Introduction
Sleep is widely recognised as a foundational biological process underpinning recovery, cognitive performance and physiological adaptation. In athletic populations, sleep is increasingly considered a modifiable performance variable alongside training load and nutrition. A consensus statement on sleep and the athlete reports that many athletes fail to achieve recommended sleep durations, particularly during periods of travel, competition and intensified training (Walsh et al., 2021). This article critically evaluates peer-reviewed evidence on sleep and athletic performance, with emphasis on physiological mechanisms, behavioural constraints and applied strategies relevant to coaches and athletes.
Sleep Physiology and Performance-Relevant Functions
Sleep consists of non-rapid eye movement (NREM) and rapid eye movement (REM) stages, both contributing to recovery and adaptation. Evidence indicates NREM sleep is associated with tissue repair, immune regulation and growth hormone secretion (Dattilo et al., 2011; Halson, 2014) while REM sleep is associated with memory consolidation and motor learning (Walker and Stickgold, 2006; Rasch and Born, 2013). Sleep is therefore involved in neuromuscular adaptation, cognitive processing and recovery from training load (Fullagar et al., 2015; Halson, 2014).
Consequences of Sleep Restriction
Sleep restriction has been associated with:
- Impaired cognitive performance and reaction time (Lim and Dinges, 2010; Pilcher and Huffcutt, 1996)
- Reduced endurance performance and increased perceived exertion (Fullagar et al., 2015; Halson, 2014)
- Reduced sprint and sport-specific performance (Mah et al., 2011; Waterhouse et al., 2007)
- Increased injury risk in youth athletes (Milewski et al., 2014; Watson, 2017)
- Impaired glucose regulation and insulin sensitivity (Spiegel et al., 1999; Tasali et al., 2008)
- Altered appetite regulation and increased energy intake (Taheri et al., 2004; St-Onge et al., 2016)
Why Athletes Experience Sleep Disruption
Evening training, elevated sympathetic activity, increased core temperature and travel all contribute to disrupted sleep patterns (Fullagar et al., 2015; Samuels, 2012).
Lifestyle Behaviours and Sleep
Video gaming, social media use, streaming and bedtime procrastination are all associated with delayed sleep onset and reduced sleep duration (Weaver et al., 2010; Levenson et al., 2017; Exelmans and Van den Bulck, 2016).
Caffeine and Alcohol
Caffeine reduces sleep duration and quality even when consumed up to 6 hours pre-bed (Drake et al., 2013). Alcohol disrupts REM sleep and increases nocturnal awakenings (Ebrahim et al., 2013).
Sleep Extension and Napping
Sleep extension improves sprint performance and reaction time in athletes (Mah et al., 2011). Short naps improve alertness and cognitive performance (Waterhouse et al., 2007).
Sleep Hygiene
Consistent routines and reduced evening stimulation improve subjective sleep quality but show variable objective effects (Irish et al., 2015).
Nutritional Interventions and Sleep
Nutrition may influence sleep via neurotransmitter synthesis, thermoregulation, glucose metabolism and circadian signalling, although the evidence base remains heterogeneous.
Carbohydrate Timing and Glycaemic Response
High glycaemic carbohydrate intake may reduce sleep onset latency via insulin-mediated amino acid shifts increasing tryptophan availability (Afaghi et al., 2007). However, systematic reviews highlight inconsistent findings and strong dependence on timing, dose and individual variability (St-Onge et al., 2016). In practice, carbohydrate intake should prioritise performance recovery rather than sleep manipulation.
Protein Intake and Pre-Sleep Nutrition
Pre-sleep protein ingestion does not impair sleep architecture and may support overnight muscle protein synthesis (Res et al., 2012; Trommelen and van Loon, 2016). However, there is no evidence that protein directly improves sleep quality, reinforcing its role in recovery rather than sleep optimisation.
Tart Cherry Juice
Tart cherry supplementation may improve sleep duration and efficiency, potentially via melatonin content and anti-inflammatory effects (Howatson et al., 2012; Pigeon et al., 2010). Evidence remains limited by small sample sizes and short trial durations.
Glycine Supplementation
Glycine may improve subjective sleep quality and reduce fatigue via thermoregulatory and inhibitory neurotransmission pathways (Inagawa et al., 2006; Bannai and Kawai, 2012). However, replication in athletic populations is lacking.
Magnesium
Magnesium influences neuromuscular excitability and stress regulation relevant to sleep physiology (Boyle et al., 2017). A randomised controlled trial showed improved sleep quality in older adults with insomnia symptoms (Abbasi et al., 2012). However, systematic reviews highlight limited and inconsistent evidence, with poor generalisability to young athletic populations (Boyle et al., 2017). Magnesium should therefore be targeted primarily at individuals with low dietary intake rather than used universally.
Melatonin
Melatonin is effective for circadian disruption such as jet lag but shows inconsistent benefits in healthy non-shifted populations (Herxheimer and Petrie, 2002; Ferracioli-Oda et al., 2013).
Caffeine–Sleep Interaction
Caffeine significantly impairs sleep duration and quality even when consumed 6 hours before bedtime (Drake et al., 2013; Clark and Landolt, 2017).
Wearable Sleep Tracking
Wearable devices are widely used in sport for sleep monitoring but show only moderate accuracy for total sleep time and poor accuracy for sleep staging compared with polysomnography (de Zambotti et al., 2018; Chinoy et al., 2021). Their primary value lies in tracking behavioural metrics such as sleep opportunity, bedtime consistency and wake timing rather than physiological sleep architecture. Athletic populations may experience further inaccuracies due to elevated heart rate and training stress. Psychological effects such as orthosomnia may also influence sleep perception. Wearables should therefore be used as behavioural monitoring tools rather than diagnostic instruments.
Practical Recommendations (Evidence-Graded)
Strong Evidence
- Aim for 8–10 hours sleep opportunity per night (Walsh et al., 2021)
- Avoid caffeine within 6 hours of sleep (Drake et al., 2013)
- Avoid alcohol before bedtime (Ebrahim et al., 2013)
- Maintain consistent sleep–wake schedules (Irish et al., 2015)
Moderate Evidence
- Sleep extension during heavy training (Mah et al., 2011)
- Short naps (~20–30 min) for performance and alertness (Waterhouse et al., 2007)
- Sleep hygiene strategies (Irish et al., 2015)
- Reduce evening digital stimulation (Levenson et al., 2017)
Emerging Evidence
- Tart cherry supplementation (Howatson et al., 2012)
- Glycine supplementation (Inagawa et al., 2006)
- Melatonin for jet lag/circadian disruption (Ferracioli-Oda et al., 2013)
Conclusion
Sleep is a key recovery modulator in athletic performance, with strong evidence linking restriction to impaired cognitive, metabolic and physical outcomes. However, sleep is influenced by behavioural, nutritional and environmental factors including caffeine, alcohol, digital media use and training schedules. The strongest interventions remain behavioural: increasing sleep opportunity, reducing evening stimulation and maintaining consistent routines. Nutritional and technological interventions may offer adjunct support but remain secondary to foundational sleep behaviours.
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