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Shona L. Halson and Michele Lastella

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Cassandra Ferguson, Brad Aisbett, Michele Lastella, Spencer Roberts, and Dominique Condo

Objectives: To investigate the effect of evening whey protein supplementation, rich in tryptophan, on sleep in elite male Australian Rules Football players. Design: Double-blinded, counterbalanced, randomized, cross-over study. Methods: Sleep was assessed using wrist activity monitors and sleep diaries in 15 elite male Australian Football League players on two training and nontraining days following evening consumption of an isocaloric whey protein supplement or placebo in preseason. A 5-day preintervention period was implemented to determine habitual dietary intake and baseline sleep measures. These habitual data were used to inform the daily dietary intake and timing of ingestion of the evening whey protein supplement or placebo on the intervention days. The whey protein supplement or placebo was consumed 3 hr prior to habitual bedtime. Results: Separate one-way repeated-measures analyses of covariance revealed no differences between the whey protein supplement and the placebo on sleep duration, sleep onset latency, sleep efficiency, or wake after sleep onset on either training or nontraining days. Conclusions: Evening whey protein supplementation, rich in tryptophan, does not improve acute sleep duration or quality in elite male Australian Football League players. However, elite athletes may be able to ingest a high protein/energy intake close to bedtime without impairing sleep, which is important for athlete recovery. Future research should investigate the effect of evening protein intake, high in tryptophan, on sleep duration and quality, including sleep staging during periods of restricted sleep and in poor-sleeping athletes.

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Charli Sargent, Michele Lastella, Shona L. Halson, and Gregory D. Roach

Purpose: Anecdotal reports indicate that many elite athletes are dissatisfied with their sleep, but little is known about their actual sleep requirements. Therefore, the aim of this study was to compare the self-assessed sleep need of elite athletes with an objective measure of their habitual sleep duration. Methods: Participants were 175 elite athletes (n = 30 females), age 22.2 (3.8) years (mean [SD]) from 12 individual and team sports. The athletes answered the question “how many hours of sleep do you need to feel rested?” and they kept a self-report sleep diary and wore a wrist activity monitor for ∼12 nights during a normal phase of training. For each athlete, a sleep deficit index was calculated by subtracting their average sleep duration from their self-assessed sleep need. Results: The athletes needed 8.3 (0.9) hours of sleep to feel rested, their average sleep duration was 6.7 (0.8) hours, and they had a sleep deficit index of 96.0 (60.6) minutes. Only 3% of athletes obtained enough sleep to satisfy their self-assessed sleep need, and 71% of athletes fell short by an hour or more. Specifically, habitual sleep duration was shorter in athletes from individual sports than in athletes from team sports (F 1,173 = 13.1, P < .001; d = 0.6, medium), despite their similar sleep need (F 1,173 = 1.40, P = .24; d = 0.2, small). Conclusions: The majority of elite athletes obtain substantially less than their self-assessed sleep need. This is a critical finding, given that insufficient sleep may compromise an athlete’s capacity to train effectively and/or compete optimally.

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Michele Lastella, Gregory D. Roach, Grace E. Vincent, Aaron T. Scanlan, Shona L. Halson, and Charli Sargent

Purpose: To quantify the sleep/wake behaviors of adolescent, female basketball players and to examine the impact of daily training load on sleep/wake behaviors during a 14-day training camp. Methods: Elite, adolescent, female basketball players (N = 11) had their sleep/wake behaviors monitored using self-report sleep diaries and wrist-worn activity monitors during a 14-day training camp. Each day, players completed 1 to 5 training sessions (session duration: 114 [54] min). Training load was determined using the session rating of perceived exertion model in arbitrary units. Daily training loads were summated across sessions on each day and split into tertiles corresponding to low, moderate, and high training load categories, with rest days included as a separate category. Separate linear mixed models and effect size analyses were conducted to assess differences in sleep/wake behaviors among daily training load categories. Results: Sleep onset and offset times were delayed (P < .05) on rest days compared with training days. Time in bed and total sleep time were longer (P < .05) on rest days compared with training days. Players did not obtain the recommended 8 to 10 hours of sleep per night on training days. A moderate increase in sleep efficiency was evident during days with high training loads compared with low. Conclusions: Elite, adolescent, female basketball players did not consistently meet the sleep duration recommendations of 8 to 10 hours per night during a 14-day training camp. Rest days delayed sleep onset and offset times, resulting in longer sleep durations compared with training days. Sleep/wake behaviors were not impacted by variations in the training load administered to players.

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Aaron T. Scanlan, Robert Stanton, Charli Sargent, Cody O’Grady, Michele Lastella, and Jordan L. Fox

Purpose: To quantify and compare internal and external workloads in regular and overtime games and examine changes in relative workloads during overtime compared with other periods in overtime games in male basketball players. Methods: Starting players for a semiprofessional male basketball team were monitored during 2 overtime games and 2 regular games (nonovertime) with similar contextual factors. Internal (rating of perceived exertion and heart-rate variables) and external (PlayerLoad and inertial movement analysis variables) workloads were quantified across games. Separate linear mixed-models and effect-size analyses were used to quantify differences in variables between regular and overtime games and between game periods in overtime games. Results: Session rating-of-perceived-exertion workload (P = .002, effect size 2.36, very large), heart-rate workload (P = .12, 1.13, moderate), low-intensity change-of-direction events to the left (P = .19, 0.95, moderate), medium-intensity accelerations (P = .12, 1.01, moderate), and medium-intensity change-of-direction events to the left (P = .10, 1.06, moderate) were higher during overtime games than during regular games. Overtime periods also exhibited reductions in relative PlayerLoad (first quarter P = .03, −1.46, large), low-intensity accelerations (first quarter P = .01, −1.45, large; second quarter P = .15, −1.22, large), and medium-intensity accelerations (first quarter P = .09, −1.32, large) compared with earlier periods. Conclusions: Overtime games disproportionately elevate perceptual, physiological, and acceleration workloads compared with regular games in starting basketball players. Players also perform at lower external intensities during overtime periods than earlier quarters during basketball games.

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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.

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Aaron T. Scanlan, Neal Wen, Joshua H. Guy, Nathan Elsworthy, Michele Lastella, David B. Pyne, Daniele Conte, and Vincent J. Dalbo

Purpose: To examine correlations between peak force and impulse measures attained during the isometric midthigh pull (IMTP) and basketball-specific sprint and jump tests. Methods: Male, adolescent basketball players (N = 24) completed a battery of basketball-specific performance tests. Testing consisted of the IMTP (absolute and normalized peak force and impulse at 100 and 250 ms); 20-m sprint (time across 5, 10, and 20 m); countermovement jump (CMJ; absolute and normalized peak force and jump height); standing long jump (distance); and repeated lateral bound (distance). Correlation and regression analyses were conducted between IMTP measures and other attributes. Results: An almost perfect correlation was evident between absolute peak force attained during the IMTP and CMJ (r = .94, R 2 = 56%, P < .05). Moderate to very large correlations (P < .05) were observed between IMTP normalized peak force and 5-m sprint time (r = −.44, R 2 = 19%), 10-m sprint time (r = −.45, R 2 = 20%), absolute (r = .57, R 2 = 33%), normalized (r = .86, R 2 = 73%) CMJ peak force, and standing long-jump distance (r = .51, R 2 = 26%). Moderate to very large correlations were evident between impulse measures during the IMTP and 5-m sprint time (100 ms, r = −.40, R 2 = 16%, P > .05) and CMJ absolute peak force (100 ms, r = .73, R 2 = 54%; 250 ms, r = .68, R 2 = 47%; P < .05). Conclusions: The IMTP may be used to assess maximal and rapid force expression important across a range of basketball-specific movements.