Comparative Analysis of Data Driven Techniques to Predict Transfer Prices of Football Players

Football clubs from all around the world are in constant business of buying and selling players each transfer window. These transactions of signing and selling players involve multi-million dollar deals. Therefore, it is essential for buyer clubs to estimate the cost of acquiring the services of a player they have set their eyes upon before they make the decision of spending millions of dollars for that particular player. This need has caught the attention of researchers, statisticians and enthusiasts of the sport, which has led to the development of several techniques and platforms which predict the how much the player would cost. Transfermarkt is one such platform which relies heavily on its community to decide market values of players. This assessment is subjective and results in inconsistencies. As a result, there is a proliferation in the number of data-driven techniques being developed to statistically predict price of players. In this paper, we review and compare such several data-driven techniques for predicting player prices in the footballing world.