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2018 | OriginalPaper | Buchkapitel

Player Performance Evaluation in Team-Based First-Person Shooter eSport

verfasst von : David Bednárek, Martin Kruliš, Jakub Yaghob, Filip Zavoral

Erschienen in: Data Management Technologies and Applications

Verlag: Springer International Publishing

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Abstract

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.

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Fußnoten
2
In most tournaments, the map pool is limited to 7 standard maps.
 
3
Normally, we would use C to denote set of clusters, but we have selected K as they are produced by k-means to avoid ambiguity with values \(C_i\) computed for counterterrorists.
 
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Metadaten
Titel
Player Performance Evaluation in Team-Based First-Person Shooter eSport
verfasst von
David Bednárek
Martin Kruliš
Jakub Yaghob
Filip Zavoral
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-94809-6_8