About this Event
Tennis Match Serve Prediction
Pravalika Kanchala
Advisor: Dr. Ying Zhu
The goal of this project is to use machine learning to analyze an available historical tennis dataset to predict the possibility of winning or losing a given tennis serve point. Tennis matches depend on a huge number of factors, making them both exciting and unpredictable. Instead of predicting the outcome using gut instincts, a machine-learning model does a better job. Often, important factors that contribute to the likeliness of winning or losing are ignored, including fatigue level, serve side, and serve direction. Our project includes these factors to create a more effective model. The dataset is trained using several methods (logistic regression, decision tree, and random forest) for classification.
Committee
Dr. Ying Zhu (chair)
Dr. Yanqing Zhang