Football AI Tutorial: From Basics to Advanced Stats with Python

This post provides a comprehensive tutorial on enhancing football AI analysis using Python. It covers detecting and tracking players, ball, and referees on the pitch, using Sly embeddings to divide players into teams, and employing keypoint detection and homography to create advanced visualizations like radar views and Voronoi diagrams. The guide is approachable for those with basic Python knowledge, with models and data publicly available for ease of replication. The tutorial uses tools like YOLO V8, Google Colab, and the Roboflow platform for model training and deployment.