This project focuses on automated tennis player and ball tracking to support performance analysis and training. It uses computer vision techniques to detect players and the tennis ball, enabling measurement of key metrics such as player speed, ball shot speed, and shot count. YOLO (You Only Look Once) is used for real-time object detection, while Convolutional Neural Networks (CNNs) help extract court key points for accurate tracking and motion analysis. The system processes video input to provide detailed insights into player movement and shot dynamics. This solution can assist coaches, analysts, and players in improving strategies and refining performance through data-driven analysis.