March Madness Tournament Predictions Model: A Mathematical Modeling Approach
Abstract
This paper proposes a model to predict the outcome of the March Madness tournament based on historical NCAA basketball data since 2013. The framework of this project is a simplification of the FiveThrityEight NCAA March Madness prediction model, where the only four predictors of interest are Adjusted Offensive Efficiency (ADJOE), Adjusted Defensive Efficiency (ADJDE), Power Rating, and Two-Point Shooting Percentage Allowed. A logistic regression was utilized with the aforementioned metrics to generate a probability of a particular team winning each game. Then, a tournament simulation is developed and compared to real-world March Madness brackets to determine the accuracy of the model. Accuracies of performance were calculated using a naive approach and a Spearman rank correlation coefficient.
Keywords
Cite
@article{arxiv.2503.21790,
title = {March Madness Tournament Predictions Model: A Mathematical Modeling Approach},
author = {Christian McIver and Karla Avalos and Nikhil Nayak},
journal= {arXiv preprint arXiv:2503.21790},
year = {2025}
}
Comments
7 pages, 5 figures