In this work, we explore the relation between expressive head movement and user pro¯le information in game play settings. Facial ges- ture analysis cues are statistically correlated with players' demographic characteristics in two di®erent settings, during game-play and at events of special interest (when the player loses during game play). Experi- ments were conducted on the Siren database, which consists of 58 par- ticipants, playing a modi¯ed version of the Super Mario. Here, as player demographics are considered the gender and age, while the statistical importance of certain facial cues (other than typical/universal facial ex- pressions) was analyzed. The proposed analysis aims at exploring the option of utilizing demographic characteristics as part of users' pro¯l- ing scheme and interpreting visual behavior in a manner that takes into account those features.