Affiliations: [a] Department of Mathematics, Yonsei University, Seoul, South Korea
| [b] School of Aerospace and Mechanical Engineering, Korea Aerospace University, Goyangm, South Korea
| [c] School of Liberal Arts and Science, Korea Aerospace University, Goyang, South Korea
Correspondence:
[*]
Corresponding author. Seung Hoe Choi, School of Liberal arts and Science, Korea Aerospace University, Goyang, South Korea. E-mail: [email protected].
Abstract: Soccer recently has become an intellectual game by predicting the outcome of games. In this study, we use path analysis to find the variable that affects the outcome of the Korea National Football Team (KNFT) matches the most, and consequently the odds of victory, defeat, or a draw, as announced by the betting company. We will also investigate the influence of the variables inferred from the path analysis and Korea’s ELO Rating on the difference between scoring and losing points of the KNFT. We will represent the dividend and the difference between scoring and losing points as fuzzy numbers using the fuzzy decomposition, and then infer the fuzzy regression model for the result of the KNFT’s match. For this purpose, we use data on 113 games of the KNFT from September 2011 to June 2019 and the dividend rate of the KNFT obtained from Wise Toto company.
Keywords: ELO rating, dividend, path analysis, fuzzy partition, regression analysis
