Presentation Title
Predictive Modeling of the University of Vermont Women’s Basketball Games
Abstract
Every year the University of Vermont Women’s Basketball team plays 16 games for the America East Conference. Data was collected over two seasons to create a linear model designed to predict the score of a game. Zone percentages were also collected in addition to score-book statistics. Variables in the model were first picked based on linearity, then finalized using Akaike’s Information Criterion. The resulting model was then evaluated in R. This model is intended to help the UVM Women’s Basketball Team understand what the most important factors of their games are.
Primary Faculty Mentor Name
Bernard Cole
Status
Undergraduate
Student College
College of Engineering and Mathematical Sciences
Program/Major
Statistics
Primary Research Category
Engineering & Physical Sciences
Predictive Modeling of the University of Vermont Women’s Basketball Games
Every year the University of Vermont Women’s Basketball team plays 16 games for the America East Conference. Data was collected over two seasons to create a linear model designed to predict the score of a game. Zone percentages were also collected in addition to score-book statistics. Variables in the model were first picked based on linearity, then finalized using Akaike’s Information Criterion. The resulting model was then evaluated in R. This model is intended to help the UVM Women’s Basketball Team understand what the most important factors of their games are.