Analysis of Significant Factors in Division I Men's College Basketball and Development of a Predictive Model

Abstract

While a number of statistics are collected during an NCAA Division I men’s college basketball game, it is potentially of interest to universities, coaches, players, and fans which of these variables are most significant in determining wins and losses. To this end, statistics were collected from two seasons of games and analyzed using logistic and least squares regression methods. The differences between the two competing teams in four common statistics were found to be significant to determining victory: assists, free throw attempts, defensive rebounds, and turnovers. The logistic and least squares models were then used with data from the 2011- 2012 season to verify the accuracy of the models. To determine the accuracy of the models in predicting future game outcomes, four prior game median statistics were collected for teams competing in a sample of games from 2011-2012, with the differences taken and used in the models.