HOOP PROPS
NBA Props, Modeled — Not Marketed
NBA Player Props, Quantified. Not Guessed.
Hoop Props is a data-driven NBA player prop analysis platform that converts posted lines into estimated probabilities and confidence tiers you can review.
Every slate is modeled using multiple independent statistical methods to highlight where model estimates diverge from posted lines.
Stop guessing. Start with the data.
Data-Driven NBA Player Prop Analysis Built for Long-Term Evaluation
Hoop Props analyzes NBA player props using a multi-model probability engine designed to surface meaningful signal, not short-term noise.
The result: clear, transparent player prop probabilities and confidence tiers that help you decide when a prop is worth a closer look and when to pass.
- Historical performance distributions
- Bayesian priors to stabilize small samples
- Kernel Density Estimates (KDE) for non-normal outcomes
- Monte Carlo simulations to stress-test variance
Why Hoop Props Is Different?
Every prop includes model-derived probability estimates: no hype language, no promises.
Props are graded only when several independent statistical methods agree, reducing false confidence.
See where model estimates diverge from posted lines and where they align.
Lines refresh as markets move, so probabilities stay relevant, not stale screenshots.
Designed for people focused on process, discipline, and long-term evaluation.
Built for Serious NBA Prop Analysis
Hoop Props is for fans who care about transparent math and prefer passing low-signal slates over forcing action.
If you're tired of guessing or blindly following chatter, Hoop Props gives you a framework to think independently.
- Care about probability estimates, not gut feel
- Want transparent math, not black-box outputs
- Prefer passing low-signal slates over forcing action
- Think in probabilities, not guarantees