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The main purpose of this study is to use the method of multiple linear regression to conduct a comprehensive discussion on "Factors affecting the market price of Premier League striker players". In the era of increasingly hot soccer, the transfer of stars is a big attraction in the transfer period every year, but there are still many clubs signing overpaid and underpaid players. The overall objective of this study is to find the determinants of players' price, so as to provide a reference for clubs to improve the utilization of funds in the transfer period. In this study, a dataset of player data for the 17-18 Premier League season was first downloaded via Kaggle. Then, the dataset obtained from Kaggle was used for empirical analysis to identify correlations that significantly affect the market price of players, and multiple linear regression analysis was performed after processing these data. Through the calculations, it was determined that match performance and goals scored had a significant positive impact on market value, and age and match possession had a non-significant negative impact on market value, which suggests that there is a need for the relevant team managers to optimize these aspects in order to promote a virtuous cycle of club development and team performance.
W. J. Liu (2024) studied this question.