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Is it possible to predict the motivation of players just by observing theirgameplay data? Even if so, how should we measure motivation in the first place?To address the above questions, on the one end, we collect a large dataset ofgameplay data from players of the popular game Tom Clancy's The Division. Onthe other end, we ask them to report their levels of competence, autonomy,relatedness and presence using the Ubisoft Perceived Experience Questionnaire.After processing the survey responses in an ordinal fashion we employpreference learning methods based on support vector machines to infer themapping between gameplay and the reported four motivation factors. Our keyfindings suggest that gameplay features are strong predictors of playermotivation as the best obtained models reach accuracies of near certainty, from92% up to 94% on unseen players.

Your Gameplay Says It All: Modelling Motivation in Tom Clancy's The Division