Application of Machine Learning Methods to Analysis of Cyber-Sport Events

Student: Savostyanov Dmitriy

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Final Grade: 9

Year of Graduation: 2017

In this paper, we present a novel approach of ranking individual player's impact based on their contribution in team victory. The work was focused on Dota 2 ESport discipline. Every single player was represented by role, which he performed in a corresponding team. Such a representation allows us to make use of machine learning methods and a history of professional matches for estimating each team player influence on team victory/defeat. TrueSkill model was used to establish a lower bound for the accuracy of winning team prediction.

Full text (added May 28, 2017)

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