Machine Learning Application in Assessment and Prediction of Effectiveness of Transfer Deals in Football

Student: Kambachekov Timur

Educational Programme: Data Science and Business Analytics (Bachelor)

Year of Graduation: 2024

Present study is aimed to tackle transfer deals assessment in football with the application of machine learning learning methods. The research derives a transfer effectiveness assessment metric and uses boosting algorithms, like XGBoost, Catboost and LightGBM in different approaches to predict players' market value after the transfer deal and use it to present the efficiency metric, which could be used by clubs to predict the success of the future transfer.

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