Predictive Analysis on eSports Games: A Case Study on League of Legends (LoL) eSports Tournaments

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Last Modified
  • February 28, 2019
Creator
  • Wang, Tian
    • Affiliation: School of Information and Library Science
Abstract
  • This paper discusses about how different features influence League of Legends eSports game results. Logistic regression and decision trees are used as the main predictive analysis methods for making a prediction. In this study, three types of features: champion selection, in-game factors, and player performance, are tested to see how closely they are related to the game results. This paper also compares the similarity and difference between predictive analytics on traditional sports and eSports games, and discusses about potential approaches to improve eSports prediction accuracy in the future.
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Rights statement
  • In Copyright
Advisor
  • Rajasekar, Arcot
Degree
  • Master of Science in Information Science
Academic concentration
  • Library and Information Science
Degree granting institution
  • University of North Carolina at Chapel Hill
Graduation year
  • 2018
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  • b5e54e12-b67d-486e-a727-21c42b2e1946
Date uploaded
  • April 4, 2018

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