March Madness Tournament Predictions Model: A Mathematical Modeling Approach
This is an incremental improvement for sports analytics enthusiasts and bracket predictors, applying a simplified version of an existing model to specific data.
The paper tackled predicting March Madness tournament outcomes using historical NCAA basketball data, resulting in a model that simulates games and compares accuracy to real brackets with performance metrics like Spearman rank correlation.
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.