Maps for Reasoning in Ultimate.

Existing statistical ultimate (Frisbee) analyses rely on data aggregates to produce numeric statistics, such as completion percentage and scoring rate, that assess strengths and weaknesses of individuals and teams. We leverage sequential, location-based data to develop completion and scoring maps. These are visual tools that describe the aggregate statistics as a function of location. From these maps we observe that player and team statistics vary in meaningful ways, and we show how these maps can inform throw selection and guide both offensive and defensive game planning. We validate our model on real data from highlevel ultimate, show that we can characterize both individual and team playing, and show that we can use map comparisons to highlight team strengths and weaknesses.