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.