I will develop object detection, player ball tracking system for football analytics

K
kimlonah5
K
kimlonah5
Kim L

About this gig

Want to automatically analyze football games with AI?


I will develop a computer visionbased tracking system that detects and follows all players, referees, and the ball throughout a match turning your video into structured data and clear performance metrics.


Using YOLOv8, DeepSORT, OpenCV, and PyTorch, this system maintains consistent IDs, computes player distances, and outputs match analytics in CSV or dashboard form ready for tactical review or performance improvement.


What You will Get :


  • Player, ball, and referee detection
  • Auto player ID assignment across frames
  • Distance, speed, possession, and coverage metrics
  • Optional heatmaps and visual overlays
  • Structured outputs: CSV / JSON / XLSX
  • Integration-ready codebase for future expansion


Tech Stack: YOLOv8, DeepSORT, OpenCV, PyTorch, TensorRT

Output Formats: CSV, JSON, XLSX, or video overlay (MP4)


Why Me:

  • Expertise in football and multisport CV systems
  • Accurate tracking even under occlusion or camera motion
  • Clean, optimized Python scripts with documentation
  • MVP-ready within weeks


Lets build the foundation of your AI-powered football analytics system today.

Get to know Kim L

Kim L

sports computer vision and AI analytics developer

  • FromUnited Kingdom
  • Member sinceNov 2025
  • Languages

    English, Spanish
I’m a sports computer vision and AI analytics developer who transforms raw match videos into intelligent data and performance insights. Using advanced machine learning models (YOLOv8, DeepSORT, OpenCV, PyTorch), I build automated systems that detect and track players, balls, referees, and game events across any sport — football, basketball, volleyball, or more.