Date of Award


Document Type

Thesis open access


Computer Science

First Advisor

Matthew Hibbs

Second Advisor

Yu Zhang


Sports prediction has always been an interesting problem in the entertainment industry. Many data scientists have come out different methods on this problem. We hope to see how well a neural network model can predict an individual game outcome and the final ranking on NBA data. We examined the possibility of different unbiased deep learning models can perform as well as other mathematics methods. We were also looking for what types of data are more influential for the models. Then, we can make some assumptions on our models and the other sports prediction methods.