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Prediction of sports results using neural networks
Šipoš, Daniel ; Kuboň, David (advisor) ; Vidová Hladká, Barbora (referee)
This thesis focuses on creating models of two different types of neural network used for predicting results of selected football and tennis matches and comparing these two models in terms of their accuracy and potential profit, if we had bet on those games in an average betting agency. Compared types of neural networks are feed-forward and recurrent neural network. Predicted football matches consist of league matches of three European leagues. Specific feature of this thesis is tracking accuracy in predicting matches, where neither team is a clear favorite to win according to the bookmakers. 1

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