Where to go : Computational and visual what-if analyses in soccer

dc.contributor.authorStein, Manuel
dc.contributor.authorSeebacher, Daniel
dc.contributor.authorMarcelino, Rui
dc.contributor.authorSchreck, Tobias
dc.contributor.authorGrossniklaus, Michael
dc.contributor.authorKeim, Daniel A.
dc.contributor.authorJanetzko, Halldor
dc.date.accessioned2019-08-19T13:25:26Z
dc.date.available2019-08-19T13:25:26Z
dc.date.issued2019-12-17
dc.description.abstractTo 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.eng
dc.description.versionpublishedeng
dc.identifier.doi10.1080/02640414.2019.1652541eng
dc.identifier.pmid31402759eng
dc.identifier.ppn1682422496
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/46696
dc.language.isoengeng
dc.rightsterms-of-use
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/
dc.subjectVisual analytics; sports analytics; soccer analytics; information visualisationeng
dc.subject.ddc004eng
dc.titleWhere to go : Computational and visual what-if analyses in soccereng
dc.typeJOURNAL_ARTICLEeng
dspace.entity.typePublication
kops.citation.bibtex
@article{Stein2019-12-17Where-46696,
  year={2019},
  doi={10.1080/02640414.2019.1652541},
  title={Where to go : Computational and visual what-if analyses in soccer},
  number={24},
  volume={37},
  issn={0264-0414},
  journal={Journal of Sports Sciences},
  pages={2774--2782},
  author={Stein, Manuel and Seebacher, Daniel and Marcelino, Rui and Schreck, Tobias and Grossniklaus, Michael and Keim, Daniel A. and Janetzko, Halldor}
}
kops.citation.iso690STEIN, Manuel, Daniel SEEBACHER, Rui MARCELINO, Tobias SCHRECK, Michael GROSSNIKLAUS, Daniel A. KEIM, Halldor JANETZKO, 2019. Where to go : Computational and visual what-if analyses in soccer. In: Journal of Sports Sciences. 2019, 37(24), pp. 2774-2782. ISSN 0264-0414. eISSN 1466-447X. Available under: doi: 10.1080/02640414.2019.1652541deu
kops.citation.iso690STEIN, Manuel, Daniel SEEBACHER, Rui MARCELINO, Tobias SCHRECK, Michael GROSSNIKLAUS, Daniel A. KEIM, Halldor JANETZKO, 2019. Where to go : Computational and visual what-if analyses in soccer. In: Journal of Sports Sciences. 2019, 37(24), pp. 2774-2782. ISSN 0264-0414. eISSN 1466-447X. Available under: doi: 10.1080/02640414.2019.1652541eng
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    <dcterms:abstract xml:lang="eng">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.</dcterms:abstract>
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