A Machine Learning Approach to Player Value and Decision Making in Professional Ultimate Frisbee

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Authors

Eberhard, Braden; Miller, Jacob; Sandholz, Nate

Abstract

In this paper, we pioneer the integration of advanced metrics into Ultimate Frisbee, utilizing machine learning on a novel play-by-play dataset. By modeling completion percentage and field value, we introduce innovative metrics that more accurately assess player contributions and optimal throw choices. These tools offer valuable insights for identifying high-impact players, optimizing team strategies, and enhancing player development.