Crowdsourcing is a new Web phenomenon, in which a firm takes a function once performed in-house and outsources it to a crowd, usually in the form of an open contest. Designing efficient crowdsourcing mechanisms is not possible without deep understanding of incentives and strategic choices of all participants. This paper presents an empirical analysis of determinants of individual performance in multiple simultaneous crowdsourcing contests using a unique dataset for the world’s largest competitive software development portal: TopCoder.com. Special attention is given to studying the effects of the reputation system currently used by TopCoder.com on behavior of contestants. We find that individual specific traits together with the project payment and the number of project requirements are significant predictors of the final project quality. Furthermore, we find significant evidence of strategic behavior of contestants. High rated contestants face tougher competition from their ...