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Review Paper | Economics and Finance | Volume 15 Issue 7, July 2026 | Pages: 767 - 772 | India
What Factors Influence the Transfer Fees of Professional Football Players, and How Have They Been Modelled?
Abstract: This systematic review examines the factors influencing professional football transfer fees and the statistical methods used to model them. Six representative studies covering multiple linear regression, stepwise regression, machine learning, and systematic review approaches were synthesized in this review. Across the literature, player age, contract length, and performance metrics consistently emerged as the strongest predictors of transfer fees by having the most influence in determining the fee. Machine learning models generally demonstrated higher predictive accuracy than regression models but were used less frequently because of reduced interpretability. This review also identifies important research gaps, including the limited consideration of popularity, time-related variables, and non-European markets in the field as a whole. Overall, the findings of this review suggest that future research should combine broader predictor variables such as popularity and time with more diverse modeling approaches going beyond regression to improve transfer fee estimation.
Keywords: Football transfer market, Player valuation, Transfer fees, Multiple linear regression, Machine learning, SHAP, Performance metrics, Predictive modeling
How to Cite?: Reyahn Bantia, "What Factors Influence the Transfer Fees of Professional Football Players, and How Have They Been Modelled?", Volume 15 Issue 7, July 2026, International Journal of Science and Research (IJSR), Pages: 767-772, https://www.ijsr.net/getabstract.php?paperid=SR26708113259, DOI: https://dx.doi.org/10.21275/SR26708113259