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
Nessan Costello, Jim McKenna, Louise Sutton, Kevin Deighton and Ben Jones
Designing and implementing successful dietary intervention is integral to the role of sport nutrition professionals as they attempt to positively change the dietary behavior of athletes. High-performance sport is a time-pressured environment where immediate results can often supersede pursuit of the most effective evidence-based practice. However, efficacious dietary intervention necessitates comprehensive, systematic, and theoretical behavioral design and implementation, if the habitual dietary behaviors of athletes are to be positively changed. Therefore, this case study demonstrates how the Behaviour Change Wheel was used to design and implement an effective nutritional intervention within a professional rugby league. The eight-step intervention targeted athlete consumption of a high-quality dietary intake of 25.1 MJ each day to achieve an overall body mass increase of 5 kg across a 12-week intervention period. The capability, opportunity, motivation, and behavior model and affordability, practicability, effectiveness/cost-effectiveness, acceptability, safety, and equity criteria were used to identify population-specific intervention functions, policy categories, behavior change techniques, and modes of intervention delivery. The resulting intervention was successful, increasing the average daily energy intake of the athlete to 24.5 MJ, which corresponded in a 6.2 kg body mass gain. Despite consuming 0.6 MJ less per day than targeted, secondary outcome measures of diet quality, strength, body composition, and immune function all substantially improved, supporting sufficient energy intake and the overall efficacy of a behavioral approach. Ultimately, the Behaviour Change Wheel provides sport nutrition professionals with an effective and practical stepwise method to design and implement effective nutritional interventions for use within high-performance sport.
Gregory Roe, Joshua Darrall-Jones, Kevin Till, Padraic Phibbs, Dale Read, Jonathon Weakley and Ben Jones
This study established the between-days reliability and sensitivity of a countermovement jump (CMJ), plyometric push-up, well-being questionnaire, and whole-blood creatine kinase concentration ([CK]) in elite male youth rugby union players. The study also established the between-days reliability of 1, 2, or 3 CMJs and plyometric-push-up attempts. Twenty-five players completed tests on 2 occasions separated by 5 d (of rest). Between-days typical error, coefficient of variation (CV), and smallest worthwhile change (SWC) were calculated for the well-being 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 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 < SWC). The well-being questionnaire and [CK] demonstrated between-days CVs >5% (7.1% and 26.1%, respectively) and poor sensitivity (CV > SWC). 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.
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.
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.
Joshua Darrall-Jones, Gregory Roe, Shane Carney, Ryan Clayton, Padraic Phibbs, Dale Read, Jonathon Weakley, Kevin Till and Ben Jones
To evaluate the difference in performance of the 30-15 Intermittent Fitness Test (30–15IFT) across 4 squads in a professional rugby union club in the UK and consider body mass in the interpretation of the end velocity of the 30-15IFT (VIFT).
One hundred fourteen rugby union players completed the 30-15IFT midseason.
VIFT demonstrated small and possibly lower (ES = –0.33; 4/29/67) values in the under 16s compared with 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 that does not increase from under-16 to senior level. However, the associated increases in body mass with increased playing level suggest that the ability to perform high-intensity running increases with age, although not translating 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, but it needs to be monitored during periods where increases in body mass are evident.
Deborah R. Smith, Ben Jones, Louise Sutton, Roderick F.G.J. King and Lauren C. Duckworth
Good nutrition is essential for the physical development of adolescent athletes, however data on dietary intakes of adolescent rugby players are lacking. This study quantified and evaluated dietary intake in 87 elite male English academy rugby league (RL) and rugby union (RU) players by age (under 16 (U16) and under 19 (U19) years old) and code (RL and RU). Relationships of intakes with body mass and composition (sum of 8 skinfolds) were also investigated. Using 4-day diet and physical activity diaries, dietary intake was compared with adolescent sports nutrition recommendations and the UK national food guide. Dietary intake did not differ by code, whereas U19s consumed greater energy (3366 ± 658 vs. 2995 ± 774 kcal·day-1), protein (207 ± 49 vs. 150 ± 53 g·day-1) and fluid (4221 ± 1323 vs. 3137 ± 1015 ml·day-1) than U16s. U19s consumed a better quality diet than U16s (greater intakes of fruit and vegetables; 4.4 ± 1.9 vs. 2.8 ± 1.5 servings·day-1; nondairy proteins; 3.9 ± 1.1 vs. 2.9 ± 1.1 servings·day-1) and less fats and sugars (2.0 ± 1. vs. 3.6 ± 2.1 servings·day-1). Protein intake vs. body mass was moderate (r = .46, p < .001), and other relationships were weak. The findings of this study suggest adolescent rugby players consume adequate dietary intakes in relation to current guidelines for energy, macronutrient and fluid intake. Players should improve the quality of their diet by replacing intakes from the fats and sugars food group with healthier choices, while maintaining current energy, and macronutrient intakes.
Kevin Till, Ben Jones, John O’Hara, Matthew Barlow, Amy Brightmore, Matthew Lees and Karen Hind
To compare the body size and 3-compartment body composition between academy and senior professional rugby league players using dual-energy X-ray absorptiometry (DXA).
Academy (age 18.1 ± 1.1 y, n = 34) and senior (age 26.2 ± 4.6 y, n = 63) rugby league players received 1 total-body DXA scan. Height, body mass, and body-fat percentage alongside total and regional fat mass, lean mass, and bone mineral content (BMC) were compared. Independent t tests with Cohen d effect sizes and multivariate analysis of covariance (MANCOVA), controlling for height and body mass, with partial eta-squared (η2) effect sizes, were used to compare total and regional body composition.
Senior players were taller (183.2 ± 5.8 vs 179.2 ± 5.7 cm, P = .001, d = 0.70) and heavier (96.5 ± 9.3 vs 86.5 ± 9.0 kg, P < .001, d = 1.09) with lower body-fat percentage (16.3 ± 3.7 vs 18.0 ± 3.7%, P = .032, d = 0.46) than academy players. MANCOVA identified significant overall main effects for total and regional body composition between academy and senior players. Senior players had lower total fat mass (P < .001, η 2 = 0.15), greater total lean mass (P < .001, η 2 = 0.14), and greater total BMC (P = .001, η 2 = 0.12) than academy players. For regional sites, academy players had significantly greater fat mass at the legs (P < .001, η 2 = 0.29) than senior players.
The lower age, height, body mass, and BMC of academy players suggest that these players are still developing musculoskeletal characteristics. Gradual increases in lean mass and BMC while controlling fat mass is an important consideration for practitioners working with academy rugby league players, especially in the lower body.
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.
Jonathon Weakley, Kevin Till, John Sampson, Harry Banyard, Cedric Leduc, Kyle Wilson, Greg Roe and Ben Jones
Feedback can enhance acute physical performance. However, the effects of feedback on physical adaptation has received little attention. Therefore, the purpose of this study was to determine the effect of feedback during a four-week training programme on jump, sprint and strength adaptations.
Twenty-eight semi-professional male rugby union players were strength-matched into two groups (feedback and non-feedback). During the four-week training programme, the Feedback group received immediate, objective feedback on a) mean concentric velocity during resistance training repetitions, b) distance feedback for standing broad jumps, and c) time for sprints. The Non-Feedback group were not provided additional information. Across the four-week mesocycle, subjects completed three strength and conditioning sessions per week. Countermovement jump (CMJ), standing long jump, 10 and 20m sprint, and three repetition maximum (3RM) barbell back squat and bench press were measured pre- and post- the training intervention. Magnitude-based inferences assessed meaningful changes within- and between-groups.
The Feedback group showed small to moderate improvements in outcome measures, while the Non-Feedback group demonstrated trivial to small improvements. Improvements in CMJ relative peak power (effect size ±90% confidence limits: 0.34±0.42), 10m (0.20±0.35) and 20m sprint (0.40±0.21), and 3RM back squat (0.23±0.17) were possibly to likely greater for the Feedback condition compared to Non-Feedback.
Results indicate that providing augmented feedback during strength and conditioning routines can enhance training adaptations when compared to 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.