Esports Analytics Through Encounter Detection

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Abstract

Esports is computer games played in a competitive environment, and analytics in this domain is focused on player and team behavior. Multiplayer Online Battle Arena (MOBA) games are among the most played digital games in the world. In these es, teams of players fight against each other in enclosed arena environs, with a complex gameplay focused on tactical combat. Here we present a technique for segmenting matches into spatio‐temporally defined components referred to as encounters, enabling performance analysis. We apply encounter‐based analysis to match data from the popular esport game DOTA, and present win probability predictions based on encounters. Finally,metrics for evaluating team performance during match runtime are proposed.

Details

Authors
  • Matthias Schubert
  • Anders Drachen
  • Tobias Mahlmann
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Computer Science

Keywords

  • esports, dota2, machine learning, team encounter
Original languageEnglish
Title of host publicationProceedings of the MIT Sloan Sports Analytics Conference 2016
PublisherMIT Sloan
Number of pages18
Publication statusPublished - 2016
Publication categoryResearch
Peer-reviewedYes
EventMIT Sloan Sports Analytics Conference - Boston
Duration: 2016 Mar 11 → …

Conference

ConferenceMIT Sloan Sports Analytics Conference
Period2016/03/11 → …

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