All major league sports teams are interested in projecting the performance of their players into the future. The seemingly most important feature of a model to project future performance is age. On average, players tend to improve from their rookie (earliest) season in the league, until they retire from the league (due to poor performance or injuries, for example). In this project we apply Functional Principal Component Analysis (FPCA) to the careers of NHL players in order to fit individual aging curves for each player. We compare the results of three methods: ImFuncPCA, SOAP and PACE.
Copyright is held by the author(s).
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Member of collection