Extracting common behaviours from a group of players in a serious game is interesting for game designers to understand how said players perform during the game, and also indicates some points for game improvement. Process mining is an interesting field for generating models based on the users traces, models that can be used to improve the studied process. However, when there is a large number of logs, the generated models are incomprehensible, which means that the logs need to be separated into different groups in order to obtain understandable models. In this article, we propose a method based on Formal Concept Analysis, the NextPriorityConcept and the Galactic framework to generate concepts that represent clusters of the data based on the prefix of the trace. Traces are formalized into sequences of actions then prefix common subsequences are computed to group players. Experimentation shows that our method successfully extracted common behaviour shared between players, but also strictly identical behaviour. The knowledge extracted from the traces can then be used to improve the game.