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Summary: Elite athletes and coaches believe sleep is the most important recovery strategy and widely consider it critical to optimal performance. Despite this perceived importance, there are numerous circumstances that can reduce sleep quantity and quality in athletic populations. Because of the effects of sleep loss on various physical, neurophysiological, and cognitive parameters, such perturbations can have consequences for performance and recovery outcomes. Although peer-reviewed literature examining the interaction between sleep, performance, and recovery in athletes is increasing, understanding of these issues remains equivocal. Perhaps most pertinently, the effect of sleep on sport performance does not align with a one-size-fits-all approach and rather depends on numerous factors such as type of sport, scheduling, time of the season, and the intraindividual requirements for sleep. The relationship between brain plasticity and memory, which in turn can influence learning processes and long-term memory consolidation, suggests that sleep may play an important role in learning new skills and tactics for both elite and developing athletes. The aim of this special issue review was to analyze the evidence of sleep loss on sport performance and recovery, with a specific focus on elite athletes. An assessment of these sleep-compromising situations that elite athletes may face during a typical season and practical considerations for alleviating these issues is also provided to further the understanding for medical professionals, scientists, and applied sporting practitioners alike., Competing Interests: The authors have no funding or conflicts of interest to disclose., (Copyright © 2023 by the American Clinical Neurophysiology Society.)

Brown, GA, Veith, S, Sampson, JA, Whalan, M, and Fullagar, HHK. Influence of training schedules on objective measures of sleep in adolescent academy football players. J Strength Cond Res 34(9): 2515-2521, 2020-Football academy settings may pose risks to adolescent athletes achieving sufficient sleep because of the contextual challenges these players face (e.g., psychosocial pressure, changes in training, competition, and academic stress). Given the importance of sleep to overall health as well as physical athletic development and injury risk, this study aimed to investigate whether differences in training schedules (morning vs. evening training sessions) affected objective measures of sleep in adolescent academy football (soccer) players. Twelve academy players (mean age 14.18 ± 1.36 years) wore an ActiGraph accelerometer on nights before, and nights of, training days in 2 separate weeks where morning (09:00-11:00 hours) and evening (18:00-20:00 hours) training occurred. Objective sleep parameters and training load data were collected. Night-time sleep periods were categorized as sleep preceding morning training, preceding evening training, or after evening training. One-way univariate and multivariate analyses of variance for repeated measures were performed to determine the impact of the training schedule on sleep. Significance levels were set at p < 0.05. The total sleep time was below the recommended guidelines (<8 hours) across conditions. A large significant effect of the training schedule on time attempted to fall asleep (p = 0.004, effect size [ES] = 0.40) and time of sleep (p = 0.003, ES = 0.41) was present, with post-evening sessions resulting in the latest times. Overall, the players' sleep behavior was resilient to changes in training schedules. However, the low sleep durations (and potential risks to physical performance/injury) suggest that sleep education coupled with practical interventions are required in this cohort.

Purpose: To investigate the recovery time course of customized wellness markers (sleep, soreness, energy, and overall wellness) in response to match play in American Division I-A college football players., Methods: A retrospective research design was used. Wellness data were collected and analyzed for 2 American college football seasons. Perceptions of soreness, sleep, energy, and overall wellness were obtained for the day before each game (GD-1) and the days after each game (GD+2, GD+3, and GD+4). Standardized effect-size (ES) analyses ± 90% confidence intervals were used to interpret the magnitude of the mean differences between all time points for the start, middle, and finish of the season, using the following qualitative descriptors: 0-0.19 trivial, 0.2-0.59 small, 0.6-1.19 moderate, 1.2-1.99 large, <2.0 very large., Results: Overall wellness showed small ES reductions on GD+2 (d = 0.22 ± 0.09, likely [94.8%]), GD+3 (d = 0.37 ± 0.15, very likely), and GD+4 (d = 0.29 ± 0.12, very likely) compared with GD-1. There were small ES reductions for soreness between GD-1 and GD+2, GD+3, and GD +4 (d = 0.21 ± 0.09, likely, d = 0.29 ± 0.12, very likely, and 0.30 ± 0.12, very likely, respectively). Small ES reductions were also evident between GD-1 and GD+3 (d = 0.21 ± 0.09, likely) for sleep. Feelings of energy showed small ESs on GD+3 (d = 0.27 ± 0.11, very likely) and GD+4 (d = 0.22 ± 0.09, likely) compared with GD-1., Conclusion: All wellness markers were likely to very likely worse on GD+3 and GD+4 than on GD-1. These findings show that perceptual wellness takes longer than 4 d to return to pregame levels and thus should be considered when prescribing training and/or recovery.

Sleep is fundamental to normal physiological and cognitive function. Sleep promotion strategies have been used extensively in clinical settings, as a treatment for various ailments (ie, insomnia). However, sleep problems are prevalent outside these realms, with 56% of American, 31% of Western European and 29% of Japanese people suffering from sleep problems the previous year. The global public health concern over sleep has increased the demand for sleep promotion interventions, but the efficacy of these strategies is unclear in otherwise healthy and athletic populations. One possibility is due to the presentation and analysis of grouped data, despite sleep naturally being a highly variable and inherent trait. We argue the case for (1) presenting sleep data at the individual level and (2) individualising sleep promotion interventions., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)

While the effects of sleep loss on performance have previously been reviewed, the effects of disturbed sleep on recovery after exercise are less reported. Specifically, the interaction between sleep and physiological and psychological recovery in team-sport athletes is not well understood. Accordingly, the aim of the current review was to examine the current evidence on the potential role sleep may play in postexercise recovery, with a tailored focus on professional team-sport athletes. Recent studies show that team-sport athletes are at high risk of poor sleep during and after competition. Although limited published data are available, these athletes also appear particularly susceptible to reductions in both sleep quality and sleep duration after night competition and periods of heavy training. However, studies examining the relationship between sleep and recovery in such situations are lacking. Indeed, further observational sleep studies in team-sport athletes are required to confirm these concerns. Naps, sleep extension, and sleep-hygiene practices appear advantageous to performance; however, future proof-of-concept studies are now required to determine the efficacy of these interventions on postexercise recovery. Moreover, more research is required to understand how sleep interacts with numerous recovery responses in team-sport environments. This is pertinent given the regularity with which these teams encounter challenging scenarios during the course of a season. Therefore, this review examines the factors that compromise sleep during a season and after competition and discusses strategies that may help improve sleep in team-sport athletes.

Athletes are increasingly required to travel domestically and internationally, often resulting in travel fatigue and jet lag. Despite considerable agreement that travel fatigue and jet lag can be a real and impactful issue for athletes regarding performance and risk of illness and injury, evidence on optimal assessment and management is lacking. Therefore 26 researchers and/or clinicians with knowledge in travel fatigue, jet lag and sleep in the sports setting, formed an expert panel to formalise a review and consensus document. This manuscript includes definitions of terminology commonly used in the field of circadian physiology, outlines basic information on the human circadian system and how it is affected by time-givers, discusses the causes and consequences of travel fatigue and jet lag, and provides consensus on recommendations for managing travel fatigue and jet lag in athletes. The lack of evidence restricts the strength of recommendations that are possible but the consensus group identified the fundamental principles and interventions to consider for both the assessment and management of travel fatigue and jet lag. These are summarised in travel toolboxes including strategies for pre-flight, during flight and post-flight. The consensus group also outlined specific steps to advance theory and practice in these areas. [ABSTRACT FROM AUTHOR]

Purpose: The current study examined the sleep, travel, and recovery responses of elite footballers during and after long-haul international air travel, with a further description of these responses over the ensuing competitive tour (including 2 matches). Methods: In an observational design, 15 elite male football players undertook 18 h of predominantly westward international air travel from the United Kingdom to South America (-4-h time-zone shift) for a 10-d tour. Objective sleep parameters, external and internal training loads, subjective player match performance, technical match data, and perceptual jet-lag and recovery measures were collected. Results: Significant differences were evident between outbound travel and recovery night 1 (night of arrival; P < .001) for sleep duration. Sleep efficiency was also significantly reduced during outbound travel compared with recovery nights 1 (P = .001) and 2 (P = .004). Furthermore, both match nights (5 and 10), showed significantly less sleep than nonmatch nights 2 to 4 and 7 to 9 (all P < .001). No significant differences were evident between baseline and any time point for all perceptual measures of jet-lag and recovery (P > .05), although large effects were evident for jet-lag on d 2 (2 d after arrival). Conclusions: Sleep duration is truncated during long-haul international travel with a 4-h time-zone delay and after night matches in elite footballers. However, this lost sleep appeared to have a limited effect on perceptual recovery, which may be explained by a westbound flight and a relatively small change in time zones, in addition to the significant increase in sleep duration on the night of arrival after the long-haul flight. [ABSTRACT FROM AUTHOR]

Despite the perceived importance of sleep for elite footballers, descriptions of the duration and quality of sleep, especially following match play, are limited. Moreover, recovery responses following sleep loss remain unclear. Accordingly, the present study examined the subjective sleep and recovery responses of elite footballers across training days (TD) and both day and night matches (DM and NM). Sixteen top division European players from three clubs completed a subjective online questionnaire twice a day for 21 days during the season. Subjective recall of sleep variables (duration, onset latency, time of wake/sleep, wake episode duration), a range of perceptual variables related to recovery, mood, performance and internal training loads and non-exercise stressors were collected. Players reported significantly reduced sleep durations for NM compared to DM (−157 min) and TD (−181 min). In addition, sleep restfulness (SR; arbitrary scale 1 = very restful, 5 = not at all restful) and perceived recovery (PR; acute recovery and stress scale 0 = not recovered at all, 6 = fully recovered) were significantly poorer following NM than both TD (SR: +2.0, PR: −2.6), and DM (SR: +1.5; PR: −1.5). These results suggest that reduced sleep quantity and quality and reduced PR are mainly evident following NM in elite players. [ABSTRACT FROM PUBLISHER]

Firefighters are exposed to numerous stressors during wildfire suppression, including working in hot temperatures and sleep restricted conditions. Research has shown that when sleep restricted, individuals choose foods higher in carbohydrates, fat, and sugar, and have increased cravings for calorie dense foods. However, there is currently no research on the combined effect of heat and sleep restriction on snacking behaviour. Conducting secondary analyses from a larger study, the current study aimed to investigate the impact of heat and sleep restriction on snacking behaviour and food cravings. Sixty-six firefighters completed three days of simulated physically demanding firefighting work and were randomly allocated to either the control (n = 18, CON; 19 °C, 8 h sleep opportunity), sleep restricted (n = 16, SR; 19 °C, 4-h sleep opportunity), hot (n = 18, HOT; 33 °C, 8 h sleep opportunity), or hot and sleep restricted (n = 14 HOT + SR; 33 °C, 4-h sleep opportunity) condition. During rest periods firefighters were able to self-select sweet, savoury, or healthy snacks from a ration pack and were asked to rate their hunger, fullness, and cravings every two hours (eating block). Mixed model analyses revealed no difference in total energy intake between conditions, however there was a significant interaction between eating block and condition, with those in the CON, HOT, and HOT + SR condition consuming significantly more energy between 1230 and 1430 compared to the SR condition (p = 0.002). Sleep restriction and heat did not impact feelings of hunger and fullness across the day, and did not lead to greater cravings for snacks, with no differences between conditions. These findings suggest that under various simulated firefighting conditions, it is not the amount of food that differs but the timing of food intake, with those that are required to work in hot conditions while sleep restricted more likely to consume food between 1230 and 1430. This has potential implications for the time of day in which a greater amount of food should be available for firefighters. [ABSTRACT FROM AUTHOR]