Football Players Market Value Prediction Using Machine Learning

Abstract — Soccer clubs spend enormous amount of money to buy professional soccer players each year during the transfer window. Predicting the value of a player in the transfer market is one of the difficult tasks for a club manager. Transfermarkt.com uses football professionals to determine the value of a player. Due to the need for crowdsourcing, is rarely updated with many users participating, are error prone, and data scientists use this topic to use data from around the world. And create a dataset and an estimation method. The data-driven method seems to be an alternative approach for crowd-driven website to estimate the market value of player. Regression analysis was used to estimate the market value of players. Player stats like height, weight, player position, speed, physic, overall, potential, defending, dribbling, passing and mentality is selected as the training dataset.