Do players and staff sleep more during the pre- or competitive season of elite rugby league?

Sleep patterns before and after competition: A real-world examination of elite athletes

Good sleep before and after competitions is crucial to cognitive, physiological performance and recovery. Yet, elite athletes face a unique set of challenges when acquiring good sleep before and after competitions, and indeed commonly report sleep problems when it matters most. This study examined the sleep of elite athletes before and after competition compared to before and after free days. A total of 1808 unique nights of actigraphy (n = 1495) and sleep diary (n = 1335) data from elite Australian Football League and National Rugby League male athletes (N = 85, M-age = 24.4 ± 3.6) were collected and analysed using multi-level mixed models. On nights before competitions, athletes advanced sleep timings (p < .001, d = 0.63) and increased total sleep time (p < .001, d = 0.65) compared to nights before free days. On nights after competitions, athletes delayed sleep timings (p < .001, d = 1.64), reduced total sleep time (p < .001, d = 1.28), and had significantly worse quality sleep (p < .001, d = 0.71) compared to nights after free days. Sleep was especially worse following night competitions. While elite athletes and organisations may be implementing effective sleep strategies to optimise sleep the night before competitions, strategies to improve sleep after competitions may be lacking. We discuss potential factors contributing to this asymmetry and propose areas for research moving forward.

The Sleep Parameters of Paralympic Athletes: Characteristics and Assessment Instruments

CONTEXT

Sleep serves many important functions for athletes, particularly in the processes of learning, memory, recovery, and cognition.

OBJECTIVES

Define the sleep parameters of Paralympic athletes and identify the instruments used to assess and monitor sleep Paralympic athletes.

EVIDENCE ACQUISITION

This systematic review was carried out based on the PRISMA guidelines. The survey was conducted in April 2020, the searches were carried out again in September 2021 to check whether there were new scientific publications in the area of sleep and Paralympic sport, searches were performed in the following databases: PubMed, Web of Science, Scopus, SPORTDiscus, Virtual Health Library (BIREME), and SciELO. This systematic review has included studies that investigated at least one of the following sleep parameters: total sleep time, sleep latency, sleep efficiency, number of awakenings, quality of sleep, daytime sleepiness, and chronotype; the participants were comprised of athletes with disabilities. Studies published at any time in English, Portuguese, and Spanish, were included.

EVIDENCE SYNTHESIS

Data extraction and study selection were performed by 2 researchers independently, and a third author was consulted as necessary. The search returned a total of 407 studies. Following the screening based on exclusion and inclusion criteria, a total of 13 studies were considered. Paralympic athletes have a low amount (7.06 h) of sleep with poor quality and sleep latency (28.05 min), and 57.2% have daytime sleepiness, with the majority belonging to the indifferent chronotype (53, 5%). Moreover, 11 studies assess sleep using subjective instruments (questionnaires), and 2 studies used an objective instrument (actigraphy).

CONCLUSIONS

Sleep disorders are common among Paralympic athletes, poor sleep quality and quantity, and high rates of daytime sleepiness. Subjective methods are most commonly used to assess sleep.

Case Report: Effect of low energy availability and training load on sleep in a male combat sport athlete

Purpose

The aim of this case report was to describe the sleep responses in a male combat sport athlete, who was engaging in both chronic (CWL) and acute (AWL) weight loss practices in order to reduce body mass for a national competition.

Methods

During the first seven weeks of training (Phases 1 and 2), the athlete adhered to a daily energy intake (EI) equating to their resting metabolic rate (1700 kcal·day^-1) followed by a reduction in EI (915-300 kcal·day^-1) in the 5 days before weighing in (Phase 3). Nocturnal sleep was monitored throughout the 8-week training period using wristwatch actigraphy and frequent measurements of body mass/composition, daily exercise energy expenditure and training load (TL) were taken.

Results

The athlete was in a state of low energy availability (LEA) during the entire training period. There was a very large decrease in LEA status during phase 3 compared with phases 1 and 2 (3 vs. 20 kcal·kgFFM·day^-1) and there was a small decrease in TL during phase 3 compared with phase 2 (410 vs. 523 AU). The athlete's sleep efficiency increased throughout the training period, but total sleep time displayed a small to moderate decrease in phase 3 compared with phases 1 and 2 (386 vs. 429 and 430 min). However, correlational analysis demonstrated trivial to small, non-significant relationships between sleep characteristics and the athlete's LEA status and TL.

Conclusion

These findings suggest that CWL and AWL practices that cause fluctuations in LEA and TL may be implemented without compromising the sleep of combat sport athletes.

An Individualized Intervention Increases Sleep Duration in Professional Athletes

ABSTRACT

Sargent, C, Lastella, M, Schwerdt, S, and Roach, GD. An individualized intervention increases sleep duration in professional athletes. J Strength Cond Res 35(12): 3407-3413, 2021-Athletes typically obtain less sleep than is generally recommended for healthy adults. The aim of this study was to determine whether individualized feedback could increase sleep duration in professional cricket players in the 3 weeks before the start of the domestic season. Players were randomly assigned to a control group (i.e., no individual feedback; n = 8) or an intervention group (i.e., individual feedback about bedtime, wake time, and sleep duration; n = 7). Night-time sleep and daytime naps were monitored using wrist activity monitors in conjunction with self-report sleep diaries for 1 week before, and 1 week after, the feedback intervention. Cumulative sleep duration was calculated as the sum of the sleep duration for a night-time sleep episode and any naps that occurred on the following day. Differences in cumulative sleep duration before and after the intervention were examined using a mixed-effects analysis of variance. There was an interaction between group and week for cumulative sleep duration (p = 0.039; η2 = 0.6; large). The average cumulative sleep duration was longer (+36 minutes) in the intervention group in week 2 compared with week 1. Individualized feedback can be used to increase sleep duration in professional cricket players. In future, it will be important to determine whether improvements in sleep duration can be maintained throughout the season.

Deconstructing athletes' sleep: A systematic review of the influence of age, sex, athletic expertise, sport type, and season on sleep characteristics

PURPOSE

This systematic review aimed to describe objective sleep parameters for athletes under different conditions and address potential sleep issues in this specific population.

METHODS

PubMed and Scopus were searched from inception to April 2019. Included studies measured sleep only via objective evaluation tools such as polysomnography or actigraphy. The modified version of the Newcastle-Ottawa Scale was used for the quality assessment of the studies.

RESULTS

Eighty-one studies were included, of which 56 were classified as medium quality, 5 studies as low quality, and 20 studies as high quality. A total of 1830 athletes were monitored over 18,958 nights. Average values for sleep-related parameters were calculated for all athletes according to sex, age, athletic expertise level, training season, and type of sport. Athletes slept on average 7.2 ± 1.1 h/night (mean ± SD), with 86.3% ± 6.8% sleep efficiency (SE). In all datasets, the athletes' mean total sleep time was <8 h. SE was low for young athletes (80.3% ± 8.8%). Reduced SE was attributed to high wake after sleep onset rather than sleep onset latency. During heavy training periods, sleep duration and SE were on average 36 min and 0.8% less compared to pre-season and 42 min and 3.0% less compared to in-season training periods, respectively.

CONCLUSION

Athletes' sleep duration was found to be short with low SE, in comparison to the general consensus for non-athlete healthy adults. Notable sleep issues were revealed in young athletes. Sleep quality and architecture tend to change across different training periods.

Complete sleep evaluation of top professional cross-country mountain bikers athletes

BACKGROUND

Despite growing interest in athletes' sleep, few studies have focused on professional athletes, especially in individual sports. Moreover, limited investigations included female athletes. This study aims to evaluate sleep chronotype, as well as objective and subjective sleep characteristics in male and female professional cross-country mountain bikers.

METHODS

Thirteen athletes (7 males and 6 females) of the French national team took part in this study. The Chronotype was assessed by the Horne and Östberg Morningness-Eveningness Questionnaire and sleep by actigraphy for one month, by ambulatory polysomnography (PSG) for one night and by the Pittsburgh Sleep Quality Index.

RESULTS

Most athletes (77 %) are classified as moderately morning type and a minority of athletes (23 %) are intermediate type. Athletes sleep on average 8 hours per night and during the night recorded by PSG, N3 and REM sleep stages represented 21.2 ± 3.4 % and 20.9 ± 3.1 % of the total sleep time, respectively. These good sleep parameters were confirmed by subjective data with 77 % good sleepers. Except the poorer subjective sleep quality in female athletes (5.7 ± 1.6) compared to male athletes (2.6 ± 1.7, p < 0.05), no significant sex difference was found for all characteristics evaluated.

CONCLUSIONS

The professional status of these athletes and the organization of mountain bike calendar may explain their good sleep characteristics.

To Nap or Not to Nap? A Systematic Review Evaluating Napping Behavior in Athletes and the Impact on Various Measures of Athletic Performance

PURPOSE

The objective of this systematic review was to 1) determine how studies evaluated napping behavior in athletes (frequency, duration, timing and measurement); 2) explore how napping impacted physical performance, cognitive performance, perceptual measures (eg, fatigue, muscle soreness, sleepiness and alertness), psychological state and night-time sleep in athletes.

METHODS

Five bibliographic databases were searched from database inception to 11 August 2020. Observational and experimental studies comprising able-bodied athletes (mean age ≥12 years), published in English, in peer-reviewed journal papers were included. The Downs and Black Quality Assessment Checklist was used for quality appraisal.

RESULTS

Thirty-seven studies were identified of moderate quality. Most studies did not include consistent information regarding nap frequency, duration, and timing. Napping may be beneficial for a range of outcomes that benefit athletes (eg, physical and cognitive performance, perceptual measures, psychological state and night-time sleep). In addition, napping presents athletes with the opportunity to supplement their night-time sleep without compromising sleep quality.

CONCLUSION

Athletes may consider napping between 20 to 90 min in duration and between 13:00 and 16:00 hours. Finally, athletes should allow 30 min to reduce sleep inertia prior to training or competition to obtain better performance outcomes. Future studies should include comprehensive recordings of nap duration and quality, and consider using sleep over a 24 hour period (daytime naps and night-time sleep period), specifically using objective methods of sleep assessment (eg, polysomnography/actigraphy).

Sleep of Wheelchair Rugby Athletes: Training, Rest and Competition

The aim of this study was to evaluate the sleep-wake cycle of wheelchair rugby athletes during the pre-season compared to in-season. Wheelchair Rugby athletes wore an actigraph monitor during two respective 10-day periods: 1) pre-season and 2) in-season, each of which comprised three training days, three rest days, and four competition days, respectively. In addition, the players completed questionnaires regarding sleepiness, subjective quality of sleep, and chronotype, as well as the use of the sleep diary along with the actigraph measurements (20 days). The wheelchair rugby athletes had poor subjective sleep quality in both stages observed by sleep efficiency below 85% (ES 0.31) and high score in the Pittsburgh questionnaire (effect size-ES 0.55), the actigraphy results presented an increase of sleep latency (ES 0.47), and wake after sleep onset (ES 0.42). When comparing the athlete’s routine, the competition days, demonstrated a reduction in the total time of sleep and the sleep efficiency, in addition to an increase in wakefulness after sleep onset when compared with the training and rest periods. As a result, the wheelchair rugby players did not describe a pattern of sleep-wake cycle during different training phases, as well as poor sleep quality.

A critical review on sleep assessment methodologies in athletic populations: factors to be considered

A growing body of research focus on athletes' sleep in order to investigate the effects of sleep in sports performance and recovery or the prevalence of sleep disorders in athletes. At the same time, several sleep monitoring tools have been developed and used in athletic populations for fulfilling these purposes. This review aimed to provide critical assessment to the most used by athletes' methodological approaches and compared them with the gold standard approach. Advantages and disadvantages of the various sleep monitoring tools were critically discussed. Literature related to aspects of athletes' sleep was reviewed. From the shortlisted studies, several factors that seem to affect sleep in athletes were identified using objective methods such as polysomnography/electroencephalography and actigraphy. These factors were associated to sleep (eg such as sleep environment, familiarization procedures and napping) and daily habits (eg nutrition, fluid consumption, alcohol and caffeine intake, tobacco use). The selected studies that evaluated sleep objectively were screened according the reporting rates of these variables. The majority of the screened studies were found to underreport these variables. Practical issues were addressed and recommendations about reporting sleep-related factors were made in order to improve studies' quality assessment and allow for more robust comparisons between studies.

Sleep Quality and Quantity of International Rugby Sevens Players During Pre-season

Leduc, C, Jones, B, Robineau, J, Piscione, J, and Lacome, M. Sleep quality and quantity of international rugby sevens players during pre-season. J Strength Cond Res 33(7): 1878-1886, 2019-The aim of this study was to investigate the influence of training load on objective and subjective sleep measures among elite rugby sevens players during pre-season. Nine international male rugby sevens players participated in this study. Actigraphic and subjective sleep assessment were performed on a daily basis to measure sleep parameters. Training load was measured during the entire pre-season period, and sleep data from the highest and lowest training load week were used in the analysis through magnitude-based inferences. During the highest training load, likely to possibly small, moderate decreases in time in bed (effect sizes; ±90% confidence limits: -0.42; ±0.44 for session rating of perceived exertion [sRPE], -0.69; ±0.71 for total distance covered [TDC]) and total sleep time (-0.20; ±0.37 for sRPE, -0.23; ±0.35 for TDC) were found. Possibly small (-0.21; ±0.35 for high-speed distance, -0.52; ±0.73 for acceleration/deceleration [A/D]) and likely moderate (-074; ±0.67 for TDC) decreases were observed in subjective sleep quality. Possibly small to very likely moderate changes in sleep schedule were observed. Sleep quantity and subjective quality seem to be deteriorated during higher loads of training. This study highlights the necessity to monitor and improve sleep among elite rugby sevens players, especially for the intense period of training.

Sleep practices implemented by team sport coaches and sports science support staff: A potential avenue to improve athlete sleep?

OBJECTIVES

The primary aims of the present study were to assess the sleep hygiene knowledge of high performance team sport coaches and sports science support staff; the sleep practices these individuals implement with athletes; and the barriers to the more frequent use of these practices.

DESIGN

Cross-sectional observational study.

METHODS

A sample of 86 Australian coaches and sports science support staff working within high performance team sport volunteered to complete a four-part questionnaire, including the Sleep Beliefs Survey used to assess sleep hygiene knowledge.

RESULTS

Overall sleep hygiene knowledge was adequate (15.3±2.9, score range 0-20; mean±SD), however knowledge of sleep-wake cycle behaviours (score 4.9±1.6 out of 7) and thoughts and attitudes about sleep (3.6±1.0 out of 5) were inadequate. Over half (56%) of coaches and support staff had monitored athlete sleep, while 43% had promoted sleep hygiene. Lack of resources (response range 44-60%) and knowledge (16-41%) were the two main barriers to the implementation of sleep monitoring and sleep hygiene practices.

CONCLUSIONS

Team sport coaches and sports science support staff have adequate overall sleep hygiene knowledge, yet some specific areas (e.g. sleep-wake cycle behaviours) warrant improvement. There appear to be limited sleep practices implemented with athletes, particularly regarding the promotion of sleep hygiene. The development of educational sleep resources for coaches and support staff to implement with athletes may help address the identified barriers and improve sleep knowledge.

Which parameters to use for sleep quality monitoring in team sport athletes? A systematic review and meta-analysis

Background

Sleep quality is an essential component of athlete's recovery. However, a better understanding of the parameters to adequately quantify sleep quality in team sport athletes is clearly warranted.

Objective

To identify which parameters to use for sleep quality monitoring in team sport athletes.

Methods

Systematic searches for articles reporting the qualitative markers related to sleep in team sport athletes were conducted in PubMed, Scopus, SPORTDiscus and Web of Science online databases. The systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. For the meta-analysis, effect sizes with 95% CI were calculated and heterogeneity was assessed using a random-effects model. The coefficient of variation (CV) with 95% CI was also calculated to assess the level of instability of each parameter.

Results

In general, 30 measuring instruments were used for monitoring sleep quality. A meta-analysis was undertaken on 15 of these parameters. Four objective parameters inferred by actigraphy had significant results (sleep efficiency with small CV and sleep latency, wake episodes and total wake episode duration with large CV). Six subjective parameters obtained from questionnaires and scales also had meaningful results (Pittsburgh Sleep Quality Index (sleep efficiency), Likert scale (Hooper), Likert scale (no reference), Liverpool Jet-Lag Questionnaire, Liverpool Jet-Lag Questionnaire (sleep rating) and RESTQ (sleep quality)).

Conclusions

These data suggest that sleep efficiency using actigraphy, Pittsburgh Sleep Quality Index, Likert scale, Liverpool Jet-Lag Questionnaire and RESTQ are indicated to monitor sleep quality in team sport athletes.

PROSPERO registration number

CRD42018083941.

Effects of training and competition on the sleep of elite athletes: a systematic review and meta-analysis

Objectives

To characterise the sleep of elite athletes and to identify factors associated with training and competition that negatively affect sleep.

Design

Prognosis systematic review.

Data sources

Three databases (PubMed, SCOPUS and SPORTDiscus) were searched from inception to 26 February 2018.

Eligibility criteria for selecting studies

Included studies objectively reported total sleep time (TST) and/or sleep efficiency (SE) in elite athletes. Studies were required to be observational or to include an observational trial.

Results

Fifty-four studies were included. During training, many studies reported athletes were unable to achieve TST (n=23/41) and/or SE (n=16/37) recommendations. On the night of competition, most studies reported athletes were unable to achieve TST (n=14/18) and/or SE (n=10/16) recommendations. TST was shorter (60 min) the night of competition compared with previous nights. SE was lower (1%) the night of competition compared with the previous night. TST was shorter the night of night competition (start ≥18:00; 80 min) and day competition (20 min) compared with the previous night. SE was lower (3%–4%) the night of night competition but unchanged the night of day competition compared with previous nights. Early morning training (start <07:00), increases in training load (>25%), late night/early morning travel departure times, eastward air travel and altitude ascent impaired sleep.

Conclusion

Athletes were often unable to achieve sleep recommendations during training or competition periods. Sleep was impaired the night of competition compared with previous nights. Early morning training, increases in training load, travel departure times, jet lag and altitude can impair athletes’ sleep.

PROSPERO registration number

CRD42017074367.

The Variability of Sleep Among Elite Athletes

Practicing sport at the highest level is typically accompanied by several stressors and restrictions on personal life. Elite athletes’ lifestyle delivers a significant challenge to sleep, due to both the physiological and psychological demands, and the training and competition schedules. Inter-individual variability of sleep patterns (e.g., sleep requirements, chronotype) may have important implications not only for recovery and training schedules but also for the choice of measures to possibly improve sleep. This article provides a review of the current available literature regarding the variability of sleep among elite athletes and factors possibly responsible for this phenomenon. We also provide methodological approaches to better address the inter-individual variability of sleep in future studies with elite athletes. There is currently little scientific evidence supporting a specific influence of one particular type of sport on sleep; sleep disorders may be, however, more common in strength/power and contact sports. Sleep behavior may notably vary depending on the athlete’s typical daily schedule. The specificity of training and competition schedules possibly accounts for the single most influential factor leading to inconsistency in sleep among elite athletes (e.g., “social jet lag”). Additionally, athletes are affected by extensive exposure to electric light and evening use of electronic media devices. Therefore, the influence of ordinary sleep, poor sleep, and extended sleep as important additional contributors to training load should be studied. Future experimental studies on sleep and elite sport performance should systematically report the seasonal phase. Boarding conditions may provide a good option to standardize as many variables as possible without the inconvenience of laboratory. The use of interdisciplinary mixed-method approaches should be encouraged in future studies on sleep and elite sport. Finally, high inter- and intra-individual variability in the athletes’ sleep characteristics suggests a need for providing individual responses in addition to group means.