This article looks into the nature of cognitive associations between verbs and argument structure constructions (ASCs). Existing research has shown that distributional and semantic factors affect speakers' choice of verbs in ASCs. A formal account of this theory has been proposed by Ellis, O'Donnell, and Römer, who show that the frequency of production of verbs within an ASC can be predicted from joint verb–construction frequency, contingency of verb–construction mapping, and prototypicality of verb meaning. We simulate the verb production task using a computational model of ASC learning, and compare its performance to the available human data. To account for individual variation between speakers and for order of verb preference, we carry out two additional analyses. We then compare a number of prediction models with different variables, and propose a refined account of verb selection within ASCs: overall verb frequency is an additional factor affecting verb selection, while the effects of joint frequency and contingency may be combined rather than independent.