Academic Journal of Computing & Information Science, 2020, 3(5); doi: 10.25236/AJCIS.2020.030503.
Suzhou Science and Technology Town Foreign Language School
The purpose of this paper is to evaluate the state of the team through the player’s post-match scores and game data. the correlation of these indicators is very strong. Then SVM, a classic classification algorithm, is used to predict the winner of FIFA Football World and it has good classification performance. The results showed that SVM with gauss kernel suppressed that with linear kernel. The average score of all players in a team reflects the strength and state of the team. Using player ratings to predict game results is more accurate than using historical records and the relationship between team wins and losses.
Game Predication, FIFA Football World Cup, Support Vector Machine
Shengtai Ding. Game Predication of FIFA Football World Cup Based on Support Vector Machine. Academic Journal of Computing & Information Science (2020), Vol. 3, Issue 5: 17-22. https://doi.org/10.25236/AJCIS.2020.030503.
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