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http://dx.doi.org/10.7465/jkdi.2017.28.2.237

Development of game indicators and winning forecasting models with game data  

Ku, Jimin (Department of Information and Statistics, Duksung Women's University)
Kim, Jaehee (Department of Information and Statistics, Duksung Women's University)
Publication Information
Journal of the Korean Data and Information Science Society / v.28, no.2, 2017 , pp. 237-250 More about this Journal
Abstract
A new field of e-sports gains the great popularity in Korea as well as abroad. AOS (aeon of strife) genre games are quickly gaining popularity with gamers from all over the world and the game companies hold game competitions. The e-sports broadcasting teams and webzines use a variety of statistical indicators. In this paper, as an AOS genre game, League of Legends game data is used for statistical analysis using the indicators to predict the outcome. We develop new indicators with the factor analysis to improve existing indicators. Also we consider discriminant function, neural network model, and SVM (support vector machine) for make winning forecasting models. As a result, the new position indicators reflect the nature of the role in the game and winning forecasting models show more than 95 percent accuracy.
Keywords
Discriminant analysis; factor analysis; game data; neural network; SVM(support vector machine); winning forecasting model;
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Times Cited By KSCI : 5  (Citation Analysis)
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