Sporting events can be seen as controlled, real-world, miniature laboratory environments, approaching the idea of "holding other things equal" when exploring the implications of decisions, incentives, and constraints in a competitive setting (Goff and Tollison 1990, Torgler 2009). Thus, a growing number of studies have used sports data to study decision making questions that have guided behavioural economics literature. Creative application of sports data can offer insights into behavioural aspects with implications beyond just sports. In this chapter, we will discuss the methodological advantages of seeing sport as a behavioural economics lab, concentrating on the settings, concepts, biases, and challenging areas. Beyond that, we will discuss questions that have not yet been analysed, offering ideas for future studies using sports data. We will further reflect on how AI has evolved; focusing, for example, on chess, which provides insights into the mechanism and machinery of decision-making.