Dr Josh Darrall-Jones

Strength and conditioning is essential for the youth rugby player. It supports the development of strength, power, speed, aerobic fitness, and improved body composition that is required for long-term success. This chapter summarises the scientific literature that has investigated strength and conditioning training interventions in youth rugby players and discusses the changes in physical qualities that occur following different forms of training. Specifically, it examines the literature that has investigated different forms of conditioning (e.g., sprint-intervals, high-intensity interval training, small-sided games) and resistance training (e.g., programming methods, periodisation models), and provides an overview of these different training interventions. Due to the many different forms of training that can be implemented, this chapter highlights limitations of the current literature and provides future research directions to support the physical development of youth rugby players.

Strength and conditioning is important for the optimal development of strength, power, speed, aerobic fitness, and improved body composition in the youth rugby player. This chapter summarises the scientific literature and provides practical recommendations relating to how it can be implemented. Specifically, the first half of this chapter details the research to date and the expected adaptations that can occur when different methods of resistance training and conditioning are applied. Guided by the evidence, the second half of this chapter provides recommendations on the implementation of these training methods and considerations around the acute-training variables that underpin all training programme designs. The chapter concludes with several recommendations that can be employed to enhance training adaptations and allow for continued long-term athlete development.

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.

Purpose The aim was to develop and validate an individualised internal training exposure method by deriving weighting factors for each heart rate (HR) from detrended fluctuation analysis of heart rate variability (DFA-α1) during a graded exercise test. Methods Thirty-seven participants (17 females; 32.72 ± 9.26 years; maximal oxygen uptake, O2max = 48.32 ± 7.95 mL kg−1 min−1) completed a step- and a ramp incremental test to measure blood lactate (BLa), DFA-α1, and cardiorespiratory fitness (CRF) variables, i.e. speed at lactate, ventilatory thresholds (LTs/VTs), and O2max. Exponential fitting of the fractional elevation of HR (ΔHR) with BLa (individualised training impulse; iTRIMP) or DFA-α1 (αTRIMP) generated individualised coefficients for both methods. The TRIMP weightings were interpolated values of BLa or DFA-α1 derived at each ΔHR through coefficients to represent individualised physiological intensity. Principal component regression evaluated the relationship between combined CRF variables and the TRIMP coefficients or weightings. Results Large inter-individual variation was observed at the same physiological thresholds (ΔHR at LT1/VT1 = 0.51–0.83 and LT2/VT2 = 0.63–0.96), underscoring the need for TRIMP methods to weight ΔHR and account for different exposure at similar intensity. CRF had a moderate relationship with coefficients for iTRIMP and αTRIMP methods (R2average = 0.52–0.67), but a moderate to strong relationship with their weightings at a fixed ΔHR (R2average = 0.67–0.78). Conclusion αTRIMP is a valid and practically accessible method for quantifying internal training exposure using ECG-based HR monitors, which individualises physiological intensity through DFA-α1-derived weightings among individuals of varied fitness exercising at same percentages of HR.

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.

OBJECTIVE: Develop a questionnaire to monitor symptoms of player perceived shoulder function/dysfunction. DESIGN: 3-Stage Online Delphi Study. METHODS: Participants: surgeons, sports and exercise medics, academic researchers, strength and conditioning coaches, therapists and athletes split by level of expertise/experience. Stage-1: experts (n = 12) rated constructs/items from the steering group and made changes/proposed additional constructs/items. Stage-2: experts rated/amended new constructs/items from stage-1. Stage-3: experienced professionals (n = 25) rated/ranked constructs/items from stage 2. Consensus thresholds were defined per stage (≥50% agreement/4-5 rating on 1-5 Likert scale (stages 1-2), ≥68% agreement, and items ranked for perceived importance (stage-3)). RESULTS: Stage-1, all four constructs (a. Activities of daily living, b. Range of motion, c. Strength and conditioning, d. Sports specific training and competition) and 26/42 original items achieved consensus. Twelve items were combined into five items. Four new items were also proposed. Stage-2, the combined items and three of the four new items achieved consensus. Stage-3 the four constructs and 22 items all achieved consensus. CONCLUSIONS: Following a 3-stage online Delphi process, involving expert and experienced clinicians, practitioners and athletes, a new four construct, 22 item RSF questionnaire has been developed which can be used with rugby players, to monitor perceived shoulder performance and symptoms.

Establishing normative ranges for Bone Mineral Density in female team sport athletes Purpose: It is common that female athlete cohorts generally have higher bone density compared to non-athletic controls or typical reference populations. However, activity specific reference databases are required to identify athletes who have comparatively low BMD within their sport, as this may highlight increased risk of stress fractures or occurrences of low energy availability. Method: A secondary data analysis of three female team sport cohorts (cricket, rugby league, netball, n=103) will be completed from previous dual x-ray absorptiometry scans (Lunar iDXA, GE Medical Systems). Bone mineral density (total, lumbar spine [L1-L4], total hip and neck of femur) will be analysed alongside age, mass, stature, and fat free lean mass. Results: Data is yet to be analysed. Conclusion: Sport specific ranges will inform improved practice to enable early identification of athletes at present risk or stress fracture or low energy availability outcomes as well as future risk of osteoporosis or fracture with ageing.

The purpose of the present study was to evaluate the anthropometric and physical characteristics of English regional academy rugby union academy players by age category (under 16, under 18 and under 21s). Data were collected on 67 academy players at the beginning of the pre-season period and comprised anthropometric (height, body mass and sum of 8 skinfolds) and physical (5 m, 10 m, 20 m & 40 m sprint, acceleration, velocity & momentum; agility 505; vertical jump; yo-yo intermittent recovery test level 1; 30-15 Intermittent Fitness Test; absolute and relative 3 repetition maximum (3RM) front squat, split squat, bench press, prone row and chin; and isometric mid-thigh pull). One way analysis of variance demonstrated significant increases across the three age categories (p < 0.05) for height (e.g., 16s = 178.8 ± 7.1; 18s = 183.5 ± 7.2; 21s = 186.7 ± 6.61 cm), body mass (e.g., 16s = 79.4 ± 12.8; 18s = 88.3 ± 11.9; 21s = 98.3 ± 10.4kg), countermovement jump height and peak power, sprint momentum, velocity and acceleration; absolute, relative and isometric (e.g., 16s = 2157.9 ± 309.9; 18s = 2561.3 ± 339.4; 21s = 3104.5 ± 354.0 N) strength. Momentum, maximal speed and the ability to maintain acceleration were all discriminating factors between age categories, suggesting that these variables may be more important to monitor rather than sprint times. These findings highlight that anthropometric and physical characteristics develop across age categories and provide comparative data for English academy Rugby Union players.

The purpose of the present study was to evaluate the anthropometric, sprint and high-intensity running profiles of English academy rugby union players by playing positions, and to investigate the relationships between anthropometric, sprint and high intensity running characteristics. Data was collected from 67 academy players following the off-season period and consisted of anthropometric (height, body mass, sum of 8 skinfolds [∑SF]), 40 m linear sprint (5, 10, 20 30 & 40 m splits), the Yo-Yo intermittent recovery test level 1(Yo-Yo IRTL-1) and the 30-15 intermittent fitness test (30-15IFT). Forwards displayed greater stature, body mass and ∑SF; sprint times and sprint momentum, with lower high-intensity running ability and sprint velocities than backs. Comparisons between age categories demonstrated body mass and sprint momentum to have the largest differences at consecutive age categories for forwards and backs; whilst 20-40 m sprint velocity was discriminate for forwards between Under 16s, 18s and 21s. Relationships between anthropometric, sprint velocity, momentum and high-intensity running ability demonstrated body mass to negatively impact upon sprint velocity (10 m; r = -0.34 to -0.46); positively affect sprint momentum (e.g., 5 m; r = 0.85 to 0.93), with large to very large negative relationships with the Yo-Yo IRTL-1 (r= -0.65 to -0.74) and 30-15IFT (r= -0.59 to -0.79). These findings suggest that there are distinct anthropometric, sprint and high-intensity running ability differences between and within positions in junior rugby union players. The development of sprint and high-intensity running ability may be impacted by continued increases in body mass as there appears to be a trade-off between momentum, velocity and the ability to complete high-intensity running.

Poster presentation

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.

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.

Abstract

Introduction: Physical and nutritional behaviours among female cricketers have yet to be explored. Therefore, the purpose of the present study was to estimate energy intake (EI), total energy expenditure (TEE), macronutrient and fluid intake in elite and highly trained female cricketers over 24-hour periods across 50-over home fixtures. Methods: Ten elite and highly trained female cricketers (age 24.1 ± 4.9 years; body mass 73.8 ± 7.8 kg; stature 171.3 ± 3.2 cm) were observed over three 50-over home matches. Body composition was measured using dual X-ray absorptiometry. EI was assessed through a combination of food photography and weighing of food intake. Resting metabolic rate was measured using indirect calorimetry, physical activity was monitored using accelerometry, and thermic effect of food was estimated; therefore, TEE was inferred. Results: The mean daily EI, TEE and resulting energy balance (EB) were 2558 ± 622 kcal·day

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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.

Background The evaluation of physical qualities in talent identification and development systems is vital and commonplace in supporting youth athletes towards elite sport. However, the complex and dynamic development of physical qualities in addition to temporal challenges associated with the research design, such as unstructured data collection and missing data, requires appropriate statistical methods to be applied in research to optimise the understanding and knowledge of long-term physical development. Aim To collate and evaluate the application of methodological and statistical methods used in studies investigating the development of physical qualities within youth athletes. Methods Electronic databases were systematically searched form the earliest record to June 2021 and reference lists were hand searched in accordance with the PRISMA guidelines. Studies were included if they tested physical qualities over a minimum of 3 timepoints, were observational in nature and used youth sporting populations. Results Forty articles met the inclusion criteria. The statistical analysis methods applied were qualitatively assessed against the theoretical underpinnings (i.e. multidimensional development, non-linear change and between and within athlete change) and temporal challenges (i.e. time variant and invariant variables, missing data, treatment of time and repeated measures) encountered with longitudinal physical testing research. Multilevel models were implemented most frequently (50%) and the most appropriately used statistical analysis method when qualitatively compared against the longitudinal challenges. Independent groups ANOVA, MANOVA and X were also used, yet failed to address any of the challenges posed within longitudinal physical testing research. Conclusions This methodological review identified the statistical methods currently employed within longitudinal physical testing research and addressed the theoretical and temporal challenges faced in longitudinal physical testing research with varying success. The findings can be used to support the selection of statistical methods when evaluating the development of youth athletes through the consideration of the challenges presented.

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.

This study aims to establish the validity and reliability of the prone Yo-YoIRL1 in elite female rugby league players (part one) and determine the anthropometric and physical characteristics contributing to 15m prone Yo-YoIRL1 performance (part two). Part one, 21 subjects completed one Yo-YoIRL1, one 20m and two 15m prone Yo-YoIRL1 tests over four sessions, with 7–14 days in-between. Part two, ten subjects completed a testing battery, including body mass, height, dual-energy x-ray absorptiometry, isometric mid-thigh pull, isometric bench-press, 10m and 20m sprints and an incremental treadmill test (V˙O2max). The 15m prone YoYoIRL1 demonstrated poor reliability with a typical error of 68m (21%) and a smallest worthwhile change of 54m (9%). Validity analysis found the prone versions of the YoYoIRL1 were not sensitive measures of intermittent running performance. Both prone YoYoIRL1 test distances demonstrated large mean bias (76% and -37% respectively) and typical error of the estimate (19% and 21%, respectively) in comparison to the YoYoIRL1. Body mass (r = -0.89), lean mass (r = -0.64), body fat % (r = -0.68), V˙O2max (l∙min-1) (r = -0.64), IMTP (r = -0.69), IBP (r = -0.15), 10m (r = -0.77) and 20m (r = -0.72) momentum displayed large negative relationships with 15m prone Yo-YoIRL1 performance. Due to the poor validity of the 20m prone YoYoIRL1, the poor validity and reliability of the 15m prone YoYoIRL1, and the anthropometric and physical characteristics which negatively impact performance, practitioners should reconsider the use of the prone YoYoIRL1 test to monitor high intensity intermittent running performance.

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.

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.

The purpose of this study was to evaluate the annual and long-term (i.e., 4 years) development of anthropometric and physical characteristics in academy (16-20 years) rugby league players. Players were assessed at the start of preseason over a 6-year period and were required to be assessed on consecutive years to be included in the study (Under 16-17, n = 35; Under 17-18, n = 44; Under 18-19, n = 35; Under 19-20, n = 16). A subset of 15 players were assessed for long-term changes over 4 years (Under 16-19). Anthropometric (height, body mass, sum of 4 skinfolds) and physical (10- and 20-m sprint, 10-m momentum, vertical jump, yo-yo intermittent recovery test level 1, 1 repetition maximum [1RM] squat, bench press, and prone row) assessments were collected. Paired t-tests and repeated measures analysis of variance demonstrated significant annual (e.g., body mass, U16 = 76.4 ± 8.4, U17 = 81.3 ± 8.3 kg; p < 0.001, d = 0.59) and long-term (e.g., vertical jump, Under 16 = 44.1 ± 3.8, Under 19 = 52.1 ± 5.3 cm; p < 0.001, d = 1.74) changes in anthropometric and physical characteristics. Greater percentage changes were identified between the Under 16-17 age categories compared with the other ages (e.g., 1RM squat, U16-17 = 22.5 ± 19.5 vs. U18-19 = 4.8 ± 6.4%). Findings demonstrate the annual and long-term development of anthropometric and physical characteristics in academy rugby league players establishing greater changes occur at younger ages upon the commencement of a structured training program within an academy. Coaches should understand the long-term development of physical characteristics and use longitudinal methods for monitoring and evaluating player performance and development.

This two-part study evaluated the inter- and intra-unit reliability of Catapult Vector S7 microtechnology units in an indoor court-sport setting. In part-one, 27 female netball players completed a controlled movement series on two separate occasions to assess the inter- and intra-unit reliability of inertial movement analysis (IMA) variables (acceleration, deceleration, changes of direction and jumps). In part-two, 13 female netball players participated in 10 netball training sessions to assess the inter-unit reliability of IMA and PlayerLoadTM variables. Participants wore two microtechnology units placed side-by-side. Reliability was assessed using intraclass correlation coefficient (ICC), coefficient of variation (CV) and typical error (TE). Total IMA events showed good inter-unit reliability during the movement series (ICC, 1.00; CV, 3.7%) and training sessions (ICC, 0.99; CV, 4.5%). Inter-unit (ICC, 0.97; CV, 4.7%) and intra-unit (ICC, 0.97; CV, 4.3%) reliability for total IMA jump count was good in the movement series, with moderate CV (7.7%) during training. Reliability decreased when IMA counts were categorised by intensity and movement type. PlayerLoadTM (ICC, 1.00; CV, 1.5%) and associated variables revealed good inter-reliability, except peak PlayerLoadTM (moderate) and PlayerLoadSLOW (moderate). Counts of IMA variables, when considered as total and low-medium counts, and PlayerLoad variables are reliable for monitoring indoor court-sports players.

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.

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.

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.

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.

© 2017 Thomas Sawczuk, Ben Jones, Sean Scantlebury, Jonathan Weakley, Dale Read, Nessan Costello, Joshua David Darrall-Jones, Keith Stokes, and Kevin Till This study aimed to evaluate the between-day reliability and usefulness of a fitness testing battery in a group of youth sport athletes. Fifty-nine youth sport athletes (age = 17.3 ± 0.7 years) undertook a fitness testing battery including the isometric mid-thigh pull, counter-movement jump, 5–40 m sprint splits, and the 5–0-5 change of direction test on two occasions separated by 7 days. Usefulness was assessed by comparing the reliability (typical error) to the smallest worthwhile change. The typical error was 5.5% for isometric mid-thigh pull and 3.8% for counter-movement jump. The typical error values were 2.7, 2.5, 2.2, 2.2, and 1.8% for the 5, 10, 20, 30, and 40 m sprint splits, and 4.1% (left) and 5.4% (right) for the 5–0-5 tests. The smallest worthwhile change ranged from 1.1 to 6.1%. All tests were identified as having “good” or “acceptable” reliability. The isometric mid-thigh pull and counter-movement jump had “good” usefulness, all other tests had “marginal” usefulness.

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.

Till, K, Jones, B, Darrall-Jones, J, Emmonds, S, and Cooke, C. Longitudinal development of anthropometric and physical characteristics within academy rugby league players. J Strength Cond Res 29(6): 1713-1722, 2015-The purpose of this study was to evaluate the annual and long-term (i.e., 4 years) development of anthropometric and physical characteristics in academy (16-20 years) rugby league players. Players were assessed at the start of preseason over a 6-year period and were required to be assessed on consecutive years to be included in the study (Under 16-17, n 35; Under 17-18, n=44; Under 18-19, n=35; Under 19-20, n=16). A subset of 15 players were assessed for long-term changes over 4 years (Under 16-19). Anthropometric (height, body mass, sum of 4 skinfolds) and physical (10-and 20-m sprint, 10-m momentum, vertical jump, yo-yo intermittent recovery test level 1, 1 repetition maximum [1RM] squat, bench press, and prone row) assessments were collected. Paired t-tests and repeated measures analysis of variance demonstrated significant annual (e.g., body mass, U16=76.4 ± 8.4, U17=81.3 ± 8.3 kg; p < 0.001, d=0.59) and long-term (e.g., vertical jump, Under 16=44.1 ± 3.8, Under 19=52.1 ± 5.3 cm; p < 0.001, d=1.74) changes in anthropometric and physical characteristics. Greater percentage changes were identified between the Under 16-17 age categories compared with the other ages (e.g., 1RM squat, U16-17 22.5 ± 19.5 vs. U18-19 4.8 ± 6.4%). Findings demonstrate the annual and long-term development of anthropometric and physical characteristics in academy rugby league players establishing greater changes occur at younger ages upon the commencement of a structured training program within an academy. Coaches should understand the long-term development of physical characteristics and use longitudinal methods for monitoring and evaluating player performance and development.