Comparing Player Rating Awarding Systems: Evaluating Performance Metrics in Soccer: An in-Depth Analysis of Rating Methodologies and Their Impact on Player Assessment and Team Performance

The primary objective of this paper is to develop a method for accurately and consistently rating football players. A secondary objective is to evaluate the suitability of artificial neural networks for this purpose, particularly with the available data. To address these objectives, data was collected from various sources, including APIs and the WhoScored website via web scraping. Multiple solutions were explored for implementing the player rating system, encompassing both AI-based and mathe-matical approaches. In the pursuit of AI-based models, ratings provided by WhoScored were utilized as a target due to their recognized precision and consistency. Following the implemen-tation of various models, comprehensive testing and evaluation using diverse metrics and methods were conducted to identify the most effective approach, or determine if certain models are better suited for specific scenarios. Overall, this research contributes to the integration of data from multiple sources to enhance player rating methodologies in football analysis.