With technology evolving and opening new doors to behavior insights different fields are using advanced models to reduce error and burnout enhancing productivity and results.
Sports are using it with incredible support from science.. One example is Mitchell Smith, a Ph.D. student in the Faculty of Health at the University of Technology Sydney. He has spent extensive time testing athletes to their mental limit to find out what impact fatigue has on performance.
In his study, he focused on the effects of mental fatigue on intermittent running performance. By exposing athletes to a different context that affect mental fatigue, some variables were measured such as velocity, heart rate, oxygen consumption, blood glucose and lactate concentrations, and ratings of perceived exertion (RPE) were measured throughout the 45-min intermittent running protocol. This study demonstrated that mental fatigue significantly reduced velocity at low intensities, whereas high-intensity running and peak velocities were not significantly affected. Ratings of perceived exertion during the intermittent running protocol were not significantly different between conditions despite lower overall velocity in the mental fatigue condition, concluding that mental fatigue impairs intermittent running performance. This negative effect of mental fatigue seems to be mediated by a higher perception of effort.
On an article published by Wired on Benfica, Portugal’s 2017 Primeira Liga’s Champion, the importance of data gathering and analysis is presented as a critical factor for success. Since as the put it, “Every club is looking for prediction models,” in order to improve athlete's performance and recovery. Right now the club has very good models for players stress and fatigue, but now machine learning can help to explore this even more. The usage of machine learning presents itself as the game changer shedding light on subtle patterns that are invisible to the naked eye. “The future of sports is trending towards data dependence – making it actionable will be key,” says Steve Fox, leading software engineering manager at Microsoft, who works with S.L. Benfica.
Using platforms like Performetric allows staff can dig into it, understand more about the athletes and predict their future fitness, recovery and performance levels. This information can also be sliced and visualized to provide personnel with the critical information they need.