Abstract
In this paper, we present novel winning team predicting models and compare the accuracy of the obtained prediction with TrueSkill model of ranking individual players impact based on their impact in team victory for the two most popular online games: “Dota 2” and “Counter-Strike: Global Offensive”. In both cases, we present game analytics for predicting winning team based on game statistics and TrueSkill.
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Acknowledgments
The work was supported by the Russian Science Foundation under grant 17-11-01294 and performed at National Research University Higher School of Economics, Russia. We would like to thank Alexander Semenov and Petr Romov for their piece of advice.
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Makarov, I., Savostyanov, D., Litvyakov, B., Ignatov, D.I. (2018). Predicting Winning Team and Probabilistic Ratings in “Dota 2” and “Counter-Strike: Global Offensive” Video Games. In: van der Aalst, W., et al. Analysis of Images, Social Networks and Texts. AIST 2017. Lecture Notes in Computer Science(), vol 10716. Springer, Cham. https://doi.org/10.1007/978-3-319-73013-4_17
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