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Pregled bibliografske jedinice broj: 1072656

The use of machine learning in sport outcome prediction: A review


Horvat, Tomislav; Job, Josip
The use of machine learning in sport outcome prediction: A review // Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery, 1 (2020), e1380, 28 doi:10.1002/widm.1380 (međunarodna recenzija, pregledni rad, znanstveni)


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Naslov
The use of machine learning in sport outcome prediction: A review

Autori
Horvat, Tomislav ; Job, Josip

Izvornik
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (1942-4787) 1 (2020); E1380, 28

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, pregledni rad, znanstveni

Ključne riječi
learning algorithms ; machine learning ; outcome prediction ; sport

Sažetak
The increase in the volume of structured and unstructured data related to more than just sport events leads to the development and increased use of techniques that extract information and employ machine-learning algorithms in predicting process outcomes based on input but not necessarily output data. Taking sports into consideration, predicting outcomes, and extracting valuable information has become appealing not only to sports workers but also to the wider audience, particularly in the areas of team management and sports betting. The aim of this article is to review the existing machine learning (ML) algorithms in predicting sport outcomes. Over 100 papers were analyzed and only some of these papers were taken into consideration. Almost all of the analyzed papers use some sort of feature selection and feature extraction, most often prior to using the machine-learning algorithm. As an evaluation method of ML algorithms, researchers, in most cases, use data segmentation with data being chronologically distributed. In addition to data segmentation, researchers also use thek-cross-evaluation method. Sport predictions are usually treated as a classification problem with one class being predicted and rare cases being predicted as numerical values. Mostly used ML models are neural networks using data segmentation.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek,
Sveučilište Sjever, Koprivnica

Profili:

Avatar Url Josip Job (autor)

Avatar Url Tomislav Horvat (autor)

Poveznice na cjeloviti tekst rada:

doi

Citiraj ovu publikaciju:

Horvat, Tomislav; Job, Josip
The use of machine learning in sport outcome prediction: A review // Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery, 1 (2020), e1380, 28 doi:10.1002/widm.1380 (međunarodna recenzija, pregledni rad, znanstveni)
Horvat, T. & Job, J. (2020) The use of machine learning in sport outcome prediction: A review. Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery, 1, e1380, 28 doi:10.1002/widm.1380.
@article{article, author = {Horvat, Tomislav and Job, Josip}, year = {2020}, pages = {28}, DOI = {10.1002/widm.1380}, chapter = {e1380}, keywords = {learning algorithms, machine learning, outcome prediction, sport}, journal = {Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery}, doi = {10.1002/widm.1380}, volume = {1}, issn = {1942-4787}, title = {The use of machine learning in sport outcome prediction: A review}, keyword = {learning algorithms, machine learning, outcome prediction, sport}, chapternumber = {e1380} }
@article{article, author = {Horvat, Tomislav and Job, Josip}, year = {2020}, pages = {28}, DOI = {10.1002/widm.1380}, chapter = {e1380}, keywords = {learning algorithms, machine learning, outcome prediction, sport}, journal = {Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery}, doi = {10.1002/widm.1380}, volume = {1}, issn = {1942-4787}, title = {The use of machine learning in sport outcome prediction: A review}, keyword = {learning algorithms, machine learning, outcome prediction, sport}, chapternumber = {e1380} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





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