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Where to go: Computational and visual what-if analyses in soccer
Manuel Stein1, Daniel Seebacher1, Rui Marcelino2,3
1Department of Computer and Information Science, University of Konstanz , Konstanz , Germany.
This study introduces an automated system for analyzing soccer matches, detecting faulty player movements, and suggesting improvements. The approach significantly speeds up analysis and enhances coaches' ability to refine team strategies.
Area of Science:
- Sports Science
- Data Analytics
- Human-Computer Interaction
Background:
- Professional soccer analysts manually review numerous matches daily, a process that is time-consuming and subjective.
- Identifying and correcting suboptimal player movements relies heavily on expert intuition and experience.
Purpose of the Study:
- To develop an automated system for region-based "what-if" analyses in soccer.
- To automatically detect faulty player movement behavior and suggest improved alternatives.
Main Methods:
- The proposed system automatically identifies region-based faulty movement patterns.
- It generates suggestions for improved alternative player movements.
- Domain experts can interactively adjust suggested movements and their impact on region control.
Main Results:
- The automated approach significantly speeds up the analysis of soccer matches.
- An expert study showed 83% agreement with the system's suggested player movements.
- The system effectively supports analysts and coaches in match investigation.
Conclusions:
- The automated system enhances analytical capabilities in professional soccer.
- It enables more efficient and data-driven analysis of team performance.
- The approach integrates domain expertise with automated suggestions for improved movement strategies.
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