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.
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Thomas Sawczuk, Ben Jones, Sean Scantlebury, and Kevin Till
Emma Boocock, Sergio Lara-Bercial, Lea Dohme, Andrew Abraham, Dave Piggott, and Kevin Till
Dave Piggott, Emma Boocock, Kevin Till, Lea Dohme, Andrew Abraham, and Sergio Lara-Bercial
Jonathon Weakley, Kevin Till, John Sampson, Harry Banyard, Cedric Leduc, Kyle Wilson, Greg Roe, and Ben Jones
Purpose: Feedback can enhance acute physical performance. However, its effects on physical adaptation have received little attention. Therefore, the purpose of this study was to determine the effect of feedback during a 4-wk training program on jump, sprint, and strength adaptations. Methods: A total of 28 semiprofessional male rugby union players were strength-matched into 2 groups (feedback and nonfeedback). During the 4-wk training program, the Feedback group received immediate, objective feedback on (1) mean concentric velocity during resistance training repetitions, (2) distance feedback for standing broad jumps, and (3) time for sprints. The Nonfeedback group was not provided additional information. Across the 4-wk mesocycle, subjects completed 3 strength and conditioning sessions per week. Countermovement jump, standing long jump, 10- and 20-m sprint, and 3-repetition-maximum barbell back squat and bench press were measured before and after the training intervention. Magnitude-based inferences assessed meaningful changes within and between groups. Results: The Feedback group showed small to moderate improvements in outcome measures, whereas the Nonfeedback group demonstrated trivial to small improvements. Improvements in countermovement-jump relative peak power (effect size ± 90% confidence limits: 0.34 ± 0.42), 10-m (0.20 ± 0.35) and 20-m sprints (0.40 ± 0.21), and 3-repetition-maximum back squats (0.23 ± 0.17) were possibly to likely greater for the Feedback condition than for Nonfeedback. Conclusions: Providing augmented feedback during strength and conditioning routines can enhance training adaptations compared with athletes who do not receive feedback. Consequently, practitioners should consider providing kinematic outputs, displacement, or sprint time at the completion of each repetition as athletes train.
Thomas Sawczuk, Ben Jones, Mitchell Welch, Clive Beggs, Sean Scantlebury, and Kevin Till
Purpose: To evaluate the relative importance and predictive ability of salivary immunoglobulin A (s-IgA) measures with regards to upper respiratory illness (URI) in youth athletes. Methods: Over a 38-week period, 22 youth athletes (age = 16.8 [0.5] y) provided daily symptoms of URI and 15 fortnightly passive drool saliva samples, from which s-IgA concentration and secretion rate were measured. Kernel-smoothed bootstrapping generated a balanced data set with simulated data points. The random forest algorithm was used to evaluate the relative importance (RI) and predictive ability of s-IgA concentration and secretion rate with regards to URI symptoms present on the day of saliva sampling (URIday), within 2 weeks of sampling (URI2wk), and within 4 weeks of sampling (URI4wk). Results: The percentage deviation from average healthy s-IgA concentration was the most important feature for URIday (median RI 1.74, interquartile range 1.41–2.07). The average healthy s-IgA secretion rate was the most important feature for URI4wk (median RI 0.94, interquartile range 0.79–1.13). No feature was clearly more important than any other when URI symptoms were identified within 2 weeks of sampling. The values for median area under the curve were 0.68, 0.63, and 0.65 for URIday, URI2wk, and URI4wk, respectively. Conclusions: The RI values suggest that the percentage deviation from average healthy s-IgA concentration may be used to evaluate the short-term risk of URI, while the average healthy s-IgA secretion rate may be used to evaluate the long-term risk. However, the results show that neither s-IgA concentration nor secretion rate can be used to accurately predict URI onset within a 4-week window in youth athletes.
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.
A.J. Rankin-Wright, Jason Tee, Tom Mitchell, Ian Cowburn, Kevin Till, and Sergio Lara-Bercial
Tom O. Mitchell, Ian H.J. Cowburn, David Piggott, Martin A. Littlewood, Tony Cook, and Kevin Till
The possession of certain psychosocial characteristics can offer performance advantages in a range of domains. However, integrating a program to support the development of psychosocial characteristics is a lengthy process and involves context-specific knowledge and effective working relationships with stakeholders. The aim of this article is to present a real-life example of the design, delivery, and implementation of a theoretically informed psychosocial development program for players within an academy soccer setting to include player workshops, coach delivery, and ways to influence the environment. This multifaceted approach included formal and informal meetings, observations, coach education, and social media groups. Initial reflections suggested workshops are an effective method to “teach” some of the aspects within the program. Integrating coaches throughout design and implementation is recommended. Key stakeholders should consider investing time in education for coaches to develop strategies to foster psychosocial development in their players. Limitations and future recommendations are discussed.
Sam McCormack, Ben Jones, Sean Scantlebury, Neil Collins, Cameron Owen, and Kevin Till
Purpose: To compare the physical qualities between academy and international youth rugby league (RL) players using principal component analysis. Methods: Six hundred fifty-four males (age = 16.7 [1.4] y; height = 178.4 [13.3] cm; body mass = 82.2 [14.5] kg) from 11 English RL academies participated in this study. Participants completed anthropometric, power (countermovement jump), strength (isometric midthigh pull; IMTP), speed (10 and 40 m speed), and aerobic endurance (prone Yo-Yo IR1) assessments. Principal component analysis was conducted on all physical quality measures. A 1-way analysis of variance with effect sizes was performed on 2 principal components (PCs) to identify differences between academy and international backs, forwards, and pivots at under 16 and 18 age groups. Results : Physical quality measures were reduced to 2 PCs explaining 69.4% of variance. The first PC (35.3%) was influenced by maximum and 10-m momentum, absolute IMTP, and body mass. Ten and forty-meter speed, body mass and fat, prone Yo-Yo, IMTP relative, maximum speed, and countermovement jump contributed to PC2 (34.1%). Significant differences (P < .05, effect size = −1.83) were identified between U18 academy and international backs within PC1. Conclusion: Running momentum, absolute IMTP, and body mass contributed to PC1, while numerous qualities influenced PC2. The physical qualities of academy and international youth RL players are similar, excluding U18 backs. Principal component analysis can reduce the dimensionality of a data set and help identify overall differences between playing levels. Findings suggest that RL practitioners should measure multiple physical qualities when assessing physical performance.
Tom O. Mitchell, Adam Gledhill, Ross Shand, Martin A. Littlewood, Lewis Charnock, and Kevin Till
There is an increasing awareness of the importance of the environment in academy players’ development, yet limited research has investigated players’ perceptions of their talent development environments (TDEs). This study focused on academy soccer players’ perceptions of their TDE and compared perceptions across the English soccer academy categorization (CAT) system. A total of 136 U.K.-based male soccer players (M age = 17.7, SD = 1.03 years) representing all four categories (1 = highest to 4 = lowest) of soccer academies aligned to professional soccer clubs completed the TDE Questionnaire-5 (TDEQ-5). The players within the CAT1 academies had significantly more positive perceptions of their support network (p = .01) and holistic quality preparation (p = .03) than their CAT3 counterparts. Across CAT2–CAT3, holistic quality preparation was the least positively perceived subscale within the TDEQ-5, suggesting the need for additional coach education in this area. Soccer academies should consider how they ensure that all areas of their service are associated with optimal TDEs by offering a well-communicated and holistic development experience for their players to enhance effective personal and player development. The findings may have implications for player experience and associated progression rates of lower categorized soccer academies.