With basketball a lucrative and competitive sport in the US, teams have incentives to accurately project player quality. The NBA competition has become so fierce that minor details about players could have a dramatic impact on game results. For example, taking shots under pressure, from different angles, and at different times of the game are very hard to accurately assess qualitatively. Using statistical methods to assess these shots would help us identify the quality of players and would provide us with the ideal situations of taking shots. To do so, one would need to analyze every player at different points in time, and luckily we could do so by using the spatio-temporal data acquired by special techniques recently developed.
Basketball is an invasion sport, which means that players move freely during every second of the game. In order for us to evaluate a player, it is highly beneficial to consider the movements of all the players on the basketball court. A more complete understanding of a player’s performance can be achieved by taking into account the spatio-temporal considerations of movement and player interactions.