Sleep Of Athletes Research Articles

The Potential Impact of Heat on Athletes' Sleep at the Paris 2024 Olympics and Paralympics Games

AbstractIn 2024, Paris will host the Olympic (during July and August) and Paralympic (during September) Summer Games. Despite temperatures often exceeding 40°C in Paris in July, the International Olympic Committee (IOC) has indicated that there will be no installation of air conditioning in the athletes' rooms. High ambient temperatures can impair the quantity and quality of sleep and, consequently, impair athletic performance. In this overview, we present the rationale behind and explain the process of how a warm environment is unfavorable to the sleep of Olympic and Paralympic athletes, as well as offer practical recommendations on how to mitigate the effects of environment heat for a restful and effective night's sleep during the Paris 2024 Olympics and Paralympics Games.

Sleep deprivation and recovery: Endurance racing as a novel model.

The aim of this study was to investigate sleep-wake behavior and gain insights into perceived impairment (sleep, fatigue, and cognitive function) of athletes competing in two international multi-day adventure races. Twenty-four athletes took part across two independent adventure races: Queensland, Australia and Alaska, USA. Individual sleep periods were determined via actigraphy, and racers self-reported their perceived sleep disturbances, sleep impairment, fatigue and cognitive function. Each of these indices was calculated for pre-, during- and post-race periods. Sleep was severely restricted during the race period compared to pre-race (Queensland, 7:46 [0:29] vs. 2:50 [1:01]; Alaska, 7:39 [0:58] vs. 2:45 [2:05]; mean [SD], hh:mm). As a result, there was a large cumulative sleep debt at race completion, which was not 'reversed' in the post-race period (up to 1week). The deterioration in all four self-reported scales of perceived impairment during the race period was largely restored in the post-race period. This is the first study to document objective sleep-wake behaviors and subjective impairment of adventure racers, in the context of two geographically diverse, multi-day, international adventure races. Measures of sleep deprivation indicate that sleep debt was extreme and did not recover to pre-race levels within 1week following each race. Despite this objective debt continuing, perceived impairment returned to pre-race levels quickly post-race. Therefore, further examination of actual and perceived sleep recovery is warranted. Adventure racing presents a unique scenario to examine sleep, performance and recovery.

The training times of athletes could play a role in clinical sleep problems due to their associations with sleep difficulty scores

ObjectivesSleep is a key component of athletic recovery, yet training times could influence the sleep of athletes. The aim of the current study was to compare sleep difficulties in athletes across different training time groups (early morning, daytime, late evening, early morning plus late evening) and to investigate whether training time can predict sleep difficulties. MethodsAthletes from various sports who performed at a national-level (n = 273) answered the Athlete Sleep Screening Questionnaire (ASSQ) along with several other questionnaires related to demographics, exercise training, and mental health. From the ASSQ, a Sleep Difficulty Score (SDS) was calculated. Transformed SDS (tSDS) was compared across different training time categories using multiple one-way ANOVAs. A stepwise regression was then used to predict tSDS from various sleep-related factors. ResultsSDSs ranged from none (31%), mild (38%), moderate (22%), and severe (9%). However, the one-way ANOVAs revealed training earlier or later vs. training daytime shifted the tSDS in a negative direction, a trend toward increased sleep difficulty. In particular, athletes training in the late evening (>20:00 or >21:00) had a significantly higher tSDS when compared to daytime training (p = .03 and p < .01, respectively). The regression model (p < .001) explained 27% of variance in the tSDS using depression score, age, training time, and chronotype score. ConclusionAmong a heterogeneous sample of national-level athletes, 31% displayed moderate to severe SDSs regardless of their training time. However, when athletes trained outside daytime hours there was a tendency for the prevalence of sleep difficulties to increase.

Exhausted by design: coaching, care, and sleep in the NCAA

This article explores a growing cultural preoccupation with sleep in college sports and the implications of this trend for coach researchers and practitioners. Using an interdisciplinary framework, this work adds to conversations about care in coaching from a socio-cultural perspective. While new interest in the sleep of college athletes could be seen as compassionate, it is vital for coaches to be aware of the politics and consequences of sleep-enhancement frameworks. Issues around rest and recovery can reveal the limits of care and how well-intended coaching strategies that incorporate sleep may ultimately undermine athlete welfare and deflect attention from the systematic and ecological foundations of wellbeing in sport and society.

Sleep Status and Chronotype in University Athletes with and without Chronic Low Back Pain: A Cross-Sectional Study

Abstract Objective This study aimed to evaluate the status of sleep, chronotype, and related variables of university athletes with and without chronic low back pain (CLBP),to find the correlation between CLBP, sleep difficulty score (SDS), and chronotype, and to determine if SDS and chronotype predict CLBP. Methods Ninety-two university athletes [46 with CLBP (Age: 22.08±2.74 years) and 46 healthy athletes (Age: 22.32±3.11 years) completed the athlete sleep screening questionnaire (ASSQ), also, their demographic, anxiety, depression, and sports-related details were collected. A Pearson correlation and logistic regression models (univariate and multivariate) were used for the statistical analysis. Results The results demonstrated a higher SDS and evening type preference in CLBP athletes, a significant negative correlation between CLBP and chronotype (r = −0.40, p&lt;0.01), a significant correlation between SDS and CLBP (r = 0.25, p = 0.01). SDS and chronotype were not found to be significant independent predictors of CLBP. Conclusion This study concludes that there exists a correlation of CLBP, SDS, and chronotype However, despite the relationship, SDS and chronotype cannot predict CLBP.

Sleep, Nutrition, and Injury Risk in Adolescent Athletes: A Narrative Review.

This narrative review explores the impact of sleep and nutrition on injury risk in adolescent athletes. Sleep is viewed as essential to the recuperation process and is distinguished as an active participant in recovery through its involvement in growth, repair, regeneration, and immunity. Furthermore, the literature has shown that the sleep of athletes impacts elements of athletic performance including both physical and cognitive performance, recovery, injury risk, and mental well-being. For sleep to have a restorative effect on the body, it must meet an individual's sleep needs whilst also lasting for an adequate duration and being of adequate quality, which is age-dependent. The literature has suggested that athletes have increased sleep needs compared to those of the general population and thus the standard recommendations may not be sufficient for athletic populations. Therefore, a more individualised approach accounting for overall sleep health may be more appropriate for addressing sleep needs in individuals including athletes. The literature has demonstrated that adolescent athletes achieve, on average, ~6.3 h of sleep, demonstrating a discrepancy between sleep recommendations (8-10 h) and actual sleep achieved. Sleep-wake cycles undergo development during adolescence whereby adaptation occurs in sleep regulation during this phase. These adaptations increase sleep pressure tolerance and are driven by the maturation of physiological, psychological, and cognitive functioning along with delays in circadian rhythmicity, thus creating an environment for inadequate sleep during adolescence. As such, the adolescent period is a phase of rapid growth and maturation that presents multiple challenges to both sleep and nutrition; consequently, this places a significant burden on an adolescent athletes' ability to recover, thus increasing the likelihood of injury. Therefore, this article aims to provide a comprehensive review of the available literature on the importance of sleep and nutrition interactions in injury risk in adolescent athletes. Furthermore, it provides foundations for informing further investigations exploring the relation of sleep and nutrition interactions to recovery during adolescence.

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

ABSTRACT 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.

P095 Factors associated with sleep and mental health problems following athletic retirement

Abstract Introduction Despite growing research on the sleep and mental health of athletes, there is limited literature on their sleep health following retirement from sport. The aim of this study was to investigate potential factors associated with symptoms of sleep and mental health disorders in former athletes. Methods Former athletes (N=173, 50% women) who retired from any sport or competition level ≤20 years ago completed an online survey, consisting of the Athlete Sleep Screening Questionnaire (ASSQ), Personal Wellbeing Index-Adult (PWI-A), Center for Epidemiologic Studies Depression Scale-Revised (CESD-R), and Generalised Anxiety Disorder Assessment (GAD-7). Results Self-disclosed lifetime diagnosis of sleep disorder(s) and mental health disorder(s) was reported by 28.3% and 45.1% of former athletes, respectively. Binary logistic regressions showed that age (OR=0.95[95% CI:0.92, 0.99], p=.007) and gender (OR=2.28[95% CI:1.09, 4.79], p=.029) were associated with anxiety symptoms, with women and younger ex-athletes presenting greater risk. Increased BMI was associated with risk for sleep disordered breathing (OR=1.20[95% CI:1.10, 1.30], p&amp;lt;.001), sleep difficulty (OR=1.13[95% CI:1.03, 1.23], p=.008), and poor wellbeing (OR=0.91[95% CI:0.85, 0.98], p=.010). Those who placed a lower priority on sport whilst competing had greater risk for sleep disordered breathing (OR=2.00[95% CI:1.05, 3.80], p=.035). Recency of retirement was not associated with any measures. Discussion Findings indicate that former athletes are not exempt from poor sleep and mental ill-health. Results provide preliminary insight into predictive factors for difficulty transitioning out of sport. Future longitudinal research should consider the interplay between sport reintegration and the timing of sleep and mental health problems.

The Impact Of Post-Competitive Sleeping Hours On The Sleep Quality Of Female Pencak Silat Athletes

This research is motivated by the large number of pencak silat athletes who pay less attention to the quality of their sleep after competing. As a result of these issues, the aim of this study is to find out how the quality of sleep and sleep habits of athletes in the post-competition stage have an impact on the performance and psychology of pencak silat athletes in the future and how important it is for athletes to maintain good sleep quality in order to maintain their post-martial arts achievements competition. This study used a qualitative correlation technique using a PSQI (the Pittsburgh Sleep Quality Index) questionnaire distributed via a Google Form. The people who participated in this study were female pencak silat athletes from several areas in West Java from different clubs or universities, for a total of 46 persons who were consequently rejected by 6 people, which resulted in 40 female pencak silat athletes. The technique used for sampling is Non-random sampling is also called probability sampling. Based on the results of the study, it was stated that there was a positive relationship between hours of sleep after competition and the sleep quality of female pencak silat athletes, The results reveal a significance level of &lt;0.05 based on the linear test and single correlation using the SPSS 25 application. The conclusions from this study conclude that the good or bad hours of sleep of athletes after competition can impact their quality of sleep in the next competition.

The impact of long haul travel on the sleep of elite athletes

In order to manage and implement strategies to alleviate the symptoms of jet lag it is essential to assess the impact of jet lag in athletes. The aim of this study was to assess the impact of long haul eastward travel on elite athletes' (n = 7 elite national track cyclists; male n = 3, and female n = 4) sleep. The athletes’ sleep was monitored before, during and after travel using both actigraphy and self-report measures. Participants wore an activity monitor for 5 days prior to travel, during the long haul travel and 5 days upon arrival at their destination and completed a daily online sleep diary Actigraphy highlighted significant reductions in time in bed, total sleep time and sleep efficiency (%) due to long haul eastward travel, particularly in the 48 h after travel. Sleep diary data exhibited significant reductions in time in bed, total sleep time, sleep efficiency, sleep quality and a significant increase in fatigue going to bed as a result of long haul eastward travel. In order to facilitate the development of interventions to reduce the symptoms and severity of jet lag objective and subjective assessments of sleep should be coupled with assessments of chronotype and perceived sleep need.

Impact of COVID-19 Infection on Cardiorespiratory Fitness, Sleep, and Psychology of Endurance Athletes-CAESAR Study.

COVID-19 has a deteriorating impact on health which is especially important for endurance athletes (EAs) who need to maintain continuity of training. The illness affects sleep and psychology, which influence sport performance. The aims of this study were: (1) to assess the consequences of mild COVID-19 on sleep and psychology and (2) to assess the consequences of mild COVID-19 on cardiopulmonary exercise test (CPET) results. A total of 49 EAs (males = 43, 87.76%; females = 6, 12.24%; age = 39.9 ± 7.8 years; height = 178.4 ± 6.8 cm; weight = 76.3 ± 10.4 kg; BMI = 24.0 ± 2.6 kg·m-2) underwent a maximal cycling or running CPET pre- and post-COVID-19 and completed an original survey. Exercise performance deteriorated after COVID-19 (maximal oxygen uptake, VO2max = 47.81 ± 7.81 vs. 44.97 ± 7.00 mL·kg·min-1 pre- and post-infection, respectively; p < 0.001). Waking up at night affected the heart rate (HR) at the respiratory compensation point (RCP) (p = 0.028). Sleep time influenced pulmonary ventilation (p = 0.013), breathing frequency (p = 0.010), and blood lactate concentration (Lac) (p = 0.013) at the RCP. The maximal power/speed (p = 0.046) and HR (p = 0.070) were linked to the quality of sleep. Stress management and relaxation techniques were linked with VO2max (p = 0.046), maximal power/speed (p = 0.033), and maximal Lac (p = 0.045). Cardiorespiratory fitness deteriorated after mild COVID-19 and was correlated with sleep and psychological indices. Medical professionals should encourage EAs to maintain proper mental health and sleep after COVID-19 infection to facilitate recovery.

The Influence of Coaches and Support Staff on the Sleep Habits of Esports Athletes Competing at Professional and Semiprofessional Level

The present study investigated the influence and perspective of esports coaches and support staff on the sleep habits of esports athletes competing at professional and semiprofessional levels. Eighty-four esports coaches and support staff from 19 countries completed an online questionnaire. The first section obtained demographic information. The second section evaluated sleep hygiene knowledge using the Sleep Beliefs Scale. The third section assessed sleep monitoring and sleep hygiene practices used by coaches and support staff with esports athletes, barriers to the use of these practices, and conditions that impact the sleep of esports athletes. Overall, sleep hygiene knowledge was inadequate (&lt;75%, based on the study of Miles et al.). Sleep monitoring frequency was low (48.8%), while sleep hygiene practices were implemented more often (66.7%). The most common barrier to sleep monitoring and sleep hygiene practices was players not liking it (50% and 46.3%, respectively). Night competitions (64.6%), congested competition times (51.2%), and night training schedules (47.6%) all rated highly as having an impact on esports athletes’ sleep. Sleep education and training for coaches and support staff in the optimal use of sleep monitoring and sleep hygiene practices may increase the frequency and quality of sleep health support provided to esports athletes.

Sleep and nutritional profile of endurance and ultra-endurance running athletes.

Sleeping and eating before and during an ultramarathon can directly affect an athlete's performance, who may also have their physiological adaptations and recovery process hindered by sleeping problems. Endurance and ultra-endurance athletes may have different sleep and nutrition profiles. Thus, this study aimed to describe the sleep profile (during preparation) and nutritional profile (during competition) of endurance (10-20km) and ultra-endurance (50-100km) running athletes. For this, 16 healthy volunteers answered questionnaires related to sleep quality (Pittsburgh sleep quality index), chronotype (morningness-eveningness questionnaire), and sleepiness (excessive daytime sleepiness questionnaire). Immediately after a competition, a form prepared by the research team about nutritional variables and volunteers' food records during the competition was applied. According to test scoring criteria (Pittsburgh sleep quality index >5; sleepiness >10), endurance running athletes showed low sleep quality. In addition, all athletes showed consumption of carbohydrates and lipids below the recommended, but excessive consumption of proteins. A positive association between sleepiness and sodium intake in endurance runners was observed (r=0.862; p=0.027). Sleep efficiency and race time showed a negative correlation only for ultra-endurance athletes (r=-0.834; p=0.039). The data obtained show that endurance athletes presented more sleep pattern alterations, however, endurance and ultra-endurance athletes showed inadequate nutritional consumption during the competition.

The Impact of Dietary Factors on the Sleep of Athletically Trained Populations: A Systematic Review.

Many athletic populations report poor sleep, especially during intensive training and competition periods. Recently, diet has been shown to significantly affect sleep in general populations; however, little is known about the effect diet has on the sleep of athletically trained populations. With sleep critical for optimal recovery and sports performance, this systematic review aimed to evaluate the evidence demonstrating that dietary factors influence the sleep of athletically trained populations. Four electronic databases were searched from inception to May 2022, with primary research articles included if they contained a dietary factor(s), an outcome measure of sleep or sleepiness, and participants could be identified as ‘athletically trained’. Thirty-five studies were included, with 21 studies assessed as positive quality, 13 as neutral, and one as negative. Sleep or sleepiness was measured objectively in 46% of studies (n = 16). The review showed that evening (≥5 p.m.) caffeine intakes >2 mg·kg−1 body mass decreased sleep duration and sleep efficiency, and increased sleep latency and wake after sleep onset. Evening consumption of high glycaemic index carbohydrates and protein high in tryptophan may reduce sleep latency. Although promising, more research is required before the impact of probiotics, cherry juice, and beetroot juice on the sleep of athletes can be resolved. Athletic populations experiencing sleep difficulties should be screened for caffeine use and trial dietary strategies (e.g., evening consumption of high GI carbohydrates) to improve sleep.

Sleep Knowledge, Beliefs and Practices in Youth Sports Coaches and Science Support Staff

Background: The primary purpose of this study was to assess sleep hygiene knowledge among coaches and sports science support staff working with youth athletes, their sleep practices implemented with athletes, and their sleep education. Materials and methods: A sample of 139 Polish coaches and sports science support staff working with youth athletes volunteered to complete a survey focused on sleep monitoring, hygiene practices, and sleep education. The Sleep Beliefs Scale (SBS) was also included. Results: Overall sleep hygiene knowledge was inadequate for the whole sample (14.86 ± 2.70, score range 0 - 20; mean ± SD). However, the overall SBS score for science support staff was adequate (15.44 ± 2.71) and significantly higher than the inadequate score obtained by coaches (14.48 ± 2.65, p = 0.013). Less than half (48%) of coaches and science support staff promoted or administered sleep hygiene strategies, and only 17% monitored sleep of youth athletes. Most coaches and science support staff (only 35% of “Yes” responses) were not educated in sleep knowledge. However, there were significant differences between coaches and science support staff (28 % vs 46 %, respectively; p = 0.030) in their education in the field of sleep hygiene. Conclusions: Coaches working with youth athletes had inadequate overall sleep hygiene knowledge, while sports science support staff’s knowledge was adequate. Sleep hygiene strategies, sleep monitoring practices, and sleep education of coaches and science support staff seemed to be limited. We suggest that a broader approach to sleep education in youth sports staff might be necessary to improve sleep practices in youth athletes.

Evaluation of a Brief Sleep Intervention Designed to Improve the Sleep, Mood, and Cognitive Performance of Esports Athletes.

This study evaluated a brief sleep intervention designed to improve the sleep, mood, and cognitive performance of professional electronic sports (esports) athletes from three major esports regions (i.e., Asia, North America, and Oceania). Fifty-six esports athletes from South Korea (N = 34), the United States (N = 7), and Australia (N = 15) completed the study. Participants completed an initial 2-week pre-intervention phase to establish a baseline, followed by a 2-week intervention phase that involved a group sleep education class, 1:1 session with a trained clinical psychologist, and daily biofeedback. A wrist activity monitor and daily sleep diary were used to monitor sleep during both phases, while at pre- and post-intervention, participants completed a battery of sleep and mood questionnaires and underwent cognitive performance testing. Sleep knowledge increased from pre- to post-intervention (d = 0.83 [95% CI −1.21, −0.43], p =< 0.001), while there were modest improvements in sleep diary estimates (i.e., sleep onset latency (Mdiff = −2.9 min, p = 0.02), sleep onset time (Mdiff = −12 min, p = 0.03), and sleep efficiency (Mdiff = 1.1%, p = 0.004)) and wrist activity monitor estimates (i.e., sleep onset time (Mdiff = −18 min, p = 0.01)). Insomnia severity scores decreased significantly (d = 0.47 [95% CI 0.08, 0.84], p = 0.001), while sleepiness scores increased but not meaningfully (d = 0.23 [95% CI −0.61, 0.14], p = 0.025). However, there was no significant change in mood (i.e., depression and anxiety) or cognitive performance scores (i.e., mean reaction time or lapses). Sleep interventions for esports athletes require further investigation. Future research should examine whether a stepped-care model, whereby increasing therapeutic input is provided as needed, can optimize sleep, mood, and cognitive performance outcomes.

How Do the Habitual Sleep Patterns of Elite Female Basketball and Soccer Athletes Compare With the General Population?

To compare the habitual sleep of female basketball and soccer athletes to age- and sex-matched controls and to characterize the sleep of basketball and soccer athletes at different competition locations and on the days surrounding competition. Using an observational case-control design, 41 female participants were recruited to participate, consisting of 11 basketball athletes (mean [SD]: age = 24.1 [4.9]y), 10 soccer athletes (24.8 [6.4]y), and 20 nonathletic controls (24.2 [2.8]y). Sleep was monitored using actigraphy for four 7-day periods throughout the preseason and subsequent competition season. Generalized linear models were used to analyze the effect of group and competition situation (eg,Home or Away) on sleep. During habitual conditions, basketball athletes had longer sleep durations (7.4 [1.5]h) than soccer athletes (7.0 [1.2]h, P < .001) and controls (7.3 [1.2]h, P = .002). During competition, basketball and soccer athletes had longer sleep durations following home (7.7 [1.7] and 7.2 ± 1.3h) compared with away games (6.8 [1.8] and 7.0 [1.3]h). In addition, basketballers went to bed earlier (23:49 [01:25]) and woke earlier (07:22 [01:59]) following away games compared with soccer athletes (00:10 [01:45] and 08:13 [01:45]). Basketballers had longer habitual sleep durations compared with soccer athletes and nonathletic controls. During competition, basketballers had earlier bed and wake times compared with soccer athletes following away games, highlighting the need for individualized sleep strategies.

Sleep and Athletes

Sleep is recognized as an essential component to optimize health and human performance, and as such the topic is of increasing interest to athletes. Yet, the sleep of athletes is affected by multiple sports-specific, and societal factors. Hence the recent emergence of the important role of sleep science in athlete health and performance. This review focuses on the fundamentals of sleep physiology and elaborates on the affects sleep has on athlete health and performance. Despite sports practitioners recognizing the importance of sleep on health and performance, findings report that insufficient sleep, and poor sleep quality are prevalent among athletic populations. This paper will describe sleep in athletes, define sleep characteristics, discuss the impact of sleep restriction following travel and competition, and strategies to mitigate sleep difficulties. Sleep is arguably the most undervalued pillar of health and performance.

Subjective Sleep Patterns and Jet Lag Symptoms of Junior Netball Players Prior to and During an International Tournament: A Case Study.

To assess the impact of long-haul transmeridian travel on subjective sleep patterns and jet lag symptoms in youth athletes around an international tournament. An observational descriptive design was used. Subjective sleep diaries and perceived responses to jet lag were collected and analyzed for a national junior netball team competing in an international tournament. Sleep diaries and questionnaires were completed daily prior to and during travel, and throughout the tournament. Results were categorized into pretravel, travel, training, and match nights. Means were compared performing a paired Student t test with significance set at P < .05. Data are presented as mean (SD) and median (minimum, maximum). Athletes reported significantly greater time in bed on match days compared with training (P < .001) and travel (P = .002) days, and on pretravel days compared with travel (P < .001) and training (P = .028) days. Sleep ratings were significantly better on pretravel days compared with match (P = .013) days. Perceived jet lag was worse on match (P = .043) days compared with pretravel days. Significant differences were also observed between a number of conditions for meals, mood, bowel activity, and fatigue. Youth athletes experience significantly less opportunity for sleep during long-haul transmeridian travel and face disruptions to daily routines during travel which impact food intake. Young athletes also experience disturbed sleep prior to and during competition. These results highlight the need for practices to alleviate jet lag symptoms and improve the sleep of young athletes traveling for tournaments in an effort to optimize recovery and performance.

Does Caffeine Consumption Influence Postcompetition Sleep in Professional Rugby League Athletes? A Case Study.

To examine the sleep of rugby league athletes the night before and following an evening match and to investigate the association between caffeine intake and sleep on the night of competition. On the night prior to, night of, and night after a professional rugby league match, 15 athletes had their sleep monitored using wrist activity monitors. Additionally, saliva samples were collected 60 minutes before and 30 minutes after the competition to assess salivary caffeine concentration. Differences in sleep across the 3 nights were examined using linear mixed models, and changes were assessed using effect size (ES). Pearson correlation (r) assessed the relationship between salivary caffeine levels and sleep indices. On the night of competition, athletes went to bed later than the night before (P = .00002, ES = 1.84) and night after (P = .0003, ES = 1.49) competition. Consequently, their sleep duration was reduced on the night of competition compared with the previous night (P < .0000003, ES = 2.36) and night after competition (P = .001, ES = 1.53). Postcompetition salivary caffeine concentration was substantially elevated in athletes when compared with precompetition measures (P < .00000001, ES = 4.44), and moderate, nonsignificant correlations were observed between changes in salivary caffeine concentration and delayed bedtime (r = .48, P = .07), increased sleep latency (r = .45, P = .09), decreased sleep duration (r = -.30, P = .28), and reduced sleep efficiency (r = -.34, P = .22). These results demonstrate that evening competition results in sleep disturbance in rugby league athletes, and caffeine supplementation prior to and during competition leads to substantial increases in postcompetition salivary caffeine concentration.