Player Performance Evaluation in Team-Based First-Person Shooter eSport
Electronic sports or pro gaming have become very popular in this millenium and the increased value of this new industry is attracting investors with various interests. One of these interest is game betting, which requires player and team rating, game result predictions, and fraud detection techniques. This paper discusses several aspects of analysis of game recordings in Counter-Strike: Global Offensive game including decoding the game recordings, matching of different sources of player data, quantifying player performance, and evaluation of economical aspects of the game.
KeywordsE-sport Data analysis Data integration Data quality Player rating
This work was supported by project PROGRES Q48.
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