The book and movie Moneyball makes the case that baseball statistics are a better heuristic than the traditional instinct of professional scouts and managers in determining which players to draft and where to position them in a team. On the other hand, in the film Trouble with the Curve, we get another perspective where it is the experience of an ageing scout whose wisdom (accumulated human capital) generates superior results to that produced by young university diploma stats gurus. We argue that both these heuristics advantage decision-making in sports teams. Statistical analysis represents additional time savings in the process of player engagement and positioning. The important role statistics and statistical software and hardware can play in decision-making is not new. It was long ago emphasized by Herbert Simon as he argued that in the real world of bounded rationality the brain is a scarce computational resource and these new technologies are valuable. But he also makes the point that the context within which these decisions are made is critically important. Using the Moneyball narrative, we make the case that when used together, statistics and nuanced experience generate optimal or best possible outcomes for sports teams in terms of success on the field. This conclusion sits well with Kahneman’s recent arguments on the importance of both slow and fast thinking (different types of heuristics) and of Gigerenzer’s fast and frugal heuristics to the decision-making process. We argue that integrating both approaches serves to improve our understanding of how better decisions can be made in general and within the realm of sports specifically.
|Title of host publication||Behavioural sports economics|
|Subtitle of host publication||A research companion|
|Editors||Hannah Josepha Rachel Altman, Morris Altman|
|Number of pages||19|
|Publication status||Published - 20 Dec 2021|