Predicting selected basketball match events
Predikce vybraných událostí v basketbalovém utkání
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České vysoké učení technické v Praze
Czech Technical University in Prague
Czech Technical University in Prague
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V rámci této bakalářské práce byl vytvořen model predikující celkový počet vstřelených bodů v následujícím vývoji basketbalového zápasu NBA. Predikce jsou založeny na datech z předchozích zápasů a statistik, které v daném zápase již byly zveřejněny. Za účelem získání dat byla provedena rešerše dostupných zdrojů, které se následně povedlo úspěšně využít pro vytvoření dostatečných materiálů k natrénování predikčního modelu. Také byl proveden průzkum již dokončených prací, zabývající se podobnou tématikou. Na základě nabytých poznatků byl zvolen pro predikci model lineární regrese a do výše zmíněných dat byly přidány zajímavé příznaky, které měly zlepšit predikci modelu. Model se povedlo natrénovat a jeho výsledky na testovacích datech se jevily jako příznivé. Avšak úplnou kvalitu výsledků by bylo možné získat pouze při testování na aktuálně hraných zápasech. To bohužel nebylo z důvodu pandemie COVID-19, která probíhala během tvorby bakalářské práce, možné.
Within this bachelor's thesis, a model predicting the total number of points scored in future match development in NBA basketball match was created. Predictions are based on data from previous games and statistics, which were already published in the ongoing match. In order to obtain the data, a study of existing materials was made, which were then successfully used for the creation of sufficient materials for the training of the prediction model. Also, the research of already finished theses, which are focused on a similar topic, was made. Based on the gathered data, a linear regression prediction model was chosen, and interesting attributes were added to the data mentioned above, which were meant to improve the model's predictions. The model was trained successfully, and it's results on the testing set of data seemed to be favourable. Although the full quality of the results would be possible to obtain by testing the model on currently played matches. Unfortunately, this wasn't possible due to the ongoing COVID-19 pandemic, which took place during the creation of this bachelor's thesis.
Within this bachelor's thesis, a model predicting the total number of points scored in future match development in NBA basketball match was created. Predictions are based on data from previous games and statistics, which were already published in the ongoing match. In order to obtain the data, a study of existing materials was made, which were then successfully used for the creation of sufficient materials for the training of the prediction model. Also, the research of already finished theses, which are focused on a similar topic, was made. Based on the gathered data, a linear regression prediction model was chosen, and interesting attributes were added to the data mentioned above, which were meant to improve the model's predictions. The model was trained successfully, and it's results on the testing set of data seemed to be favourable. Although the full quality of the results would be possible to obtain by testing the model on currently played matches. Unfortunately, this wasn't possible due to the ongoing COVID-19 pandemic, which took place during the creation of this bachelor's thesis.