A Bayesian adjusted plus-minus analysis for the esport Dota 2

Clark Nicholas (), Macdonald Brian and Kloo Ian ()
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Clark Nicholas: Department of Mathematical Sciences, United States Military Academy, West Point, NY, USA
Macdonald Brian: ESPN Inc, Bristol, CT, USA
Kloo Ian: Department of Systems Engineering, United States Military Academy, West Point, NY, USA

Journal of Quantitative Analysis in Sports, 2020, vol. 16, issue 4, 325-341

Abstract: Analytics and professional sports have become linked over the past several years, but little attention has been paid to the growing field of esports within the sports analytics community. We seek to apply an Adjusted Plus Minus (APM) model, an accepted analytic approach used in traditional sports like hockey and basketball, to one particular esports game: Defense of the Ancients 2 (Dota 2). As with traditional sports, we show how APM metrics developed with Bayesian hierarchical regression can be used to quantify individual player contributions to their teams and, ultimately, use this player-level information to predict game outcomes. In particular, we first provide evidence that gold can be used as a continuous proxy for wins to evaluate a team’s performance, and then use a Bayesian APM model to estimate how players contribute to their team’s gold differential. We demonstrate that this APM model outperforms models based on common team-level statistics (often referred to as “box score statistics”). Beyond the specifics of our modeling approach, this paper serves as an example of the potential utility of applying analytical methodologies from traditional sports analytics to esports.

Keywords: adjusted plus minus; Bayesian hierarchical regression; Dota2; esports (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1515/jqas-2019-0103

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