Football Data Analysis: Extracting & Visualizing Match Stats with WhoScored & GitHub скачать в хорошем качестве

Football Data Analysis: Extracting & Visualizing Match Stats with WhoScored & GitHub

Welcome back to my channel! In this video, I’m diving into football data analysis with a step-by-step tutorial on using a GitHub project to extract and visualize match stats from WhoScored. After a break due to work and family commitments, I’m thrilled to be back sharing content with you! Here’s what you’ll learn: How to set up a GitHub project originally created by Muhammad Adnan (shoutout to his amazing work!) and modified by me to focus solely on WhoScored data after FootMob extraction issues. A walkthrough of the code in Jupyter Notebook, including creating folders for HTML files and team badges. How to generate stunning visualizations like pass networks, shot maps, defensive actions, and match momentum charts—using Aston Villa vs. Brentford as an example. Key insights from the match data, such as Brentford’s dominance and Aston Villa’s clutch win. Tips for troubleshooting errors and customizing the code for your own projects. Resources: GitHub Project: https://github.com/adnaaan433/Post-Match-R... My Modified Jupyter Notebook: DM me on X @booteful_game for a copy! WhoScored: https://www.whoscored.com/ In future videos, I’ll show you how to create custom visuals using this extracted data, so hit that subscribe button and stay tuned! If you enjoy this tutorial, please like, share, and drop a comment below—I’d love to hear your thoughts. Perfect for: Football fans, data enthusiasts, and anyone curious about sports analytics with Python!