A Reinforcement Learning Based Approach to Play Calling in Football

With the advances in computer power and the ability to both acquire and store huge quantities of data, so goes the corresponding advance of the machine (aka algorithm) to replace the human as a primary source of decision making. The number of successful applications is increasing at a rapid pace; in games, such as Chess and Go, medical imaging and diagnosing tumours, to automated driving, and even the selection of candidates for jobs. The notion of reinforcement learning is one key principle, whereby a game or set of decisions is studied and rewards recorded so a machine can learn long term benefits from local decisions, often negotiating a sequence of complex decisions. For example, Silver et al. (2017) discuss how a machine can become an expert at the game Go simply by playing against itself, with Bai and Jin (2020) looking at more general self-play algorithms.