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Sleep Monitoring: Critical? Or A Snoozefest?


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Sleep–waking cycles are fundamental in human circadian rhythms and their disruption can have consequences for behaviour and performance. Athletes often have low sleep quality and quantity. Insufficient sleep among athletes may be due to scheduling constraints, competitive anxiety, training demands or disordered/disruptive sleep (Mah et al., 2011). Compared with non-athletes, athletes tend to sleep less (~6.5 h per night) and the quality of their sleep tends to be lower than non-athletes. In this report we explore how sleep quality and quantity is purported to impact athletic performance and injury risk from a theoretical perspective. Then we illustrate the importance of monitoring and analysing different components of sleep (quantity, quality and perception of fatigue) to understand how sleep impacts performance and injury risk.


Research has reported that exercise performance is negatively affected by sleep loss; however, conflicting findings mean that the extent, influence, and mechanisms of sleep loss affecting exercise performance remain uncertain. Some studies have shown that even after one night’s sleep loss, glycogen stores are reduced and objective performance (distance covered) is reduced (Skein et al., 2011).

In contrast, some maximal physical efforts and gross motor performances can be maintained. However, some studies have shown that sleep-loss does reduce sports-specific performance. The effects of sleep loss on physiological responses to exercise remain unclear, however, it appears a reduction in sleep quality and quantity could result in an autonomic nervous system imbalance, simulating symptoms of the overtraining syndrome.


There are a number of theories proposed in research to explain the impact of sleep for athletes. Three specific theories include

  • the restorative effects on the immune and the endocrine systems,
  • a neurometabolic theory suggesting that sleep assists in the recovery of the nervous and metabolic cost imposed by the waking state, and
  • cognitive development and performance, purporting that sleep has a vital role in synaptic plasticity, decision making and reaction time.

Based on the theoretical underpinnings, both sleep quality and quantity could have an impact on both contact and non-contact injury incidence. For example, decreased peripheral vision and cognitive functioning could increase risk of contact injury due to compromised reaction times. Equally, poor sleep could reduce recovery and alter immune or hormonal function resulting in higher risk of non-contact injury.


In addition to physical and physiological manifestations of changes in sleep quality and quantity, perceptual fatigue is an important component that can be used to understand how athletes’ are responding to training demands. Fatigue is a commonly used term and has many different connotations that are context dependent. For example, from a medic’s perspective fatigue may be considered a compromise of systemic function. An exercise physiologist may categorise fatigue as a reduced capacity to produce maximal force.

From an athlete’s perspective, fatigue is more commonly considered a conscious perception or sensation typically occurring from an altered physical state. However, it is largely accepted that other psychological factors also influence perceptions of fatigue. Furthermore, previous experience and memory interplay with conscious perceptions of fatigue relative to an activity. Thus monitoring fatigue can provide important information about individual athletes’ perception of their own stress and stress response mechanisms.


Optimal sleep duration appears to be dependent on both individual and task specific factors. Belenky et al., (2003) took an in-depth look at both sleep quantity and sleep quality and its effect on performance. The study found that irrespective of sleep quality those subjects with a reduced sleep duration performed worse in the psychomotor vigilance test.

There appears to be an inflection point or minimum amount of nightly sleep required to achieve a state of equilibrium in which daytime alertness and performance can be maintained which appears to be approximately 4 hours per night.

Conversely, a study by Luke et al., (2007) found that less than 7 hours sleep a night and less than a 48 hours recovery period between activities were more likely to incur an acute fatigue related injury e.g. hamstring or ACL injury resulting from altered biomechanics due to delayed activation and recruitment.


Clearly the amount of sleep required for optimal performance and recovery varies from athlete to athlete. Similar to stress monitoring, tracking sleep quality and sleep duration on a daily basis can aid in coaches and athletes understanding optimal sleep patterns and allow early identification of sleep disturbances. To illustrate our point, we have have examined the relationship between both sleep quantity and sleep quality and injury rate.


Sleep and injury data from 2012-2016 from a professional rugby league team was examined.

Interestingly, from the data we see that a higher number of sleep hours was associated with an increased training injury rate for all injuries types (contact and non-contact). Specifically, players who reported greater than 5 hours sleep were 2.7 times more likely to get injured during a training session. Notably, critical consideration is required when interpreting this information. There are a number of confounding factors that could have contributed to the elevated injury rate. For example sample size, players rarely reported less than 5 hours.

Changes in sleep quality also appeared to be associated with increased rate of training injury. For example, players reporting a large decrease in sleep quality were at higher risk of training injury than players reporting smaller changes in sleep quality.


Players who reported an increase in fatigue from average were more likely to get injured in a game than players who reported a decrease in fatigue. However, the relationship between fatigue and training injuries appeared to be different.

For this team, a decrease in fatigue was associated with higher training injury risk. Interesting, as we can see from the above example, decreased sleep quality appears to be related to a higher injury rate, conversely decreased fatigue also appears to be related to a higher injury rate. Further investigation of conflicting findings is required to establish whether players are interpreting and rating fatigue appropriately. There are also a number of confounding factors that should be considered in conjunction with this information, for example, decrease in fatigue could also be associated with decreased work load and missed training sessions resulting in a detraining effect that leaves players more susceptible to injury.

  • Game injuries
  • Training injuries


It is important to note that these findings are correlational and not causational and to understand the meaning behind these findings, other confounding factors must be considered. For example, jet-lag, travel and scheduling constraints in the lead up to a tournament or game may cause fluctuations in sleep quality and duration. Thus, sleep should be monitored regularly to identify cyclical patterns of sleep variation that relate to higher performance and lower injury rate on an individual basis. Fatigue, sleep quality and sleep quantity can be used to track recovery and stress response in player monitoring programmes. Combined with professional judgement, it is advisable that sleep and fatigue metrics are interrogated relative to both game and training injury rate to understand how these parameters relate to risk for your players.


  • Mah, C. D., Mah, K. E., Kezirian, E. J. and Dement W. C. (2011) The Effects of Sleep Extension on the Athletic Performance of Collegiate
    Basketball Players. SLEEP, Vol. 34, No. 7, 2011
  • Taylor, S. R., Rogers, G. G. and Driver, H. S. (1997) Effects of training volume on sleep, psychological, and selected physiological profiles of elite female swimmer. Medicine and Science in Sports and Exercise, Volume 29(5), May 1997, pp 688-693
  • Belenky, G., Wesensten, N. J., Thorne, D. R., Thomas, M. L., Sing, H. C., Redmond, D. P., Russo, M. B. and Balkin, T. J. (2003) Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose-response study. J. Sleep Res. (2003) 12, 1–12
  • Borresen, Jill, and Michael I. Lambert. “Quantifying training load: a comparison of subjective and objective methods.” International journal of sports physiology and performance 3.1 (2008): 16.
  • Clarke, Nick, et al. “Quantification of training load in Canadian football: application of session-RPE in collision-based team sports.” The Journal of Strength & Conditioning Research 27.8 (2013): 2198-2205.
  • Day, Meghan L., et al. “Monitoring exercise intensity during resistance training using the session RPE scale.” The Journal of Strength & Conditioning Research18.2 (2004): 353-358.
  • May, J., et al. “A Psychological Study of Health, Injury, and Performance in Athletes on the US Alpine Ski Team.” The Physician and Sportsmedicine 13.10 (1985): 111-115.
  • Galambos, S. A., et al. “Psychological predictors of injury among elite athletes.” British Journal of Sports Medicine 39:6 (2005): 351-354.



  • Athlete Monitoring
  • Performance Medicine
  • Sport Performance Analysis
  • Sports Injury Tracking
  • Sports Science

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