Differences in the Movement Skills and Physical Qualities of Elite Senior & Academy Rugby League Players.

The aim of the present study was to investigate (a) the differences in the movement skills and physical qualities between academy and senior rugby league players, and (b) the relationships between movement skills and physical qualities. Fifty-five male rugby league players (Senior, n=18; Under 19 n=23; Under 16, n=14) undertook a physical testing battery including anthropometric (stature & body mass), strength (isometric mid-thigh pull; IMTP) and power (countermovement jump; CMJ) qualities, alongside the athletic ability assessment (AAA; comprised of overhead squat, double lunge, single-leg Romanian deadlift, press-up and pull-up exercises). Univariate analysis of variance demonstrated significant (p<0.001) differences in body mass, IMTP peak force, CMJ mean power, and AAA movement skills between groups. The greatest observed differences for total movement skills, peak force and mean power were identified between Under 16 and 19 academy age groups. Spearman's rank correlation coefficients demonstrated a significant moderate (r=0.31) relationship between peak force and total movement skill. Furthermore, trivial (r=0.01) and small (r=0.13; r=0.22) relationships were observed between power qualities and total movement skill. These findings highlight that both movement skills and physical qualities differentiate between academy age groups, and provides comparative data for English senior and academy rugby league players

The Use of Microtechnology to Quantify the Peak Match Demands of the Football Codes: A Systematic Review.

BACKGROUND: Quantifying the peak match demands within the football codes is useful for the appropriate prescription of external training load. Wearable microtechnology devices can be used to identify the peak match demands, although various methodologies exist at present. OBJECTIVES: This systematic review aimed to identify the methodologies and microtechnology-derived variables used to determine the peak match demands, and to summarise current data on the peak match demands in the football codes. METHODS: A systematic search of electronic databases was performed from earliest record to May 2018; keywords relating to microtechnology, peak match demands and football codes were used. RESULTS: Twenty-seven studies met the eligibility criteria. Six football codes were reported: rugby league (n = 7), rugby union (n = 5), rugby sevens (n = 4), soccer (n = 6), Australian Football (n = 2) and Gaelic Football (n = 3). Three methodologies were identified: moving averages, segmental and 'ball in play'. The moving averages is the most commonly used (63%) and superior method, identifying higher peak demands than other methods. The most commonly used variables were relative distance covered (63%) and external load in specified speed zones (57%). CONCLUSION: This systematic review has identified moving averages to be the most appropriate method for identifying the peak match demands in the football codes. Practitioners and researchers should choose the most relevant duration-specific period and microtechnology-derived variable for their specific needs. The code specific peak match demands revealed can be used for the prescription of conditioning drills and training intensity

“It’s Important, but it’s Not Everything”: Practitioners’ Use, Analysis and Perceptions of Fitness Testing in Academy Rugby League

A plethora of research exists examining the physical qualities of rugby league players. However, no research has investigated practitioners’ insights into the use, analysis and perceptions of such fitness testing data that is vital for applying research into practice. Therefore, this study aimed to examine practitioners’ (coaches and strength & conditioning [S&C] coaches) perceptions and challenges of using fitness testing and the development of physical qualities. Twenty-four rugby league practitioners were purposefully sampled and completed a semi-structured interview. Interviews were transcribed and thematically analysed identifying five themes (it’s important, but it’s not everything; monitoring; evaluation and decision making; motivation; and other external challenges). The theme of “it’s important, but it’s not everything” emerged as a fundamental issue with regard fitness testing and the use of such data and that physical data alone does not inform coaches decisions. There appears conflicts between coaches and S&C coaches’ perceptions and use of fitness data, identifying complexities of supporting players in multidisciplinary teams. Collectively, the findings highlight the multifaceted nature of academy rugby league and suggest that practitioners should utilise fitness testing to inform player evaluations, positively influence training and assist with decision making. Moreover, practitioners should understand the combination of factors that influence fitness testing and work collaboratively to enhance talent development strategies

Overcoming the problem of multicollinearity in sports performance data: A novel application of partial least squares correlation analysis

Objectives Professional sporting organisations invest considerable resources collecting and analysing data in order to better understand the factors that influence performance. Recent advances in non-invasive technologies, such as global positioning systems (GPS), mean that large volumes of data are now readily available to coaches and sport scientists. However analysing such data can be challenging, particularly when sample sizes are small and data sets contain multiple highly correlated variables, as is often the case in a sporting context

A comparison of U18 school and academy rugby union match play

Introduction Understanding the physical demands of rugby union can assist coaches in the preparation of players. Match demands in senior players for domestic competitions (Cahill et al., 2013) and international games (Quarrie et al., 2013) are well established. However, despite adolescent rugby union players playing concurrently at various standards, there is no study that has attempted to compare them. Therefore, the purpose of this study was to compare the physical demands of U18 school vs. academy rugby union match play. Methods A full season of games from the academy (6 games) were analysed and matched by six games from the school standard. Each player wore a microtechnology unit which contained a global positioning system and tri-axial accelerometer in addition to a heart rate monitor. The players were spilt into forwards and backs with only players who participated in the entire game included in the subsequent analysis (Forwards; school [n=25], academy [n=21] and Backs; school [n=25], academy [n=24]). All data were analysed using magnitude based inferences. Institutional ethical approval was granted. Results Forwards: Total distance was almost certainly greater in academy forwards (5461 ± 360 vs. 4881 ± 388 m). Distance walking was unclear between the two groups, but jogging, striding and sprinting was almost certainly, very likely and likely greater in academy forwards in comparison to school forwards. PlayerLoadTM slow was possibly greater for academy forwards whilst heart rate mean and maximum was likely lower for academy forwards. Backs: Total distance was very likely greater in academy backs (5597 ± 383 vs. 5260 ± 441 m). Distance walking and sprinting was unclear. Distance jogging was almost certainly greater in the academy backs and striding was possibly greater. PlayerLoadTM slow was possibly greater in academy backs whilst heart rate mean and maximum was unclear between the two groups. Discussion This study shows that academy rugby union provides forwards and backs with a greater physical demand than school players of the same position. The increase in PlayerLoadTM slow suggests an increase in static exertions for academy players. Future research should look to explore the interaction between physical and technical performances between different standards of adolescent rugby union

Validity of Daily and Weekly Self-Reported Training Load Measures in Adolescent Athletes

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

The influence of resistance training experience on the between-day reliability of commonly used strength measures in male youth athletes

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

Between-Day Reliability and Sensitivity of Common Fatigue Measures in Rugby Players.

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% (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

Training Practices of Academy Rugby League and their alignment to Physical Qualities deemed important for Current and Future Performance

This study aimed to investigate rugby league coaches’ perceptions of physical qualities for current and future performance, while also establishing the training practices of Under-16 and Under-19 players. Twenty-four practitioners (rugby coach, strength and conditioning coach) working within nine Super League clubs completed a questionnaire. The questionnaire required practitioners to rank eleven physical qualities (i.e., strength, power, acceleration, maximum speed, aerobic endurance, change of direction, agility, height, body mass, lean mass and fat mass) by importance for current performance, future performance and career longevity according to playing position (forwards, backs, hookers & halves). Practitioners were asked to provide detail on the frequency and duration of each type of training session completed during a typical week throughout each phase of the season; pre-season, in-season (early), in-season (mid), and in-season (late). Typically, practitioners ranked strength, power and acceleration qualities highest, and endurance and anthropometric qualities lowest. The importance of physical qualities varied according to each playing level and position. Training practices of U16 and U19 players differed during each phase of the season, with U19 players undertaking greater training volumes than U16s players. Overall, the physical qualities coaches perceived as most important were not reflected within their training practices. Rugby league practitioners can use this information as a reference source to design long term athletic development plans, prescribe training and during player development procedures. Moreover, these data can inform and improve training practices while influencing the design of pre-season preparatory phases and in-season periods

We know they train, but what do they do? Implications for coaches working with adolescent rugby union players

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