Zach Miller, Student, M.S. Business Analytics and Data Science, Oklahoma State University
Weston Salmon, Student - M.S. Business Analytics and Data Science, Oklahoma State University
The National Basketball Association (NBA) has long been a league where impressive events happen on a regular basis. Because of this the standard for noteworthy achievements has been raised time and time again. You will frequently see social media posts from top sports accounts regarding players scoring 30+ points or incredible dunks. However, you rarely see a post about a comeback victory unless the team overcame the insurmountable odds of being down by, what appears to be, too many points to win. This presentation considers the individual plays, players, and salary figures that give a team the best chance at achieving a comeback victory. Descriptive analytics are used to gain valuable insights into how often a team can produce a comeback when trailing by ten or more points at half, which teams are achieving them most often, which players are most involved in producing comebacks and the salaries of those players. The focus for the predictive portion of the analysis is on predicting the involvement of players based on their career stats and salary figures and the types of plays NBA teams can prioritize to achieve comeback victories more often.
