Padel AI

Project Overview

• Edge computing with AI-powered analytics platform for Padel.
• Automatically analyzes match videos in real-time.
• Uses Computer Vision/ML for tracking and stats.
• Detects players, ball, and classifies shot types.
• Provides deep, positional gameplay insights.
• Deployed in 17+ Countries.

Challenges

Edge Computing & Mobile Solution

• Hardware: NVIDIA Jetson devices for on-court, edge-based processing.
• Real-time analysis of 4K video footage at 90 FPS.
• AI/ML models for player and ball tracking, gesture recognition, and shot classification.
• Player positioning and ball trajectory analysis.

Dedicated Mobile App

• Primary interface for players, coaches, and viewers.
• Real-time display of key metrics and statistics.
• Visualization of player heatmaps, zone maps, and ball trajectory.
• Access to historical performance data and club rankings.
• Platform for sharing and consuming game insights.

Advanced Performance Analytics

• Shot Classification: AI recognizes Forehand, Smash, Volley, Lob, and Error shots.
• Player Statistics: Tracks speed and distance throughout the match.
• Heatmap & Zone Map: Visualizations of player movement, court coverage, and dominant zones.
• Auto Highlights: 15 clips generated per match using the On-Court Trigger system.

Personalized Game Intelligence

• Performance Radar with overall skill breakdown.
• Personalized recommendations per player for offensive, defensive, and dead zone strategies.
• Movement analysis with energy conservation tips for crucial points.
• Unforced error reduction through controlled rally drill recommendations.

Vision

• Real-time AI & Computer Vision padel analysis via Edge Computing.
• Edge-based processing on NVIDIA Jetson for 4K video.
• Advanced AI for tracking, gesture, and shot classification.
• Detailed metrics: heatmaps, distance, ball speed, and shot types.

Technology Stack