Korištenje prediktivne analize u košarci

undergraduate thesis

• Title (english): The use of predictive analysis in basketball
• Author: Ivan Ukaš Korać
• Mentor: Marina Bagić Babac (mentor)
• Committee member: Marina Bagić Babac (predsjednik povjerenstva)
• Committee member: Tomislav Kos (član povjerenstva)
• Committee member: Mihael Kovač (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2023-02-23, 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: košarka; NBA; igrač; statistika; strojno učenje; algoritam; podaci; skup podataka; atribut; značajka
• Keywords (english): basketball; NBA; player; statistics; machine learning; algorithm; data; dataset; attribute; feature
• Language: english
• URN:NBN: urn:nbn:hr:168:607586
• Study programme: Title: 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 resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-07-13 10:12:34