Effects of competition on the sleep patterns of elite rugby union players

Habitual Nocturnal Sleep, Napping Behavior, and Recovery Following Training and Competition in Elite Water Polo: Sex-Related Effects

PURPOSE

To examine nocturnal sleep patterns, napping behaviors, and subjective wellness responses of elite water polo players within an in-season week and to identify whether sleeping patterns differ between men and women.

METHODS

Sleep characteristics of 10 male and 17 female professional water polo players were objectively assessed during 1 week of the in-season period, including 5 training days, 1 match day, and 1 day of rest. Internal load (rating of perceived exertion × duration of training or match) was assessed 30 minutes posttraining or postmatch, and the total quality of recovery was recorded every morning. A series of multilevel models were used to analyze the data.

RESULTS

Time in bed and wake-up time were earlier on both training (P < .001) and rest days (P < .001) than on the day of the match. Internal workload did not predict any of the players' sleeping patterns. Midday naps predicted less time in bed (P = .03) and likely less sleep time (P = .08). The total quality of recovery was predicted only by the total sleep time (P < .01). Women exhibited higher sleep efficiency (P < .001), less waking after sleep onset (P = .01), and a lower number of awakenings (P = .02) than men.

CONCLUSIONS

The current results indicate that the nocturnal sleep patterns of elite water polo players are not associated with internal load and that women display better nocturnal sleep quality compared with men. As long naps interfere with nocturnal sleep, and total nocturnal sleep time predicts total quality of recovery, we suggest that athletes follow hygiene sleep strategies to facilitate adequate nocturnal sleep and next-day recovery.

Sleep architecture of elite soccer players surrounding match days as measured by WHOOP straps

This study aimed to quantify and compare sleep architecture before and after home and away matches in elite soccer players from the English Premier League. Across two seasons, 6 male players (age 28 ± 5 y; body mass 85.1 ± 9.5 kg; height 1.86 ± 0.09 m) wore WHOOP straps to monitor sleep across 13 matches that kicked off before 17:00 h. For each, sleep was recorded the night before (MD-1), after (MD) and following the match (MD +1). Across these 3 days total sleep time (TST), sleep efficiency (SE), sleep disturbances, wake time, light sleep, deep sleep, REM sleep, sleep and wake onsets, alongside external load, were compared. TST was reduced after MD versus MD +1 (392.9 ± 76.4 vs 459.1 ± 66.7 min, p = 0.003) but no differences existed in any other sleep variables between days (p > 0.05). TST did not differ after home (386.9 ± 75.7 min) vs. away matches (401.0 ± 78.3 min) (p = 0.475), nor did other sleep variables (p > 0.05). GPS-derived external load peaked on MD (p < 0.05). In conclusion, despite reduced TST on MD, sleep architecture was unaffected after matches played before 17:00 h, suggesting sleep quality was not significantly compromised.

Real-World Fatigue Testing in Professional Rugby Union: A Systematic Review and Meta-analysis

BACKGROUND

Professional rugby union is a high-intensity contact sport with position-specific high training and match volumes across a season that may lead to periods of fatigue if above a typically experienced threshold. This study assesses the influence of match play and/or training on fatigue levels in rugby union players.

OBJECTIVE

We aimed to perform a systematic review and meta-analysis of measures used to assess fatigue status in male professional rugby union players.

METHODS

Using electronic databases (PubMed, SPORTDiscus, Web of Science, Cochrane Library, EMBASE, and MEDLINE), a systematic review of fatigue testing in rugby union was conducted on (1) neuromuscular, (2) subjective self-report, (3) biochemical, and (4) heart rate-derived measures.

RESULTS

Thirty-seven articles were included in this systematic review, of which 14 were further included in a meta-analysis. The results of the meta-analysis revealed small, yet not significant, decreases in countermovement jump height immediately after (effect size [ES] =  - 0.29; 95% confidence interval [CI] - 0.64 to 0.06), 24 h (ES =  - 0.43; 95% CI - 3.99 to 3.21), and 48 h (ES =  - 0.22; 95% CI - 0.47 to 0.02) after exposure to rugby union match play or training. Reported wellness (ES =  - 0.33; 95% CI - 1.70 to 1.04) and tiredness (ES =  - 0.14; 95% CI - 1.30 to 1.03) declined over a period of a few weeks (however, the results were not-statistically significant), meanwhile muscle soreness increased (ES = 0.91; 95% CI 0.06 to 1.75) within the 96 h after the exposure to rugby union match play or training. Finally, while cortisol levels (ES = 1.87; 95% CI - 1.54 to 5.29) increased, testosterone declined (ES =  - 1.54; 95% CI - 7.16 to 4.08) within the 24 h after the exposure. However, these results were not statistically significant.

CONCLUSIONS

Subjective measures of muscle soreness can be used to assess fatigue after match play and training in rugby union players. Within-study and between-study variability for countermovement jump height, biochemical markers, and heart rate-derived measures means the utility (practical application) of these measures to assess fatigue in professional rugby union players after matches and training is unclear.

CLINICAL TRIAL REGISTRATION

PROSPERO ID: CRD42020216706.

A high incidence of injury among male university student rugby players requires urgent injury prevention strategies

OBJECTIVES

Determine the epidemiology and clinical characteristics of training and match injuries in university student rugby players over a two-season period.

DESIGN

Prospective cohort.

SETTING

Varsity Cup (VC) and Young Guns (YG) rugby tournaments (2018 and 2019).

PARTICIPANTS

171 male university student rugby players.

MAIN OUTCOME MEASURES

For time-loss injuries: injury incidence (injuries per 1000 player-hours), injured player proportion (% of injured players) and the frequency (n, %) of injury characteristics (new or recurrent, anatomical region, body area, severity.

RESULTS

The injury incidence was 2.4 per 1000 player-hours for training injuries and 131.1 per 1000 player-hours for match injuries. The overall injured player proportion was 59.6%. New injuries (83.9%) were more frequent than recurrent injuries. Most injuries occurred in the lower limb involving muscle/tendon (56.7%) and ligament/joint capsule (27.2%). The shoulder (19.6%) and ankle (15.7%) were the most common body areas of injury during matches and training, respectively.

CONCLUSIONS

There was a high injured player proportion and match injury incidence among university student rugby players. Most injuries were new. Lower limb injuries were most common in training whereas upper limb injuries were most common in matches. These findings highlight the need to prioritise future injury prevention among university student rugby players.

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.

Comparing Perceived Sleep Quality, Practices, and Behaviors of Male and Female Elite Rugby Union Athletes with the Use of Sleep Questionnaires

Objective  To evaluate the differences in subjective sleep quality, quantity, and behaviors among male and female elite rugby union athletes through two common sleep questionnaires. Materials and Methods  A sample of 38 male and 27 female elite rugby union athletes filled out the Athlete Sleep Behavior Questionnaire (ASBQ) and the Pittsburgh Sleep Quality Index (PSQI). Global scores and individual items for each questionnaire were compared to assess differences between sexes. Results  Male athletes reported significantly longer sleep duration (7 h 50 m ± 50 m versus 7h 12 m ± 58 m respectively; p ≤ 0.01; d  = 0.70) and higher habitual sleep efficiency (88% versus 83% respectively; p  < 0.05; d  = 0.54) when compared with female athletes. Individual items of the ASBQ revealed significant differences between male and female athletes for five questions. Male athletes displayed higher instances of taking stimulants before training or competition and consuming alcohol within 4 hours of going to bed. Conversely, female athletes expressed greater thought or worry while in bed and a higher instance of training late at night. Discussion  Male athletes displayed better self-reported sleep quality and quantity than female athletes; however, the present study highlighted that male and female elite rugby union athletes face specific challenges that differ. It appears that the differences observed between male and female elite rugby union athletes may be due to differing levels of professionalism or differences in training or competition schedules.

40-min nap opportunity attenuates heart rate and perceived exertion and improves physical specific abilities in elite basketball players

The effect of a 40-min nap opportunity on physiological responses and specific abilities was investigated. Twelve high-level professional basketball players (26.33±5.2 years; 193.17±7.1 m; 87.48±11.2 kg) undertook randomly 40-min nap opportunity (NAP) and control condition (CON). Wellness (Hooper Index) and Epworth Sleepiness Scale (ESS) were measured before and after both conditions. Defensive (DA) and offensive (OA) agility and upper body power (UBP) were assessed after both conditions. Shooting skill (SST) performance was evaluated prior and after a fatiguing task (FT). Heart rate (HR) and rating of perceived exertion (RPE) were recorded during SST-test, FT and SST-retest. ESS, Hooper's stress and fatigue score were significantly lower after nap compared to those before nap (0.009 ≤ p ≤ 0.03). Better performance was obtained in NAP compared to CON condition for DA, OA and UBP (0.0005 ≤ p ≤ 0.02). SST performance was significantly higher in NAP compared to CON in the retest session (p = 0.003, Δ = 20.2%).         The improved performance was associated with significant lower HRpeak (p = 0.01, Δ = 5.25%) and RPE (p = 0.003, Δ = 15.12%). In conclusion, NAP reduced sleepiness and stress and fatigue and enhances physical outcomes of specific skills in elite basketball players.

The Impact of Kiwifruit Consumption on the Sleep and Recovery of Elite Athletes

BACKGROUND

Poor sleep and resultant under-recovery can negatively impact training adaptations, increase the risk of injury and reduce subsequent performance. Due to the 'food first' approach adopted by many athletes, there is scope for investigation of 'functional food' based interventions (i.e., kiwifruit contains melatonin which plays a role in circadian rhythm regulation) designed to promote athlete recovery and/or enhance sleep quality and quantity.

METHODS

Following the baseline assessment (Week 1) all subjects began the intervention (Weeks 2-5). During the 4-week intervention, participants were asked to consume 2 medium-sized green kiwifruit (Actinidia Deliciosa) an hour before bed. Participants completed a questionnaire battery at baseline and post-intervention, and a daily sleep dairy for the duration of the study.

RESULTS

The results demonstrated a positive impact of kiwifruit consumption on key aspects of sleep and recovery in elite athletes. From baseline to post-intervention, there were clinically significant improvements in sleep quality (i.e., improved PSQI global scores and sleep quality component scores) and improvements in recovery stress balance (reduced general stress and sports stress scales). Moreover, the intervention improved sleep as evidenced by significant increases in total sleep time and sleep efficiency % and significant reductions in number of awakenings and wake after sleep onset.

CONCLUSION

The findings broadly suggested that kiwifruit does impact positively on sleep and recovery in elite athletes.

Effect of Training/Competition Load and Scheduling on Sleep Characteristics in Professional Rugby League Athletes

ABSTRACT

Conlan, G, McLean, B, Kemp, J, and Duffield, R. Effect of training/competition load and scheduling on sleep characteristics in professional rugby league athletes. J Strength Cond Res 36(12): 3390-3397, 2022-This study examined the effect of training/competition load, scheduling, and associated factors on sleep behavior in professional rugby league athletes. Sleep characteristics were assessed in 26 professional rugby league athletes using wrist-mounted actigraphy and nightly sleep diaries. Sleep actigraphy assessed the time into and out of bed, the duration in bed, sleep duration, efficiency, latency, wake after sleep onset, number of awakenings, and the awakening length. Sleep was measured during 3 different weeks: (a) preseason low training load (TL) (2,356 ± 322 AU), (b) preseason high TL (3,542 ± 445 AU), and (c) in-season match week (1,526 ± 409 AU). The influences of internal TL (session rating of perceived exertion load), training schedule, age, and training location on sleep behavior were analyzed. Repeated-measures 2-way analysis of variance and effect size analyses (d) compared sleep variables between training weeks. The mean weekly sleep duration was significantly lower during high TL week (5 hours 53minutes ± 14 min/night; p = 0.015, d = 0.59) compared with the low TL (6 hours 25minutes ± 8 min·night -1 ) or match weeks (6 hours 26minutes ± 10 min·night -1 ; p = 0.02, d = 2.04). Reduced sleep duration in the high TL week occurred alongside earlier out-of-bed times compared with the low TL ( p = 0.003, d = 1.46) and match weeks ( p = 0.001, d = 5.99). Regardless, the lowest sleep duration was on match night ( p = 0.0001, d = 1.22). Earlier training start times resulted in earlier wake times ( p = 0.003, d = 4.84), shorter in-bed durations ( p = 0.0001, d = 0.62), and shorter sleep durations ( p = 0.002, d = 0.32). Younger athletes slept for longer durations ( p = 0.029, d = 1.70) and perceived their sleep quality to be superior ( p = 0.006, d = 14.94) compared with older athletes. Sleep attained by rugby league athletes is influenced by training and competition schedules, with early training start times and late-night matches being primary drivers of sleep behavior. Coaching staff should have awareness surrounding the implications of training and playing schedules on athlete sleeping patterns.

Sleep and the Young Athlete

CONTEXT

Sleep plays a vital role in cognitive and physical performance. Teenage athletes (ages 13-19 years) are considered especially at risk for disordered sleep and associated negative cognitive, physical, and psychosomatic effects. However, there is a paucity of evidence-based recommendations to promote sleep quality and quantity in athletes who fall within this age range. We performed a review of the literature to reveal evidence-based findings and recommendations to help sports instructors, athletic trainers, physical therapists, physicians, and other team members caring for young athletes provide guidance on sleep optimization for peak sports performance and injury risk reduction.

METHODS

PubMed, Scopus, and Cochrane CENTRAL were searched on May 11, 2016, and then again on September 1, 2020, for relevant articles published to date.

STUDY DESIGN

Narrative review.

LEVEL OF EVIDENCE

Level 4.

RESULTS

Few studies exist on the effects disordered sleep may have on teenage athletes. By optimizing sleep patterns in young athletes during training and competitions, physical and mental performance, and overall well-being, may be optimized. Adequate sleep has been shown to improve the performance of athletes, although further studies are needed.

CONCLUSION

Twenty-five percent of total sleep time should be deep sleep, with a recommended sleep time of 8 to 9 hours for most young athletes. Screen and television use during athletes' bedtime should be minimized to improve sleep quality and quantity. For young athletes who travel, jet lag can be minimized by allowing 1 day per time zone crossed for adjustment, limiting caffeine intake, planning meals and onboard sleeping to coincide with destination schedules, timing arrivals in the morning whenever possible, and using noise-canceling headphones and eyeshades.

STRENGTH-OF-RECOMMENDATION TAXONOMY (SORT)

B.

Running on Empty: Self-Reported Sleep/Wake Behaviour during Ultra-Marathon Events Exceeding 100 Miles

The aim of this study was to examine sleep/wake behaviour and sleep strategies before, during and after ultra-marathon running events exceeding 100 miles (161 km). A total of 119 athletes completed a web-based questionnaire regarding their habitual sleep/wake behaviour before, during, and after ultra-marathon participation. Event-specific data were grouped by race distance categories; 100–149 miles (161–240 km), 150–199 miles (241–321 km), and ≥200 miles (322 km). Athletes commonly reported not sleeping throughout the duration of their races (74%). However, for events that were ≥200 miles, athletes reported more sleep opportunities, longer sleep duration, and more total sleep when compared to events that were 100–149 miles in distance (p ≤ 0.001). This suggests that for races of shorter distances, the benefit of continuous racing outweighs the negative impact of continuous wakefulness/sleep deprivation. However, for longer races (≥200 miles), there is an apparent tradeoff between sleep deprivation and race strategy, whereby athletes cannot sustain a desired level of performance without obtaining sleep. This is consistent with established sleep/wake behaviour models suggesting that sleep need increases as wakefulness increases, or in this case, as race duration increases. For athletes participating in ultra-marathons, sleep management education and/or consultation with a sleep scientist prior to racing may be beneficial. Future research should examine the optimal strategies concerning the frequency and duration of sleep during ultra-marathons and the subsequent impact on performance.

The Effect of Rugby Union Match Play on Sleep Patterns and Subsequent Impact on Postmatch Fatigue Responses

PURPOSE

Sleep is recognized as an important recovery strategy, yet little is known regarding its impact on postmatch fatigue. The aims of this study were to (1) describe sleep and postmatch fatigue, (2) understand how sleep is affected by contextual and match factors, and (3) assess how changes in sleep can affect postmatch fatigue.

METHODS

Twenty-three male rugby union players were monitored across 1 season (N = 71 player-match observations). Actigraphy was used during preseason to establish baseline sleep quality and quantity. Sleep was then measured 1 and 2 days after each match day (MD + 1 and MD + 2). Global positioning systems, notational analysis, and rating of perceived exertion represented external and internal load from matches. Subjective wellness and a standardized run were used to characterize postmatch fatigue 2 days prior (baseline) and at MD + 1 and MD + 2. Linear mixed models established the magnitude of change (effect size [ES]) between baseline, MD + 1, and MD + 2 for sleep and postmatch fatigue. Stepwise forward selection analysis ascertained the effect of match load on sleep and the effect of sleep on postmatch fatigue. Each analysis was combined with magnitude-based decisions.

RESULTS

Sleep characteristics and neuromuscular and perceptual postmatch fatigue were negatively affected at MD + 1 and MD + 2 (ES = small to very large). Kickoff and travel time had the greatest effect on sleep (ES = small). Wellness and soreness were influenced by sleep (fall-asleep time and fragmentation index) and collisions, respectively (ES = small).

CONCLUSION

Sleep quality and quantity were affected independently of the match load (ie, running activity) sustained, and changes in sleep marginally affected postmatch fatigue.

The impact of matches and travel on rugby players’ sleep, wellness and training

Matches and travel, which are common in professional team sports, may have a negative impact on players. The aim of this study was to quantify the impact on sleep, wellness and training of Super Rugby players. Sleep of 122 players from four teams was monitored using activity monitors for up to three nights before and after matches played at home and overseas. Wellness and internal training load (questionnaires) and external training load (GPS/accelerometer) were also recorded. Separate analyses were performed for each team using a general linear mixed model to estimate the mean effects of travel (translocation overseas and return to the home country) on sleep, wellness and training. The mean effects of matches on sleep and wellness on the nights before, of and after matches. were also estimated. Teams generally experienced small to large reductions in sleep and wellness when overseas; on return, sleep and wellness recovered somewhat. The impact of matches on sleep and wellness differed in magnitude and direction (large reductions to small increases) between teams. External load overseas and upon return was reduced for three of the four teams, whilst internal load was reduced for the three teams that measured it. The changes in sleep, wellness and training can be explained by a combination of travel- and match-related stressors that differed between teams. Teams should consider remediation strategies to mitigate the effects of travel.

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.

Around the world in 16 days: the effect of long-distance transmeridian travel on the sleep habits and behaviours of a professional Super Rugby team

There is a scarcity of research examining the effects of long-distance transmeridian travel (LDTT) on the sleep and match performance of team sport players. To address this, 37 elite male rugby union players from a Super Rugby team undertaking LDTT were recruited. The participants completed validated sleep questionnaires and wore a wrist-worn activity monitor (Readiband™) during a Super Rugby season (including during periods of LDTT crossing 5, 6, and 13 time-zones) to ascertain objective measures of sleep. Sleep measures were compared using mixed model analysis to ascertain the effects of competition and LDTT on sleep. Total sleep time (TST) increased in the days prior to matches, and decreased following matches (accompanied by a later time at sleep onset), particularly when next-day early-morning flights were required. TST was decreased when sleep was attempted during LDTT, except for in the last travel bout where players napped in addition to achieving night-time sleep. TST was also reduced for the night immediately following LDTT, except for in Condition 3 where players delayed wake time and also achieved naps. This study exemplifies the challenges that team-sport athletes face in obtaining regular sleep when LDTT is required.

Benefits of Daytime Napping Opportunity on Physical and Cognitive Performances in Physically Active Participants: A Systematic Review

BACKGROUND

Evidence suggests that athletes often experience chronic sleep disturbance. Napping is widely recommended as a safe and non-invasive intervention to counteract the negative effects of partial sleep deprivation. However, systematic reviews on the benefits of napping have yet to be undertaken.

OBJECTIVE

(i) To evaluate the effectiveness of diurnal napping opportunities on athletes' physical and cognitive performance and (ii) to outline how aspects of the study design (i.e., nap duration, exercise protocol, participants' fitness level and previous sleep quantity) can influence the potential effects of napping through a systematic appraisal of the literature.

METHODS

This systematic review was conducted in accordance with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. PubMed, Web of Science and SCOPUS databases were searched up to June 2020 for relevant studies investigating the effect of napping on physical and cognitive performances in physically active participants. Fourteen strong-quality and four moderate-quality (mean QualSyst score = 75.75 ± 5.7%) studies met our inclusion criteria and were included in the final sample (total participants: 158 physically active and 168 athletes).

RESULTS

Most studies (n = 15) confirmed the beneficial effects of napping and showed that diurnal napping improved short-term physical performance (n = 10), endurance performance (n = 3) and specific skills performance (n = 2). Two studies showed no significant napping effect and only one study showed reduced sprint performance following diurnal napping. Moreover, napping improved reaction time (n = 3), attention (n = 2) and short-term memory (n = 1) performances. Importantly, "replacement naps" improved both physical and cognitive performance regardless of the type of exercise. However, "prophylactic naps" improved only jump, strength, running repeated-sprint, attention and reaction time performances. In addition, this systematic review revealed that longer nap opportunities (i.e., 90 min) resulted in better improvement of physical and cognitive performance and lower induced fatigue.

CONCLUSIONS

A diurnal nap seems to be an advantageous intervention to enhance recovery process and counteract the negative effect of partial sleep deprivation on physical and cognitive performance. Particularly, to optimize physical performances of athletes experiencing chronic lack of sleep, findings from the included individual studies suggest 90 min as the optimal nap duration. Diurnal napping may be beneficial for athletes but this benefit should be viewed with caution due to the quality of the evidence, risk of bias and the limited evidence about napping interventions.

The Sleep and Recovery Practices of Athletes

BACKGROUND

Athletes maintain a balance between stress and recovery and adopt recovery modalities that manage fatigue and enhance recovery and performance. Optimal TST is subject to individual variance. However, 7-9 h sleep is recommended for adults, while elite athletes may require more quality sleep than non-athletes.

METHODS

A total of 338 (elite n = 115, 74 males and 41 females, aged 23.44 ± 4.91 years; and sub-elite n = 223, 129 males and 94 females aged 25.71 ± 6.27) athletes were recruited from a variety of team and individual sports to complete a battery of previously validated and reliable widely used questionnaires assessing sleep, recovery and nutritional practices.

RESULTS

Poor sleep was reported by both the elite and sub-elite athlete groups (i.e., global PSQI score ≥5-elite 64% [n = 74]; sub-elite 65% [n = 146]) and there was a significant difference in sport-specific recovery practices (3.22 ± 0.90 vs. 2.91 ± 0.90; p < 0.001). Relatively high levels of fatigue (2.52 ± 1.32), stress (1.7 ± 1.31) and pain (50%, n = 169) were reported in both groups. A range of supplements were used regularly by athletes in both groups; indeed, whey (elite n = 22 and sub-elite n = 48) was the most commonly used recovery supplement in both groups. Higher alcohol consumption was observed in the sub-elite athletes (12%, n = 26) and they tended to consume more units of alcohol per drinking bout.

CONCLUSION

There is a need for athletes to receive individualised support and education regarding their sleep and recovery practices.

Sleep Characteristics and Mood of Professional Esports Athletes: A Multi-National Study

Esports is becoming increasingly professionalized, yet research on performance management is remarkably lacking. The present study aimed to investigate the sleep and mood of professional esports athletes. Participants were 17 professional esports athletes from South Korea (N = 8), Australia (N = 4), and the United States (N = 5) who played first person shooter games (mean age 20 ± 3.5 years, 100% male). All participants wore a wrist-activity monitor for 7–14 days and completed subjective sleep and mood questionnaires. Participants had a median total sleep time of 6.8 h and a sleep efficiency of 86.4% per night. All participants had significantly delayed sleep patterns (median sleep onset 3:43 a.m. and wake time 11:24 a.m.). Participants had a median sleep onset latency of 20.4 min and prolonged wake after sleep onset of 47.9 min. Korean players had significantly higher depression scores compared to the other groups (p < 0.01) and trained longer per day than the Australian or United States teams (13.4 vs. 4.8 vs. 6.1 h, respectively). Depression scores were strongly correlated with number of awakenings, wake after sleep onset, and daily training time (p < 0.05). As the first pilot sleep study in the esports field, this study indicates that esports athletes show delayed sleep patterns and have prolonged wake after sleep onset. These sleep patterns may be associated with mood (depression) and training time. Sleep interventions designed specifically for esports athletes appear warranted.

Get sleep or get stumped: sleep behaviour in elite South African cricket players during competition

Despite evidence supporting the positive affect sleep has on sport performance, there is limited application of sleep research in cricket. This study investigated the sleep behaviours of 26 elite South African cricket players (28.6 ± 4.0 years) during home and away competition. Players completed an altered version of the Core Consensus Sleep Diary every morning post-travel, pre-match and post-match. Linear mixed model regression was used to compare differences in sleep between time-periods, venues and formats. Spearman's correlations (r_s) assessed the relationship of match performance and sleep. Post-match total sleep time (06:31 ± 01:09) was significantly (p < 0.05) shorter compared to post-travel (07:53 ± 01:07; g = 1.19) and pre-match (08:43 ± 01:03; g = 1.98). Post-travel sleep onset latency and sleep efficiency were significantly shorter (-20; g = 1.35) and higher (+10.4%; g = 0.74) at home than away respectively. Longer sleep onset latencies and shorter total sleep times were significantly associated with poorer One-Day International (r_s = -0.57) and Test (r_s = 0.59) batting performances respectively. The poor post-match sleep behaviour, and the sleep and performance correlations, provide motive for future interventions to focus on recovery and the use of sleep monitoring as a competitive advantage.

The Impact of Sleep Duration on Performance Among Competitive Athletes: A Systematic Literature Review

The athletic advantage of sleep, although commonly touted by coaches, trainers, and sports physicians, is still unclear and likely varies by sport, athletic performance metric, and length of sufficient or insufficient sleep. Although recent literature reviews have highlighted circadian and nutritional factors that influence different aspects of athletic performance, a systematic summary of the effects of sleep duration and sleep quality on performance among competitive athletes is lacking. Here we systematically review the relationship between sleep duration and sleep quality and objective athletic performance among competitive athletes across 19 studies representing 12 sports. Taken holistically, we find that the sports requiring speed, tactical strategy, and technical skill are most sensitive to sleep duration manipulations. Furthermore, longer-term sleep manipulations are more likely than acute sleep manipulations (whether deprivation or extension) to affect athletic performance. Thus, the importance of sleep for competitive athletes to achieve high performance is dependent on the demands of the sport as well as the length of sleep interventions. In light of the limited number of studies investigating sleep quality and performance, the potential relevance of subjective sleep quality remains an interesting question for future work.

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.

Effect of an Innovative Mattress and Cryotherapy on Sleep after an Elite Rugby Match

INTRODUCTION

This study aimed to explore the relationship between elite rugby union match and postmatch sleep architecture and to investigate the effects of a high-heat capacity mattress (MAT) and a whole-body cryotherapy (WBC) session on postmatch sleep architecture.

METHODS

Nineteen elite male U23 rugby union players performed in three official matches, followed by three experimental conditions, in a randomized order: MAT, WBC, and no intervention (CONT). Match load was evaluated using GPS trackers and video analyses. Sleep architecture was assessed by polysomnography (PSG). Core body temperature (CBT) and mattress surface temperature were monitored during sleep. Linear mixed-effects models were conducted to assess the effects of each experimental condition on sleep, with match load variables as covariates.

RESULTS

A lower wake after sleep onset (β = -10.5 min, P < 0.01) and higher rapid eye movement sleep proportion (β = +2.8%, P < 0.05) were reported for MAT compared with CONT. Moreover, lower mean CBT (β = -0.135°C, P < 0.001) and mean mattress surface temperature (β = -2.736°C, P < 0.001) during sleep were observed for MAT compared CONT. WBC did not affect nocturnal CBT nor interfere with sleep architecture. For every 100-m increase in high-speed running distance, a higher slow wave sleep (β = +1.1%, P = 0.05) and lower light sleep proportion (β = -1.2%, P < 0.05) proportion were observed. Conversely, for every 10 supplementary collisions, lower slow wave sleep (β = -1.9, P = 0.09) and higher light sleep (β = +2.9%, P < 0.001) proportion were observed.

CONCLUSION

MAT use had a positive effect on sleep architecture after an elite rugby union match, potentially through a more efficient nocturnal heat transfer.

You Snooze, You Win? An Ecological Dynamics Framework Approach to Understanding the Relationships Between Sleep and Sensorimotor Performance in Sport

Sleep has a widespread impact across different domains of performance, including sensorimotor function. From an ecological dynamics perspective, sensorimotor function involves the continuous and dynamic coupling between perception and action. Sport performance relies on sensorimotor function as successful movement behaviors require accurate and efficient coupling between perceptions and actions. Compromised sleep impairs different aspects of sensorimotor performance, including perceptual attunement and motor execution. Changes in sensorimotor performance can be related to specific features of sleep, notably sleep spindles and slow waves. One unaddressed area of study is the extent to which specific sleep features contribute to overall sport-specific performance.

No Effect of Partial-Body Cryotherapy on Restoration of Countermovement Jump or Well-Being Performance in Elite Rugby Union Players During the Competitive Phase of the Season

PURPOSE

Partial body cryotherapy (PBC) has been shown to be beneficial for postexercise recovery; however, no study has demonstrated the effectiveness of PBC for recovery following elite rugby union training. Rugby union is a unique sport that involves high-velocity collisions and may induce greater performance decrements than other sports; thus, PBC could be beneficial. The application of PBC in "real world" has rarely been investigated during the competitive phase of a playing season and warranted investigation.

METHODS

In a counterbalanced sequential research design, professional rugby athletes (n = 18; age 25.4 [4.0] y; training age 7.2 [4.0] y; mass 99.8 [10.6] kg; height 188.3 [6.0] cm) were assigned to a 12-week PBC intervention, washout period (4 wk), and reassessed as their own controls. Self-reported well-being, muscle soreness, sleep quality, and countermovement jump height were assessed before and 40 hours after "real-world" training. Wilcoxon signed-rank tests and Cohen d were used for statistical analysis.

RESULTS

No differences were observed between PBC and control conditions (P > .05; d = 0.00-0.14) for well-being (-0.02% [0.08%] vs 0.01% [0.06%]), muscle soreness (-0.01% [0.11%] vs 0.01% [0.16%]), sleep quality (-0.03% [0.14%] vs 0.10% [0.29%]), or countermovement jump height (36.48-36.59 vs 38.13-37.52 cm; P = .54).

CONCLUSIONS

These results suggest PBC is ineffective for the restoration of selected performance parameters during the performance maintenance phase of the competitive season. To ascertain the appropriation of its use, future investigations should seek to assess the use of cryotherapies at various phases of the elite rugby union competitive season.

High-intensity exercise in the evening does not disrupt sleep in endurance runners

PURPOSE

To investigate the effect of early evening exercise training at different intensities on nocturnal sleep and cardiac autonomic activity in endurance-trained runners.

METHODS

Eight runners completed three experimental trials in a randomised, counterbalanced order. In the early evening (end of exercise 3.5 h before bedtime), participants performed either: (i) a 1 h high-intensity interval running session (HIGH, 6 × 5 min at 90% VO_2peak interspersed with 5 min recovery); (ii) a 1 h low-intensity running session (LOW, 60 min at 45% VO_2peak) or (iii) no exercise (CON). Subsequent nocturnal sleep was assessed using polysomnography, wristwatch actigraphy, and subjective sleep quality. A two-lead electrocardiogram recorded nocturnal cardiac autonomic activity.

RESULTS

Total sleep time increased after HIGH (477.4 ± 17.7 min, p = 0.022) and LOW (479.6 ± 15.6 min, p = 0.006) compared with CON (462.9 ± 19.0 min). Time awake was lower after HIGH (31.8 ± 18.5 min, p = 0.047) and LOW (30.4 ± 15.7 min, p = 0.008) compared with CON (46.6 ± 20.0 min). There were no differences between conditions for actigraphy and subjective sleep quality (p > 0.05). Nocturnal heart rate variability was not different between conditions, but average nocturnal heart rate increased after HIGH (50 ± 5 beats min^-1) compared with LOW (47 ± 5 beats min^-1, p = 0.02) and CON (47 ± 5 beats min^-1, p = 0.028).

CONCLUSION

When performed in the early evening, high-intensity exercise does not disrupt and may even improve subsequent nocturnal sleep in endurance-trained runners, despite increased cardiac autonomic activity. Additionally, low-intensity exercise induced positive changes in sleep behaviour that are comparable to those obtained following high-intensity exercise.

Performance indicators during international rugby union matches are influenced by a combination of physiological and contextual variables

OBJECTIVES

Research has linked physiological (e.g., hormonal, affective, fatigue) outcomes to performance indicators in rugby competition, but no work has integrated and contextualised these factors within a test-match environment. We addressed this gap by monitoring 29 athletes from a training squad across eight international rugby matches.

DESIGN

Longitudinal observational study.

METHODS

Pre-match (8-9am) measures of salivary testosterone and cortisol concentrations, sleep duration, pulse rate, muscle soreness, stress, mood, and motivation were taken. Contextual factors were playing time, internal training load (ITL), test-match experience, opponent ranking, and crowd size. Performance was indexed by coach and player ratings of performance (CRP, PRP) and quantitative metrics; offloads, turnovers, runs with ball in hand (RWB), tackles, passes, and defenders beaten (DFB).

RESULTS

Morning cortisol, sleep and mood were positively related to CRP and PRP (standardised coefficient estimates from 0.17 to 0.22). Cortisol, sleep, stress, mood and motivation were associated with one (or more) of turnovers, RWB, tackles, passes and DFB (incidence rate ratio [IRR] from 0.74 to 1.40). Playing time was positively related to all quantitative performance indicators (IRR from 1.01 to 1.04) with ITL, opponent ranking, and crowd size predicting selected outputs (IRR from 0.89 to 1.15). The explanatory models varied (conditional R²=0.15-0.83) but were generally stronger with both physiological and contextual inputs.

CONCLUSIONS

Multiple physiological and contextual factors appear to contribute to player performance in international rugby competition. Measurement of these factors may guide training and management practices, a potential practical consequence but also advancing understanding from marker to causal link.

Sleep Patterns and Alertness in an Elite Super Rugby Team During a Game Week

Sleep is a vital component of preparation, performance and recovery for a Super Rugby game. The purpose of this study was to quantify sleep behaviours and alertness of professional rugby union players during training and a game. Thirty-six rugby union players from a Super Rugby team wore a wrist-activity device (Readiband™) to measure sleep for 3 days before, 3 days after and on the night of an evening game. Players were separated into those selected to play the game (n = 23) and those who were not (n = 13). Alertness was assessed for all training and game times using bio-mathematical modelling. Alertness measures ≤90% were considered to reflect impaired reaction time. Those selected to play in the game progressively increased sleep duration over the nights prior to the game (by 92 min p ≤ 0.05) by delaying wake time. Players went to bed later after the game (02:20 ± 114 min vs 22:57 ± 60 min; p ≤ 0.001) which resulted in decreased sleep duration on game night compared to pre-game nights (296 ± 179 min vs 459 ± 78 min; p ≤ 0.05). Four players did not achieve any sleep on game night. Sleep duration appeared to be truncated by early morning training sessions (before 08:00) on the second and third mornings after the game. Alertness was >90% for all training and game times for all players. In conclusion, in the days leading into a Super Rugby game, players delay morning time at wake and consequently increase sleep duration with post-game sleep reduced in some.

Evidence-based post-exercise recovery strategies in rugby: a narrative review

In the sport of rugby, athletes need a multitude of sport-specific skills along with endurance, power, and speed to optimize performance. Further, it is not unusual for athletes to play several competitive matches with insufficient recovery time. Rugby requires repeated bouts of high-intensity actions intermixed with brief periods of low-to-moderate active recovery or passive rest. Specifically, a match is characterized by repeated explosive activities, such as jumps, shuffles, and rapid changes of direction. To facilitate adequate recovery, it is necessary to understand the type of fatigue induced and, if possible, its underlying mechanisms. Common approaches to recovery may include nutritional strategies as well as active (active recovery) and passive recovery (water immersions, stretching, and massage) methods. However, limited research exists to support the effectiveness of each strategy as it related to recovery from the sport of rugby. Therefore, the main aim of the current brief review is to present the relevant literature that pertains to recovery strategies in rugby.

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.

Changes in Subjective Sleep Quality Before a Competition and Their Relation to Competitive Anxiety

OBJECTIVE/BACKGROUND

The aim of this study was to examine the effects of competitions on subjective sleep quality. Previous studies have been inconclusive and lack differentiated and standardized measurements of subjective sleep quality. Furthermore the temporal relation between precompetitive anxiety and sleep quality was investigated. Anxiety and nervousness associated with competitions are considered to cause sleep impairments.

PARTICIPANTS

A convenience sample of N = 79 elite male athletes from various sports participated.

METHODS

In a time-to-event paradigm, sleep quality and competitive anxiety were assessed via standardized self-report measurements 4 days before a competition and on the day of the competition. Univariate analyses were used to examine differences between time points. To examine cross-lagged effects between anxiety and sleep quality a latent change score model (LCSM) was specified that tested an effect of anxiety on changes in sleep quality.

RESULTS

Evaluations of nocturnal sleep deteriorated significantly from 4 days before competition to the day of competition, but there were no differences regarding perceptions of the restorative value of sleep. LCSM revealed that athletes who reported more intense worry symptoms 4 days before competition also reported greater deterioration in evaluations of nocturnal sleep.

CONCLUSIONS

The findings support earlier reports of impaired subjective sleep quality before competitions. Precompetitive sleep impairments appear also to be preceded by cognitive anxiety. Whereas interventions should thus address worry-cognitions associated with competition and sleep, research should address the practical importance of these perceptions of sleep impairments.

Prevalence of sleep disorders and sleep problems in an elite super rugby union team

The aim of this study was to determine the prevalence of sleep disorders in an elite rugby union team using in-laboratory polysomnography (PSG) and sleep questionnaires. Twenty-five elite rugby union players underwent a night of PSG during the "off-season" of the Super Rugby competition to assess their sleep. Of interest were measurements that detected the presence of obstructive sleep apnea (OSA; apnea-hypopnea index ≥5 events/hr) and the presence of moderate-severe periodic leg movements during sleep (PLMs; ≥15 events/hr). Players completed sleep-related questionnaires to assess daytime sleepiness, perception of insomnia, risk of OSA, and the presence of restless legs syndrome (RLS) and underwent basic anthropometric assessments including body mass index and neck circumference. OSA was present in 24% (n=6) of players and PLMs ≥15 events/hr in 12% (n=3). Questionnaire responses showed that all players had insomnia defined subthreshold insomnia and excessive daytime sleepiness, two players were identified as being at risk for OSA and none were classified as having RLS. In conclusion, sleep disorders and excessive sleepiness are common in elite rugby union players. A process to identify and manage sleep disorders should be considered by teams to optimise their physical recovery, athletic performance and to safeguard their health.

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.

From pillow to podium: a review on understanding sleep for elite athletes

Sleep is considered vital to human health and well-being, and is critical to physiological and cognitive functioning. Elite athletes experience high training and competition demands, and are often exposed to various factors, situations, and environments that can cause sleep impairments. Previous research has shown that athletes commonly experience sleep loss in the lead up to and following competition, which could have significant impacts on their preparation, performance, and recovery. In particular, the results from previous research show significant reductions in total sleep time (~1:40 h:min) and significant increases in sleep latency (~45 minutes) following evening competition. Napping is common in both the training and competition setting in athletes; however, research on the effect of napping on physiology and performance is limited. In contrast, research on strategies and interventions to improve sleep are increasing in the athletic population, with sleep hygiene research resulting in significant improvements in key sleep indices. This review investigates the physiological importance of sleep in athletes, current tools to monitor athletes' sleep, the role of sleep for cognitive functioning and athletic performance, the prevalence of sleep disturbances and the potential mechanisms causing sleep disturbances, the role of napping, and different intervention strategies to improve sleep.

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.

Does Elite Sport Degrade Sleep Quality? A Systematic Review

BACKGROUND

Information on sleep quality and insomnia symptomatology among elite athletes remains poorly systematised in the sports science and medicine literature. The extent to which performance in elite sport represents a risk for chronic insomnia is unknown.

OBJECTIVES

The purpose of this systematic review was to profile the objective and experienced characteristics of sleep among elite athletes, and to consider relationships between elite sport and insomnia symptomatology.

METHODS

Studies relating to sleep involving participants described on a pre-defined continuum of 'eliteness' were located through a systematic search of four research databases: SPORTDiscus, PubMed, Science Direct and Google Scholar, up to April 2016. Once extracted, studies were categorised as (1) those mainly describing sleep structure/patterns, (2) those mainly describing sleep quality and insomnia symptomatology and (3) those exploring associations between aspects of elite sport and sleep outcomes.

RESULTS

The search returned 1676 records. Following screening against set criteria, a total of 37 studies were identified. The quality of evidence reviewed was generally low. Pooled sleep quality data revealed high levels of sleep complaints in elite athletes. Three risk factors for sleep disturbance were broadly identified: (1) training, (2) travel and (3) competition.

CONCLUSION

While acknowledging the limited number of high-quality evidence reviewed, athletes show a high overall prevalence of insomnia symptoms characterised by longer sleep latencies, greater sleep fragmentation, non-restorative sleep, and excessive daytime fatigue. These symptoms show marked inter-sport differences. Two underlying mechanisms are implicated in the mediation of sport-related insomnia symptoms: pre-sleep cognitive arousal and sleep restriction.

The Effects of Sleep Extension on Sleep, Performance, Immunity and Physical Stress in Rugby Players

(1) Background: The purpose of the present study was to examine the efficacy of sleep extension in professional rugby players. The aims were to: (i) characterise sleep quantity in elite rugby players and determine changes in immune function and stress hormone secretion during a pre-season training programme; (ii) evaluate the efficacy of a sleep extension intervention in improving sleep, markers of physical stress, immune function and performance. (2) Methods: Twenty five highly trained athletes from a professional rugby team (age (mean ± SD) 25 ± 2.7 years; height 1.87 ± 0.07 m; weight 105 ± 12.1 kg) participated in a six week pre-post control-trial intervention study. Variables of sleep, immune function, sympathetic nervous activity, physiological stress and reaction times were measured. (3) Results: Sleep extension resulted in a moderate improvement in sleep quality scores ([mean; ± 90% confidence limits] −24.8%; ± 54.1%) and small to moderate increases in total sleep time (6.3%; ± 6.3%) and time in bed (7.3%; ± 3.6%). In addition, a small decrease in cortisol (−18.7%; ± 26.4%) and mean reaction times (−4.3%; ± 3.1%) was observed following the intervention, compared to the control. (4) Conclusions: Professional rugby players are at risk of poor sleep during pre-season training, with concomitant rises in physical stress. Implementing a sleep extension programme among professional athletes is recommended to improve sleep, with beneficial changes in stress hormone expression and reaction time performance.

Sleep and stress hormone responses to training and competition in elite female athletes

Stress hormone and sleep differences in a competition versus training setting are yet to be evaluated in elite female team-sport athletes. The aim of the current study was to evaluate salivary cortisol and perceptual stress markers during competition and training and to determine the subsequent effects on sleep indices in elite female athletes. Ten elite female netball athletes (mean ± SD; age: 23 ± 6 years) had their sleep monitored on three occasions; following one netball competition match (MATCH), one netball match simulation session (TRAIN), and one rest day (CONTROL). Perceived stress values and salivary cortisol were collected immediately pre- (17:15 pm) and post-session (19:30 pm), and at 22:00 pm. Sleep monitoring was performed using wrist actigraphy assessing total time in bed, total sleep time (TST), efficiency (SE%), latency, sleep onset time and wake time. Cortisol levels were significantly higher (p < .01) immediately post MATCH compared with TRAIN and CONTROL (mean ± SD; 0.700 ± 0.165, 0.178 ± 0.127 and 0.157 ± 0.178 μg/dL, respectively) and at 22:00 pm (0.155 ± 0.062, 0.077 ± 0.063, and 0.089 ± 0.083 μg/dL, respectively). There was a significant reduction in TST (-118 ± 112 min, p < .01) and SE (-7.7 ± 8.5%, p < .05) following MATCH vs. TRAIN. Salivary cortisol levels were significantly higher, and sleep quantity and quality were significantly reduced, following competition when compared to training and rest days.

No Compromise of Competition Sleep Compared With Habitual Sleep in Elite Australian Footballers

Purpose: To assess the impact of match-start time and days relative to match compared with the habitual sleep characteristics of elite Australian Football (AF) players. Methods: 45 elite male AF players were assessed during the preseason (habitual) and across 4 home matches during the season. Players wore an activity monitor the night before (−1), night of (0), 1 night after (+1), and 2 nights (+2) after each match and completed a self-reported rating of sleep quality. A 2-way ANOVA with Tukey post hoc was used to determine differences in sleep characteristics between match-start times and days relative to the match. Two-way nested ANOVA was conducted to examine differences between competition and habitual phases. Effect size ± 90% confidence interval (ES ± 90% CI) was calculated to quantify the magnitude of pairwise differences. Results: Differences observed in sleep-onset latency (ES = 0.11 ± 0.16), sleep rating (ES = 0.08 ± 0.14), and sleep duration (ES = 0.08 ± 0.01) between competition and habitual periods were trivial. Sleep efficiency was almost certainly higher during competition than habitual, but this was not reflected in the subjective rating of sleep quality. Conclusions: Elite AF competition does not cause substantial disruption to sleep characteristics compared with habitual sleep. While match-start time has some impact on sleep variables, it appears that the match itself is more of a disruption than the start time. Subjective ratings of sleep from well-being questionnaires appear limited in their ability to accurately provide an indication of sleep quality.