Πρόγνωση αποτελεσμάτων αγώνων βόλεϋ με χρήση τεχνικών μηχανικής μάθησης
Prediction of volleyball match results using machine learning techniques
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Keywords
Volley ball ; Πετοσφαίριση ; Volley League ; Random forest ; Python ; Machine learningAbstract
This specific master's thesis will focus on the analysis of data from the sport of volleyball, with the aim of developing an innovative method that will allow for the accurate prediction of match outcomes. To achieve this goal, the methodology of machine learning will be utilized, ensuring effective and efficient data processing, thereby enabling the production of reliable and useful results.
In this thesis, a review of the relevant literature will be conducted, focusing on previous studies and sources related to outcome prediction in sports. This review will provide a framework for understanding the challenges and achievements in the field, highlighting the importance of data analysis and modern technologies.
Various programs will be used for data processing, including Excel and Python, which will facilitate the management and analysis of the data. Python will be critical for implementing machine learning algorithms and producing the necessary statistical results.
Subsequently, the results of applying these methods to a rich dataset will be presented. The data used will include the results of men's matches in the Volley League in Greece from 2011 to the present, offering an extensive foundation for analysis and comparisons.
Finally, this work will address the challenges that may arise during the development of prediction programs, as well as the prospects for using similar methods not only in volleyball but also in other sports. Delving into data analysis and applying advanced techniques can provide significant benefits for coaches, athletes, and analysts, contributing to the improvement of strategies and performance in matches.