A Bayesian adjusted plus-minus analysis for the esport Dota 2
No Thumbnail Available
Authors
Clark, Nicholas J.
Macdonald, Brian
Kloo, Ian
Issue Date
2020
Type
journal-article
Language
Keywords
Adjusted Plus Minus , Bayesian hierarchical regression , Dota2
Alternative Title
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.
Description
Citation
Clark, Nicholas, Macdonald, Brian and Kloo, Ian. "A Bayesian adjusted plus-minus analysis for the esport Dota 2" Journal of Quantitative Analysis in Sports 16, no. 4 (2020): 325-341. https://doi.org/10.1515/jqas-2019-0103
Publisher
Journal of Quantitative Analysis in Sports
License
Journal
Volume
Issue
PubMed ID
ISSN
1559-0410
2194-6388
2194-6388