TY - GEN
T1 - Inferring player rating from performance data in massively multiplayer online role-playing games (MMORPGs)
AU - Shim, Kyong Jin
AU - Ahmad, Muhammad Aurangzeb
AU - Pathak, Nishith
AU - Srivastava, Jaideep
PY - 2009
Y1 - 2009
N2 - This paper examines online player performance in EverQuest II, a popular massively multiplayer online role-playing game (MMORPG) developed by Sony Online Entertainment. The study uses the game's player performance data to devise performance metrics for online players. We report three major findings. First, we show that the game's point-scaling system overestimates performances of lower level players and underestimates performances of higher level players. We present a novel pointscaling system based on the game's player performance data that addresses the underestimation and overestimation problems. Second, we present a highly accurate predictive model for player performance as a function of past behavior. Third, we show that playing in groups impacts individual performance and that player-level characteristics alone are insufficient in explaining an individual's performance, which calls for a different set of performance metrics methods.
AB - This paper examines online player performance in EverQuest II, a popular massively multiplayer online role-playing game (MMORPG) developed by Sony Online Entertainment. The study uses the game's player performance data to devise performance metrics for online players. We report three major findings. First, we show that the game's point-scaling system overestimates performances of lower level players and underestimates performances of higher level players. We present a novel pointscaling system based on the game's player performance data that addresses the underestimation and overestimation problems. Second, we present a highly accurate predictive model for player performance as a function of past behavior. Third, we show that playing in groups impacts individual performance and that player-level characteristics alone are insufficient in explaining an individual's performance, which calls for a different set of performance metrics methods.
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U2 - 10.1109/CSE.2009.452
DO - 10.1109/CSE.2009.452
M3 - Conference contribution
AN - SCOPUS:70849127985
SN - 9780769538235
T3 - Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009
SP - 1199
EP - 1204
BT - Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009 - 2009 IEEE International Conference on Social Computing, SocialCom 2009
T2 - 2009 IEEE International Conference on Social Computing, SocialCom 2009
Y2 - 29 August 2009 through 31 August 2009
ER -