FPSRec: Football Players Scouting Recommendation System based on Generative AI

Player scouting in soccer is witnessing a surge of interest from the research community. Traditional scouting methods are often limited by subjectivity and biases in evaluation. Moreover, the lack of structured data and models hinders the progress of the field. To overcome these limitations, we introduce a novel player recommendation system which integrates similarity techniques and generative artificial intelligence. It aims to support player recruitment by providing a data-driven and inclusive approach. The novelty of our work lies in its use of advanced machine learning and artificial intelligence to accurately predict player potential and performance by similarity measures, thereby mitigating the influence of subjective biases that often affect talent identification. Our contributions represent a significant advancement in the field of sports analytics and talent identification, offering a more equitable and efficient approach to scouting and recruitment. The results obtained underscore the effectiveness of the proposed system, demonstrating the transformative potential of artificial intelligence in revolutionizing talent scouting.