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Fiverr Pro
Nederlands
$
USD
I will create football match analysis with player detection and tactical map
Faisalkhan
Level 1
Over deze dienst
Revolutionize how you analyze football with AI-powered computer vision!
I build Football Vision AI systems that detect and track players, referees, goalkeepers, and the ball in real-time from match footage automatically generating tactical insights and broadcast-style visualizations.
What I offer:
- Real-time player, referee & goalkeeper detection
- Ball tracking with trajectory & possession detection
- Automatic team assignment (jersey color clustering)
- ️ Top-down tactical radar / mini-map (bird's-eye view)
- Player speed, distance covered & heatmaps
- Jersey number & player ID tracking
- Match stats + annotated output video
️ Tech Stack: Python, YOLO, OpenCV, ByteTrack/tracking, NumPy
Why choose me:
- Robust tracking with consistent player IDs (minimal ID switches)
- Accurate team separation & ball possession logic
- Works on broadcast clips or tactical-cam footage
- Clean, documented, ready-to-run code
- Custom stats & visualizations on request
Perfect for sports analytics, coaching & scouting, betting/data platforms, content creators, and AI/CV portfolios.
Message me before ordering to discuss your footage & goals
Maak kennis met Faisalkhan
Faisalkhan
Computer Vision AI Expert
Level 1
- Afkomstig uitPakistan
- Lid sindsjul 2025
- Gem. reactietijd1 uur
- Laatste levering1 maand
Talen
Engels, Urdu, Arabisch
Experienced Computer Vision Engineer and Deep Learning Expert with strong skills in Python, TensorFlow, PyTorch, and OpenCV. Specialized in object detection, pose estimation, generative AI, and predictive analytics. Proficient in Power BI, Tableau, and deploying AI at scale using Databricks, SQL, and cloud platforms. Delivered solutions for medical imaging, smart cities, and R&D with advanced models like YOLO, ViT, GANs, and DeepSORT
Mijn portfolio
Andere Software development diensten die ik aanbied
Veelgestelde vragen
What do I need to provide to get started?
Just a sample match clip (broadcast or fixed-cam footage) and your goal — player tracking, team stats, tactical map, etc. Clear, steady footage gives the best tracking accuracy. Share details and I'll advise on the best approach
What footage works best?
Broadcast TV clips, tactical fixed-cam, or drone footage all work. Steady, wide-angle views where players are clearly visible give the most accurate tracking. Very low-resolution or shaky clips may reduce accuracy.
Can you tell which team each player belongs to?
Yes. I automatically separate teams using jersey-color clustering, and can detect ball possession. This is included from the Standard package onward.
What will I receive as the final delivery?
Clean, documented Python code, an annotated output video (boxes, IDs, tactical radar), and data export (CSV) with player positions and stats. A setup guide is included so you can run it yourself.
