A Deep Learning Approach to Predict Football Match Result

Abstract

Football is the most watched and most played sport in the world. The 21st century there were approximately 250 million football players and over 1.3 billion people interested in football. Predicting the outcome of football matches has always been a topic of great interest among sports enthusiasts, analysts, and betting enthusiasts. With the rise of deep learning techniques and the availability of vast amounts of data, there has been an increased interest in developing accurate predictive models for football match results. This thesis presents a comprehensive study on using deep learning algorithms to predict the outcome of football matches. The goal is to leverage the power of deep learning models to improve prediction accuracy and provide valuable insights into the factors that influence match outcomes.