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In this study, we demonstrate how data from the PGA Tour, combined withstochastic shortest path models (MDPs), can be employed to refine thestrategies of professional golfers and predict future performances. We presenta comprehensive methodology for this objective, proving its computationalfeasibility. This sets the stage for more in-depth exploration into leveragingdata available to professional and amateurs for strategic optimization andforecasting performance in golf. For the replicability of our results, and toadapt and extend the methodology and prototype solution, we provide access toall our codes and analyses (R and C++).

Enhancing PGA Tour Performance: Leveraging ShotlinkTM Data for Optimization and Prediction