Dinkmate
Dinkmate is a vision-based rating platform for pickleball that analyzes recorded gameplay videos to deliver objective player ratings and personalized improvement insights. Users upload match footage to the app, where machine learning models trained specifically for pickleball performance generate a Vision-Based Rating (VBR) for each player. The platform supports fair tournament seeding, prevents sandbagging, and assists coaches with data-driven skill assessment.
- Sports Technology
- Artificial Intelligence
- Data & Analytics
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Traditional pickleball rating systems rely on self-assessment or subjective human evaluation, which often leads to inaccurate player ratings and mismatched competition levels. This creates frustration for players, enables sandbagging in tournaments, and makes it difficult to organize fair level-based training groups or properly seed competitive events.
Solution
Dinkmate provides a vision-based rating (VBR) platform that analyzes recorded gameplay videos to deliver accurate, objective player ratings. Users simply upload a video of their match to the Dinkmate app, and advanced machine learning models trained specifically for pickleball performance process the footage to generate a Vision-Based Rating for each player. The system also produces personalized improvement insights, helping players understand their strengths and weaknesses. This data-driven approach eliminates guesswork and provides a consistent, objective measurement standard that supports fair competition, tournament seeding, and targeted skill development.
Target Audience
Primary users are pickleball players seeking accurate self-assessment, tournament organizers needing objective seeding data, and coaches looking for data-driven tools to support player development and level-based training.
Features
- Vision-based rating (VBR) technology that analyzes gameplay from standard video recordings without requiring special hardware or sensors
- Machine learning models trained specifically for pickleball performance analysis
- Instant player rating generation after video upload
- Personalized improvement insights for each player based on gameplay analysis
- Objective, data-driven rating system that helps identify and prevent sandbagging
- Supports tournament seeding and level-based training group organization
- Coaching support capabilities for skill assessment and development planning