Where to go: Computational and visual what-if analyses in soccer. Issue 24 (17th December 2019)

• Record Type: Journal Article
• Authors: Stein, Manuel; Seebacher, Daniel; Marcelino, Rui; Schreck, Tobias; Grossniklaus, Michael; Keim, Daniel A.; Janetzko, Halldor
• Is Part Of: Journal of sports sciences. Volume 37:Issue 24(2019)
• Page Start: 2774
• Page End: 2782
• Publication Date: 2019-12-17
• Subjects: Visual analytics -- sports analytics -- soccer analytics -- information visualisation; Sports -- Periodicals; Sports -- Physiological aspects -- Periodicals; Sports -- Psychological aspects -- Periodicals; 612.044
• DOI: 10.1080/02640414.2019.1652541
• Languages: English
• ISSNs: 0264-0414

Abstract

ABSTRACT: 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.