Investigating the Sketchplan : A Novel Way of Identifying Tactical Behavior in Massive Soccer Datasets
Investigating the Sketchplan : A Novel Way of Identifying Tactical Behavior in Massive Soccer Datasets
Loading...
Date
2023
Editors
Journal ISSN
Electronic ISSN
ISBN
Bibliographical data
Publisher
Series
URI (citable link)
DOI (citable link)
International patent number
Link to the license
EU project number
Project
Open Access publication
Collections
Title in another language
Publication type
Journal article
Publication status
Published
Published in
IEEE Transactions on Visualization and Computer Graphics ; 29 (2023), 4. - pp. 1920-1936. - IEEE. - ISSN 1077-2626. - eISSN 1941-0506
Abstract
Coaches and analysts prepare for upcoming matches by identifying common patterns in the positioning and movement of the competing teams in specific situations. Existing approaches in this domain typically rely on manual video analysis and formation discussion using whiteboards; or expert systems that rely on state-of-the-art video and trajectory visualization techniques and advanced user interaction. We bridge the gap between these approaches by contributing a light-weight, simplified interaction and visualization system, which we conceptualized in an iterative design study with the coaching team of a European first league soccer team. Our approach is walk-up usable by all domain stakeholders, and at the same time, can leverage advanced data retrieval and analysis techniques: a virtual magnetic tactic-board. Users place and move digital magnets on a virtual tactic-board, and these interactions get translated to spatio-temporal queries, used to retrieve relevant situations from massive team movement data. Despite such seemingly imprecise query input, our approach is highly usable, supports quick user exploration, and retrieval of relevant results via query relaxation. Appropriate simplified result visualization supports in-depth analyses to explore team behavior, such as formation detection, movement analysis, and what-if analysis. We evaluated our approach with several experts from European first league soccer clubs. The results show that our approach makes the complex analytical processes needed for the identification of tactical behavior directly accessible to domain experts for the first time, demonstrating our support of coaches in preparation for future encounters.
Summary in another language
Subject (DDC)
004 Computer Science
Keywords
Conference
Review
undefined / . - undefined, undefined. - (undefined; undefined)
Cite This
ISO 690
SEEBACHER, Daniel, Tom POLK, Halldor JANETZKO, Daniel A. KEIM, Tobias SCHRECK, Manuel STEIN, 2023. Investigating the Sketchplan : A Novel Way of Identifying Tactical Behavior in Massive Soccer Datasets. In: IEEE Transactions on Visualization and Computer Graphics. IEEE. 29(4), pp. 1920-1936. ISSN 1077-2626. eISSN 1941-0506. Available under: doi: 10.1109/TVCG.2021.3134814BibTex
@article{Seebacher2023Inves-55956, year={2023}, doi={10.1109/TVCG.2021.3134814}, title={Investigating the Sketchplan : A Novel Way of Identifying Tactical Behavior in Massive Soccer Datasets}, number={4}, volume={29}, issn={1077-2626}, journal={IEEE Transactions on Visualization and Computer Graphics}, pages={1920--1936}, author={Seebacher, Daniel and Polk, Tom and Janetzko, Halldor and Keim, Daniel A. and Schreck, Tobias and Stein, Manuel} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/55956"> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:title>Investigating the Sketchplan : A Novel Way of Identifying Tactical Behavior in Massive Soccer Datasets</dcterms:title> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/55956"/> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:creator>Schreck, Tobias</dc:creator> <dc:contributor>Janetzko, Halldor</dc:contributor> <dc:creator>Stein, Manuel</dc:creator> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/55956/1/Seebacher_2-b2gumppw7pst7.pdf"/> <dc:creator>Polk, Tom</dc:creator> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dc:rights>terms-of-use</dc:rights> <dc:creator>Janetzko, Halldor</dc:creator> <foaf:homepage rdf:resource="http://localhost:8080/"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-12-21T10:39:53Z</dc:date> <dc:creator>Keim, Daniel A.</dc:creator> <dc:contributor>Stein, Manuel</dc:contributor> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/55956/1/Seebacher_2-b2gumppw7pst7.pdf"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:contributor>Keim, Daniel A.</dc:contributor> <dcterms:issued>2023</dcterms:issued> <dcterms:abstract xml:lang="eng">Coaches and analysts prepare for upcoming matches by identifying common patterns in the positioning and movement of the competing teams in specific situations. Existing approaches in this domain typically rely on manual video analysis and formation discussion using whiteboards; or expert systems that rely on state-of-the-art video and trajectory visualization techniques and advanced user interaction. We bridge the gap between these approaches by contributing a light-weight, simplified interaction and visualization system, which we conceptualized in an iterative design study with the coaching team of a European first league soccer team. Our approach is walk-up usable by all domain stakeholders, and at the same time, can leverage advanced data retrieval and analysis techniques: a virtual magnetic tactic-board. Users place and move digital magnets on a virtual tactic-board, and these interactions get translated to spatio-temporal queries, used to retrieve relevant situations from massive team movement data. Despite such seemingly imprecise query input, our approach is highly usable, supports quick user exploration, and retrieval of relevant results via query relaxation. Appropriate simplified result visualization supports in-depth analyses to explore team behavior, such as formation detection, movement analysis, and what-if analysis. We evaluated our approach with several experts from European first league soccer clubs. The results show that our approach makes the complex analytical processes needed for the identification of tactical behavior directly accessible to domain experts for the first time, demonstrating our support of coaches in preparation for future encounters.</dcterms:abstract> <dc:contributor>Schreck, Tobias</dc:contributor> <dc:language>eng</dc:language> <dc:contributor>Polk, Tom</dc:contributor> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-12-21T10:39:53Z</dcterms:available> <dc:creator>Seebacher, Daniel</dc:creator> <dc:contributor>Seebacher, Daniel</dc:contributor> </rdf:Description> </rdf:RDF>
Internal note
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Examination date of dissertation
Method of financing
Comment on publication
Alliance license
Corresponding Authors der Uni Konstanz vorhanden
International Co-Authors
Bibliography of Konstanz
Yes
Refereed
Yes