries 207–208 maturation 222, 227, 228, 230, 232–235 maturational variability 227–229 Meir, R. A. 129, 134 Mellalieu, S. D. 167 Mendham, A. E. 267 men’s community rugby 210–211 men’s elite rugby 208–210 mental imagery 162–164 micronutrients 111; deficient, assessing 113–114; minerals 113; vitamins 111–112 Milburn, P. D. 193 Miyamoto, N. 89 modified rugby 258–270; for health 266–267 momentum 178–179 Montgomery, P. G. 91 morning priming exercise 73–74 Mountjoy, M. 248 movement demands 3; activity and recovery cycles 6–7; collision, and peak movement demands 4–6; overall physical demands 3–4; repeated high-intensity effort 4–6; repeated-sprint 4–6 muscular strength 9, 15–16, 242, 247 new time zone 141, 145–148, 151–153 normative data 19; maximum strength 19; power capabilities 19–20 O’Donoghue, P. 175, 176 Ogden, T. M. 263 Osgnach, C. 39 Parmar, N. 175, 176 passing 197–198 Passos, P. 180 performance analysis 173–182 performance indicators 174–175 performance profiling 175–177 perturbations 180–181 physical preparation 2–12

277

physical qualities 7, 9–11, 47, 48, 55, 57, 260, 263, 266, 270; recovery and injury risk 10–11; relationship, activity profiles 9–10; relationship, tackling ability 8–9; on team selection 7–8 placebo effect 93 plant-based proteins 108 Pointon, M. 84 post-activation potentiation (PAP) 71–72 power 15–16; training 15, 17, 19, 21 pre-adjustment strategy 146 Preatoni, E. 188 professional rugby league 4–7 protein requirements 107; timing 108–109; total protein 107; type, protein 107 psychological characteristics 160–161 psychological demands 160 psychological preparation 167–168 Randers, M. B. 30 recovery, perceptions 93 recovery modalities 20, 94 recovery strategies 83, 90, 91, 93 repeated bout effect (RBE) 92–93 resistance training 38, 91, 242, 247 respiratory infection symptoms, elite athletes 153–154 Roberts, S. P. 211 Roe, G. 53 rugby league 3–5, 7, 15, 16, 31, 34, 174–179, 207, 208, 222; players 9, 10, 33, 35, 39, 230–233 rugby match 29, 31, 52, 84, 85, 91, 92, 94, 102, 105, 106 rugby sevens 174, 258, 259; competition demands 258–259; physical qualities 260–263; training demands 259–260 rugby training 38, 48, 84, 110 rugby union 5, 7, 15, 16, 31, 174, 175, 176, 178–181, 208, 218, 240, 249 Sawka, M. N. 135 Schneiders, A. G. 211 scrum 188–191 Seibold, A. J. 9, 10 self-talk 164–165 Seminati, E. 193, 194 Sheppy, E. 5 side-stepping (cutting) 198–199 Silva, L. M. 68 Silvestros, P. 194 sleep 91–92 sport nutrition 101, 115

278

Index

sports medicine 111, 115 sports nutrition 115 sports nutritionist 101, 102, 115, 120; role 101–102 sports performance 163, 174, 175, 180, 181, 246 sports sciences 101, 159, 173, 174, 239 sports supplements 102, 107, 114–115 sprinting 198–199 strength qualities 17, 18, 22 strength training 242, 247, 250 stretching 91 Swaminathan, R. 189 tackling 191–194; ability 9 tag or flag rugby: competition demands 264–265; physical qualities 266 talent, defined 223–224 Tanabe, Y. 193 Tavares, F. 84 team dynamics 168–169 team sport athletes 92, 127, 131 technique analysis 176, 178 TID systems 224–227 Till, K. 229–232 time-loss injuries 208, 211, 213 touch rugby: competition demands 263–264; physical qualities 266 tracking data 181 training adaptation 93 training applications: development, retention and decay 20–21; external demands, monitoring 29–30; GPS

devices 31–37; internal demands, monitoring 37–40; maximum strength 21–22; multiple camera systems 30–31; power capabilities 22–24; time-motion analysis (TMA) 30 training schedules 57, 60, 83, 152, 153 travel fatigue vs. jet lag 141–145 travel times 146 Turner, A. P. 72 Tyler, C. J. 131 Vaile, J. 88 Versey, N. 88 vitamins 111–112; fat-soluble vitamins 112; water-soluble vitamins 112 Waldron, M. 192 Waterhouse, J. 140 Webb, N. P. 91 wheelchair rugby 258, 268, 270; competition demands 268–269; physical qualities 269–270 wheelchair rugby players 268–270 Williams, R. D. 69 Williams, S. 210 women’s game 240 women’s rugby 215–217, 239, 241, 243, 250 young rugby players 223, 227, 229, 231, 234, 235 youth rugby 211–215, 234