Machine learning for data analysis in football: A survey of methods and problems (CROSBI ID 729261)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Tokić, Saša ; Panjkota, Ante ; Matetić, Maja
engleski
Machine learning for data analysis in football: A survey of methods and problems
Machine learning is growing exponentially, and its applications are getting more and more traction in the sports analysis community in recent years. The application of machine learning methods on spatiotemporal data in sports like football is getting attention from football clubs, academics, and amateur analysts and is the main focus of this survey. This survey analyses and identifies current trends in research papers and literature to determine current and future applications in football analytics using spatiotemporal data.
spatiotemporal ; sports analytics, event data ; deep neural networks, machine learning
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Podaci o prilogu
0503-0510.
2022.
objavljeno
10.2507/33rd.daaam.proceedings.070
Podaci o matičnoj publikaciji
Katalinić, Branko
DAAAM International Vienna
978-3-902734-36-5
1726-9679
2304-1382
Podaci o skupu
33rd DAAAM International Symposium
predavanje
27.10.2022-28.10.2022
Beč, Austrija; online