This group project for STA 160 at UC Davis consists of home run analysis in the 2021 MLB season. I was responsible for the model building portion for predicting home runs by batters, where I used a logistic regression model, a logistic generalized additive model, and neural networks model. I calculated the misclassification rates to determine which is the best model for predicting home runs. The data is collected through the baseball-scraper package in python which webscrapes from Statcast and Fangraphs.