Purpose: To assess the relationships between training load, sleep duration, and 3 daily well-being, recovery, and fatigue measures in youth athletes. Methods: Fifty-two youth athletes completed 3 maximal countermovement jumps (CMJs), a daily well-being questionnaire (DWB), the perceived recovery status scale (PRS), and provided details on their previous day’s training loads (training) and self-reported sleep duration (sleep) on 4 weekdays over a 7-week period. Partial correlations, linear mixed models, and magnitude-based inferences were used to assess the relationships between the predictor variables (training and sleep) and the dependent variables (CMJ, DWB, and PRS). Results: There was no relationship between CMJ and training (r = −.09; ±.06) or sleep (r = .01; ±.06). The DWB was correlated with sleep (r = .28; ±.05, small), but not training (r = −.05; ±.06). The PRS was correlated with training (r = −.23; ±.05, small), but not sleep (r = .12; ±.06). The DWB was sensitive to low sleep (d = −0.33; ±0.11) relative to moderate; PRS was sensitive to high (d = −0.36; ±0.11) and low (d = 0.29; ±0.17) training relative to moderate. Conclusions: The PRS is a simple tool to monitor the training response, but DWB may provide a greater understanding of the athlete’s overall well-being. The CMJ was not associated with the training or sleep response in this population.
Thomas Sawczuk, Ben Jones, Sean Scantlebury and Kevin Till
A.J. Rankin-Wright, Jason Tee, Tom Mitchell, Ian Cowburn, Kevin Till and Sergio Lara-Bercial
Amy Brightmore, John O’Hara, Kevin Till, Steve Cobley, Tate Hubka, Stacey Emmonds and Carlton Cooke
To evaluate the movement and physiological demands of Australasian National Rugby League (NRL) referees, officiating with a 2-referee (ie, lead and pocket) system, and to compare the demands of the lead and pocket referees.
Global positioning system devices (10 Hz) were used to obtain 86 data sets (lead, n = 41; pocket, n = 45) on 19 NRL referees. Total distance, relative distance covered, and heart rate per half and across match play were examined within and between referees using t tests. Distance, time, and number of movement “efforts” were examined in 6 velocity classifications (ie, standing <0.5, walking 0.51–2.0, jogging 2.01–4.0, running 4.01–5.5, high-speed running 5.51–7.0, and sprinting >7.0 m/s) using analysis of variance. Cohen d effect sizes are reported.
There were no significant differences between the lead and pocket referees for any movement or physiological variable. There was an overall significant (large, very large) effect for distance (% distance) and time (% time) (P < .001) between velocity classifications for both the lead and pocket referees. Both roles covered the largest distance and number of efforts at velocities of 0.51–2.0 m/s and 2.01–4.0 m/s, which were interspersed with efforts >5.51 m/s.
Findings highlight the intermittent nature of rugby league refereeing but show that there were no differences in the movement and physiological demands of the 2 refereeing roles. Findings are valuable for those responsible for the preparation, training, and conditioning of NRL referees and to ensure that training prepares for and simulates match demands.
Sergio Lara-Bercial, Lea Dohme, Emma Boocock, Andrew Abraham, Dave Piggott and Kevin Till
Emma Boocock, Sergio Lara-Bercial, Lea Dohme, Andrew Abraham, Dave Piggott and Kevin Till
Nick Dobbin, Richard Hunwicks, Ben Jones, Kevin Till, Jamie Highton and Craig Twist
Purpose: To examine the criterion and construct validity of an isometric midthigh-pull dynamometer to assess whole-body strength in professional rugby league players. Methods: Fifty-six male rugby league players (33 senior and 23 youth players) performed 4 isometric midthigh-pull efforts (ie, 2 on the dynamometer and 2 on the force platform) in a randomized and counterbalanced order. Results: Isometric peak force was underestimated (P < .05) using the dynamometer compared with the force platform (95% LoA: −213.5 ± 342.6 N). Linear regression showed that peak force derived from the dynamometer explained 85% (adjusted R 2 = .85, SEE = 173 N) of the variance in the dependent variable, with the following prediction equation derived: predicted peak force = [1.046 × dynamometer peak force] + 117.594. Cross-validation revealed a nonsignificant bias (P > .05) between the predicted and peak force from the force platform and an adjusted R 2 (79.6%) that represented shrinkage of 0.4% relative to the cross-validation model (80%). Peak force was greater for the senior than the youth professionals using the dynamometer (2261.2 ± 222 cf 1725.1 ± 298.0 N, respectively; P < .05). Conclusion: The isometric midthigh pull assessed using a dynamometer underestimates criterion peak force but is capable of distinguishing muscle-function characteristics between professional rugby league players of different standards.
Lea Dohme, Emma Boocock, Andrew Abraham, Dave Piggott, Kevin Till and Sergio Lara-Bercial
Gregory Roe, Joshua Darrall-Jones, Kevin Till, Padraic Phibbs, Dale Read, Jonathon Weakley and Ben Jones
To evaluate changes in performance of a 6-s cycle-ergometer test (CET) and countermovement jump (CMJ) during a 6-wk training block in professional rugby union players.
Twelve young professional rugby union players performed 2 CETs and CMJs on the 1st and 4th mornings of every week before the commencement of daily training during a 6-wk training block. Standardized changes in the highest score of 2 CET and CMJ efforts were assessed using linear mixed modeling and magnitude-based inferences.
After increases in training load during wk 3 to 5, moderate decreases in CMJ peak and mean power and small decreases in flight time were observed during wk 5 and 6 that were very likely to almost certainly greater than the smallest worthwhile change (SWC), suggesting neuromuscular fatigue. However, only small decreases, possibly greater than the SWC, 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.
The greater weekly changes in CMJ metrics in comparison with 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 to determine the efficacy of each test for monitoring neuromuscular function in rugby union players.
Gregory Roe, Joshua Darrall-Jones, Christopher Black, William Shaw, Kevin Till and Ben Jones
The purpose of this study was to investigate the validity of timing gates and 10-Hz global positioning systems (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 3 maximal 40-m sprints with 3 min rest between efforts 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 1 wore a single unit during each sprint.
When compared with the radar gun, mean biases for GPSOpen, GPSSprint, and timing gates were 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 a small TEE existed when GPSOpenfield was compared with GPSSprint.
Based on these findings, both 10-Hz GPS and timing gates provide valid measures of 40-m Vmax assessment 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.