Team-Builder: Toward More Effective Lineup Selection in Soccer.

Area of Science:

• Sports Analytics
• Human-Computer Interaction
• Computational Science

Background:

• Soccer lineup selection is critical for match success, involving complex player performance considerations.
• Existing computational tools often use oversimplified models and lack interactive coach input.
• There's a need for advanced methods that integrate diverse factors and support coach-driven analysis.

Purpose of the Study:

• To develop a visual analytics method for optimizing soccer lineup selection.
• To address challenges in characterizing essential lineup factors and supporting coach-driven analysis.
• To create an interactive system for lineup generation, explanation, and comparison.

Main Methods:

• Developed a lineup selection model incorporating spatial player actions and defensive interactions.
• Created a visualization system, Team-Builder, with multiple coordinated views.
• Utilized real-world soccer event data for case studies.

Main Results:

• The proposed model effectively integrates key factors for optimal lineup generation.
• Team-Builder provides coaches with interactive control over the lineup selection process.
• Case studies demonstrated the system's usefulness and effectiveness in analyzing real soccer data.

Conclusions:

• The visual analytics approach enhances soccer lineup selection by integrating complex factors.
• The Team-Builder system supports coach-driven decision-making through interactive visualization.
• This method offers a more comprehensive and effective tool for soccer strategy development.