Football Player Transfer Value Prediction Using Advanced Statistics and FIFA 22 Data

In football, transfers are one of the most exciting things for fans. A transfer involves a player moving from one club to another. The buying club will pay a large amount of money to the selling club to acquire the services of the player. This amount is really large and its crucial not to overpay for players for the sustainability of a club. In this study, we make use of the FIFA 22 game data and information from football data websites like FBref and Transfermarkt to accurately predict what a player is worth, using regression machine learning models. Other than player skills, we also considered important factors like age and contract remaining, which has a significant impact on transfer value. Results show that Gradient Boosting and eXtreme Gradient boosting were found to be the best algorithms. This work is beneficial for professional teams as well as football websites.