Player Matching using Personal Characteristics for Asynchronous Multiplayer Exergames

Participation in regular exercise can help with maintaining good health. However, exercise interventions, including those that are game based, while successful at capturing initial interest, usually suffer from retention as adherence declines overtime. To maintain continued interest, recent efforts are exploring the effects of gradual release of game features, tailoring gamified systems to personality, and matchmaking for multiplayer games. To encourage a better workout, asynchronous experiences, where the gameplay and exercise occur at separate times, are also being designed and investigated. The experience of fun and social affiliation are good predictors of long-term intention to play, yet current player matching algorithms are poor at facilitating and utilizing social connectedness and grouping based on compatible characteristics. Grounded in psychological and sociological theories, we propose player matching based on personal characteristics as an attempt to create a more socially satisfying playing experience and address the retention problem. We start by exploring the effectiveness of pairing players based on personality types and simple game features such as competitive and cooperative team challenges. The results of our 60-day study show that grouping players based on similar personalities seems to increase the level of game engagement and retention compared to dissimilar ones. Using a storyboard approach, we further examined the effects of matching based on player types and various social features on increasing exergame retention. We found strong relationships between social game elements and player types. Correlational analyses demonstrated that the gamification element of "lottery", unlockable content, and "update and encouragement" was strongly related to the "Achiever" player type, while "virtual character", "custom goal" and "leaderboard" elements were most strongly related to both "Philanthropist" and "Socialiser" player types. We believe game designers can use these results and improve game and exercise adherence by offering more socially rewarding interactions between players through personalized features.