This paper analyses the link between relative market value of representative subsets of athletes in the National Basketball Association (NBA) and individual wages. NBA athletes are categorised with respect to multiple performance characteristics utilising the k-means algorithm to cluster observations and a group's market value is calculated by averaging real annual salaries. Employing GMM estimation techniques to a dynamic wage equation, we find a statistically significant and positive effect of one-period lagged relative market value of an athletess representative cluster on individual wages after controlling for past individual performance. This finding is consistent with the theory of prototype heuristic, introduced by Kahneman and Frederick (2002), that NBA teams' judgement about an athlete's future performance is based on a comparison of the player to a prototype group consisting of other but comparable athletes.