The Dwight Effect: A New Ensemble of Interior Defense Analytics for the NBA
Basketball is a dualistic sport: all players compete on both offense and defense, and the core strategies of basketball revolve around scoring points on offense and preventing points on defense. However, conventional basketball statistics emphasize offensive performance much more than defensive performance. In the basketball analytics community, we do not have enough metrics and analytical frameworks to effectively characterize defensive play. However, although measuring defense has traditionally been difficult, new player tracking data are presenting new opportunities to understand defensive basketball. This paper introduces new spatial and visual analytics capable of assessing and characterizing the nature of interior defense in the NBA. We present two case studies that each focus on a different component of defensive play. Our results suggest that the integration of spatial approaches and player tracking data not only promise to improve the status quo of defensive analytics, but also reveal some important challenges associated with evaluating defense.