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Shi, Z., Moorthy, S., & Zimmermann, A. (2013). Predicting NCAAB Match Outcomes Using ML Techniques-Some Results and Lessons Learned. ECML/PKDD 2013 Workshop on Machine Learning and Data Mining for Sports Analytics.

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• TITLE: Neural Network Algorithm in Predicting Football Match Outcome Based on Player Ability Index

  AUTHORS: Hengzhi Chen

  KEYWORDS: Convolutional Neural Network, Football Match Prediction, FIFA

  JOURNAL NAME: Advances in Physical Education, Vol.9 No.4, September 10, 2019

  ABSTRACT: Nowadays, when people want to predict the result of a football match, most of them just refer to their own experience or some specialists’ opinions. However, since artificial intelligence is very good at analyzing big data, it is more and more used to predict the result instead of one’s experience in order to approachthe accuracy. There are three typical algorithms—convolutional neural network (ANN), random forest (RF) and support vector machine (SVM). In this paper, these three algorithms are all applied to predict the result of a football match, and the accuracy of themisalso compared.