The Success Factors of Rest Defense in Soccer – A Mixed-Methods Approach of Expert Interviews, Tracking Data, and Machine Learning Article Swipe
Leander Forcher
,
Leon Forcher
,
Stefan Altmann
,
Darko Jekauc
,
Matthias Kempe
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.52082/jssm.2023.707
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.52082/jssm.2023.707
While the tactical behavior of soccer players differs between specific phases of play (offense, defense, offensive transition, defensive transition), little is known about successful behavior of players during defensive transition (switching behavior from offense to defense). Therefore, this study aims to analyze the group tactic of rest defense (despite in ball possession, certain players safeguard quick counterattacks in case of ball loss) in defensive transition. A mixed-methods approach was used, involving both qualitative and quantitative analysis. Semi-structured expert interviews with seven professional soccer coaches were conducted to define rest defense. In the quantitative analysis, several KPIs were calculated, based on tracking and event data of 153 games of the 2020/21 German Bundesliga season, to predict the success of rest defense situations in a machine learning approach. The qualitative interviews indicated that rest defense can be defined as the positioning of the deepest defenders during ball possession to prevent an opposing counterattack after a ball loss. For instance, the rest defending players created a numerical superiority of 1.69 ± 1.00 and allowed a space control of the attacking team of 11.51 ± 9.82 [%] in the area of rest defense. The final machine learning model showed satisfactory prediction performance of the success of rest defense (Accuracy: 0.97, Precision: 0.73, f1-Score: 0.64, AUC: 0.60). Analysis of the individual KPIs revealed insights into successful behavior of players in rest defense, including controlling deep spaces and dangerous counterattackers. The study concludes regaining possession as fast as possible after a ball loss is the most important success factor in defensive transition.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.52082/jssm.2023.707
- https://www.jssm.org/hfpdf.php?volume=22&issue=4&page=707
- OA Status
- bronze
- Cited By
- 7
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4388547168
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4388547168Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.52082/jssm.2023.707Digital Object Identifier
- Title
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The Success Factors of Rest Defense in Soccer – A Mixed-Methods Approach of Expert Interviews, Tracking Data, and Machine LearningWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-11-09Full publication date if available
- Authors
-
Leander Forcher, Leon Forcher, Stefan Altmann, Darko Jekauc, Matthias KempeList of authors in order
- Landing page
-
https://doi.org/10.52082/jssm.2023.707Publisher landing page
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https://www.jssm.org/hfpdf.php?volume=22&issue=4&page=707Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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bronzeOpen access status per OpenAlex
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https://www.jssm.org/hfpdf.php?volume=22&issue=4&page=707Direct OA link when available
- Concepts
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Rest (music), Offensive, Counterattack, Computer science, Artificial intelligence, Computer security, Applied psychology, Psychology, Operations research, Engineering, Law, Medicine, Political science, CardiologyTop concepts (fields/topics) attached by OpenAlex
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7Total citation count in OpenAlex
- Citations by year (recent)
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2025: 6, 2024: 1Per-year citation counts (last 5 years)
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41Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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