https://github.com/varshan1123/football-analysis
Designed a soccer analytics system using YOLOv11 for player and ball tracking, with team classification and real-world movement analysis, enabling precise speed and distance assessments. Integrated automated reporting to enhance data-driven decisions for coaches and analysts.
https://github.com/varshan1123/football-analysis
gemini-api kmeans-clustering numpy opencv ultralytics yolov11
Last synced: 13 days ago
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Designed a soccer analytics system using YOLOv11 for player and ball tracking, with team classification and real-world movement analysis, enabling precise speed and distance assessments. Integrated automated reporting to enhance data-driven decisions for coaches and analysts.
- Host: GitHub
- URL: https://github.com/varshan1123/football-analysis
- Owner: Varshan1123
- Created: 2024-11-15T17:42:53.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-11-15T18:06:28.000Z (12 months ago)
- Last Synced: 2025-06-05T00:52:11.413Z (5 months ago)
- Topics: gemini-api, kmeans-clustering, numpy, opencv, ultralytics, yolov11
- Language: Jupyter Notebook
- Homepage:
- Size: 29.2 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Soccer Performance Analytics: Leveraging YOLOv11 and Image Processing for Data-Driven Insights
In the rapidly evolving field of soccer analytics, leveraging advanced technologies is essential for performance evaluation and strategic decision-making. This project utilizes the newly introduced YOLOv11, a state-of-the-art object detection model, to detect and track players and the ball in video footage from multiple camera angles. Integrated object trackers ensure continuity across frames, while K-means clustering classifies players into teams based on t-shirt colors. Through image processing techniques like optical flow and perspective transformation, player movements are converted into real-world measurements, enabling precise assessments of speed and distance covered. Additionally, Gemini AI is incorporated to automatically generate detailed reports based on the analyzed data, providing comprehensive insights for coaches, analysts, and sports authorities. This system aims to empower data-driven decision-making in soccer management and elevate the effectiveness of performance analysis.