Recent advancements in computer vision have significantly impacted sports analytics by automating the collection, analysis, and interpretation of data from sports video footage. Traditionally, data collection and labeling in sports has relied heavily on manual effort, which is both time-consuming and costly. However, computer vision offers a more efficient alternative by employing advanced algorithms to extract meaningful information from video footage, thus enabling detailed insights into player movements and team tactics. Computer vision is applied across various tasks including field registration, object tracking, action recognition and detection, and pose estimation. These tasks leverage machine learning models to handle large volumes of visual data. This chapter explores how these technologies are transforming sports analytics, introducing interesting research examples and highlighting the importance of automated data collection for sports analytics.