Optimizing performance in cycling through machine learning - Boone, J.; Latré, S.; Verdonck, T. (Journal of Science and Cycling, 2023)
In professional sports, optimal performance requires a balance between training and subsequent recovery. To follow-up on this balance, it is important to monitor training load, symptoms of fatigue and predict changes in performance. At present, performance is mostly monitored and predicted based on white-box mathematical models, which were historically based on rigorously configured test protocols and taken under controlled settings with a moderate number of athletes. While these models have clear scientific evidence and provide great value, they are often too coarse grained to assess and predict subtle changes in performance. Moreover, in monitoring performance through e.g., lactate tests, the disruption of the athlete`s training schedule can also not be neglected.