This research aims to contribute to the scientific debate on financial performance in football organizations by evaluating the enabling role of talent management practices. Grounded in Resource-Based Theory (RBT) and Transaction-Cost Economics (TCE), the analysis highlights the financial impact of strategic decisions made by sports directors. Using a two-step machine learning approach, the study reveals that investing in academies can yield higher financial returns. The findings confirm that teams adopting this strategy are better positioned to meet the financial objectives set by international and national regulators, such as UEFA and FIFA. By addressing the knowledge gap on the role of youth sector development in financial performance, this research offers valuable insights for both academia and sports management.
Keywords: Football, Machine Learning, Transfermarkt, Sport Finance, Resource-Based View
