Prediction of Winners in MOBA Games

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dc.contributor.authorAlmeida, Carlos E. M. [UNESP]
dc.contributor.authorCorreia, Ronaldo C. M. [UNESP]
dc.contributor.authorEler, Danilo M. [UNESP]
dc.contributor.authorOlivete-, Celso [UNESP]
dc.contributor.authorGarcia, Rogerio E. [UNESP]
dc.contributor.authorScabora, Lucas C.
dc.contributor.authorSpadon, Gabriel
dc.contributor.authorIEEE
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.date.accessioned2018-11-26T15:47:39Z
dc.date.available2018-11-26T15:47:39Z
dc.date.issued2017-01-01
dc.description.abstractMultiplayer Online Battle Arena (MOBA) games are very popular in the current eSport scenario, being highlighted in several competitions around the world. However, the domain of knowledge contained in these games is large, which makes it difficult to discover and predict the course of a match. The present work proposes the application of classification algorithms to determine the team with more chances to win a match. Two classifications procedures were used, one based on the composition of heroes in each team and another considering the duration of the match. The experiments were performed on data collected from 123,326 matches of Dota 2, showing that it was possible to achieve approximately 77% accuracy. The results demonstrate the effectiveness of the application when using techniques assisted by computers, and when using the methodology described in championships or other similar games that require the definition of strategies.en
dc.description.affiliationUniv Estadual Paulista FCT UNESP, DMC, Presidente Prudente, SP, Brazil
dc.description.affiliationUniv Sao Paulo, Dept Ciencias Comp SCC, ICMC, Sao Carlos, SP, Brazil
dc.description.affiliationUnespUniv Estadual Paulista FCT UNESP, DMC, Presidente Prudente, SP, Brazil
dc.format.extent6
dc.identifier.citation2017 12th Iberian Conference On Information Systems And Technologies (cisti). New York: Ieee, 6 p., 2017.
dc.identifier.issn2166-0727
dc.identifier.lattes2616135175972629
dc.identifier.urihttp://hdl.handle.net/11449/160148
dc.identifier.wosWOS:000426896900103
dc.language.isopor
dc.publisherIeee
dc.relation.ispartof2017 12th Iberian Conference On Information Systems And Technologies (cisti)
dc.rights.accessRightsAcesso aberto
dc.sourceWeb of Science
dc.subjectData Mining
dc.subjectClassification
dc.subjectStrategic Games
dc.titlePrediction of Winners in MOBA Gamesen
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dcterms.rightsHolderIeee
unesp.author.lattes2616135175972629[4]

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