Armand McQueen
Jenna Wiens
John Guttag
Abstract: The pick and roll is a powerful tool; as former coach Stan Van Gundy once said of his Magic team, "[The pick and roll is] what we're going to be in when the game's on the line. [...] I don't care how good you are, you can't take away everything" [1]. In today's perimeter oriented NBA, the pick and roll is more important than ever before. The player tracking data that is now being collected across all arenas in the NBA holds out the promise of deepening our understanding of offensive strategies. In this paper we approach part of that problem by introducing a pattern recognition framework for identifying on- ball screens. We use a machine learning classifier on top of a rule-based algorithm to recognize on-ball screens. Tested on 21 quarters from 14 NBA games from last season our algorithm achieved a sensitivity of 82% and positive predictive value of 80%