Superstat provides an AI-powered computer vision platform that automates sports game footage analysis to generate comprehensive player and team statistics. Users upload game video to receive detailed performance data, including box scores, shot charts, and automated highlight reels, streamlining data collection and delivering objective performance feedback.
Funding
Funding not disclosed
Founders
Product
Problem
Manual game footage analysis for sports statistics is time-consuming and prone to human error, leading to incomplete data and delayed insights for player development and team strategy. This process often requires dedicated personnel and lacks the precision needed for advanced performance metrics.
Solution
Superstat offers an AI-powered computer vision platform that automates the analysis of sports game footage to generate comprehensive player and team statistics. By uploading game video, users receive detailed performance data, including shot charts, box scores, and automated highlight reels. The system leverages custom-trained computer vision models to track player and ball movements, identify key events, and map court positions, providing actionable insights without manual intervention. This streamlines the data collection process and delivers objective performance feedback for coaches and athletes.
Target Audience
The primary users are sports coaches, athletes, and sports analytics professionals seeking to enhance performance through automated statistical analysis of game footage.
Features
- AI-driven computer vision models for automated analysis of game footage.
- Real-time ball tracking to detect passes, rebounds, and shot attempts.
- Automatic player recognition and labeling for individual stat tracking.
- Court line and zone mapping for location-based statistics and heatmaps.
- Generation of complete box scores and shot charts, including makes and misses.
- Automated creation of highlight reels from key game events.
- Play-by-play breakdowns and match reports for team performance analysis.
- Suggested training drills based on identified performance trends.