Applications & implications of data-driven analytics in the football player valuation - Islam Khandakar Tahurul; Nahid Mehzabul Hoque (SHS Web of Conferences)
This paper aims to explore the diverse applications and implications of data-driven analytics in valuing football players. The objective is to extract key themes from published papers concerning the use of data-driven analytics in football player valuation, providing insights into current practices, applications and future implications for player valuation in the context of data-driven analytics. The systematic literature review was employed to investigate the impact of data-driven analytics on football player valuation in the transfer market. This study identified key themes in football analytics, including market value estimation, data analytics and machine learning, AI’s role in sports business, strategic analysis in football management, and challenges and future directions in football analytics. The findings contribute to advancing knowledge in football analytics, offering insights for researchers, practitioners, and stakeholders interested in optimizing player valuation processes and decision-making in the football industry.