The following paper presents the players profiling methodology applied to the turn-based computer game in the audience-driven system. The general scope are mobile games where the players compete against each other and are able to tackle challenges presented by the game engine. As the aim of the game producer is to make the gameplay as attractive as possible, the players should be paired in a way that makes their duel the most exciting. This requires the proper player profiling based on their previous games. The paper presents the general structure of the system, the method for extracting information about each duel and storing them in the data vector form and the method for classifying different players through the clustering or predefined category assignment. The obtained results show the applied method is suitable for the simulated data of the gameplay model and clustering of players may be used to effectively group them and pair for the duels.