Data Pointes Lab
Finding the right pointe shoe is one of the hardest problems in ballet — and most dancers still do it by word of mouth. Data Pointes Lab is the first open-source database built to change that: 400+ models across 16+ brands, with verified specs, real-time pricing, and four interactive tools designed around how dancers and fitters actually think about fit.
Four Tools
Corps de Data
The core database explorer — filter 400+ models across 20 fields including box shape, shank strength, vamp length, platform, price, and availability.
Relevé Relatives
An interactive similarity network. Select any shoe, adjust weighted sliders for each attribute, and find every model that matches your feel — with percentage similarity scores on each connection.
Barre Graphs
Statistical explorer for browsing brand distributions, attribute breakdowns, and price spreads. Click any bar to drill into the matching models.
AI-Verified Specs
Many specs go unpublished by manufacturers. AI inference fills those gaps using multi-source evidence and fitting expertise, with confidence thresholds applied before any field is shown.
Screenshots
Data & Coverage
400+ Models, 16+ Brands
Covers the full market — major brands like Freed, Gaynor Minden, and Bloch alongside boutique makers. Discontinued models tracked too.
Real-Time Pricing
Pricing and availability scraped weekly directly from brand sites, keeping the data current.
Open Database
Full dataset downloadable as CSV. MIT licensed, community contributions welcome.