Stein, Manuel
[Author];
Seebacher, Daniel
[Author];
Marcelino, Rui
[Author];
Schreck, Tobias
[Author];
Grossniklaus, Michael
[Author];
Keim, Daniel A.
[Author];
Janetzko, Halldor
[Author]
Where to go : Computational and visual what-if analyses in soccer
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Media type:
E-Article;
Text
Title:
Where to go : Computational and visual what-if analyses in soccer
Contributor:
Stein, Manuel
[Author];
Seebacher, Daniel
[Author];
Marcelino, Rui
[Author];
Schreck, Tobias
[Author];
Grossniklaus, Michael
[Author];
Keim, Daniel A.
[Author];
Janetzko, Halldor
[Author]
imprint:
KOPS - The Institutional Repository of the University of Konstanz, 2019-12-17
Published in:Journal of Sports Sciences. 2019, 37(24), pp. 2774-2782. ISSN 0264-0414. eISSN 1466-447X. Available under: doi:10.1080/02640414.2019.1652541
Footnote:
Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
Description:
To prepare their teams for upcoming matches, analysts in professional soccer watch and manually annotate up to three matches a day. When annotating matches, domain experts try to identify and improve suboptimal movements based on intuition and professional experience. The high amount of matches needing to be analysed manually result in a tedious and time-consuming process, and results may be subjective. We propose an automatic approach for the realisation of effective region-based what-if analyses in soccer. Our system covers the automatic detection of region-based faulty movement behaviour, as well as the automatic suggestion of possible improved alternative movements. As we show, our approach effectively supports analysts and coaches investigating matches by speeding up previously time-consuming work. We enable domain experts to include their domain knowledge in the analysis process by allowing to interactively adjust suggested improved movement, as well as its implications on region control. We demonstrate the usefulness of our proposed approach via an expert study with three invited domain experts, one being head coach from the first Austrian soccer league. As our results show that experts most often agree with the suggested player movement (83%), our proposed approach enhances the analytical capabilities in soccer and supports a more efficient analysis. ; published