Hype Score as a Leading Indicator

While demand_score measures what's happening now, hype_score is designed to predict where a shoe is headed — typically 2–4 weeks out.

How it's built

Hype score draws primarily from pre-release signals: announced colorways, early reservation data, influencer coverage, and community discussion volume. Post-release, it shifts to tracking early secondary market momentum.

We backtested the signal against 18 months of actual price data. Shoes with hype scores above 80 at release outperformed the catalog median by 34% in resale value during the first 30 days.

The Jordan 4 Bred Reimagined case study

The Jordan 4 Bred Reimagined showed a hype score of 91 three weeks before release. By release day it had climbed to 96. Secondary prices came in at 2.4× retail — above what our model predicted (1.9×), but directionally correct.

What the model missed: a supply constraint that wasn't public until 48 hours before the drop. Pure market data can't catch everything.

Using it in your app

The hype score works best as a filter rather than a rank. Use it to surface shoes worth watching in your release calendar, not to auto-trade.