It’s Mean to Just Look at the Average: Athletic Sleep Research and Data
The purpose of today's training is to defeat yesterday's understanding.
Many of us love sports; they provide escapism from our day-to-day lives, and can be a means for us to socialize, band together and enjoy the pursuit of victory. The chance to sit back and watch teams battle each other, such as football or basketball, or individual athletes compete in a sport that requires a high level of skill, timing and precision, such as boxing or mixed martial arts, draws us into the world of sports.
What equally draws our attention is what these athletes do outside of competition to prepare for such events. We want to know their strength and conditioning routines, diet and mindset, and in the last five to 10 years, we have wanted to know more about their recovery strategies such as sleep, sleep timing, and sleep before and after a competition. Famous athletes such as Tom Brady and LeBron James have publicly spoken about the importance of sleep, specifically as they get older. Irish rugby scrum half player Peter Stringer played rugby into his forties and credits a focus on sleep, nutrition and recovery to his longevity in the sport. I have worked with elite athletes over 30 years old to focus specifically on these areas in Major League Baseball (MLB) and Formula 1 (F1). Athletes at this level grapple with repeated competition, such as baseball with 162 games in a season, the duration of the competition, such as an F1 race, and travel and jet lag associated with travelling the world to compete. Therefore, a focus on sleep and recovery is paramount to an athlete’s performance.
But how much do we know about sleep, recovery and performance in elite athletic populations? How good is the research? Are the practitioners' approaches to athletes adequate? Since 2010 we have observed a significant increase in the quantity and quality of athletic research. More than 80% of this research is original and the vast majority of it has taken place in the last five years.
Two main countries have contributed to this research. They are Australia, where I live (although I am from Ireland), and the United States. Australia is also home to the top four academic institutions that publish this research, including the Australian Institute of Sport; Central Queensland University; University of Technology Sydney and the University of Western Australia, where I am currently an adjunct senior research fellow.
While this increase in research and research outputs is excellent, the current approach is generally geared towards collecting large data sets to appease the statistical power required to find an effect over time or prove an intervention. Achieving large-scale data or repeated data collection over a day, week/s or season becomes cumbersome and difficult with athletes who are often overburdened with lots of data collection. It gets in the way of the technical aspect of the sport and the sport-specific training. Imagine asking players to self-report one to two times a day their fatigue, sleepiness or mood and then imagine that over an entire season. The athlete and the coaches start viewing the data collection as non-value adding and a pain to keep collecting over time.
In many studies, the focus has been on group data to collect sleep-wake behaviors over time using wearable devices such as actigraphy and sleep diaries or questionnaires. This helps generate group
or team data to identify trends on specific days or nights, home versus away games, and for extended travel or periods of extreme jet lag. In addition, coaches and performance staff can use this data to plan
practice times, travel, recovery and media engagements. However, we may be losing out with this approach as we are missing so much related to the individuals who make up that data point with standard deviation. We tend to lack the focus on the individual athlete, and there is a scarcity of studies in athletic populations aimed to support the individual athlete.