Sport Analytics Data for Player Performance and Financial Risk Management

This study investigates the relationship between various player characteristics and the performance metrics in professional football using sport data analytics. Utilising a data set of over 10,000 observations, the analysis employs regression models to identify the significant determinants of player performance and value. Results highlight that most factors are positively correlated and that subjective opinions on metrics which normally influence player performance and values are supported by objective evidence. These insights demonstrate the positive impacts of utilizing sport data analytics in enhancing decision-making in football. The findings also provide insights into how objective performance data can support better financial decisions in football.