Pregled bibliografske jedinice broj: 1027452
Data-driven Basketball Web Application for Support in Making Decisions
Data-driven Basketball Web Application for Support in Making Decisions // Proceedings of the 7th International Conference on Sport Sciences Research and Technology Support
Beč, Austrija, 2019. str. 239-244 doi:10.5220/0008388102390244 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1027452 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Data-driven Basketball Web Application for Support in Making Decisions
Autori
Horvat, Tomislav ; Havaš, Ladislav ; Srpak, Dunja ; Medved, Vladimir
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Skup
Proceedings of the 7th International Conference on Sport Sciences Research and Technology Support
Mjesto i datum
Beč, Austrija, 20.09.2019. - 21.09.2019
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Basketball, Information system, Making decisions, Statistics analysis, Web application
Sažetak
Statistical analysis combined with data mining and machine learning is increasingly used in sports. This paper presents an overview of existing commercial information systems used in game analysis and describes the new and improved version of originally developed data- driven Web application / information system called Basketball Coach Assistant (later BCA) for sports statistics and analysis. The aim of BCA is to provide the essential information for decision making in training process and coaching basketball teams. Special emphasis, along with statistical analysis, is given to the player’s progress indicators and statistical analysis based on data mining methods used to define played game point’s difference classes. The results obtained by using BCA information system, presented in tables, proved to be useful in programing training process and making strategic, tactical and operational decisions. Finally, guidelines for the further information system development are given primarily for the use of data mining and machine learning methods
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Ustanove:
Sveučilište Sjever, Koprivnica