Artificial Intelligence in Football: Coaching and Decision Support

Abstract

The advent of artificial intelligence (AI) in football coaching marks a significant paradigm shifts in the way the sport is approached, understood, and played. This thesis explores the multifaceted impact of AI-driven technologies on football coaching, focusing on performance enhancement, strategic decision-making, injury prevention, and player development. Drawing upon a comprehensive literature review, this study examines the evolution of AI applications in football, from basic performance metrics to sophisticated predictive analytics and computer vision systems. Research findings highlight the transformative potential of AI in revolutionizing player analysis, tactical insights, talent scouting, and recruitment strategies. Utilizing the Technology Acceptance Model (TAM) as a theoretical framework, the thesis investigates the factors influencing the adoption of AIdriven technologies among football coaches and practitioners. Through in-depth interviews, participants' perceptions of the usefulness, ease of use, awareness, price value, facilitating conditions, and ethical considerations surrounding AI technologies in football coaching are analysed. The research findings shed light on the attitudes, beliefs, and experiences of football analysts towards AI-driven coaching tools, offering valuable insights into the adoption process and identifying key drivers and barriers to technology acceptance. Practical implications for coaches, technology developers, and sports organizations are discussed, aiming to facilitate the successful integration of AI in football coaching practices. Overall, this thesis contributes to advancing our understanding of the role of AI in football coaching, paving the way for future research and innovation in leveraging technology to optimize player performance, strategy formulation, and overall player and team success.