At the highest level of sport avoiding fatigue is crucial to success. The purpose of the project is to develop a method for measuring fatigue and use this method to study of evidence of fatigue in professional tennis.
What is a suitable model for fatigue in service speeds in a professional match?
What is the extent and magnitude of fatigue in grand slam tennis?
Point level outcomes for all points played at the 4 major events of the calendar--the Grand Slams--from 2014 to 2018. Each row corresponds to a point in a match and includes information about the server, receiver, speed of the serve, serve number and the point outcome.
Using service speed as the outcome, we will develop a Bayesian dose-response model to relate the time in the match (indexed by serve number, point number, or actual time) to the expected service speed. Effects for different servers will be incorporated thru a hierarchical structure.
Burris, K., & Coleman, J. (2018). Out of gas: quantifying fatigue in MLB relievers. Journal of Quantitative Analysis in Sports, 14(2), 57-64.
Kruschke, J. (2014). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan. Academic Press.