Purpose: To quantify the demands of specific on- and off-court sessions, using internal and external training load metrics, in elite squash. Methods: A total of 15 professional squash players (11 males and 4 females) wore a 100-Hz triaxial accelerometer/global positioning system unit and heart rate monitor during on-court “Group,” “Feeding,” “Ghosting,” “Matchplay,” and off-court “Conditioning” sessions across a 2-week in-season microcycle. Comparisons of absolute training load (total values) and relative intensity (per minute) were made between sessions for internal (session rating of perceived exertion, differential rating of perceived exertion, TRIMP) and external (Playerload, very high–intensity movements [>3.5 m·s−2]) metrics. Results: The Group sessions were the longest (79  min), followed by Feeding (55  min), Matchplay (46  min), Conditioning (37  min), and Ghosting (35  min). Time >90% maximum heart rate was the lowest during Feeding (vs all others P < .05) but other sessions were not different (all P > .05). Relative Playerload during Conditioning (14.3 [3.3] arbitrary unit [a.u.] per min, all P < .05) was higher than Ghosting (7.5 [1.2] a.u./min) and Matchplay (6.9 [1.5] a.u./min), with no difference between these 2 sessions (P ≥ .999). Conditioning produced the highest Playerloads (519  a.u., all P < .001), with the highest on-court Playerloads from Group (450  a.u., all P < .001). The highest session rating of perceived exertion (all P < .001), Edward’s TRIMP (all P < .001), and TEAM-TRIMP (all P < .019) occurred during the Group sessions. Conclusions: Squash Matchplay does not systematically produce the highest training intensities and loads. Group sessions provide the highest training loads for many internal and external parameters and, therefore, play a central role within the training process. These findings facilitate planning or adjustment of intensity, volume, and frequency of sessions to achieve desirable physical outcomes.
Carl James, Aishwar Dhawan, Timothy Jones, and Olivier Girard
Jeffrey A. Rothschild, Matthieu Delcourt, Ed Maunder, and Daniel J. Plews
Purpose: To present a case report of an elite ultra-endurance cyclist, who was the winner and course record holder of 2 distinct races within a 4-month span: a 24-hour solo cycling race and a 2-man team multiday race (Race Across America). Methods: The athlete’s raw data (cycling power, heart rate [HR], speed, and distance) were obtained and analyzed for 2 ultra-endurance races and 11 weeks of training in between. Results: For the 24-hour race, the athlete completed 861.6 km (average speed 35.9 km·h−1, average power 210 W [2.8 W·kg−1], average HR 121 beats per minute) with a 37% decrease in power and a 22% decrease in HR throughout the race. During the 11 weeks between the 24-hour race and Race Across America, training intensity distribution (Zone 1/2/3) based on HR was 51%/39%/10%. For the Race Across America, total team time to complete the 4939-km race was 6 days, 10 hours, 39 minutes, at an average speed of 31.9 km·h−1. Of this, the athlete featured in this case study rode 75.2 hours, completing 2532 km (average speed 33.7 km·h−1, average power 203 W [2.7 W·kg−1]), with a 12% decrease in power throughout the race. Power during daytime segments was greater than nighttime (212  vs 189  W, P < .001,
Simon A. Feros, Damon A. Bednarski, and Peter J. Kremer
Purpose: To investigate the relationship between prescribed (preDI), perceived (perDI), and actual delivery intensity (actDI) in cricket pace bowling. Methods: Fourteen male club-standard pace bowlers (mean [SD]: age 24.2 [3.2] y) completed 1 bowling session comprising 45 deliveries. The first 15 deliveries composed the warm-up, where participants bowled 3 deliveries each at a preDI of 60%, 70%, 80%, 90%, and 95%. Bowlers reported the perDI after each delivery. The fastest delivery in the session was used as a reference to calculate relative ball-release speed for the warm-up deliveries, with this measure representing the actDI. Ball-release speed was captured by a radar gun. Results: For perDI, there was a very large relationship with preDI (rs = .90, P < .001). Similarly, for actDI, there was a large relationship with preDI (rs = .52, P < .001). Higher concordance was observed between perDI and preDI from 60% to 80% preDI. A plateau was observed for actDI from 70% to 95% preDI. Conclusions: The relationship between perDI and actDI was very large and large with respect to preDI, indicating that both variables can be used to monitor delivery intensity against the planned intensity and thus ensure healthy training adaptation. The optimal preDI that allowed pace bowlers to operate at submaximal perDI but still achieve close to maximal ball-release speeds was 70%. Bowling at the optimal preDI may significantly reduce the psychophysiological load per delivery in exchange for a trivial loss in ball-release speed.
Spencer S.H. Roberts, Emma Falkenberg, Alysha Stevens, Brad Aisbett, Michele Lastella, and Dominique Condo
Purpose: Australian football has elite men’s (Australian Football League; AFL) and women’s (Australian Football League Women’s; AFLW) competitions. This study compared AFL and AFLW players’ sleep and characterized players’ sleep in the context of current sleep recommendations. Methods: A total of 70 players (36 AFL, 34 AFLW) had their sleep monitored via actigraphy over a 10-day preseason period. Sleep outcomes and their intraindividual variation, were compared between AFL and AFLW players using linear mixed models. Proportions of players sleeping ≥7 and ≥8 hours per night, and achieving ≥85% sleep efficiency, were compared using chi-square analyses. Results: Compared with AFL players, AFLW players slept less (7.9 [0.5] vs 7.1 [0.6] h, P = .000), had lower sleep efficiency (89.5% [2.8%] vs 84.0% [4.4%], P = .000), and greater intraindividual variation in sleep efficiency (3.1% [0.9%] vs 5.1% [2.1%], P = .000). A total of 47% of AFLW versus 3% of AFL players averaged <7 hours sleep (χ 2 = 18.6, P = .000). A total of 88% of AFLW versus 50% of AFL players averaged <8 hours sleep (χ 2 = 11.9, P = .001). A total of 53% of AFLW versus 14% of AFL players averaged <85% sleep efficiency (χ 2 = 12.1, P = .001). Conclusions: AFLW players slept less and had poorer sleep quality than AFL players. Many AFLW players do not meet current sleep duration or sleep quality recommendations. Research should test strategies to improve sleep among Australian rules footballers, particularly among elite women.
Cédric Leduc, Julien Robineau, Jason C. Tee, Jeremy Cheradame, Ben Jones, Julien Piscione, and Mathieu Lacome
Purpose: To explore the effects of travel related to international rugby sevens competition on sleep patterns. Methods: A total of 17 international male rugby sevens players participated in this study. Actigraphic and subjective sleep assessments were performed daily during 2 separate Sevens World Series competition legs (Oceania and America). The duration of each competition leg was subdivided into key periods (pretour, precompetition, tournament 1, relocation, tournament 2, and posttour) lasting 2 to 7 nights. Linear mixed models in combination with magnitude-based decisions were used to assess (1) the difference between preseason and key periods and (2) the effect of travel direction (eastward or westward). Results: Shorter total sleep time (hours:minutes) was observed during tournament 2 (mean [SD], 06:16 [01:08]), relocation (06:09 [01:09]), and the pretour week (06:34 [01:24]) compared with the preseason (06:52 [01:00]). Worse sleep quality (arbitrary units) was observed during tournament 1 (6.1 [2.0]) and 2 (5.7 [1.2]), as well as during the relocation week (6.3 [1.5]) than during the preseason (6.5 [1.8]). When traveling eastward compared with westward, earlier fall-asleep time was observed during tournament 1 (ES − 0.57; 90% CI, −1.12 to −0.01), the relocation week (−0.70 [−1.11 to −0.28]), and the posttour (−0.57 [−0.95 to −0.18]). However, possibly trivial and unclear differences were observed during the precompetition week (0.15 [−0.15 to 0.45]) and tournament 2 (0.81 [−0.29 to 1.91]). Conclusion: The sleep patterns of elite rugby sevens players are robust to the effects of long-haul travel and jet lag. However, the staff should consider promoting sleep during the tournament and relocation week.
Leanne K. Elliott, Jonathan A. Weiss, and Meghann Lloyd
Early motor skill interventions have been shown to improve the motor skill proficiency of children with autism spectrum disorder; however, little is known about the secondary effects associated with these types of interventions (e.g., influence on behavior, social skills, family dynamics). The purpose of this qualitative study was to (a) investigate parents’ perceptions of the child-level benefits associated with a fundamental motor skill intervention for their 4-year-olds with autism spectrum disorder and (b) explore how child-level benefits influenced the family unit. Eight parents (N = 8) were interviewed (semistructured) about their experiences with the intervention for their child(ren); the study was grounded in phenomenology. Five main child-level benefits emerged, including improvements with (a) motor skills, (b) social skills, (c) listening skills, (d) turn-taking skills, and (e) transition skills. The child-level benefits then extended to family members in a number of ways (e.g., more positive sibling interactions). These findings highlight several important secondary effects that should be investigated in future research.
Wing-Chun V. Yeung, Chris Bishop, Anthony N. Turner, and Sean J. Maloney
Purpose: Previously, it has been shown that loaded warm-up (LWU) can improve change-of-direction speed (CODS) in professional badminton players. However, the effect of asymmetry on CODS in badminton players and the influence of LWU on asymmetry has not been examined. Methods: A total of 21 amateur badminton players (age 29.5 [8.4] y, playing experience 8.4 [4.2] y) completed 2 trials. In the first, they performed a control warm-up. In the second, they performed the same warm-up but with 3 exercises loaded with a weight vest (LWU). Following both warm-ups, players completed single-leg countermovement jump and badminton-specific CODS tests. Results: No significant differences between control warm-up and LWU were observed for CODS, single-leg countermovement jump, or single-leg countermovement jump asymmetry. However, small effect sizes suggested faster CODS (mean difference: −5%; d = −0.32) and lower asymmetries (mean difference: −3%; d = −0.39) following LWU. Five players (24%) experienced CODS improvements greater than the minimum detectable change while 2 (10%) responded negatively. Asymmetry was not correlated with CODS following control warm-up (ρ = .079; P = .733) but was negatively associated with CODS after LWU (ρ = −.491; P = .035). Conclusion: LWU may prove a strategy to trial on an individual basis, but generic recommendations should not be applied.
Thomas Mullen, Craig Twist, Matthew Daniels, Nicholas Dobbin, and Jamie Highton
Purpose: To identify the association between several contextual match factors, technical performance, and external movement demands on the subjective task load of elite rugby league players. Methods: Individual subjective task load, quantified using the National Aeronautics and Space Administration Task Load Index (NASA-TLX), was collected from 29 professional rugby league players from one club competing in the European Super League throughout the 2017 season. The sample consisted of 26 matches (441 individual data points). Linear mixed modeling revealed that various combinations of contextual factors, technical performance, and movement demands were associated with subjective task load. Results: Greater number of tackles (effect size correlation ± 90% confidence intervals; η 2 = .18 ± .11), errors (η 2 = .15 ± .08), decelerations (η 2 = .12 ± .08), increased sprint distance (η 2 = .13 ± .08), losing matches (η 2 = .36 ± .08), and increased perception of effort (η 2 = .27 ± .08) led to most likely–very likely increases in subjective total task load. The independent variables included in the final model for subjective mental demand (match outcome, time played, and number of accelerations) were unclear, excluding a likely small correlation with technical errors (η 2 = .10 ± .08). Conclusions: These data provide a greater understanding of the subjective task load and their association with several contextual factors, technical performance, and external movement demands during rugby league competition. Practitioners could use this detailed quantification of internal loads to inform recovery sessions and current training practices.
Ricardo Augusto Silva de Souza, André Guedes da Silva, Magda Ferreira de Souza, Liliana Kataryne Ferreira Souza, Hamilton Roschel, Sandro Fernandes da Silva, and Bryan Saunders
CrossFit® is a high-intensity functional training method consisting of daily workouts called “workouts of the day.” No nutritional recommendations exist for CrossFit® that are supported by scientific evidence regarding the energetic demands of this type of activity or dietary and supplement interventions. This systematic review performed in accordance with PRISMA guidelines aimed to identify studies that determined (a) the physiological and metabolic demands of CrossFit® and (b) the effects of nutritional strategies on CrossFit® performance to guide nutritional recommendations for optimal recovery, adaptations, and performance for CrossFit® athletes and direct future research in this emerging area. Three databases were searched for studies that investigated physiological responses to CrossFit® and dietary or supplementation interventions on CrossFit® performance. Various physiological measures revealed the intense nature of all CrossFit® workouts of the day, reflected in substantial muscle fatigue and damage. Dietary and supplementation studies provided an unclear insight into effective strategies to improve performance and enhance adaptations and recovery due to methodological shortcomings across studies. This systematic review showed that CrossFit® is a high-intensity sport with fairly homogenous anaerobic and aerobic characteristics, resulting in substantial metabolic stress, leading to metabolite accumulation (e.g., lactate and hydrogen ions) and increased markers of muscle damage and muscle fatigue. Limited interventional data exist on dietary and supplementation strategies to optimize CrossFit® performance, and most are moderate to very low quality with some critical methodological limitations, precluding solid conclusions on their efficacy. High-quality work is needed to confirm the ideal dietary and supplemental strategies for optimal performance and recovery for CrossFit® athletes and is an exciting avenue for further research.