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  • Writer's pictureJo Clubb

Athlete Sleep Tracking: Navigating the Problems and Pitfalls

In January, many people, including sports science practitioners and athletes, resolve to improve their sleep. The importance of sleep for everyday health is well established across society. For athletes meanwhile, sleep stands as a cornerstone for physical and mental recovery.


While I’ll briefly mention the benefits of sleep tracking, this post primarily explores the potential pitfalls. Do we adequately consider these downsides? Are they out of our control now that sleep tracking has widely become the athlete’s individual choice? In light of these reflections, I’ll provide practical strategies for sports science practitioners to effectively collect and utilise sleep tracking data in the applied environment.

 

The Benefits of Sleep Tracking

In the pursuit of optimal athletic performance, athletes and sports science support teams are increasingly turning to technology to gain insights into their athletes. In my 10 Challenges in Sports Science eBook I described this as the ‘technology tsunami’. Two decades ago, a heart rate belt might have been a luxury; now, athletes are immersed in technology throughout their training day.


Wearable technology ushered in a new era for athletes; personal devices. While hardcore endurance athletes have traditionally taken much of their training tracking into their own hands, other athletes, particularly in team sports, often lacked direct access to their data. Devices like smartwatches and sleep trackers provide a window into an athlete's physiological responses, allowing for (in theory) a nuanced understanding of their readiness and recovery.


The wealth of information from sleep trackers can contribute to the development of personalised insights, enabling athletes to make informed decisions about their recovery strategies. While sleep hygiene education has been delivered to athletes for many years, the accessibility of personal sleep data fosters improved awareness and buy-in on this topic. As such, wearables are not just integral tools for monitoring sleep patterns but also in promoting engagement and education.

 

The Dangers of Sleep Tracking

Few would argue against the earlier points. However, while the benefits of sleep tracking are apparent, there are associated dangers that athletes and practitioners must navigate.

 

Sleep Tracking Precision

Wearables often come to market ahead of independent research studies. While the untrained eye make take their data to be ‘perfect’, sports scientists scrutinise them with a critical eye. We understand the nuance of validity, reliability, and sensitivity, seeking to establish them from impartial sources. However, in practical terms, we cannot consistently rely on the gold standard – lab-based polysomnography (PSG) – for regular and affordable data collection.


So, the Precision Practicality Tradeoff leads us to the personal devices but with a sense of caution. While research on these devices is somewhat limited, findings seem consistent. Generally, sleep trackers can precisely categorise sleep and wake (i.e. two-stage categorisation), but show significantly reduced sensitivity for detecting different sleep stages (i.e. four-stage categorisation). This has been demonstrated in both Whoop bands (Miller et al., 2021) and Oura rings (de Zambotti et al., 2019).


A hynogram, which is a graph displaying sleep stages throughout the course of a night. A commonly available sleep ring is compared to the gold standard PSG measurement.
Research compares CST to gold-standard PSG. Hypnogram (sleep stages plotted as a function of time of the night) from de Zambotti et al., (2019) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6095823/

Despite being aware of these limitations, I still find myself captivated by my own sleep stage data. The shiny user interface and smooth data visualisations captivate my attention every morning, influencing my perceptions of my own sleep quality. And I’m supposed to be a scientist!


This challenge is backed by research, with patients’ perceptions proving difficult to alter despite education on the evidence of poor accuracy (Baron et al., 2022). Clearly, the discussion on metric precision needs to be an ongoing one. Athletes should be aided in understanding which metrics they can rely on and which to approach with caution.


This notably applies to cumulative ‘Readiness’ or ‘Recovery’ Scores. These measures amalgamate data from various metrics into a single number. As we’ve discussed before, simplifying complex constructs like recovery and readiness, or wellness and training load, into one number is widely appealing. However, it doesn't guarantee accuracy! Moreover, we lack clarity on how (in)accurate these scores are. Caution is certainly warranted.

 

The Stress of Sleep Tracking

In the cleverly sub-titled journal article; I Am so Good at Sleeping that I Can Do It with My Eyes Closed and My Fitness Tracker on Me, the social phenomenon "orthosomnia" is described. This refers to the obsessive pursuit of optimal sleep metrics based on fitness tracker or mobile phone app data.


The continual pursuit for an “optimal” sleep duration, Readiness or Recovery Score can create undue stress, counteracting the very purpose of using such technology for performance enhancement. How does an athlete respond if they wake up on a gameday morning to a ‘Recovery Score’ of 23%? From my experience it depends on the athlete in question; some don’t even blink, while others let it fester.


Indeed, researchers worry that “the widespread practice of self-monitoring of sleep using CST (consumer sleep technology) leads to a sleep paradox, in which preoccupation with perfect sleep induces stress, anxiety and arousal, compromising rather than improving sleep” (Jahrami et al., 2023). Given that many athletes also demonstrate perfectionist, even obsessive tendencies, they may be at even greater risk of this paradox.


preoccupation with perfect sleep induces stress, anxiety and arousal, compromising rather than improving sleep

Let’s not overlook that sport itself is seldom designed to optimise sleep. The demands of training and competition schedules, early morning training sessions, late-night games, and frequent travel pose challenges for consistent and quality sleep. Athletes often find themselves in unfamiliar sleeping environments, such as hotel rooms, which may disrupt their sleep patterns. Additionally, supplementation, particularly with high caffeine intake, can create a perfect storm for athletes. Even with the best intentions, achieving optimal sleep practices proves challenging for athletes.

 

Data Privacy and Security Concerns

As wearable technology infiltrates the realm of athletics, data privacy and security concerns come to the forefront. In 2022, FIFPRO and FIFA took a significant step by launching the Charter of Player Data Rights, aligning with the principles of the General Data Protection Regulation (GDPR). This charter grants professional footballers specific rights related to their data, emphasising the need for informed consent, data access, and protection.


Football clubs and practitioners must be acutely aware of these data privacy issues. The handling of data derived from wearable devices, including sleep trackers, necessitates a thorough understanding of GDPR principles in Europe, or the equivalent in other areas (e.g., Health Insurance Portability and Accountability Act [HIPAA] compliance in the United States). As discourse on these key topics increases, sleep tracking data may be one of the most sensitive that we deal with.

 

Strategies to Optimise Sleep Tracking for Sports Science Practitioners

Let me be clear - I am in favour of sleep tracking. As I write this, I have my own sleep ring on my finger. However, it is essential to consider drawbacks, especially when biased in favour of something. We’ve previously discussed the dangers of naïve interventionism and sleep trackers present another potential illustration of iatrogenics.


So with these potential pitfalls in mind, here are key strategies for practitioners to collect and utilise sleep tracking data effectively:


Research Data Precision and User Experience: Conduct background research on wearable devices, for both team-based solutions and individual athlete devices. Use a mixture of academic (published research) and anecdotal exploration (from peers, athletes and even yourself).


Respect Individual Decisions: Given the off-site nature of this data collection, the decision to participate in sleep tracking should be down to the individual athlete.


Use Flexible Adoption Strategies: Sleep tracking does not have to be all or nothing. Athletes may benefit from wearing devices selectively, such as excluding the night before competition. Alternatively, implement sleep tracking for a temporary period of time (e.g., four-week project) before giving athletes a break from the data collection.


Clarify Data Access: Emphasise data privacy and security. Make sure athletes know who has access to their data. If they are personal devices rather than team solutions, discuss data access but respect if/who athletes permit to view their data.


Education, Education, Education: Provide athletes with the knowledge to interpret their sleep data critically. Avoid overemphasising numerical scores or targets and encourage a qualitative understanding of sleep patterns. Athletes should be aware that deviations from the norm might be natural and not necessarily indicative of a performance issue.


Use Anonymised Data and Trends for Storytelling: This data can be valuable evidence for discussions with players and coaches. Patterns or case studies can support approaches or interventions, particularly with scheduling discussions, such as adjusting training or meeting start times to help support the team’s sleep strategies.


Contextualise Data with Training Loads: Correlate sleep data with athletes' training loads. Identify patterns between intense training periods and variations in sleep quality or duration. This contextual understanding will aid in distinguishing between fatigue induced by training and potential sleep-related issues.


Integrate Sleep Data into Multivariate Analysis: Incorporate sleep data into performance and/or injury modelling. As long as access is permitted, sleep tracking data can provide another data stream to analyse the dose-response relationship on a team and/or individual athlete level.



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