Dr Greg Roe

he aim of the thesis was to investigate changes in markers of fatigue following training and match-play in academy rugby union players. Prior to investigations, the between-day reliability of fatigue markers was investigated. Measures of lower-and upper-body neuromuscular function (countermovement jump (CMJ) and plyometric push-up) demonstrated acceptable reliability (CV = 2-6%) in a number of metrics, as did whole blood creatine kinase concentratio n ([CK]) (CV = 26.1%) and a short wellbeing questionnaire (CV = 7.1%) when considering the signal to noise ratio. Additionally, the validity of micro-technology (GPS and accelerometer metrics) was evaluated for assessing training and match characteristics. Specifically, 10 Hz GPS proved a valid measure of maximum sprint velocity (r = 0.93-0.98) while Player LoadTM slow demonstrated a useful surrogate measure of collision activity (r = 0.61-0.80). Finally, observations from a preseason training cycle showed that CMJ metrics demonstrated superior sensitivity to training than a 6-second peak power cycle ergometer test for assessing lower-body neuromuscular function.  Following match-play, substantial (likely-almost certainly greater than the smallest worthwhile change) changes in markers of fatigue were observed, which peaked at 24 hours post-match, and recovered in the first 3 days thereafter. Field-based training inclusive of contact resulted in substantially greater reductions in upper-body neuromuscular function and perception of wellbeing, and greater elevations in [CK], while exclusion of contact induced possibly greater reductions in lower-body neuromuscular function 24 hours post-training. Findings suggest it may be prudent to afford players a recovery day following either match-play or contact training. Furthermore, the results demonstrated the individual nature of fatigue, underlying the importance of individual athlete monitoring. Additionally, possible and likely increases in lower-body strength and sprint maximum velocity respectively were observed during a preseason despite substantial reductions in CMJ mean power, questioning the usefulness of a CMJ for monitoring fatigue in the context of strength and sprint velocity development. 1

This study assessed the effects of glucose-fructose co-ingestion during recovery from high-intensity rugby training on subsequent performance. Nine professional, senior academy Rugby Union players performed two trials in a double-blind, randomized, crossover design. Identical rugby training sessions were separated by a 3-hour recovery period, during which participants ingested protein (0.3 g×kg BM×h

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Background: A novel bi-exponential method has emerged to estimate critical speed (CS) and D-prime (D′) from a 3-min all- out test (3MT). Objectives: To compare CS analysis methods to determine whether parameter estimations were interchangeable. Reference values and relationships with key soccer match- play variables were explored. Methods: Thirteen elite male youth (14-15 years old) players completed a 30 m shuttle run 3MT to estimate CS, D′, rate of speed decline time constant, maximal speed (Smax), time to Smax (tmax), and fatigue index (FI), using the traditional method and bi-exponential model on average (Bi-ExpAverage) and max speed settings (Bi-ExpMax-Speed). High-speed running (HSR) and sprinting distances and counts, and the number of accelerations were collected from two matches. Magnitude- based inferences (p < 0.05) with smallest worthwhile change of 0.2 effect sizes were used to analyse differences. Pearson’s and Spearman’s correlation coefficients were used to measure associations between CS model variables and match-play parameters. Results: There were significant differences between the traditional method and both bi-exponential models for CS and D′, as well as between the bi-exponential models for all variables except tmax. Using the Bi-ExpAverage model, strong correlations (r = 0.70-0.73; p < 0.05) were observed for D′ and FI with the number of standardised and individualised HSRs, respectively. With the Bi-ExpMax-Speed model, there were strong correlations (r/ρ = 0.64-0.68; p < 0.05) between D′ and the number of standardised HSRs and sprints, and the number of individualised sprints. Conclusion: There is a lack of interchangeability between analysis methods. It appears that D′ and FI from the bi- exponential models could be associated with high-intensity actions in soccer match-play.

ABSTRACT

The core aim of this thesis was to investigate whether small-sided game (SSG) training may provide a consistent stimulus to elicit tactical, technical, and physical characteristics in professional rugby union players. Initially, a systematic review of the literature on rugby football codes SSG demonstrated that limited research was available in rugby union SSG (5 out of 20 papers included, 25%), with the majority of research papers investigating the physical characteristics, limited studies evaluating the technical characteristics, and no study assessing the tactical characteristics of the SSG. Successively, an observational study was conducted to investigate the consistency of tactical behaviour (i.e., attacking shape), and technical and physical characteristics across multiple bouts of a specific rugby union SSG. Findings indicated that consistency of tactical behaviour, and technical and physical characteristics can be achieved for the majority of the variables investigated over multiple SSG bouts. This represents the first study analysing tactical behaviours during rugby union SSG. A regression study was then implemented to identify which external load variables were more closely related to internal load across multiple rugby union SSG designs. The results demonstrated that the association between internal and external load variables changed based on the specific design of the SSG, with the frequency of players getting down to and up from the ground and the frequency and intensity of accelerations and decelerations showing the strongest effect on internal load. An additional observational study was implemented to determine the differences in physical and technical characteristics across multiple rugby union SSG designs and to quantify the variability of these characteristics during pre-season. Findings suggested that position specific SSG (e.g., only backs) may be implemented to expose players to greater physical and technical characteristics for the majority of the variables investigated. Furthermore, variability in physical and technical characteristics was identified across multiple training days. In summary, findings demonstrated that consistency can be achieved across SSG bouts, and limited variability was identified over multiple training sessions.

Abstract

Darrall-Jones, J, Roe, G, Cremen, E, and Jones, B. Can team-sport athletes accurately run at submaximal sprinting speeds? Implications for rehabilitation and warm-up protocols. J Strength Cond Res 36(8): 2218–2222, 2022—The aim of this study is to examine the ability of team-sport athletes to accurately run at a range of submaximal sprint velocities (60–90% maximal velocity; Vmax) under verbal instruction without any objective feedback. Twelve professional male rugby union players (age 19.7 ± 0.9 years, body mass 98.3 ± 13.9 kg, height 184.0 ± 7.5 cm) were verbally instructed to complete three 40-m sprints at each of 60, 70, 80, and 90% of Vmax in a randomized order. Percentage Vmax achieved during each sprint was compared with criterion velocities calculated from Vmax testing undertaken a week prior. Players underestimated (ran faster) their sprint velocity when asked to run at 60% (very large to extremely large mean bias, 23%; range, 57–88% Vmax), 70% (large to very large, 11%; 67–93% Vmax), and 80% (small, 2%; 71–91% Vmax) of their Vmax, whereas overestimated (ran slower) their sprint velocity when asked to run at 90% Vmax (moderate, −4%; 77–95% Vmax). Team sport players may require objective feedback when performing submaximal sprinting to ensure that velocities achieved are similar to those prescribed. This may be particularly important where graded exposure to maximum velocities is required, for example during rehabilitation or warm-ups.

Sports invest in research to optimise performance and enhance athlete wellbeing. Involving stakeholders allows research priorities to be determined, maximising the adoption and relevance of research findings. A three‐round modified Delphi process was used to establish wellbeing and performance research priorities for Premiership Rugby (Professional men's rugby union competition in England). Up to 10 research priorities were provided during Round 1 (grouped into higher‐order categories and themes via content analysis). In Rounds 2 and 3, participants ranked higher‐order categories on a one to five Likert scale. Consensus was defined as ≥ 70% agreement. Sixty‐five participants responded in Round 1 (41 and 32 in Rounds 2 and 3). Staff and player experience of working or playing in the Premiership was 11.0 (4.5–16.5) and 7.0 (6.0–8.5) years. Following Round 1, 393 research priorities were provided and 53 higher‐order research priorities and 26 categories were identified, within three themes: performance, wellbeing and injury. Following Round 3, 21 research priorities reached consensus within performance (n = 7), wellbeing (n = 6) and injury (n = 8). Research priorities for a professional sports league, were established by the application of a pragmatic research lens, to ensure priorities were practically minded and also developed with minimal resource requirements, minimal burden for participants and in a short amount of time, which can be applied in other leagues. Research priorities deemed feasible and lacking a relevant evidence base can be addressed in future studies to maximise impact and compliment the ongoing research programmes already established by the professional league and governing body.

This study aimed to quantify the frequency of individual and team contact events during rugby union match play in top domestic and international men’s and women’s competitions. Analyst‐coded player individual and team contact event types (tackles, carries, attacking rucks and defensive rucks, lineouts, scrums and mauls) from the 2022/2023 rugby union season were analysed from top domestic and international competitions across the world using generalised linear mixed models. For both women’s and men’s rugby, competitions generally had similar numbers of contact events per playing position. Where differences were observed, most ranged between 0.5 and six per contact event per full game equivalent (FGE). Similar trends were observed when comparing women’s to men’s rugby. However, within‐game accumulation of these different contact events for certain positional groups may have a significant impact (e.g., a front five player called up from a Farah Palmer Cup team to play in WXV1 could be involved in as much as 6 more attacking rucks, 3 more tackles and 5 more mauls per game on average). Furthermore, the small differences between competitions per FGE may accrue across matches and thus result in far greater exposures across a season (e.g., a front five player in Premiership Rugby may make 48 more tackles over 20 matches than in Top 14 on average). Although a high proportion of contact events per FGE were similar between competitions and sexes per playing position, differences that were observed may have important implications for players transitioning between competitions and the long‐term exposure of players to higher‐risk contact events.

This study aimed to investigate the differences in physical and technical characteristics among three specific rugby union small-sided games (SSG) and to examine the variability of these characteristics over three weeks within a preseason of a professional rugby union club. Eighteen backs and 22 forwards were recruited for the study. The three SSG designs were: backs only (SSG-B), forwards only (SSG-F) and both backs and forwards (SSG-BF). Physical characteristics were quantified using external (e.g., total distance covered [m·min−1]) and internal (i.e., Stagno's training impulse [AU·min−1]) load measures. Technical characteristics were quantified using the number of rucks, successful passes, unsuccessful passes, line breaks and tries per minute. The SSG-BF produced a greater high speed (>61%) running distance covered in comparison with SSG-B (1.97 vs. 1.32 m·min−1) and SSG-F (1.26 vs. 0.94 m·min−1), and more successful passes (9.47 vs. 9.36 count·min−1) and line breaks (0.98 vs. 0.65 count·min−1) than SSG-F. Conversely, all the other physical and technical characteristics were higher in SSG-B and SSG-F. All the physical and technical characteristics, except high speed (>61%) distance covered in forwards and unsuccessful passes and tries per minute, changed over days showing either a linear or quadratic pattern. Based on these findings, practitioners may implement position-specific SSG (i.e., SSG-B and SSG-F) to expose players to greater physical and technical characteristics. Furthermore, if SSGs were to be repeated across multiple days, practitioners should be aware of the possible variability in physical and technical characteristics due to potential adaptations to the constraints or the onset of fatigue.

We aimed to investigate the contextual factors influencing training load (TL), as determined by session rating of perceived exertion (sRPE-TL), accumulated within a match-to-match microcycle in rugby union players. Session rating of perceived exertion-TL data were collected daily from 35 professional rugby union players from the same team in the English Championship over the course of an in-season period. Players were split by positional groups (backs and forwards) and sRPE-TL data were categorized as: field-based on-feet sRPE-TL (sRPEField-TL), gym-based sRPE-TL (sRPEGym-TL), and the total summation of both (sRPETotal-TL). Three 2-level linear mixed models were built for each dependent variable in each positional group, with magnitude-based inferences applied. Long between-match recovery cycles (≥7 days) resulted in very likely to almost certainly small to moderate increases in sRPE-TL for all modalities and positions (fixed effect [mean range] = 28.5%–42.0%), apart from sRPEField-TL for forwards. For backs, there was a very likely small decrease in sRPEField-TL as the season progressed (−16.7% per trimester). Losing the last league match was associated with very likely and almost certainly small decreases in sRPETotal-TL and sRPEGym-TL for backs (−20.7% and −36.4%, respectively). Losing the last match in any competition resulted in a very likely small increase in sRPEField-TL (21.2%) and a possibly small decrease sRPEGym-TL (−18.5%) for backs—with a likely smaller sRPEGym-TL for forwards (−33.4%). The strength of the upcoming opposition had no effect on sRPE-TL. Our findings highlight some of the multifactorial contextual factors that must be considered when planning and evaluating training microcycles.

Typical player management processes focus on managing an athlete's physical, physiological, psychological, technical and tactical preparation and performance. Current literature illustrates limited attempts to optimize such processes in sports. Therefore, this study aimed to analyze the application of Business Process Management (BPM) in healthcare (a service industry resembling sports) and formulate a model to optimize data driven player management processes in professional sports. A systematic review, adhering to PRISMA framework was conducted on articles extracted from seven databases, focused on using BPM to digitally optimize patient related healthcare processes. Literature reviews by authors was the main mode of healthcare process identification for BPM interventions. Interviews with process owners followed by process modelling were common modes of process discovery. Stakeholder and value-based analysis highlighted potential optimization areas. In most articles, details on process redesign strategies were not explicitly provided. New digital system developments and implementation of Business Process Management Systems were common. Optimized processes were evaluated using usability assessments and pre-post statistical analysis of key process performance indicators. However, the scientific rigor of most experiments designed for such latter evaluations were suboptimal. From the findings, a stepwise approach to optimize data driven player management processes in professional sports has been proposed.

Using a pre-post-test design, this study evaluated the impact of implementing a standard on the reliability of player management decision-making within a professional rugby union environment. Five practitioners from a High-Performance Unit (HPU) rated 22 instances of Global Positioning System (GPS)–based external training load information of 14 players across the 2021–2022 season. This rating was whether a peak/trough/normal exposure in load had occurred. The ratings were repeated at four time points (separated by 2 weeks) before (Pre1, Pre2) and after (Post1, Post2) implementing a consensus statement as a subjective standard (using a dashboard) developed previously within the same environment to identify peaks/troughs in player external training loads. Inter-rater agreement between individuals at each voting round was assessed using Light's Kappa, while pre-post-standard intra-rater agreement was determined from Cohen's Kappa (both with 95% confidence intervals). Changes to dashboard usability from implementing the standard were assessed by administering the System Usability Scale to 11 HPU staff at the four time points. Pre-standard moderate inter-rater agreement (Pre1: 0.53 (0.36–0.69), Pre2: 0.60 (0.42–0.77)) increased to almost perfect agreement (Post1: 0.74 (0.57–0.89), Post2: 0.90 (0.79–1)) post-standard. The intra-rater agreement of 2/5 participants was almost perfect post-standard, while it remained within substantial levels for the others. A linear mixed model (χ2(3) = 8.85, p = 0.03) illustrated a slight increase in dashboard usability after incorporating the standard (Pre1: 84.09, Pre2: 81.36; Post1: 87.73, Post2: 87.27). Overall, the results highlighted that the subjective standard enhanced reliability of practitioner agreement for the selected decision.

In sporting environments, the knowledge necessary to manage athletes is built on information flows associated with player management processes. In current literature, there are limited case studies available to illustrate how such information flows are optimized. Hence, as the first step of an optimization project, this study aimed to evaluate the current state and the improvement opportunities in the player management information flow executed within the High-Performance Unit (HPU) at a professional rugby union club in England. Guided by a Business Process Management framework, elicitation of the current process architecture illustrated the existence of 18 process units and two core process value chains relating to player management. From the identified processes, the HPU management team prioritized 7 processes for optimization. In-depth details on the current state (As-Is) of the selected processes were extracted from semi-structured, interview-based process discovery and were modeled using Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN) standards. Results were presented for current issues in the information flow of the daily training load management process, identified through a thematic analysis conducted on the data obtained mainly from focus group discussions with the main stakeholders (physiotherapists, strength and conditioning coaches, and HPU management team) of the process. Specifically, the current state player management information flow in the HPU had issues relating to knowledge creation and process flexibility. Therefore, the results illustrate that requirements for information flow optimization within the considered environment exist in the transition from data to knowledge during the execution of player management decision-making processes.

Standards are pivotal for generating the evidence required to manage players in professional sport environments like rugby union. Resultantly, using a three-step qualitative approach, this study aimed to formulate a consensus as a subjective standard for evidence generation pertaining to player management. The consensus statement intended to identify evidence on peaks/troughs in player external training loads using Global Positioning System (GPS)-based information in the High-Performance Unit (HPU) of a Gallagher Premiership rugby union club. Initially, a systematic review adhering to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) framework was conducted to unravel the factors considered (literature-based cues) when identifying peaks/troughs in player external training loads using GPS information. Next, thematic analysis conducted on the data obtained from 7 semi-structured interviews with HPU staff highlighted that they consider 6 factors with 38 elements (practitioner-based cues) during player external training load management. Thereafter, guided by the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument and by utilising selected elements representing 4/6 factors (healthy player, GPS information, longitudinal durations and practitioner judgements on information), a consensus among practitioners for identifying peaks/troughs in player external training loads was developed with the participation of five HPU members using the nominal group technique (NGT). Practitioners reached an agreement with regard to 12 indicators to subjectively identify peaks/troughs in player external training loads within the considered environment.

INTRODUCTION: This study aimed to investigate which external load variables were associated with internal load during three small-sided games (SSG) in professional rugby union players. METHODS: Forty professional rugby union players (22 forwards, 18 backs) competing in the English Gallagher Premiership were recruited. Three different SSGs were designed: one for backs, one for forwards, and one for both backs and forwards. General linear mixed-effects models were implemented with internal load as dependent variable quantified using Stagno's training impulse, and external load as independent variables quantified using total distance, high-speed (>61% top speed) running distance, average acceleration-deceleration, PlayerLoad™, PlayerLoad™ slow (<2 m·s-1), number of get-ups, number of first-man-to-ruck. RESULTS: Internal load was associated with different external load variables dependent on SSG design. When backs and forwards were included in the same SSG, internal load differed between positional groups (MLE = -121.94, SE = 29.03, t = -4.20). DISCUSSION: Based on the SSGs investigated, practitioners should manipulate different constraints to elicit a certain internal load in their players based on the specific SSG design. Furthermore, the potential effect of playing position on internal load should be taken into account in the process of SSG design when both backs and forwards are included.

The study aimed to illustrate how contact (from match‐event data) and head acceleration event (HAE) (from instrumented mouthguard [iMG]) data can be combined to inform match limits within rugby. Match‐event data from one rugby union and rugby league season, including all competitive matches involving players from the English Premiership and Super League, were used. Playing exposure was summarised as full game equivalents (FGE; total minutes played/80). Expected contact and HAE exposures at arbitrary thresholds were estimated using match‐event and iMG data. Generalised linear models were used to identify differences in contact and HAE exposure per FGE. For 30 FGEs, forwards had greater contact than backs in rugby union (n = 1272 vs. 618) and league (n = 1569 vs. 706). As HAE magnitude increased, the differences between positional groups decreased (e.g., rugby union; n = 34 and 22 HAE >40 g for forwards and backs playing 30 FGEs). Currently, only a relatively small proportion of rugby union (2.5%) and league (7.3%) players exceeded 25 FGEs. Estimating contact and HAEs per FGE allows policymakers to prospectively plan and model estimated overall and position‐specific loads over a season and longer term. Reducing FGE limits by a small amount would currently only affect contact and HAE exposure for a small proportion of players who complete the most minutes. This may be beneficial for this cohort but is not an effective HAE and contact exposure reduction strategy at a population level, which requires individual player management. Given the positional differences, FGE limits should exist to manage appropriate HAE and contact exposure.

The aim of this study was to investigate the prevalence of oral contraceptive use in domestic rugby union, to compare symptomology by contraceptive use, and to determine symptom management strategies. Additionally, to characterise the perceived influence of oral contraceptive use and non-use on wellness and performance. A total of 238 Premiership and Championship women’s rugby union players completed an online questionnaire. The survey was comprised of questions relating to player characteristics, hormonal or non-hormonal contraceptive characteristics, perceived symptomology, symptom management strategies, and performance and wellness characteristics. The prevalence of oral contraceptive users was 26%. Non-hormonal contraceptive users reported greater perceived negative symptomology (i.e., back pain, nausea, sore breasts) and performance and wellness effects (i.e., fatigue, stress, mood, concentration, power, match-play) than oral contraceptive users. The most common symptom management strategies were medication (33%), nutritional interventions (20%), and training modulation (20%). Twelve percent of players had previously spoken to staff about their menstrual cycle (i.e., regular and irregular) or contraceptive use. The most common barriers to speaking to staff were ‘male staff’ (29%) and ‘club culture’ (24%). The importance of assisting non-hormonal contraceptive users in managing symptoms is evident. Emphasis on overcoming barriers to staff-player dialogue regarding menstrual/contraceptive cycle is required.

The aim of this study was to investigate the prevalence of oral contraceptive use in domestic rugby union, to compare symptomology by contraceptive use, and to determine symptom management strategies. Additionally, to characterise the perceived influence of oral contraceptive use and non-use on wellness and performance. A total of 238 Premiership and Championship women’s rugby union players completed an online questionnaire. The survey was comprised of questions relating to player characteristics, hormonal or non-hormonal contraceptive characteristics, perceived symptomology, symptom management strategies, and performance and wellness characteristics. The prevalence of oral contraceptive users was 26%. Non-hormonal contraceptive users reported greater perceived negative symptomology (i.e., back pain, nausea, sore breasts) and performance and wellness effects (i.e., fatigue, stress, mood, concentration, power, match-play) than oral contraceptive users. The most common symptom management strategies were medication (33%), nutritional interventions (20%), and training modulation (20%). Twelve percent of players had previously spoken to staff about their menstrual cycle (i.e., regular and irregular) or contraceptive use. The most common barriers to speaking to staff were ‘male staff’ (29%) and ‘club culture’ (24%). The importance of assisting non-hormonal contraceptive users in managing symptoms is evident. Emphasis on overcoming barriers to staff-player dialogue regarding menstrual/contraceptive cycle is required.

The purpose of the present study was to evaluate; 1) whether there were differences in sprint times at 5, 10, 20, 30 and 40 m between rugby union and rugby league players; 2) determine the reliability and usefulness of linear sprint testing in adolescent rugby players. Data were collected on 28 rugby union and league academy players over two testing sessions, with three day's rest between sessions. Rugby league players were faster at 5 m than rugby union players, with further difference unclear. Sprint time at 10, 20, 30 and 40 m were all reliable (CV = 3.1%, 1.8%, 2.0% and 1.3%) but greater than the smallest worthwhile change (SWC (0.2 x between-subject SD)), rating the test as marginal for usefulness. While the test was incapable of detecting the SWC we recommend that practitioners and researchers use Hopkins' proposed method (22); whereby plotting the change score of the individual at each split (± TE expressed as a CV) against the SWC, and visually inspecting whether the TE crosses into the SWC is capable of identifying whether a change is both real (greater than the noise of the test, i.e., >TE) and of practical significance (>SWC). Researchers and practitioners can use the TE and SWC from the present study to assess changes in performance of adolescent rugby players when using single beam timing gates.

This study examined the relationship between accelerometer metrics and both collisions and running demands during rugby union match-play. Twelve under-18 forwards and 14 under-18 backs were recruited from a professional rugby union club. Six competitive matches were filmed during which players wore micro-technological units (Optimeye S5, Catapult Innovations, Melbourne, Australia). Video footage was analysed for total collisions, while GPS data was analysed for total distance. Accelerometer metrics analysed were Player loadTM (PL), Player LoadTM 2D (PL2D), and Player LoadTM slow (PLslow). A total of 81 player observations were included in the final analysis. Data were analysed using ordinary least squares regression. A 10-fold cross validation analysis was used to validate the findings. All PL variables demonstrated very large relationships with collisions in the forwards, while PLslow demonstrated the largest relationship (large) with collisions in the backs. Therefore, based on the strong relationship in both forwards and backs, PLslow may provide the most useful metric for measuring collision-based activity in both positional groups during match-play. Additionally, nearly perfect and very large relationships were observed between PL and total distance for forwards and backs respectively, suggesting that PL can be successfully used to quantify running demands when other methods are unavailable, for example during indoor training.

This study aimed to investigate the consistency of attacking tactical and technical behaviour, and physical characteristics, over multiple bouts, and variability across days, of a specific rugby union forwards small-sided game (SSG). Data was collected from 21 professional rugby union forwards during four training sessions. The SSG, consisting of five bouts of work (150-s) interspersed by passive recovery (75-s), aimed to elicit specific attacking tactical behaviour. Tactical behaviour (i.e., regularity of attacking shape [entropy]), and technical (e.g., passes) and physical (e.g., total distance) characteristics were quantified. Results showed that technical characteristics remained consistent, whereas the regularity of width of the attacking shape and two physical characteristics (i.e., total distance, training impulse) varied across bouts. However, these effects had limited practical significance. Technical characteristics were consistent across days, but minimal variability was observed for tactical behaviour and physical characteristics, as shown by their small random effects with 95% profile likelihood confidence intervals (PLCI) including zero (e.g., SD[95%PLCI] = 0.03[0.00, 0.06]). Consequently, consistency of stimulus over bouts and days is achievable for the majority of the variables investigated, thus supporting the use of SSG to elicit consistent attacking behaviour, but also technical and physical characteristics in rugby union forwards.

This study investigated the changes in measures of neuromuscular fatigue and physical performance in young professional rugby union players during a preseason training period. Fourteen young (age: 19.1 ± 1.2 years) professional rugby union players participated in the study. Changes in measures of lower body neuromuscular fatigue (countermovement jump (CMJ) mean power, mean force, flight-time) and physical performance (lower body strength, 40 m sprint velocity) were assessed during an 11-week preseason period using magnitude-based inferences. CMJ mean power was likely to very likely decreased during week 2 (-8.1 ± 5.5% to -12.5 ± 6.8%), and likely to almost certainly decreased from weeks 5 to 11 (-10 ± 4.3% to -14.7 ± 6.9%), while CMJ flight-time demonstrated likely to very likely decreases during weeks 2, and weeks 4-6 (-2.41 ± 1% to -3.3 ± 1.3%), and weeks 9-10 (-1.9 ± 0.9% to -2.2 ± 1.5%). Despite this, possible improvements in lower body strength (5.8 ± 2.7%) and very likely improvements in 40 m velocity (5.5 ± 3.6%) were made. Relationships between changes in CMJ metrics and lower body strength or 40 m sprint velocity were trivial or small (<0.22). Increases in lower body strength and 40 m velocity occurred over the course of an 11-week preseason despite the presence of neuromuscular fatigue (as measured by CMJ). The findings of this study question the usefulness of CMJ for monitoring fatigue in the context of strength and sprint velocity development. Future research is needed to ascertain the consequences of negative changes in CMJ in the context of rugby-specific activities to determine the usefulness of this test as a measure of fatigue in this population.

The purpose of this study was to determine the between-day reliability of the Hamstring Solo for measuring peak eccentric knee flexor force (EKF) during the Nordic hamstring curl. Data were collected on 18 male Professional rugby union players across two testing sessions separated by 7 days. There was no between-session difference in EKF force for left (p = 0.440 – 0.580) or right (p = 0.477 – 0.656) leg when using the best of 1 (left = 405.3±88.2 N vs. 412.8±92.7 N; right = 408.0±88.1 N vs. 416.7±85.2 N), 2 (left = 409.9±87.6 N vs. 415.0±96.2 N; right = 413.0±87.5 N vs. 418.3±86.2 N), or 3 repetitions (left = 411.2±88.2 N vs. 417.3±92.7 N; right = 417.7±87.4 N vs. 417.7±87.4 N). The between-day reliability of EKF peak force was acceptable for left (7.2 to 8.3%) and right (8.3 to 9.8%) leg, with the typical error lowest when using the best of three repetitions. The smallest worthwhile change (SWC) was similar for left (4.2 – 4.3%) and right (3.6 – 3.7%) when using the best of 3 repetitions. As the typical error was greater than the SWC for both the left (1.71 x the SWC) and right (2.24 x the SWC) legs, changes of 2.71 (Δ 41 N; 11%) and 3.24 (Δ 47 N; 12%) xSWC are required to detect a small change in EKF peak force, taking into account the typical error. Practitioners can use the reliability statistics from this study to monitor EKF peak force in professional rugby union players, when using the Hamstring Solo device. It is recommended that when monitoring EKF peak force with the Hamstring Solo, practitioners use the best of 3 repetitions.

Practical case studies elaborating end-to-end attempts to improve the quality of information flows associated with athlete management processes are scarce in the current sport literature. Therefore, guided by a Business Process Management (BPM) approach, the current study presents the outcomes from a case study to optimize the quality of strength and conditioning (S&C) information flow in the performance department of a professional rugby union club. Initially, the S&C information flow was redesigned using integral technology, activity elimination and activity automation redesign heuristics. Utilizing the Lean Startup framework, the redesigned information flow was digitally transformed by designing data collection, management and visualization systems. Statistical tests used to assess the usability of the data collection systems against industry benchmarks using the System Usability Scale (SUS) administered to 55 players highlighted that its usability (mean SUS score of 87.6 ± 10.76) was well above average industry benchmarks of similar systems (Grade A from SUS scale). In the data visualization system, 14 minor usability problems were identified from 9 cognitive walkthroughs conducted with the High-Performance Unit (HPU) staff. Pre-post optimization information quality was subjectively assessed by administering a standardized questionnaire to the HPU members. The results indicated positive improvements in all of the information quality dimensions (with major improvements to the accessibility) relating to the S&C information flow. Additionally, the methods utilized in the study would be especially beneficial for sporting environments requiring cost effective and easily adoptable information flow digitization initiatives which need to be implemented by its internal staff members.

This systematic review aimed to identify and summarise associations between currently identified contextual factors and match running in senior male professional rugby league. Eligible articles included at least one contextual factor and used GPS to measure at least one displacement variable within competitive senior, male, professional rugby league matches. Of the 15 included studies, the identified contextual factors were grouped into factors related to individual characteristics (n = 3), match result (n = 4), team strength (n = 2), opposition strength (n = 3), match conditions (n = 6), technical and tactical demands (n = 6), spatial and temporal characteristics (n = 7), and nutrition (n = 1). Speed was the most commonly reported measure of match running (100%), followed by distance (47%), and acceleration (20%). Inconsistencies were found between studies for most contextual factors on match running. Higher speeds were generally associated with higher fitness, encountered earlier in the match and whilst defending. All 15 studies utilised a univariate approach to quantify associations of a contextual factor. The inconsistencies found in the associations of given contextual factors highlight the complex and multi-faceted nature of match running. Therefore, practitioners should consider contextual factors when analysing and interpreting GPS data.

This study aimed to quantify and compare mean head acceleration event (HAE) incidence within and between men's and women's rugby union competitions; quantify the incidence of HAEs during all contact‐events and describe individual player incidence. Players competing during the 2022/2023 season in women's (337 players; Premiership Women's Rugby, Farah Palmer Cup) and men's (371 players; Premiership Rugby, Currie Cup and Super Rugby) competitions wore instrumented mouthguards (iMGs). Mean HAE incidences using peak linear (PLA) and peak angular acceleration (PAA) were quantified by sex, positional groups and individual players per competition and for contact‐events across a range of magnitude thresholds. Within positional groups, there was high between‐player variability, with some players experiencing up to a 3‐fold greater mean HAE incidence than their positional average. Per full‐game equivalent (FGE), men had significantly higher HAE incidences in most positional groups and HAE magnitude thresholds compared to women ranging from approximately 0.11–3.44 HAEs per FGE. Incidence of HAEs (PLA > 25 g) per FGE was lowest in scrums (0.00–0.04/FGE) and highest for tackles and ball carries (0.21–1.97/FGE) in both women and men, whereas mauling was a frequent source of HAEs for men's back row (0.95/FGE). No significant differences were observed between competitions for most positional groups and HAE magnitude thresholds in both men and women. Per FGE, HAE incidences were similar within, but significant differences were apparent between men's and women's players. The scrum had the lowest HAE incidence of all contact‐events. Individual players can show large variation from the mean, emphasising the importance of HAE mitigation strategies that include individual player monitoring and management processes.

The purpose of this study was to investigate the validity of timing gates and 10 Hz GPS units (Catapult Optimeye S5) against a criterion measure (50 Hz radar gun) for assessing maximum sprint velocity (Vmax).Nine male professional rugby union players performed three maximal 40 m sprints with three minutes rest between each effort with Vmax assessed simultaneously via timing gates, 10 Hz GPSOpen (Openfield software), GPSSprint (Sprint software) and radar gun. Eight players wore 3 GPS units, while one player wore a single unit during each sprint.When compared to the radar gun, mean bias for GPSOpen, GPSSprint and timing gates was trivial, small and small respectively. The typical error of the estimate (TEE) was small for timing gate and GPSOpen, while moderate for GPSSprint. Correlations with radar gun were nearly perfect for all measures. Mean bias, TEE and correlations between GPS units were trivial, small and nearly perfect respectively, while small TEE existed when GPSOpenfield was compared to GPSSprint.Based on these findings both 10 Hz GPS and timing gates provide valid measures of 40 m Vmax assessment when compared with a radar gun. However, as error did exist between measures, the same testing protocol should be used when assessing 40 m Vmax over time. Furthermore, in light of the above results, it is recommended that when assessing changes in GPS derived Vmax over time, practitioners should use the same unit for each player and perform the analysis with the same software, preferably Catapult Openfield.

ABSTRACT Purpose: Feedback can enhance acute physical performance. However, the effects of feedback on physical adaptation has received little attention. Therefore, the purpose of this study was to determine the effect of feedback during a four-week training programme on jump, sprint and strength adaptations. Methods: Twenty-eight semi-professional male rugby union players were strength-matched into two groups (feedback and non-feedback).

Previous research in academy rugby league players has evaluated the development of physical qualities according to chronological age. However, no study has considered the training age, defined as the number of formalized years of strength and conditioning training, of these players. Therefore, the purpose of this study was to present and compare the annual changes in physical qualities of academy rugby league players according to training age. Sixty-one academy players undertook a fitness testing assessment including anthropometric (height, body mass, sum of four skinfolds) and physical (10 and 20m sprint, 10m momentum, vertical jump, Yo-Yo intermittent recovery test level 1 [Yo-Yo IRTL1], one-repetition maximum [1-RM] squat, bench press and prone row) measures at the start of pre-season on two consecutive annual occasions. Players were categorized into one of three training age groups (i.e., 0, 1 or 2 years) and were analyzed using magnitude-based inferences. Almost certain, very likely or likely annual improvements were identified for body mass, 10m momentum, Yo-Yo IRTL1, vertical jump and all strength measures for the three training age groups. When training age groups were compared, 1 years showed possibly or likely lower strength increases than 0 years training age. However, the 2 years training age group demonstrated possibly or likely increased strength changes compared to 1 years. These findings suggest that training age is an important consideration for strength and conditioning practitioners but it is likely to be a combination of chronological age, biological maturity and training experience alongside dynamic inter-player variability that influences the physical development of academy rugby league players.

PURPOSE: The study aimed to identify which combination of external and internal training load (TL) metrics capture similar or unique information for individual professional players during skills training in rugby union using principal component analysis (PCA). METHOD: TL data were collected from twenty-one male professional rugby union players across a competitive season. This included PlayerLoad™, total distance (TD), and individualised high-speed distance (HSD; >61% maximal velocity; all external TL) obtained from a micro-technology device worn by each player (Optimeye X4, Catapult Innovations, Melbourne, Australia) and the session-rating of perceived exertion (sRPE; internal TL). PCA was conducted on each individual to extract the underlying combinations of the four TL measures that best describe the total information (variance) provided by the measures. TL measures with PC "loadings" (PCL) above 0.7 were deemed to possess well-defined relationships with the extracted PC. RESULTS: The findings show that from the four TL measures, the majority of an individual's TL information (1st PC: 55 to 70%) during skills training can be explained by either sRPE (PCL: 0.72 to 0.95), TD (PCL: 0.86 to 0.98) or PlayerLoad™ (PCL: 0.71 to 0.98). HSD was the only variable to relate to the 2nd PC (PCL: 0.72 to 1.00), which captured additional TL information (+19 to 28%). CONCLUSIONS: Findings suggest practitioners could quantify the TL of rugby union skills training with one of PlayerLoad™, TD, or sRPE plus HSD whilst limiting omitted information of the TL imposed during professional rugby union skills training.

This study aimed to determine the similarity between and within positions in professional rugby league in terms of technical performance and match displacement. Here, the analyses were repeated on 3 different datasets which consisted of technical features only, displacement features only, and a combined dataset including both. Each dataset contained 7617 observations from the 2018 and 2019 Super League seasons, including 366 players from 11 teams. For each dataset, feature selection was initially used to rank features regarding their importance for predicting a player's position for each match. Subsets of 12, 11, and 27 features were retained for technical, displacement, and combined datasets for subsequent analyses. Hierarchical cluster analyses were then carried out on the positional means to find logical groupings. For the technical dataset, 3 clusters were found: (1) props, loose forwards, second-row, hooker; (2) halves; (3) wings, centres, fullback. For displacement, 4 clusters were found: (1) second-rows, halves; (2) wings, centres; (3) fullback; (4) props, loose forward, hooker. For the combined dataset, 3 clusters were found: (1) halves, fullback; (2) wings and centres; (3) props, loose forward, hooker, second-rows. These positional clusters can be used to standardise positional groups in research investigating either technical, displacement, or both constructs within rugby league.

Objectives The aim of this study was to describe the incidence and magnitude of head acceleration events (HAEs) during elite men’s and women’s rugby union training for different contact training levels and drill types. Method Data were collected during the 2022–23 and 2023–24 seasons from 203 men and 125 women from 13 clubs using instrumented mouthguards (iMGs) during in-season training. One author reviewed the training videos to identify the contact level and drill type. HAE incidence was calculated per player minute. Results For men’s forwards and backs, only 4.7% and 5.8% of HAEs were ≥ 25 g and ≥ 1.5 Krad/s2, and 3.4% and 4.4% for women’s forwards and backs, respectively. The incidence of ≥ 5 g and ≥ 0.4 Krad/s2 was highest during full-contact training for men’s forwards (0.20/min) and backs (0.16/min) and women’s forwards (0.10/min). HAE incidence was 2–3 times higher during repetition-based compared with game-based training drills for men’s forwards (0.25/min vs 0.09/min) and backs (0.22/min vs 0.09/min) and women’s forwards (0.09/min vs 0.04/min) and backs (0.08/min vs 0.03/min). HAE incidences were halved when repetition-based training drills used pads compared with no pads for men’s forwards (0.21/min vs 0.44/min) and backs (0.17/min vs 0.30/min), and women’s forwards (0.06/min vs 0.14/min) and backs (0.06/min vs 0.10/min). Conclusion The average HAE incidence (~ 13–20% of weekly HAEs) and magnitude during an in-season training week is very low compared with matches. Opportunities to materially reduce HAE exposure in training are likely more limited than previously assumed. Future research on HAE load and injury, and understanding players’ specific weekly training exposure, may inform effective individual player management.

This study aimed to quantify contact-events and associated head acceleration event (HAE) probabilities in semi-elite women's rugby union. Instrumented mouthguards (iMGs) were worn by players competing in the 2023 Farah Palmer Cup season (13 teams, 217 players) during 441 player-matches. Maximum peak linear acceleration (PLA) and peak angular acceleration (PAA) per-event were used as estimates of in vivo HAE (HAEmax), linked to video analysis-derived contact-events and analysed using mixed-effects regression. Back-rows had the highest number of contact-events per full-match (44.1 [41.2 to 47.1]). No differences were apparent between front-five and centres, or between half-backs and outside-backs. The probability of higher HAEmax occurring was greatest in ball-carries, followed by tackles, defensive rucks and attacking rucks. Probability profiles were similar between positions but the difference in contact-events for each position influenced HAEmax exposure. Overall, most HAEmax were relatively low. For example, the probability of a back-row experiencing a PLA HAEmax ≥25g was 0.045 (0.037-0.054) for ball carries (1 in every 22 carries), translating to 1 in every 2.3 full games. This study presents the first in-depth analysis of contact-events and associated HAEmax in semi-elite women's rugby union. The HAEmax profiles during contact-events can help inform both policy and research into injury mitigation strategies.

Female sports have recently seen a dramatic rise in participation and professionalism world-wide. Despite progress, the infrastructure and general sport science provisions in many female sports are behind their male counterparts. From a performance perspective, marked differences in physical and physiological characteristics can be seen between the sexes. Although physical preparation practices for male athletes are known, there are currently no published literature pertaining exclusively to female athletes. This information would provide invaluable data for both the researcher and practitioner alike. This survey therefore aimed to examine current practices utilized in female rugby codes (union, league, and sevens). A questionnaire assessing seasonal physical preparation practices, recovery, monitoring and sport science technology, and unique aspects in female rugby was developed. Thirty-seven physical preparation practitioners (32 males, 5 females) responded to the questionnaire. Most participants (78%) worked with national or regional/state level female athletes. Performance testing was more frequently assessed in the pre- (97%) and in-season (86%), than off-season (23%). Resistance, cardiovascular, sprint and plyometric training, and recovery sessions were all believed to be important to enhancing performance and implemented by most participants (≥ 89%). Sport science technologies were commonly (54%) utilized to inform current practice. Menstrual cycle phase was monitored by 22% of practitioners. The most frequently reported unique considerations in female rugby codes included psycho-social aspects (41%), the menstrual cycle (22%), and physical differences (22%). Practitioners working with female rugby can use the presented data to inform and develop current practices.

Objectives: In part 1, the objective was to undertake a systematic scoping review of applied sports science and sports medicine in women’s rugby, and in part 2 to develop a consensus statement on future research priorities. Design: In part 1, a systematic search of PubMed (MEDLINE), Scopus and SPORTDiscus (EBSCOhost) was undertaken from the earliest records to January 2021. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020, the PRISMA extension for Scoping Reviews, and the PRISMA extension protocols were followed. In part 2, 31 international experts in women’s rugby (ie, elite players, sports scientists, medical clinicians, sports administrators) participated in a three-round Delphi consensus method. These experts reviewed the findings from part 1 and subsequently provided a list of priority research topics in women’s rugby. Research topics were grouped into expert-based themes and expert-based subthemes via content analysis. Expert-based themes and expert-based subthemes were ranked from very low to very high research priority on a 1–5 Likert scale. Consensus was defined by ≥70% agreement. The median research priority agreement and IQR were calculated for each expert-based theme and subtheme. Data sources: PubMed (MEDLINE), Scopus and SPORTDiscus (EBSCOhost). Eligibility criteria for selecting studies: Studies were eligible for inclusion if they investigated applied sports science or sports medicine in women’s rugby. Results: In part 1, the systematic scoping review identified 123 studies, which were categorised into six sports science and sports medicine evidence-based themes: injury (n=48), physical performance (n=32), match characteristics (n=26), fatigue and recovery (n=6), nutrition (n=6), and psychology (n=5). In part 2, the Delphi method resulted in three expert-based themes achieving consensus on future research priority in women’s rugby: injury (5.0 (1.0)), female health (4.0 (1.0)) and physical performance (4.0 (1.0)). Summary/Conclusion: This two-part systematic scoping review and Delphi consensus is the first study to summarise the applied sports science and sports medicine evidence base in women’s rugby and establish future research priorities. The summary tables from part 1 provide valuable reference information for researchers and practitioners. The three expert-based themes that achieved consensus in part 2 (injury, female health and physical performance) provide clear direction and guidance on future research priorities in women’s rugby. The findings of this two-part study facilitate efficient and coordinated use of scientific resources towards high-priority research themes relevant to a wide range of stakeholders in women’s rugby.

Women’s rugby (rugby league, rugby union and rugby sevens) has recently grown in participation and professionalisation. There is under-representation of women-only cohorts within applied sport science and medicine research and within the women’s rugby evidence base. The aims of this article are: Part 1: to undertake a systematic-scoping review of the applied sport science and medicine of women’s rugby, and Part 2: to develop a consensus statement on future research priorities. This article will be designed in two parts: Part 1: a systematic-scoping review, and Part 2: a three-round Delphi consensus method. For Part 1, systematic searches of three electronic databases (PubMed (MEDLINE), Scopus, SPORTDiscus (EBSCOhost)) will be performed from the earliest record. These databases will be searched to identify any sport science and medicine themed studies within women’s rugby. The Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews will be adhered to. Part 2 involves a three-round Delphi consensus method to identify future research priorities. Identified experts in women’s rugby will be provided with overall findings from Part 1 to inform decision-making. Participants will then be asked to provide a list of research priority areas. Over the three rounds, priority areas achieving consensus (≥70% agreement) will be identified. This study has received institutional ethical approval. When complete, the manuscript will be submitted for publication in a peer-reviewed journal. The findings of this article will have relevance for a wide range of stakeholders in women’s rugby, including policymakers and governing bodies.

Instrumented mouthguards (iMGs) are a novel technology being used within rugby to quantify head acceleration events. Understanding practitioners' perceptions of the barriers and facilitators to their use is important to support implementation and adoption. This study assessed men's and women's rugby union and league iMG managers' perceptions of staff and player interest in the technology, data and barriers to use. Forty‐six iMG managers (men's rugby union and league n = 20 and n = 9 and women's rugby union and league n = 7 and n = 10) completed an 18‐question survey. Perceived interest in data varied across staff roles with medical staff being reported as having the most interest. The iMG devices were perceived as easy to use but uncomfortable. Several uses of data were identified, including medical applications, player monitoring and player welfare. The comfort, size and fit of the iMG were reported as the major barriers to player use. Time constraints and a lack of understanding of data were barriers to engagement with the data. Continued education on how iMG data can be used is required to increase player and staff buy‐in, alongside improving comfort of the devices. Studies undertaken with iMGs investigating player performance and welfare outcomes will make data more useful and increase engagement.

Purpose: Longitudinal studies assessing the seasonal development of strength, speed and power qualities are limited in youth soccer players. The purpose of this study was to evaluate the seasonal changes in the physical development of elite youth soccer players across Pre-, Circa- and Post-Peak Height Velocity (PHV), against a similar age and maturity matched control groups. Methods: One-hundred and twelve male elite youth soccer players (Pre-PHV n = 55; Circa-PHV n = 21; Post-PHV n = 36) and 38 controls consisting of non-elite active participants (Pre-PHV n = 18; Circa-PHV n = 10; Post-PHV n = 10) all undertook isometric mid-thigh pull strength, 10–30 m sprints, change of direction speed (CODs) and countermovement jump (CMJ) tests pre- and post-season. Results: The elite Circa-PHV improved greater than the control group for all physical qualities between pre- and post-season. The elite Pre-PHV improved greater in sprints, CODs, CMJ jump height and strength while the elite Post-PHV group improved more in CODs and strength than their respective control groups. Conclusion: Findings suggest that systematic academy soccer training enhances the development of physical qualities in youth soccer players but maturity status may impact upon such adaptations.

PURPOSE: To assess indirect markers of intestinal endothelial cell damage and permeability in academy rugby players in response to rugby training at the beginning and end of preseason. METHODS: Blood and urinary measures (intestinal fatty acid binding protein and lactulose:rhamnose) as measures of gastrointestinal cell damage and permeability were taken at rest and after a standardised collision-based rugby training session in 19 elite male academy rugby players (age: 20 ± 1 years, backs: 89.3 ± 8.4 kg; forwards: 111.8 ± 7.6 kg) at the start of preseason. A subsample (n = 5) repeated the protocol after six weeks of preseason training. Gastrointestinal symptoms (GIS; range of thirteen standard symptoms), aerobic capacity (30-15 intermittent fitness test), and strength (1 repetition maximum) were also measured. RESULTS: Following the rugby training session at the start of preseason, there was an increase (median; interquartile range) in intestinal fatty acid binding protein (2140; 1260-2730 to 3245; 1985-5143 pg/ml, p = 0.003) and lactulose:rhamnose (0.31; 0.26-0.34 to 0.97; 0.82-1.07, p < 0.001). After six weeks of preseason training players physical qualities improved, and the same trends in blood and urinary measures were observed within the subsample. Overall, the frequency and severity of GIS were low and not correlated to markers of endothelial damage. CONCLUSIONS: Rugby training resulted in increased intestinal endothelial cell damage and permeability compared to rest. A similar magnitude of effect was observed after six weeks of pre-season training. This was not related to the experience of GIS.

The aim of this study was to investigate the difference in head acceleration event (HAE) incidence between training and match‐play in women's and men's players competing at the highest level of domestic rugby union globally. Players from Women's (Premiership Women's Rugby, Farah Palmer Cup) and Men's (Premiership Rugby, Currie Cup) rugby union competitions wore instrumented mouthguards during matches and training sessions during the 2022/2023 seasons. Peak linear (PLA) and angular (PAA) acceleration were calculated from each HAE and included within generalized linear mixed‐effects models. The incidence of HAEs was significantly greater in match‐play compared to training for all magnitude thresholds in both forwards and backs, despite players spending approximately 1.75–2.5 times more time in training. For all HAEs (PLA > 5 g and PAA > 400 rad/s2), incidence rate ratios (IRRs) for match versus training ranged from 2.80 (95% CI: 2.38–3.30; men's forwards) to 4.00 (3.31–4.84; women's forwards). At higher magnitude thresholds (PLA > 25 g; PAA > 2000 rad/s2), IRRs ranged from 3.64 (2.02–6.55; PAA > 2000 rad/s2 in men's backs) to 11.70 (6.50–21.08; PAA > 2000 rad/s2 in women's forwards). Similar trends were observed in each competition. Players experienced significantly more HAEs during match‐play than training, particularly at higher magnitude thresholds. Where feasible, HAE mitigation strategies may have more scope for HAE reduction if targeted at match‐play, particularly where higher magnitude HAEs are the primary concern. However, the number of HAEs associated with different training drills requires exploration to understand if HAEs can be reduced in training, alongside optimizing match performance (e.g., enhancing contact technique).

This study investigated sources of variability in the overall and phase-specific running match characteristics in elite rugby league. Microtechnology data were collected from 11 Super League (SL) teams, across 322 competitive matches within the 2018 and 2019 seasons. Total distance, high-speed running (HSR) distance (>5·5 m·s−1), average speed, and average acceleration were assessed. Variability was determined using linear mixed models, with random intercepts specified for player, position, match, and club. Large within-player coefficients of variation (CV) were found across whole match, ball-in-play, attack and defence for total distance (CV range = 24% to 35%) and HSR distance (37% to 96%), whereas small to moderate CVs (≤10%) were found for average speed and average acceleration. Similarly, there was higher between-player, -position, and -match variability in total distance and HSR distance when compared with average speed and average acceleration across all periods. All metrics were stable between-teams (≤5%), except HSR distance (16% to 18%). The transition period displayed the largest variability of all phases, especially for distance (up to 42%) and HSR distance (up to 165%). Absolute measures of displacement display large within-player and between-player, -position, and -match variability, yet average acceleration and average speed remain relatively stable across all match-periods.

This study examined the relative contribution of exercise duration and intensity to team-sport athlete’s training load. Male, professional rugby league (n = 10) and union (n = 22) players were monitored over 6- and 52-week training periods, respectively. Whole-session (load) and per-minute (intensity) metrics were monitored (league: session rating of perceived exertion training load [sRPE-TL], individualised training impulse, total distance, BodyLoad™; union: sRPE-TL, total distance, high-speed running distance, PlayerLoad™). Separate principal component analyses were conducted on the load and intensity measures to consolidate raw data into principal components (PC, k = 4). The first load PC captured 70% and 74% of the total variance in the rugby league and rugby union datasets, respectively.. Multiple linear regression subsequently revealed that session duration explained 73% and 57% of the variance in first load PC, respectively, while the four intensity PCs explained an additional 24% and 34%, respectively. Across two professional rugby training programmes, the majority of the variability in training load measures was explained by session duration (~60–70%), while a smaller proportion was explained by session intensity (~30%). When modelling the training load, training intensity and duration should be disaggregated to better account for their between-session variability.

Small-sided games is a commonly used training method to develop technical, tactical and physical qualities concurrently. However, a review of small-sided games in rugby football codes (e.g. rugby union, rugby league) is not available. This systematic review aims to investigate the acute responses and chronic adaptations of small-sided games within rugby football codes considering the constraints applied. Four electronical databases were systematically searched until August 2020. Acute and chronic studies investigating rugby football codes small-sided games, with healthy amateur and professional athletes were included. Twenty studies were eventually included: 4 acute and 1 chronic in rugby union, 13 acute and 2 chronic in rugby league. Acute studies investigated task and individual constraints. Chronic studies showed that small-sided games would be an effective training method to improve physical performance. Current research in rugby football codes is heavily biased towards investigating how manipulating constraints can affect the physical characteristics of small-sided games, with limited literature investigating the effect on technical skills, and no studies investigating tactical behaviour. Future research is needed to evidence the effects of constraint manipulation on technical and tactical behaviour of rugby football players in small-sided games, in addition to physical characteristics.

The aim of this study was to quantify the mean weekly training load (TL) of elite adolescent rugby union players participating in multiple teams, and examine the differences between playing positions. Twenty elite male adolescent rugby union players (17.4 ± 0.7 years) were recruited from a regional academy and categorised by playing position; forwards (n=10) and backs (n=10). Global positioning system and accelerometer microtechnology was used to quantify external TL, and session-rating of perceived exertion (sRPE) was used to quantify internal TL during all sessions throughout a 10-week in-season period. A total of 97 complete observations (5 ± 3 weeks per participant) were analysed, and differences between-positions were assessed using Cohen’s d effect sizes (ES) and magnitude-based inferences. Mean weekly sRPE was 1217 ± 364 AU (between-subject coefficient of variation (CV) = 30%), with a total distance (TD) of 11629 ± 3445 m (CV= 30%), and PlayerLoadTM (PL) of 1124 ± 330 AU (CV= 29%). Within-subject CV ranged between 5-78% for sRPE, 24-82% for TD, and 19-84% for PL. Mean TD (13063 ± 3933 vs. 10195 ± 2242 m), and PL (1246 ± 345 vs. 1002 ± 279 AU) were both likely greater for backs compared to forwards (moderate ES), however differences in sRPE were unclear (small ES). Although mean internal TLs and volumes were low, external TLs were higher than previously reported during pre-season and in-season periods in senior professional players. Additionally, the large between-subject and within-subject variation in weekly TL suggests players participate in a chaotic training system.

Objectives Describe head acceleration events (HAEs) experienced by professional male rugby union players during tackle, ball‐carry, and ruck events using instrumented mouthguards (iMGs). Design Prospective observational cohort. Methods Players competing in the 2023 Currie Cup (141 players) and Super Rugby (66 players) seasons wore iMGs. The iMG‐recorded peak linear acceleration (PLA) and peak angular acceleration (PAA) were used as in vivo HAE approximations and linked to contact‐event data captured using video analysis. Using the maximum PLA and PAA per contact event (HAEmax), ordinal mixed‐effects regression models estimated the probabilities of HAEmax magnitude ranges occurring, while accounting for the multilevel data structure. Results As HAEmax magnitude increased the probability of occurrence decreased. The probability of a HAEmax ≥15g was 0.461 (0.435–0.488) (approximately 1 in every 2) and ≥45g was 0.031 (0.025–0.037) (1 in every 32) during ball carries. The probability of a HAEmax >15g was 0.381 (0.360–0.404) (1 in every 3) and >45g 0.019 (0.015–0.023) (1 in every 53) during tackles. The probability of higher magnitude HAEmax occurring was greatest during ball carries, followed by tackles, defensive rucks and attacking rucks, with some ruck types having similar profiles to tackles and ball carries. No clear differences between positions were observed. Conclusion Higher magnitude HAEmax were relatively infrequent in professional men's rugby union players. Contact events appear different, but no differences were found between positions. The occurrence of HAEmax was associated with roles players performed within contact events, not their actual playing position. Defending rucks may warrant greater consideration in injury prevention research.

Abstract

To A) evaluate the difference in performance of the 30-15 Intermittent Fitness Test (30-15IFT) across four squads in a professional rugby union club in the United Kingdom (UK), and B) consider body mass in the interpretation of the end velocity of the 30-15IFT (VIFT).One hundred and fourteen rugby union players completed the 30-15IFT mid- season.VIFT demonstrated small and possibly lower (ES = -0.33; 4/29/67) values in the Under 16s compared to the Under 21s, with further comparisons unclear. With body mass included as a covariate all differences were moderate to large, and very likely to almost certainly lower in the squads with lower body mass, with the exception of comparisons between Senior and Under 21 squads.The data demonstrate that there appears to be a ceiling to the VIFT attained in rugby union players which does not increase from Under 16s to Senior level. However, the associated increases in body mass with increased playing level suggest that the ability to perform high intensity running is increased with age, although not translated into greater VIFT due to the detrimental effect of body mass on change of direction. . Practitioners should be aware that VIFT is unlikely to improve, however it needs to be monitored during periods where increases in body mass are evident.

© 2016 National Strength and Conditioning Association. This study determined the magnitude of change in adductor strength after a competitive match in academy rugby union players and examined the relationship between locomotive demands of match-play and changes in postmatch adductor strength. A withinsubject repeated measures design was used. Fourteen academy rugby union players (age, 17.4 ± 0.8 years; height, 182.7 ± 7.6 cm; body mass, 86.2 ± 11.6 kg) participated in the study. Each player performed 3 maximal adductor squeezes at 458 of hip flexion before and immediately, 24, 48, and 72 hours postmatch. Global positioning system was used to assess locomotive demands of match-play. Trivial decreases in adductor squeeze scores occurred immediately (21.3 ± 2.5%; effect size [ES] = 20.11 ± 0.21; likely, 74%) and 24 hours after match (20.7 ± 3%; ES = 20.06 ± 0.25; likely, 78%), whereas a small but substantial increase occurred at 48 hours (3.8 ± 1.9%; ES = 0.32 ± 0.16; likely, 89%) before reducing to trivial at 72 hours after match (3.1 ± 2.2%; ES = 0.26 ± 0.18; possibly, 72%). Large individual variation in adductor strength was observed at all time points. The relationship between changes in adductor strength and distance covered at sprinting speed (VO2max 81%) was large immediately postmatch (p = 0.056, r = 20.521), moderate at 24 hours (p = 0.094, r = 20.465), and very large at 48 hours postmatch (p = 0.005, r = 20.707). Players who cover greater distances sprinting may suffer greater adductor fatigue in the first 48 hours after competition. The assessment of adductor strength using the adductor squeeze test should be considered postmatch to identify players who may require additional rest before returning to field-based training.

This study established the between-day reliability and sensitivity of a countermovement jump (CMJ), plyometric push-up, wellbeing questionnaire and whole blood creatine kinase concentration [CK] in elite male youth rugby union players. The study also established the between-day reliability of 1, 2 or 3 CMJ and plyometric push-up attempts. Twenty-five players completed tests on 2 occasions separated by 5 days (of rest). Between-day typical error (TE), coefficient of variation (CV) and smallest worthwhile change (SWC) were calculated for the wellbeing questionnaire, [CK] and CMJ and plyometric push-up metrics (peak/mean power, peak/mean force, height, flight-time and flight-time to contraction-time ratio) for 1 maximal effort or taking the highest score from 2 or 3 maximal efforts. The results from this study would suggest that CMJ mean power (2 or 3 attempts), peak force or mean force, and plyometric push-up mean force (from 2 or 3 attempts) should be used for assessing lower- and upper-body neuromuscular function respectively, due to both their acceptable reliability (CV<5%) and good sensitivity (CV 5% (7.1% and 26.1% respectively) and poor sensitivity (CV>SCW). The findings from this study can be used when interpreting fatigue markers to make an objective decision about a player's readiness to train or compete.

Purpose: This study quantified the frequencies and timings of rugby union match-play phases (i.e., attacking, defending, ball in play (BIP) and ball out of play (BOP)) and then compared the physical characteristics of attacking, defending and BOP between forwards and backs. Methods: Data were analysed from 59 male rugby union academy players (259 observations). Each player wore a micro-technology device (Optimeye S5, Catapult) with video footage analysed for phase timings and frequencies. Dependent variables were analysed using a linear mixed-effects model and assessed with magnitude-based inferences and Cohen’s d effect sizes (ES). Results: Attack, defence, BIP and BOP times were 12.7 ± 3.1, 14.7 ± 2.5, 27.4 ± 2.9 and 47.4 ± 4.1 min, respectively. Mean attack (26 ± 17 s), defence (26 ± 18 s) and BIP (33 ± 24 s) phases were shorter than BOP phases (59 ± 33 s). The relative distance in attacking phases was similar (112.2 ± 48.4 vs. 114.6 ± 52.3 m·min-1, ES = 0.00 ±0.23) between forwards and backs, while greater in forwards (114.5 ± 52.7 vs. 109.0 ± 54.8 m·min-1, ES = 0.32 ±0.23) during defence and greater in backs during BOP (ES = -0.66 ±0.23). Conclusion: Total time in attack, defence and therefore BIP was less than BOP. Relative distance was greater in forwards during defence, while greater in backs during BOP and similar between positions during attack. Players should be exposed to training intensities from in play phases (i.e., attack and defence) rather than whole-match data and practice technical skills during these intensities.

It is unknown whether instantaneous visual feedback of resistance training outcomes can enhance barbell velocity in younger athletes. Therefore, the purpose of this study was to quantify the effects of visual feedback on mean concentric barbell velocity in the back squat, and to identify changes in motivation, competitiveness, and perceived workload. In a randomised-crossover design (Feedback vs. Control) feedback of mean concentric barbell velocity was or was not provided throughout a set of 10 repetitions in the barbell back squat. Magnitude-based inferences were used to assess changes between conditions, with almost certainly greater differences in mean concentric velocity between the Feedback (0.70 ±0.04 m·s-1) and Control (0.65 ±0.05 m·s-1) observed. Additionally, individual repetition mean concentric velocity ranged from possibly (repetition number two: 0.79 ±0.04 vs. 0.78 ±0.04 m·s-1) to almost certainly (repetition number 10: 0.58 ±0.05 vs. 0.49 ±0.05 m·s-1) greater when provided feedback, while almost certain differences were observed in motivation, competitiveness, and perceived workload, respectively. Providing adolescent male athletes with visual kinematic information while completing resistance training is beneficial for the maintenance of barbell velocity during a training set, potentially enhancing physical performance. Moreover, these improvements were observed alongside increases in motivation, competitiveness and perceived workload providing insight into the underlying mechanisms responsible for the performance gains observed. Given the observed maintenance of barbell velocity during a training set, practitioners can use this technique to manipulate training outcomes during resistance training

Background: Post-match fatigue has yet to be investigated inacademy rugby union players.Objectives: To determine the magnitude of change in upper-(plyometric push-up (PP) flight-time) and lower-body(countermovement jump (CMJ) mean power) neuromuscularfunction (NMF), whole blood creatine kinase (CK) and perceptionof well-being following a competitive match in academy rugbyunion players.Methods: Fourteen academy rugby union players participatedin the study. Measures were taken 2 h pre-match (baseline) andimmediately post-match. Further testing was also undertaken at24-, 48- and 72 h respectively post-match. Changes in measuresfrom baseline were determined using magnitude-based inferences.Results: Decreases in CMJ mean power were likely substantialimmediately (-5.5±3.3%) post-match, very likely at 24 h (-7±3.9),likely at 48 h (-5.8±5.4), while likely trivial at 72 h (-0.8±3.8)post-match. PP flight-time was very likely reduced immediately(-15.3±7.3%) and 24 h (-11.5±5.7%) post-match, while possiblyincreased at 48 h (3.5±6.0%) and likely trivial at 72 h (-0.9±5.4%)post-match. Decreases in perception of well-being were almostcertainly substantial at 24 h (-24.0±4.3%), very likely at 48 h(-8.3±5.9%), and likely substantial at 72 h (-3.6±3.7%) post-match.Increases in CK were almost certainly substantial immediately(138.5±33%), 24 h (326±78%) and 48 h (176±62%) post-match,while very likely substantial at 72 h (57±35%) post-match.Conclusion: These findings demonstrate the transient andmultidimensional nature of post-match fatigue in academyrugby union players. Furthermore, the results demonstrate theindividual nature of recovery, with many players demonstratingdifferent recovery profiles from the group average.Keywords: collision sport, monitoring, sports injuries

Phibbs, PJ, Jones, B, Roe, G, Read, DB, Darrall-Jones, J, Weakley, J, Rock, A, and Till, K. Organized chaos in late specialization team sports: weekly training loads of elite adolescent rugby union players. J Strength Cond Res 32(5): 1316-1323, 2018-The aim of this study was to quantify the mean weekly training load (TL) of elite adolescent rugby union players participating in multiple teams and examine the differences between playing positions. Twenty elite male adolescent rugby union players (17.4 ± 0.7 years) were recruited from a regional academy and categorized by playing position: forwards (n = 10) and backs (n = 10). Global positioning system and accelerometer microtechnology was used to quantify external TL, and session rating of perceived exertion (sRPE) was used to quantify internal TL during all sessions throughout a 10-week in-season period. A total of 97 complete observations (5 ± 3 weeks per participant) were analyzed, and differences between positions were assessed using Cohen's d effect sizes (ES) and magnitude-based inferences. Mean weekly sRPE was 1,217 ± 364 arbitrary units (AU) (between-subject coefficient of variation [CV] = 30%), with a total distance (TD) of 11,629 ± 3,445 m (CV = 30%), and PlayerLoad (PL) of 1,124 ± 330 AU (CV = 29%). Within-subject CV ranged between 5 and 78% for sRPE, 24 and 82% for TD, and 19 and 84% for PL. Mean TD (13,063 ± 3,933 vs. 10,195 ± 2,242 m) and PL (1,246 ± 345 vs. 1,002 ± 279 AU) were both likely greater for backs compared with forwards (moderate ES); however, differences in sRPE were unclear (small ES). Although mean internal TLs and volumes were low, external TLs were higher than previously reported during preseason and in-season periods in senior professional players. Additionally, the large between-subject and within-subject variation in weekly TL suggests that players participate in a chaotic training system.

Purpose: To quantify and compare the maximum running intensities during rugby union match-play. Methods: Running intensity was quantified using micro-technology devices (S5 Optimeye, Catapult) from 202 players during 24 matches (472 observations). Instantaneous speed was used to calculate relative distance (m·min-1) using a 0.1 s rolling mean for different time durations (15 and 30 s and 1, 2, 2.5, 3, 4, 5, and 10 min). Data were analysed using a linear mixed-model and assessed with magnitude-based inferences and Cohen’s d effect sizes (ES). Results: Running intensity for consecutive durations (e.g., 15 s vs. 30 s, 30 s vs. 1 min, etc.) decreased as time increased (ES = 0.48-2.80). Running intensity was lower in forwards than backs during all durations (-0.74 ±0.21 to -1.19 ±0.21). Running intensity for the second row and back row positions was greater than the front row players at all durations (-0.58 ±0.38 to -1.18 ±0.29). Running intensity for scrum-halves was greater (0.46 ±0.43 to 0.86 ±0.39) than inside and outside backs for all durations besides 15 and 30 s. Conclusions: Front rowers and scrum-halves were markedly different from other sub-positional groups and should be conditioned appropriately. Coaches working in academy rugby can use this information to appropriately overload the intensity of running, specific to time durations and positions.

The primary aim of the study was to assess the level of agreement between the criterion session-rating of perceived exertion (sRPE30min) and a practical measure of a self-reported web-based training load questionnaire 24-hours post-training (sRPE24h) in adolescent athletes. The secondary aim was to assess the agreement between weekly summated sRPE24h values (ƩsRPE24h) and a weekly web-based training diary (sRPEweekly) for all field-based training accumulated on a subsequent training week. Thirty-six male adolescent rugby players (age 16.7 ± 0.5 years) were recruited from a regional academy. sRPE30min measures were recorded 30-minutes following a typical field-based training session. Participants then completed the sRPE24h via a web-based training load questionnaire 24-hours post-training, reporting both session duration and intensity. In addition, on a subsequent week, participants completed the sRPE24h daily and then completed the sRPEweekly at the end of the week, using the same web-based platform, to recall all field-based training session durations and intensities over those seven days. Biases were trivial between sRPE30min and sRPE24h for sRPE (0.3% [-0.9 to 1.5]), with nearly perfect correlations (0.99 [0.98 to 0.99), and small typical error of the estimate (TEE; 4.3% [3.6 to 5.4]). Biases were trivial between ƩsRPE24h and sRPEweekly for sRPE (5.9% [-2.1 to 14.2]), with very large correlations (0.87 [0.78 to 0.93]), and moderate TEE 28.5% [23.3 to 36.9]). The results of this study show that sRPE24h is a valid and robust method to quantify training loads in adolescent athletes. However, sRPEweekly was found to have a substantial TEE (29%), limiting practical application.

Limited information is available regarding the training loads (TLs) of adolescent rugby union players. One-hundred and seventy male players (age 16.1 ± 1.0 years) were recruited from ten teams representing two age categories (under-16 and under-18) and three playing standards (school, club and academy). Global positioning systems, accelerometers, heart rate and session-rating of perceived exertion (s-RPE) methods were used to quantify mean session TLs. Session demands differed between age categories and playing standards. Under-18 academy players were exposed to the highest session TLs in terms of s-RPE (236 ± 42 AU), total distance (4176 ± 433 m), high speed running (1270 ± 288 m) and PlayerLoadTM (424 ± 56 AU). Schools players had the lowest session TLs in both respective age categories. Training loads and intensities increased with age and playing standard. Individual monitoring of TL is key to enable coaches to maximise player development and minimise injury risk.

The purpose of this study was to quantify the physical demands of representative adolescent rugby union match-play and investigate the difference between playing positions and age groups. Players (n=112) were classified into 6 groups by playing position (forwards and backs) and age group (U16, U18, U20). The physical demands were measured using microsensor-based technology and analysed using magnitude based inferences to assess practical importance. Backs had a greater relative distance (except U16s) and a greater high-speed running distance per minute than forwards, with the magnitude of difference between the positions becoming larger in older age groups. Forwards had higher values of PlayerLoadTM per minute (accumulated accelerations from the three axes of movement) and PlayerLoadTM slow per minute (accumulated accelerations from the three axes of movement where velocity is <2 m.s-1) than backs at all age groups. Relative distance, low- and high-speed running per minute all had a trend to be lower in older age groups for both positions. PlayerLoadTM per minute was greater in U18 than U16 and U20 for both positions. PlayerLoadTM slow per minute was greater for older age groups besides the U18 and U20 comparisons, which were unclear. The contrasts in physical demands experienced by different positions reinforce the need for greater exposure to sprinting and collision based activity for backs and forwards, respectively. Given PlayerLoadTM metrics peak at U18 and locomotor demands seem to be lower in older ages, the demands of representative adolescent rugby union do not seem to be greater at U20 as expected.

PURPOSE: The purpose of this study was to evaluate changes in performance of a 6-second cycle ergometer test (CET) and countermovement jump (CMJ) during a 6-week training block in professional rugby union players. METHODS: Twelve young professional rugby union players performed two CET and CMJ on the first and fourth morning of every week prior to the commencement of daily training during a 6-week training block. Standardised changes in the highest score of two CET and CMJ efforts were assessed using linear mixed modelling and magnitude-based inferences. RESULTS: Following increases in training load during weeks three to five, moderate decreases in CMJ peak and mean power, and small decreases in flight-time were observed during weeks five and six that were very likely to almost certainly greater than the smallest worthwhile change, suggesting neuromuscular fatigue. However, only small decreases, possibly greater than the smallest worthwhile change, were observed in CET peak power. Changes in CMJ peak and mean power, were moderately greater than in CET peak power during this period, while the difference between flight-time and CET peak power was small. CONCLUSIONS: The greater weekly changes in CMJ metrics in comparison to CET may indicate differences in the capacities of these tests to measure training induced lower-body neuromuscular fatigue in rugby union players. However, future research is needed to ascertain the specific modes of training that elicit changes in CMJ and CET in order to determine the efficacy of each test for monitoring neuromuscular function in rugby union players.

Training that is efficient and effective is of great importance to an athlete. One method of improving efficiency is by incorporating supersets into resistance training routines. However, the structuring of supersets is still unexplored. Therefore, the purpose of this study was to assess the effects of agonist-antagonist (A-A), alternate peripheral (A-P), and similar biomechanical (SB) superset configurations on rate of perceived exertion (RPE), kinetic and kinematic changes during the bench press. 10 subjects performed resistance training protocols in a randomized-crossover design, with magnitude-based inferences assessing changes/differences within and between protocols. Changes in RPE were very likely and almost certainly greater in the A-P and SB protocols when compared with the A-A, while all superset protocols had very likely to almost certain reductions in mean velocity and power from baseline. Reductions in mean velocity and power were almost certainly greater in the SB protocol, with differences between the A-A and A-P protocols being unclear. Decreases in peak force were likely and almost certain in the A-A and SB protocols respectively, with changes in A-P being unclear. Differences between these protocols showed likely greater decreases in SB peak forces when compared to A-A, with all other superset comparisons being unclear. This study demonstrates the importance of exercise selection when incorporating supersets into a training routine. It is suggested that the practitioner uses A-A supersets when aiming to improve training efficiency and minimize reductions in kinetic and kinematic output of the agonist musculature while completing the barbell bench press.

This study investigated the change in body composition and bone mineral content (BMC) of senior rugby league players between 2008 and 2014. Twelve male professional rugby league players (age, 24.6±4.0 years; stature, 183.4±8.4 cm) received a DXA scan during pre-season in 2008 and 2014. Between 2008 and 2014, very likely increases in leg lean mass, total trunk and leg BMC, and a likely increase in arm BMC and possible increases in body mass, total and trunk fat mass, and total, trunk and arm lean mass were observed. Unlikely decreases and unclear changes in leg and arm fat mass were also found. Large negative correlations were observed between age and body mass (r=-0.72), lean mass (r=-0.70), fat mass (r=-0.61), and BMC (r=-0.84) change. Three participants (19.1 ± 1.6 years) increased lean mass by 7.0 – 9.3 kg. Younger players had the largest increases in lean mass during this period, although an older player (30 year-old) still increased lean mass. Differences in body composition change were also observed for participants of the same age, thus contextual factors should be considered. This study demonstrates the individuality of body composition changes in senior professional rugby players, while considering the potential change in young athletes.

Adolescent rugby players benefit from the implementation of resistance training. However resistance training practices and how they influence short-term physical change is unknown. Therefore the purpose of this study was to quantify resistance training practices, evaluate physical development, and relate these changes to resistance training variables across 12-weeks in adolescent rugby union players. Thirty-five male adolescent rugby union players participated in the study with subjects completing an anthropometric and physical testing battery pre- and post- a 12-week in-season mesocycle. Subjects recorded resistance training frequency, exercises, repetitions, load, minutes, and rating of perceived exertion for each session using weekly training diaries during the 12-week period. Paired sample t-tests and Cohen’s d effect sizes were used to assess change, while Pearson correlation coefficients assessed relationships between variables. Resistance training practices were variable, while significant (p ≤0.05) improvements in body mass, countermovement jump (CMJ) height, front squat, bench press, and chin up strength were observed. Resistance training volume load had moderate to strong relationships with changes in CMJ (r =0.71), chin up (r =0.73) and bench press (r =0.45). Frequency of upper and lower body compound exercises had significant moderate to large relationships with changes in CMJ (r =0.68), chin up (r =0.65), and bench press (r =0.41). Across a 12-week in-season period, adolescent rugby union players have varying resistance training practices, while anthropometric and physical characteristics appear to improve. Given the observed relationships, increased volume loads through the implementation of free-weight compound exercises could be an effective method for improving physical qualities in young rugby players. Rugby union, resistance training, strength, power

PURPOSE: Investigate the acute and short-term (i.e., 24 h) effects of traditional (TRAD), superset (SS), and tri-set (TRI) resistance training protocols on perceptions of intensity and physiological responses. METHODS: Fourteen male participants completed a familiarisation session and three resistance training protocols (i.e., TRAD, SS, and TRI) in a randomised-crossover design. Rating of perceived exertion, lactate concentration ([Lac]), creatine kinase concentration ([CK]), countermovement jump (CMJ), testosterone, and cortisol concentrations was measured pre, immediately, and 24-h post the resistance training sessions with magnitude-based inferences assessing changes/differences within/between protocols. RESULTS: TRI reported possible to almost certainly greater efficiency and rate of perceived exertion, although session perceived load was very likely lower. SS and TRI had very likely to almost certainly greater lactate responses during the protocols, with changes in [CK] being very likely and likely increased at 24 h, respectively. At 24-h post-training, CMJ variables in the TRAD protocol had returned to baseline; however, SS and TRI were still possibly to likely reduced. Possible increases in testosterone immediately post SS and TRI protocols were reported, with SS showing possible increases at 24-h post-training. TRAD and SS showed almost certain and likely decreases in cortisol immediately post, respectively, with TRAD reporting likely decreases at 24-h post-training. CONCLUSIONS: SS and TRI can enhance training efficiency and reduce training time. However, acute and short-term physiological responses differ between protocols. Athletes can utilise SS and TRI resistance training, but may require additional recovery post-training to minimise effects of fatigue.

The aims of this study were to determine the variability of weekly match and training loads in adolescent rugby union players across a competitive season, and to investigate the effect of match frequency on load distribution across different activities. Internal match and training load data (i.e., session-rating of perceived exertion: sRPE) were collected daily from 20 players from a regional academy across a 14-week season. Data were analysed using a mixed-effects linear model, and variability was reported as a coefficient of variation (CV). Differences between 0-, 1-, 2-, and 3-match weeks were assessed using Cohen’s d effect sizes and magnitude-based inferences. Mean weekly total match and training sRPE load was 1425 ± 545 arbitrary units (AU), with a between-player CV of 10 ±6% and within-player CV of 37 ±3%. Mean week-to-week change in total sRPE load was 497 ± 423 AU (35%), and 40% of weekly observations were outside of the suggested acute:chronic workload ratio ‘safe zone’. Total weekly sRPE loads increased substantially with match frequency (1210 ± 571 AU, 1511 ± 489, and 1692 ± 517 AU, for 0-, 1-, and 2-match weeks, respectively), except for 3-match weeks (1520 ± 442 AU). Weekly match and training loads were highly variable for adolescent rugby players during the competitive season, and match frequency has a substantial effect on the distribution of loads. Therefore, match and training loads should be coordinated, monitored, and managed on an individual basis to protect players from negative training consequences, and to promote long term athlete development.

The aim of this study was to compare the physical and movement demands between training and match-play in schoolboy and academy adolescent rugby union (RU) players. Sixty-one adolescent male RU players (mean ± SD; age 17.0 ± 0.7 years) were recruited from four teams representing school and regional academy standards. Players were categorised into four groups based on playing standard and position: schoolboy forwards (n=15), schoolboy backs (n=15), academy forwards (n=16) and academy backs (n=15). Global positioning system and accelerometry measures were obtained from training and match-play to assess within-group differences between conditions. Maximum data were analysed from 79 match files across 8 matches (1.3 ± 0.5 matches per participant) and 152 training files across 15 training sessions (2.5 ± 0.5 training sessions per participant). Schoolboy forwards were underprepared for low-intensity activities experienced during match-play, with schoolboy backs underprepared for all movement demands. Academy forwards were exposed to similar physical demands in training to matches, with academy backs similar to or exceeding values for all measured variables. Schoolboy players were underprepared for many key, position-specific aspects of match-play, which could place them at greater risk of injury and hinder performance, unlike academy players who were better prepared.

The aim was to compare the physical characteristics of under-18 academy and schoolboy rugby union competition by position (forwards and backs). Using a microsensor unit, match characteristics were recorded in 66 players. Locomotor characteristics were assessed by maximum sprint speed (MSS) and total, walking, jogging, striding and sprinting distances. The slow component (<2 m · s(-1)) of PlayerLoad(TM) (PLslow), which is the accumulated accelerations from the three axes of movement, was analysed as a measure of low-speed activity (e.g., rucking). A linear mixed-model was assessed with magnitude-based inferences. Academy forwards and backs almost certainly and very likely covered greater total distance than school forwards and backs. Academy players from both positions were also very likely to cover greater jogging distances. Academy backs were very likely to accumulate greater PLslow and the academy forwards a likely greater sprinting distance than school players in their respective positions. The MSS, total, walking and sprinting distances were greater in backs (likely-almost certainly), while forwards accumulated greater PLslow (almost certainly) and jogging distance (very likely). The results suggest that academy-standard rugby better prepares players to progress to senior competition compared to schoolboy rugby.

The purpose of this study was to determine the between-day reliability of commonly used strength measures in male youth athletes, while considering resistance training experience. Data were collected on 25 male athletes over two testing sessions, with 72 hours rest between, for the 3RM front squat, chin up and bench press. Subjects were initially categorized by resistance training experience (inexperienced; 6-12 months, experienced; >2 years). The assessment of the between-day reliability (coefficient of variation [CV%]) showed the front squat (experienced: 2.90%; inexperienced: 1.90%), chin up (experienced: 1.70%; inexperienced: 1.90%), and bench press (experienced: 4.50%; inexperienced: 2.40%) were all reliable measures of strength in both groups. Comparison between groups for the error of measurement for each exercise showed trivial differences. When both groups were combined, the CV% for the front squat, bench press, and chin up were 2.50%, 1.80%, and 3.70%, respectively. This study provides scientists and practitioners with the between-day reliability reference data to determine real and practical changes for strength in male youth athletes with different resistance training experience. Furthermore, this study demonstrates that 3RM front squat, chin up and bench press are reliable exercises to quantify strength in male youth athletes.

Repeated physical contact in rugby union is thought to contribute to post-match fatigue; however, no evidence exists on the effect of contact activity during field-based training on fatigue responses. Therefore, the purpose of this study was to examine the effect of contact during training on fatigue markers in rugby union players. Twenty academy rugby union players participated in the cross-over study. The magnitude of change in upper- and lower-body neuromuscular function (NMF), whole blood creatine kinase concentration [CK] and perception of well-being was assessed pre-training (baseline), immediately and 24 h post-training following contact and non-contact, field-based training. Training load was measured using mean heart rate, session rating of perceived exertion (sRPE) and microtechnology (Catapult Optimeye S5). The inclusion of contact during field-based training almost certainly increased mean heart rate (9.7; ±3.9%) and sRPE (42; ±29.2%) and resulted in likely and very likely greater decreases in upper-body NMF (-7.3; ±4.7% versus 2.7; ±5.9%) and perception of well-being (-8.0; ±4.8% versus  -3.4; ±2.2%) 24 h post-training, respectively, and almost certainly greater elevations in [CK] (88.2; ±40.7% versus 3.7; ±8%). The exclusion of contact from field-based training almost certainly increased running intensity (19.8; ±5%) and distance (27.5; ±5.3%), resulting in possibly greater decreases in lower-body NMF (-5.6; ±5.2% versus 2.3; ±2.4%). Practitioners should be aware of the different demands and fatigue responses of contact and non-contact, field-based training and can use this information to appropriately schedule such training in the weekly microcycle.

ABSTRACT

This study aimed to describe the incidence of head acceleration events (HAEs) during pitch‐based in‐season training and matches in professional male rugby league. Data were recorded using instrumented mouthguards from 108 players (70 forwards and 38 backs) at nine Super League teams (2024 season), resulting in 468 player‐training sessions and 665 player‐matches included. Peak linear and angular acceleration were calculated from each HAE and analyzed using generalized linear mixed‐effects models. During the 468 player‐training sessions, 814 HAEs above the lowest magnitude threshold (5  g and 400 rad.s −2 ) were observed and the mean HAE incidence rate per player‐hour was 1.52 (95% confidence intervals; 1.34–1.70). This was substantially lower than matches (25.78 [23.28–28.27] per player‐hour) with HAE incidence being 17 times greater during matches compared to training (incidence rate ratio 16.96 [14.92–19.01]). Higher magnitude HAEs had a lower incidence in both training and matches (e.g., > 25  g 0.04 [0.02–0.06] and 2.01 [1.79–2.24] per player‐hour). Out of 468 player‐training sessions, 307 (~66%) had no HAEs > 10  g and 441 (~94%) had no HAEs > 25  g . Overall, the incidence rates of HAEs during training were low and substantially lower than match‐play. However, a small proportion of relatively high in magnitude HAEs do occur during training, which could be the target of prevention interventions in training. However, given the different HAE rates between training and matches, interventions targeting matches (e.g., law modifications or reduced exposure) would have a larger effect on reducing HAEs for players than training interventions.

Roe, G, Shaw, W, Darrall-Jones, J, Phibbs, PJ, Read, D, Weakley, JJ, Till, K, and Jones, B. Reliability and validity of a medicine ball-contained accelerometer for measuring upper-body neuromuscular performance. J Strength Cond Res 32(7): 1915-1918, 2018-The aim of the study was to assess the between-day reliability and validity of a medicine ball-contained accelerometer (MBA) for assessing upper-body neuromuscular performance during a throwing task. Ten professional rugby union players partook in the study. Between-day reliability was assessed from the best score attained during 2 sets of 3 throws, on 2 testing occasions separated by 7 days. Validity was assessed against a criterion measure (Optioelectronic system) during 75 throws from a subgroup of 3 participants. The MBA exhibited a small between-day error of 2.2% (90% confidence intervals; 2.0-4.6%) and an almost perfect relationship with a criterion measure (r = 0.91 [90% CIs; 0.87-0.94]). However, the mean bias and standard error were moderate (7.9% [90% CIs; 6.6-9.2%] and 4.9% [90% CIs; 4.2-5.7%], respectively). Practitioners using an MBA to assess neuromuscular performance of the upper body must take into account the overestimation and error associated with such assessment with respect to a criterion measure. However, as the error associated with between-day testing was small and testing is easy to implement in applied practice, an MBA may provide a useful tool for monitoring upper-body neuromuscular performance over time.

Background: In England, rugby union is a popular sport and is widely played within schools. Despite the large participation numbers, the movement and physical demands of the sport and how they progress by age have not been explored. Method: Ninety-six male rugby union players wore microtechnology devices during six rugby union matches within the education pathway to investigate the movement and physical demands of match-play. To quantify the positional differences and progression by age, data were obtained for participants at the under 16 (U16) (n=31 participants), under 18 (U18) (n=34 participants) and university (n=31 participants) levels. Players were further divided in forwards and backs. Data were analysed using magnitude-based inferences. Results: For the movement demands, U16 total distance and ‘striding’ was likely higher for forwards than backs, whereas at U18, unclear differences were observed and from university players the inverse was observed (very likely). In all age groups sprint distance was likely to very likely greater for backs than forwards. Forwards had greater physical demands than backs at all age groups. For consecutive age groups, U16 had a likely higher relative distance than U18, and U18 had a likely lower relative distance than university players. Physical demands were similar across age groups for forwards, and greater for backs at older age groups. Conclusion: The movement and physical demands of rugby union players participating in schools (U16 and U18), may not be as expected, however, the findings from university players show a similar pattern to the senior game.

Rugby union (RU) is a skill-collision team sport played at junior and senior levels worldwide. Within England, age-grade rugby governs the participation and talent development of youth players. The RU player development pathway has recently been questioned, regarding player performance and wellbeing, which sport science research can address. The purpose of this review was to summarise and critically appraise the literature in relation to the applied sport science of male age-grade RU players in England focusing upon 1) match-play characteristics, 2) training exposures, 3) physical qualities, 4) fatigue and recovery, 5) nutrition, 6) psychological challenges and development, and 7) injury. Current research evidence suggests that age, playing level and position influence the match-play characteristics of age-grade RU. Training exposures of players are described as ‘organised chaos’ due to the multiple environments and stakeholders involved in coordinating training schedules. Fatigue is apparent up to 72 hours post match-play. Well developed physical qualities are important for player development and injury risk reduction. The nutritional requirements are high due to the energetic costs of collisions. Concerns around the psychological characteristics have also been identified (e.g., perfectionism). Injury risk is an important consideration with prevention strategies available. This review highlights the important multi-disciplinary aspects of sport science for developing age-grade RU players for continued participation and player development. The review describes where some current practices may not be optimal, provides a framework to assist practitioners to effectively prepare age-grade players for the holistic demands of youth RU and considers areas for future research.

Weakley, JJS, Till, K, Read, DB, Leduc, C, Roe, GAB, Phibbs, PJ, Darrall-Jones, J, and Jones, B. Jump training in rugby union players: barbell or hexagonal bar?. J Strength Cond Res XX(X): 000-000, 2018-The countermovement jump (CMJ) is an exercise that can develop athletic performance. Using the conventional barbell (BAR) and hexagonal barbell (HEX) while jumping, the intensity can be increased. However, the bar that provides greater adaptations is unknown. Therefore, this study aimed to assess changes in loaded and unloaded CMJ with either a BAR or HEX across a 4-week mesocycle in rugby union players. Twenty-nine subjects were strength-matched and randomized into 2 groups. Subjects completed 3 sets of CMJ at 20% of 1 repetition maximum back squat, 3 times per week for 4 weeks, using either a BAR or HEX. Subjects completed an unloaded CMJ on a force plate before and after, whereas the highest peak concentric velocity during the jump squat was recorded in the first and last training sessions using a linear position transducer. Magnitude-based inferences assessed meaningful changes within- and between-groups. Possibly greater improvements in unloaded CMJ were found in the HEX group in jump height (effect size ± 90% confidence intervals: 0.27 ± 0.27), relative peak (0.21 ± 0.23), and mean power (0.32 ± 0.36). In addition, likely to very likely greater improvements were observed in the HEX group in peak velocity (0.33 ± 0.27), relative mean power (0.53 ± 0.30), mean force (0.47 ± 0.27), and 100-ms impulse (0.60 ± 0.48). Similar raw changes in jump squat peak velocity occurred (0.20-0.25 m·s), despite the likely greater ES occurring with the BAR (0.32 ± 0.26). These results indicate that training with the HEX leads to superior unloaded CMJ adaptations. In addition, practitioners should use either the HEX or BAR when aiming to enhance loaded jump ability.

Limited research has compared the physical qualities of adolescent rugby union (RU) players across differing playing standards. This study therefore compared the physical qualities of academy and school Under-18 RU players. One-hundred and eighty-four (professional regional academy, n = 55 school, n = 129) male RU players underwent a physical testing battery to quantify height, body mass, strength (bench press and pull-up), speed (10, 20 and 40 m), 10 m momentum (calculated; 10 m velocity * body mass) and a proxy measure of aerobic fitness (Yo-Yo Intermittent Recovery Test Level 1; IRTL1). The practical significance of differences between playing levels were assessed using magnitude-based inferences. Academy players were taller (very likely small), heavier (likely moderate) and stronger (bench press possibly large; pull-up plus body mass likely small) than school players. Academy players were faster than school players over 20 and 40 m (possibly and likely small), although differences in 10 m speed were not apparent (possibly trivial). Academy players displayed greater 10 m momentum (likely moderate) and greater IRTL1 performance (likely small) than school players. These findings suggest that body size, strength, running momentum, 40 m speed and aerobic fitness contribute to a higher playing standard in adolescent rugby union.