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master's thesis
Primjena metoda dubinske analize u domeni igara na sreću
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. urn:nbn:hr:168:608682
Gojsalić, Ante
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Gojsalić, A. (2016). Primjena metoda dubinske analize u domeni igara na sreću (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:608682

Gojsalić, Ante. "Primjena metoda dubinske analize u domeni igara na sreću." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. https://urn.nsk.hr/urn:nbn:hr:168:608682

Gojsalić, Ante. "Primjena metoda dubinske analize u domeni igara na sreću." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. https://urn.nsk.hr/urn:nbn:hr:168:608682

Gojsalić, A. (2016). 'Primjena metoda dubinske analize u domeni igara na sreću', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 20 January 2025, https://urn.nsk.hr/urn:nbn:hr:168:608682

Gojsalić A. Primjena metoda dubinske analize u domeni igara na sreću [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2016 [cited 2025 January 20] Available at: https://urn.nsk.hr/urn:nbn:hr:168:608682

A. Gojsalić, "Primjena metoda dubinske analize u domeni igara na sreću", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2016. Available at: https://urn.nsk.hr/urn:nbn:hr:168:608682

Metadata
TitlePrimjena metoda dubinske analize u domeni igara na sreću
Title (english)Applying Data Mining Methods to the Business Field of Games of Chance
AuthorAnte Gojsalić
MentorDamir Pintar (mentor)
Committee memberDamir Pintar (predsjednik povjerenstva)
Committee memberBoris Vrdoljak (član povjerenstva)
Committee memberMihaela Vranić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2016-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu predstavljamo metode analize i predikcije vezane uz sportsko klađenje. Koristeći različite skupove podataka pokazali smo što sve utječe na izmjene vjerojatnosti osvajanja meča. Koristeći Markovljevu pretpostavku da je vjerojatnost osvajanja poena konstantna tijekom cijelog meča izveli smo vjerojatnosni model za klađenje uživo u odbojci. Usput smo pokazali kako različite strategije klađenja ovise o vremenski razdvojenim podatkovnim skupovima te na koji način se može upotrebljavati izvedeni vjerojatnosni model u praksi. Za kraj smo pomoću metoda nadziranog strojnog učenja pokušali aproksimirati izmjenu koeficijenata te izradom jednostavnih aplikacija pokazali usporedbu svih modela.
Abstract (english)
In this work we present analysis and prediction methods with applications in sports betting. By using different datasets we analysed how winning probbability changes depending on numerous features. With Markovian assumption that rally winning probability is contsant during the match we derived probabilistic model for live volleyball betting. We showed examples of using our probabilistic model against real world live betting algorithms by deriving multiple betting strategies which we validated on timely-separated datasets. Furthermore we observed how supervised machine learning can be used to approximate live coeficient changing.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:608682
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2018-02-06 08:56:08