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undergraduate thesis
Korištenje prediktivne analize u košarci
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:607586
Korać, Ivan Ukaš
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Korać, I. U. (2023). Korištenje prediktivne analize u košarci (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:607586

Korać, Ivan Ukaš. "Korištenje prediktivne analize u košarci." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:607586

Korać, Ivan Ukaš. "Korištenje prediktivne analize u košarci." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:607586

Korać, I. U. (2023). 'Korištenje prediktivne analize u košarci', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:607586

Korać IU. Korištenje prediktivne analize u košarci [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 December 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:607586

I. U. Korać, "Korištenje prediktivne analize u košarci", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:607586

Metadata
TitleKorištenje prediktivne analize u košarci
Title (english)The use of predictive analysis in basketball
AuthorIvan Ukaš Korać
MentorMarina Bagić Babac (mentor)
Committee memberMarina Bagić Babac (predsjednik povjerenstva)
Committee memberTomislav Kos (član povjerenstva)
Committee memberMihael Kovač (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-02-23, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Široka dostupnost velikih količina online podataka i suvremenih algoritama strojnog učenja otvorili su nove perspektive u rješavanju zadatka predviđanja ishoda košarkaških utakmica. Cilj ovog završnog rada je korištenje podataka iz prethodnih košarkaških utakmica počevši od individualnih karakteristika igrača kao što su pozicije igrača, statistike i ocjene, do timskih karakteristika i statistika za predviđanje ishoda budućih utakmica. Treba prikazati, razraditi i obrazložiti usporedbu s prednostima i nedostacima postojećih algoritama strojnog učenja u njihovoj primjeni na primjeru NBA lige.
Abstract (english)
The availability of many online data resources and state-of-the-art machine learning algorithms have opened new perspectives on the challenging task of predicting the outcomes of basketball matches. The goal of this thesis is to use data from previous basketball games ranging from individual player features such as player positions, statistics, and ratings, to team features and statistics to predict the outcome of future matches. The comparison with the advantages and disadvantages of existing machine learning algorithms in their application in a case study of NBA will be presented, elaborated, and discussed.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:607586
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-07-13 10:12:34