Did a true change occur? Improving analytical decisions for serial performance testing in sport.

Monitoring strategies are used to assess athletes physical readiness to maximize performance. These data are used to assist practitioners and coaches in making decisions about the volume and intensity of the upcoming training, practice, and competition. Often, these measurements are serial in nature, where the athlete is evaluated for longitudinal changes over the course of a competitive season. The target of these strategies is commonly directed at determining whether the athlete has recovered from the most frequent bout of training or competition or adapted to the current training. Sport scientists seek to identify individualized athlete changes from serial measurements to understand how the athlete is responding to their training and competitive demands to optimize performance. Within this paper, we demonstrate novel individualistic probabilistic Bayesian methods that improve analytical based decisions concerning true athletic changes during serial (i.e., repeated) measures. We then discuss practical examples, providing open access computer code and data, to assist the practitioner in creating future scalable resources.