Dynamic Player Significance (DPS): A new comprehensive basketball statistic David Hill Media Lab, Massachusetts Institute of Technology Cambridge, Massachusetts, USA
[email protected] 15.071 (The Analytics Edge) Final Project May 13, 2013 Abstract Dynamic player significance is a new basketball metric designed to measure each NBA player's importance, or significance, to his franchise. This metric attempts to clearly define each player's role on the team and how it fits with the team's identity. Its key aspect is that it is influenced by the on-court identity of each franchise, which is defined as the collection of factors that contribute most to a win by a given team. These factors differ for every NBA team. Therefore, two players with completely identical stats/skillsets, but different teams, will most likely have different significance values. Alternatively, if a player is traded from one team to another, his significance will differ on the new team even if his production remains constant. Hence, dynamic player significance. Here, I have broken down the components of the model and explored three case studies that clearly show how teams’ identities deviate. Additionally, player evaluations have been explored to show tendencies in the model across multiple conditions. The proposed statistic could help inform team personnel decisions and coaching strategies, in addition to gauging player effectiveness. Motivation In the NBA, one of the most important things for any team to establish is an identity. These are the traits that define a team. Often, identity is the major factor that governs all transactions, whether the team is looking for players, hiring a coach, or filling front office positions.