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Published on Mar 9, 2015
Research Paper presentation from the 9th MIT Sloan Sports Analytics Conference, Friday February 27, 2015, Boston, MA
Due to the ease of recording points, assists, and related goal-scoring statistics, the vast majority of advanced basketball metrics developed to date have focused on offensive production. It is straightforward to see who scored the most points in the 1985/86 season (Alex English, with 2414) or took the most 3-point shots in 1991/92 (Vernon Maxwell, with 473). However, try to look up who had the most points against in 2013/14, or who prevented the most shots from being taken that year, and the history books are, remarkably, empty. Thus we stand in a muddled state where offensive ability is naturally quantified with numerous directly-measured numbers, yet we attempt to explain defensive ability through statistics only loosely related to overall defensive ability, such as blocks and steals. Alternatively, we quote regression-based metrics such as adjusted plus/minus which give no insight into how or why a player is effective defensively. This paper bridges this gap, introducing a new suite of defensive metrics that aim to progress the field of basketball analytics by enriching the measurement of defensive play. The authors' results demonstrate that the combination of player tracking, statistical modeling, and visualization enable a far richer characterization of defense than has previously been possible. Their method, when combined with more traditional offensive statistics, provides a well-rounded summary of a player’s contribution to the final outcome of a game.