ParardhaKumar/Football-Analytics

Sports Analytics and Data Visualisation Using Python

With the advent of more and more talents in the field of football it is imperative for football club managers to negotiate transfer deals effectively to ensure that the club’s finances are not harmed. This project aims to propose a model for professional football players and club managers with basic guidelines for making better career decisions that would result in the collective benefit of the entire team. The research is based on a case study of twenty forward players from the football clubs participating in various European Football Leagues. For every player, the total time played, numbers of goals, assists, shots on target, shots off target are taken into account and subsequently calibrated points are calculated accordingly using simulation and optimization techniques. Results show that the combination of two strikers of the same level will not benefit the team compared to a good striker paired with an average one. Also, players tend to lose confidence when they get less playing time which affects their performance, and consequently, the performance of the team. This reversible process slowly weakens a player and leads to a change of clubs which can have potential repercussions on the player’s career. The project also introduces a concept of spikes which are quantitative indicators that can be used to help players as well as club-managers in making important career decisions.