We study whether experts and novices differ in the way they make predictionsabout National Football League games. In particular, we measure to what extenttheir predictions are consistent with five environmental regularities that couldsupport decision making based on heuristics. These regularities involve the hometeam winning more often, the team with the better win-loss record winning moreoften, the team favored by the majority of media experts winning more often, andtwo others related to surprise wins and losses in the teams’ previousgame. Using signal detection theory and hierarchical Bayesian analysis, we showthat expert predictions for the 2017 National Football League (NFL) seasongenerally follow these regularities in a near optimal way, but novicepredictions do not. These results support the idea that using heuristics adaptedto the decision environment can support accurate predictions and be an indicatorof expertise.
