AI Developer for Soccer Training Video Analysis App Project Overview We are building a next-generation soccer training platform that uses AI to analyze player movements from basic home-recorded videos (no sensors, no professional cameras). The MVP should accept videos recorded on smartphones or tablets, detect key player movements (e.g., passes, shots, dribbling, positioning), and provide actionable feedback to players and coaches—especially for youth soccer. We are not looking to reinvent existing tools like Veo or Playermaker—we want to democratize video analysis by enabling any kid, anywhere, to get feedback from a basic home video. Key Deliverables AI/ML pipeline to process soccer training videos (pose estimation, movement detection, object tracking) Frontend UI to upload videos, see results/feedback Backend for video processing + player profile storage Integration of a basic "highlight/feedback" engine Clear modular structure for future scalability (e.g., adding drills, skill tagging, performance tracking) Technical Requirements Proven experience with computer vision, pose estimation, or sports AI Familiarity with frameworks like OpenPose, MediaPipe, or Detectron2 Preferred stack: Python, TensorFlow/PyTorch, React or Next.js (for frontend), FastAPI or Flask (for backend) Bonus: Experience with youth sports apps, video annotation tools, or coaching platforms