research-article

Analyzing the Differences between Professional and Amateur Esports through Win Probability

Authors:

Peter Xenopoulos,

William Robert Freeman,

Claudio SilvaAuthors Info & Claims

WWW '22: Proceedings of the ACM Web Conference 2022

Pages 3418 - 3427

https://doi.org/10.1145/3485447.3512277

Published: 25 April 2022 Publication History

Abstract

Estimating a team’s win probability at any given point of a game is a common task for any sport, including esports, and is important for valuing player actions, assessing profitable bets, and engaging fans with interesting metrics. Past studies of win probability in esports have relied on data extracted from matches held in well-structured and organized professional tournaments. In these tournaments, players play on set teams, oftentimes where players are well acquainted with all participants. However, there has been little study of win probability modeling in casual gaming environments – those where players are randomly matched – even though these environments form the bulk of gaming hours played. Using interpretable win probability models trained on large CSGO data sets, we improve upon the current state of the art in Counter-Strike: Global Offensive (CSGO) win probability prediction. We identify important features, such as team HP and equipment value, across different skill levels. We also find a small benefit to using Elo-based player skill estimates in predicting win probability. Furthermore, we discuss how our win probability models can be used to investigate the problem of player-leaving in competitive matchmaking.

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Cited By

Elbert NPaskovski EStein NFlath C(2023)The Layers of Change: Multilevel Adaptations to Exogenous Game Patches in CS:GO2023 IEEE Conference on Games (CoG)10.1109/CoG57401.2023.10333215(1-4)Online publication date: 21-Aug-2023
https://doi.org/10.1109/CoG57401.2023.10333215
Białecki AJakubowska NDobrowolski PBiałecki PKrupiński LSzczap ABiałecki RGajewski J(2023)SC2EGSet: StarCraft II Esport Replay and Game-state DatasetScientific Data10.1038/s41597-023-02510-710:1Online publication date: 8-Sep-2023
https://doi.org/10.1038/s41597-023-02510-7

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Analyzing the Differences between Professional and Amateur Esports through Win Probability

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cover image ACM Conferences

WWW '22: Proceedings of the ACM Web Conference 2022

April 2022

3764 pages

ISBN:9781450390965

DOI:10.1145/3485447

Editors:
Frédérique Laforest
INSA Lyon, France
,
Raphaël Troncy
EURECOM, France
,
Elena Simperl
King’s College London, UK
,
Deepak Agarwal
Pinterest, USA
,
Aristides Gionis
KTH Royal Institute of Technology, Sweden
,
Ivan Herman
W3C / retired
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Lionel Médini
Université Lyon 1, France

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Published: 25 April 2022

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WWW '22: The ACM Web Conference 2022

April 25 - 29, 2022

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Cited By

Elbert NPaskovski EStein NFlath C(2023)The Layers of Change: Multilevel Adaptations to Exogenous Game Patches in CS:GO2023 IEEE Conference on Games (CoG)10.1109/CoG57401.2023.10333215(1-4)Online publication date: 21-Aug-2023
https://doi.org/10.1109/CoG57401.2023.10333215
Białecki AJakubowska NDobrowolski PBiałecki PKrupiński LSzczap ABiałecki RGajewski J(2023)SC2EGSet: StarCraft II Esport Replay and Game-state DatasetScientific Data10.1038/s41597-023-02510-710:1Online publication date: 8-Sep-2023
https://doi.org/10.1038/s41597-023-02510-7

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