A machine learning strategy for predicting march madness winners

The Division I NCAA Men's Basketball Tournament is a popular sporting event held annually to determine the leagues National Champion. Over the past several years the betting scene surrounding the tournament has become arguably more popular than the tournament itself, drawing in fans who bet billions overall on its outcome. In this paper, we discuss the statistical challenges in correctly predicting winners in the tournament and present a machine learning strategy for predicting the games. The Kaggle Machine Learning March Mania Competition was used to test the effectiveness of the model by comparing it against other machine-learning-based models submitted to the competition. Overall, the project was considered successful as it scored in the top 15 percentile of all submissions.