Profiling Players Through In-Game Animations

Current data collection methods for video-games focus on specific events or complete recordings of the gameplay sessions. The purpose of this thesis is to provide a novel method of data collection in video-games, specifically the utilisation of animation data for recording and categorising player behaviour. This alternate method is meant to be fast, with low overhead on the machine that runs it. Through this work, we conclude that animation collection is a beneficial method for data collection, and that it can be applied to future games through the development of an add-on for popular game engines.