Real-time prediction to support decision-making in soccer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Data analysis in sports has been developing for many years. However, to date, a system that provides tactical prediction in real time and promotes ideas for increasing the chance of winning has not been reported in the literature. Especially, in soccer, components of plays and games are more complicated than in other sports. This study proposes a method to predict the course of a game and create a strategy for the second half. First, we summarize other studies and propose our method. Then, data are collected using the proposed system. From past games, games to similar to a target game are extracted depending on data from their first half. Next, similar games are classified by features depending on data of their second half. Finally, a target game is predicted and tactical ideas are derived. The practicability of the method is demonstrated through experiments. However, further improvements such as increasing the number of past games and types of data are still required.

Original languageEnglish
Title of host publicationKDIR
PublisherSciTePress
Pages218-225
Number of pages8
Volume1
ISBN (Print)9789897581588
Publication statusPublished - 2015
Event7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015 - Lisbon, Portugal
Duration: 2015 Nov 122015 Nov 14

Other

Other7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2015
CountryPortugal
CityLisbon
Period15/11/1215/11/14

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Keywords

  • Clustering
  • Game prediction
  • K-NN
  • Soccer
  • Sports data

ASJC Scopus subject areas

  • Software

Cite this

Saito, Y., Kimura, M., & Ishizaki, S. (2015). Real-time prediction to support decision-making in soccer. In KDIR (Vol. 1, pp. 218-225). SciTePress.