Predicting the Pros
ML-powered draft intelligence that evaluates college wide receivers using position-aware features to predict NFL success before draft day.
Players Evaluated
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Draft Classes
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ML Features
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Current Class
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How Does This Work?
Every year, college football players leave school and try to play in the NFL. Most prospects don't make it. But some do — and scouts spend millions of dollars trying to figure out which ones.
We built a computer that studied every college wide receiver since 2001 and learned the patterns. Not just raw box-score production, but context too: age, athleticism, competition, and how a player compares to the rest of their class.
The computer gives each player a score from 0–100% — their chance of hitting 1,000+ NFL yards in at least one NFL season. Higher score = better prospect.
Think of it like a weather forecast, but for football careers.
Positions Roadmap
- ✓ Wide Receiver — Live
- ◦ Running Back — Live Beta
- ◦ Quarterback — Live Beta
- ◦ Tight End — Static Beta
- ◦ Defensive Positions — Planned
Explore the Tool
Draft Class Rankings
Full ranked list by draft year from the production global-model ensemble pipeline.
Player Profiles
Deep-dive per player: SHAP value breakdowns, comparable prospects, physical measurements, and draft history.
Feature Analysis
Explore the active 0 model features - distributions, missing-data rates, and detailed descriptions of how each is calculated.
Model Explorer
Live BetaStress-test the live model by removing top signals and reranking the supported draft classes for this position.