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Quantitative Analysis for Win/Loss Prediction of ‘League of Legends’ Utilizing the Deep Neural Network System through Big Data

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2021, 26(4), pp.213-221
  • DOI : 10.9708/jksci.2021.26.04.213
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : March 3, 2021
  • Accepted : April 22, 2021
  • Published : April 30, 2021

Si-Jae No 1 Yoo-Jin Moon 1 Young-Ho Hwang 2

1한국외국어대학교
2군산대학교

Accredited

ABSTRACT

In this paper, we suggest the Deep Neural Network Model System for predicting results of the match of ‘League of Legends (LOL).’ The model utilized approximately 26,000 matches of the LOL game and Keras of Tensorflow. It performed an accuracy of 93.75% without overfitting disadvantage in predicting the ‘2020 League of Legends Worlds Championship’ utilizing the real data in the middle of the game. It employed functions of Sigmoid, Relu and Logcosh, for better performance. The experiments found that the four variables largely affected the accuracy of predicting the match --- ‘Dragon Gap’, ‘Level Gap’, ‘Blue Rift Heralds’, and ‘Tower Kills Gap,’ and ordinary users can also use the model to help develop game strategies by focusing on four elements. Furthermore, the model can be applied to predicting the match of E-sports professional leagues around the world and to the useful training indicators for professional teams, contributing to vitalization of E-sports.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.