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Open access

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 (F1,173 = 13.1, P < .001; d = 0.6, medium), despite their similar sleep need (F1,173 = 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.

Open access

Charli Sargent, Brent Rogalski, Ashley Montero, and Gregory D. Roach

Purpose: Most athletes sleep poorly around competition. The aim of this study was to examine sleep before/after games during an entire season in elite Australian Rules footballers (N = 37) from the same team. Methods: Sleep was monitored using activity monitors for 4 consecutive nights (beginning 2 nights before games) during 19 rounds of a season. Differences in sleep on the nights before/after games, and differences in sleep before/after games as a function of game time (day vs evening), location (local vs interstate), and outcome (win vs loss), were examined using linear mixed effects models. Results: Players fell asleep earlier (+1.9 h; P < .001), and woke up later (+1 h; P < .001) on the night before games compared with the night of games. Players obtained less sleep on the night of games than on the night before games (5.2 h vs 7.7 h; P < .001), and this reduction was exacerbated when games were played in the evening—after evening games, players obtained approximately 40 minutes less sleep than after day games (P < .001). Sleep duration on the nights before and after games was not affected by game location or game outcome, but players had later sleep onset (P < .001) and offset times (P < .001) on most nights when sleeping away from home. Conclusions: Elite footballers obtain good sleep on the night before games but obtain approximately 30% less sleep on the night of games. Given the role of sleep in recovery, it will be important to determine whether a reduction in sleep duration of this magnitude impairs recovery on the days following games.

Restricted access

Georgia Romyn, Gregory D. Roach, Michele Lastella, Dean J. Miller, Nathan G. Versey, and Charli Sargent

Purpose: This study examined the impact of sleep inertia on physical, cognitive, and subjective performance immediately after a 1- or 2-hour afternoon nap opportunity. Methods: Twelve well-trained male athletes completed 3 conditions in a randomized, counterbalanced order—9 hours in bed overnight without a nap opportunity the next day (9 + 0), 8 hours in bed overnight with a 1-hour nap opportunity the next day (8 + 1), and 7 hours in bed overnight with a 2-hour nap opportunity the next day (7 + 2). Nap opportunities ended at 4:00 PM. Sleep was assessed using polysomnography. Following each condition, participants completed four 30-minute test batteries beginning at 4:15, 4:45, 5:15, and 5:45 PM. Test batteries included a warm-up, self-ratings of readiness to perform, motivation to perform and expected performance, two 10-m sprints, 2 agility tests, a 90-second response-time task, and 5 minutes of seated rest. Results: Total sleep time was not different between conditions (P = .920). There was an effect of condition on readiness (P < .001), motivation (P = .001), and expected performance (P = .004)—all 3 were lower in the 8 + 1 and 7 + 2 conditions compared with the 9 + 0 condition. There was no effect of condition on response time (P = .958), sprint time (P = .204), or agility (P = .240), but a large effect size was observed for agility. Conclusions: After waking from a nap opportunity, agility may be reduced, and athletes may feel sleepy and not ready or motivated to perform. Athletes should schedule sufficient time (∼1 h) after waking from a nap opportunity to avoid the effects of sleep inertia on performance.

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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.

Restricted access

Charli Sargent, Shona L. Halson, David T. Martin, and Gregory D. Roach

Purpose: Professional road cycling races are physiologically demanding, involving successive days of racing over 1 to 3 weeks of competition. Anecdotal evidence indicates that cyclists’ sleep duration either increases or deteriorates during these competitions. However, sleep duration in professional cyclists during stage races has not been assessed. This study examined the amount/quality of sleep obtained by 14 professional cyclists competing in the Australian Tour Down Under. Methods: Sleep was assessed using wrist activity monitors and self-report sleep diaries on the night prior to start of the race and on each night during the race. The impact of each day of the race on sleep onset, sleep offset, time in bed, sleep duration, and wake duration was assessed using separate linear mixed effects models. Results: During the race, cyclists obtained an average of 6.8 (0.9) hours of sleep between 23:30 and 07:27 hours and spent 13.9% (4.7%) of time in bed awake. Minor differences in sleep onset (P = .023) and offset times (P ≤.001) were observed during the week of racing, but these did not affect the amount of sleep obtained by cyclists. Interestingly, the 3 best finishers in the general classification obtained more sleep than the 3 worst finishers (7.2 [0.3] vs 6.7 [0.3] h; P = .049). Conclusions: Contrary to anecdotal reports, the amount of sleep obtained by cyclists did not change over the course of the 1-week race and was just below the recommended target of 7 to 9 hours for adults.