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Recommender Model for Optimal Team Composition in Dota2 Professional Matches

Student: Sidorenko Danila

Supervisor: Alexander Sirotkin

Faculty: St.Petersburg School of Economics and Management

Educational Programme: Management (Bachelor)

Final Grade: 9

Year of Graduation: 2020

Computer games have recently faced rising interest, become a big business, and created an electronic sport around themselves. Multiplayer Online Battle Arenas, being the most successful among other eSports disciplines, are also the most complex and strategic-reliant games to play. To succeed in this kind of game, teams should master the idea of finding and selecting the best heroes’ combinations. The current paper addresses the in-game units’ cooperation issue using real-world techniques to meet the demand for analysis for team composition routine optimization. Based on previous games’ history, current research creates and describes a system, which suggests the optimal hero selections to consider during ongoing matches. The performance of the system is then evaluated by comparing it to a created-by-hand game analysis done by tournament-broadcasting studios. Though the paper also provides the critical limitations of studying the exact issue and proposes possible solutions and areas for future research.

Full text (added May 31, 2020)

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