Sports (Football) match predictor

Abstract

Football match prediction has gained significant attention in recent years, especially with the advent of machine learning models. This thesis presents the development and implementation of a predictive model for football match outcomes, leveraging historical team and player statistics. The model employs Scikit-learn logistic regression model„ combined with supporting statistical techniques, to estimate match results, probable goal scorers, and influential factors behind predictions.The vital use of LLM for subjective information incorporation, this research provides a comprehensive analysis of football match forecasting, considering multiple parameters such as team performance, player attributes, and league statistics, with an website at the end demonstrating the fruitful results.