Document Type
Thesis
First Faculty Advisor
Dr. Suhong Li
Second Faculty Advisor
Thomas Dougherty
Keywords
March Madness; data analysis
Publisher
Bryant University
Rights Management
CC - BY - NC - ND
Abstract
One of the more exciting and hardest parts of the men's college basketball postseason tournament, named March Madness, is to pick who wins each game and determine the overall champion of the tournament. The data analysis conducted will help determine the overall tournament winner. A machine learning model is implemented using college basketball metrics from previous years to determine the overall winner of this prestigious tournament in 2025. The model was able to pick up the winner in 2024. The result also finds that the most important features in determining the winner of the tournament are shooting guard height, small forward height, center height, wins above bubble and defensive rebound percentage. Being able to understand the most important variables in determining a winner of the tournament can help individuals in picking the winner in their March Madness bracket groups, which is where the results can lead to implementation or future study.
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons
Comments
This research and data analysis project had been developed during my Junior and Senior years at Bryant University as part of the Honors Program. The project was developed and presented to students and faculty and hasn't been published before.