Football Prediction System is a web app that predicts football match outcomes using machine learning, statistics, and live data. Built with HTML, CSS, JavaScript, Python, and Flask, it analyzes historical stats like goals, form, and xG. It uses models such as Random Forest and Logistic Regression to generate predictions. Live APIs provide real-time updates, making the system dynamic, data-driven, and useful for football insights and analysis.
Inspired by my passion for football and curiosity about data, I built this project to explore how machine learning can reveal patterns behind match outcomes. It combines sports, statistics, and coding to turn raw data into meaningful insights about the game.
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