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Team-Scouter: Simulative Visual Analytics of Soccer Player Scouting.
IEEE Transactions on Visualization and Computer Graphics
|September 10, 2024
Summary
This study introduces Team-Scouter, a visual analytics system for soccer player scouting. It uses match simulation to predict player performance in new teams, aiding coaches in making informed decisions.
Area of Science:
- Sports Analytics
- Data Visualization
- Computational Science
Background:
- Soccer player scouting traditionally relies on historical performance, which doesn't predict future team integration.
- Existing match simulation methods primarily focus on match outcomes, lacking detailed player behavior analysis.
Purpose of the Study:
- To develop a visual analytics method for soccer player scouting using advanced match simulation.
- To create an interactive system that facilitates player navigation, comparison, and in-depth behavioral analysis.
Main Methods:
- A two-level match simulation framework was developed to estimate both match results and individual player behaviors in new team contexts.
- A visual analytics system, Team-Scouter, was built upon this framework to support interactive scouting processes.
Main Results:
- Team-Scouter enables coaches and analysts to discover potential players and compare their historical and simulated future performances.
- The system offers visual comparisons of simulated player behaviors against actual past actions for detailed investigation.
Conclusions:
- The proposed visual analytics method and Team-Scouter system effectively assist soccer player scouting by integrating match simulation with interactive visualization.
- Case studies and expert interviews validate the system's usefulness and effectiveness in identifying suitable players for enhanced team performance.
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