The utility of a quantitative model depends on the extent to which its fitted parameters vary systematically with environmental events of interest. Professional football statistics were analyzed to determine whether play selection (passing versus rushing plays) could be accounted for with the generalized matching equation, and in particular whether variations in play selection across game situations would manifest as changes in the equation's fitted parameters. Statistically significant changes in bias were found for each of five types of game situations; no systematic changes in sensitivity were observed. Further analyses suggested relationships between play selection bias and both turnover probability (which can be described in terms of punishment) and yards-gained variance (which can be described in terms of variable-magnitude reinforcement schedules). The present investigation provides a useful demonstration of association between face-valid, situation-specific effects in a domain of everyday interest, and a theoretically important term of a quantitative model of behavior. Such associations, we argue, are an essential focus in translational extensions of quantitative models.
Keywords: choice; concurrent schedules; football; generalized matching equation; play selection.