Davidsv/football_insight

Football Match Analysis

Model Description

This project uses YOLO v26 models for real-time football match analysis, including:

• —Player detection and tracking
• —Team classification by jersey color
• —Referee detection (orange/yellow/pink jerseys)
• —Formation line visualization
• —Possession and pass statistics

Intended Use

• —Sports analytics and coaching
• —Match analysis and review
• —Training video annotation
• —Research in sports computer vision

Models Used

Download models from Ultralytics.

How to Use

# Clone the repository
git clone https://github.com/YOUR_USERNAME/football-analysis.git
cd football-analysis

# Install dependencies
pip install -r requirements.txt

# Download YOLO models
# Models are automatically downloaded on first run

# Run analysis
python main.py input_video.mp4 output_video.mp4

Features

Team Classification

• —Automatic team color detection using K-means clustering
• —HSV-based referee detection (orange, yellow, pink jerseys)
• —Temporal smoothing to avoid flickering

Formation Lines

• —Detects horizontal player alignments (3+ players)
• —Maximum 2 connections per player
• —Visualizes defensive/midfield/attack lines

Statistics

• —Real-time possession percentage
• —Pass count per team
• —Footer overlay with live stats

Configuration

Key parameters in config.py:

detection_confidence = 0.3  # Player detection threshold
ball_confidence = 0.2       # Ball detection threshold
device = "mps"              # Auto-detected: mps/cuda/cpu

Limitations

• —Requires clear camera angle (broadcast view works best)
• —Teams must have distinct jersey colors
• —Possession stats are approximate (based on ball proximity)
• —Performance varies with video quality

Performance

Training Data

This project uses pre-trained YOLO v26 models from Ultralytics, trained on:

• —COCO dataset (person, sports ball classes)
• —No additional fine-tuning on football-specific data

Ethical Considerations

• —This tool is intended for sports analysis only
• —Should not be used for surveillance purposes
• —Respect privacy when analyzing non-public matches

Citation

@software{football_analysis,
  title={Football Match Analysis with YOLO v26},
  year={2026},
  url={https://github.com/David-dsv/football-analysis}
}

License

MIT License