It seems that artificial intelligence (AI) is always just five years away, but it never arrives. Recently, however, developments have made the practical utility of game theory a genuine reality. Will sport provide the petri dish in which AI will prove itself? What do domain specialists like managers and coaches want to know that they can’t currently find out, and can AI provide the answer? What competitive advantages might AI provide for recruitment, performance and tactics, health and fitness, pedagogy, broadcasting, eSports, gambling and stadium design in the future? Written by leading experts in both sports management and AI, AI for Sports begins to answer these and many other questions on the future of AI for sports.

Table of Contents

Part 1 How Did We Get to Where We Are?

1 Before Turing (pre-1950)

2 The Sports Analyst Cometh

3 Sabermetrics, Moneyball and AI

Part 2 Where Are We Now?

4 Technology Closes the Gap on Theory

5 The Sports Ecosystem

6 The Performance

7 AI in the Game

8 AI around the Game

Part 3 Where Do We Go from Here?

9 A Future within the Game

10 A Future around the Game

Conclusion

About the Authors

Professor Chris Brady is currently the Chief Intelligence Officer at Sportsology, a US-based consultancy to elite sports organizations across the globe. Professor Brady has had a varied working life ranging from a line-worker at Chrysler in Detroit in his teens to managing a bookmaker's shop, from a land surveyor to a semi-professional footballer, from a naval officer to a management consultant. Prior to joining Sportsology he was most recently Professor of Management Studies at Salford University where he founded the Centre for Sports Business which focussed on the production of high quality research with a particular emphasis on statistical analytics and future trend analysis within the global sports industry.

Karl Tuyls (FBCS) is a team lead at DeepMind (Paris, France), an honorary professor of Computer Science at the University of Liverpool, UK, and a Guest Professor at the University of Leuven, Belgium. Previously, he held academic positions at the Vrije Universiteit Brussel, Hasselt University, Eindhoven University of Technology, and Maastricht University. Prof. Tuyls has received several awards with his research, amongst which: the Information Technology prize 2000 in Belgium, best demo award at AAMAS’12, winner of various Robocup@Work competitions ('13, '14), and he was a co-author of the runner-up best paper award at ICML’18. Furthermore, his research has received substantial attention from national and international press and media, most recently his work on Sports Analytics featured in Wired UK. He is a fellow of the British Computer Society (BCS), is on the editorial board of the Journal of Autonomous Agents and Multi-Agent Systems, and is editor-in-chief of the Springer briefs series on Intelligent Systems. Prof. Tuyls is also an emeritus member of the board of directors of the International Foundation for Autonomous Agents and Multiagent Systems.

Shayegan Omidshafiei is a senior research scientist in DeepMind’s Game Theory team, where he also co-leads DeepMind’s Sports Analytics effort. His research interests include multiagent systems, reinforcement learning, robotics, and control systems. He previously received his Ph.D. at the Laboratory for Information and Decision Systems (LIDS) and Aerospace Controls Laboratory (ACL) at MIT. He received a B.A.Sc. degree from the University of Toronto in 2012, and an S.M. degree in Aeronautics and Astronautics from MIT in 2015. He is co-inventor of 5 patents filed with the United States Patent Office.