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University of Graz News Künstliche Intelligenz am Spielfeld

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Tuesday, 23 October 2018

Künstliche Intelligenz am Spielfeld

Arnold Baca, Universität Wien, Peter O'Donoghue, Cardiff School of Sport, Markus Tilp und Sigrid Thaller, beide Universität Graz, und Jürgen Perl, Universität Mainz (v.l.). Fotos: Uni Graz/Leljak.

Arnold Baca, Universität Wien, Peter O'Donoghue, Cardiff School of Sport, Markus Tilp und Sigrid Thaller, beide Universität Graz, und Jürgen Perl, Universität Mainz (v.l.). Fotos: Uni Graz/Leljak.

Vizerektorin Renate Dworczak, Adrian-Daniel Boese, Vize-Sprecher des Forschungsschwerpunkts "Modelling and Simulation", Markus Tilp und Sigrid Thaller mit Rupert Baumgartner, Vizedekan der URBI-Fakultät (v.l.).

Vizerektorin Renate Dworczak, Adrian-Daniel Boese, Vize-Sprecher des Forschungsschwerpunkts "Modelling and Simulation", Markus Tilp und Sigrid Thaller mit Rupert Baumgartner, Vizedekan der URBI-Fakultät (v.l.).

Digitalisierung bereichert die sportwissenschaftliche Forschung

Wo wird der Gegner oder die Gegnerin einen Wurf platzieren oder wie erfolgreich ist mein Taktiktraining? Solche oder ähnliche Fragen versucht die Arbeitsgruppe von Markus Tilp am Institut für Sportwissenschaft zu beantworten. „Die Digitalisierung schreitet auch in der Sportwissenschaft voran und hilft mit, taktische Muster in Sportspielen mit Hilfe künstlicher neuronaler Netze zu erkennen“, erklärt Tilp.

Die in Zusammenarbeit mit der TU Graz eigens konzipierte Software MASA („Motion and Action Sequence Analysis“) nutzen die ForscherInnen, um exakte Positionsdaten und Informationen über das SpielerInnenverhalten zu generieren. Anschließend werden die Daten mithilfe von künstlichen neuronalen Netzen untersucht. So gelingt es den SportwissenschafterInnen zum Beispiel, Offensiv- und Defensivverhalten im Handball zu analysieren und sogar die wahrscheinlichsten Wurfpositionen vorherzusagen. „Auch den Erfolg eines Taktiktrainings konnten wir anhand der künstlichen neuronalen Netze evaluieren“, so Tilp. Die SpielerInnen-Positionsdaten wurden dafür ins neuronale Netz eingespeist und mit den eintrainierten Mustern verglichen. Das Netz konnte dabei objektiv zeigen, dass 58 Prozent aller Angriffe mit den im Vorfeld eintrainierten übereinstimmen.

Diese Forschungsergebnisse wurden kürzlich an der Universität Graz im Rahmen des internationalen Workshops „Modelling & Simulation in Sports“ gemeinsam mit weiteren Anwendungsbeispielen vom Einzelmuskel bis zur Fußballmannschaft präsentiert. Alle Beiträge des Workshops sind in dem Buch „Modelling and Simulation in Sports & Exercise“ veröffentlicht worden.



Publikationslinks:

Positionsvorhersage im Handball:
https://www.tandfonline.com/doi/full/10.1080/24748668.2017.1336688

Evaluation Taktiktraining im Handball:
https://www.tandfonline.com/doi/full/10.1080/02640414.2016.1183804

Buch „Modelling and Simulation in Sports & Exercise“:
https://www.routledge.com/Modelling-and-Simulation-in-Sport-and-Exercise/Baca-Perl/p/book/9781138059931

 

 

created by Markus Tilp & Gerhild Leljak

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