Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

8-2009

Abstract

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 point-scaling 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.

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Science and Engineering

Publication

2009 IEEE Social Computing: Workshop on Social Intelligence in Applied Gaming, Vancouver, August 29-31

First Page

1199

Last Page

1204

ISBN

9780769538235

Identifier

10.1109/CSE.2009.452

Publisher

IEEE Computer Society

City or Country

Los Alamitos, CA

Additional URL

https://doi.ieeecomputersociety.org/10.1109/CSE.2009.452

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