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Who Will Score? A Machine Learning Approach to Supporting Football Team Building and Transfers

Faculty of Telecommunications, Computer Science and Electrical Engineering, UTP University of Science and Technology, 85-796 Bydgoszcz, Poland
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Entropy 2021, 23(1), 90; https://doi.org/10.3390/e23010090
Received: 14 December 2020 / Revised: 5 January 2021 / Accepted: 7 January 2021 / Published: 10 January 2021
(This article belongs to the Special Issue Theory and Applications of Information Theoretic Machine Learning)
Background: the machine learning (ML) techniques have been implemented in numerous applications, including health-care, security, entertainment, and sports. In this article, we present how the ML can be used for building a professional football team and planning player transfers. Methods: in this research, we defined numerous parameters for player assessment, and three definitions of a successful transfer. We used the Random Forest, Naive Bayes, and AdaBoost algorithms in order to predict the player transfer success. We used realistic, publicly available data in order to train and test the classifiers. Results: in the article, we present numerous experiments; they differ in the weights of parameters, the successful transfer definitions, and other factors. We report promising results (accuracy = 0.82, precision = 0.84, recall = 0.82, and F1-score = 0.83). Conclusion: the presented research proves that machine learning can be helpful in professional football team building. The proposed algorithm will be developed in the future and it may be implemented as a professional tool for football talent scouts. View Full-Text
Keywords: machine learning; big data; football support; sports analytics machine learning; big data; football support; sports analytics
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MDPI and ACS Style

Ćwiklinski, B.; Giełczyk, A.; Choraś, M. Who Will Score? A Machine Learning Approach to Supporting Football Team Building and Transfers. Entropy 2021, 23, 90. https://doi.org/10.3390/e23010090

AMA Style

Ćwiklinski B, Giełczyk A, Choraś M. Who Will Score? A Machine Learning Approach to Supporting Football Team Building and Transfers. Entropy. 2021; 23(1):90. https://doi.org/10.3390/e23010090

Chicago/Turabian Style

Ćwiklinski, Bartosz; Giełczyk, Agata; Choraś, Michał. 2021. "Who Will Score? A Machine Learning Approach to Supporting Football Team Building and Transfers" Entropy 23, no. 1: 90. https://doi.org/10.3390/e23010090

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