CASE STUDY — NFL PLAYER VALUE
NEXUS predicted what NFL players would be worth before the market did
NFL player valuation is a market full of competing opinions. NEXUS learned from decades of contracts and performance data to predict where that market would actually land.
NEXUS PREDICTION
$23.4M
ACTUAL CONTRACT
$22.5M
A market full of competing opinions
Before a player signs, nobody knows exactly what he's worth. Teams have their models. Agents have theirs. Analysts publish estimates. The market has a view. And the numbers can be wildly different. Yet teams are making multimillion-dollar, multi-year decisions based on precisely that uncertainty. We wanted to know whether NEXUS could find the signal across decades of NFL performance and contract history — and get closer to the number the market would ultimately produce.
Four decades of NFL economics
NEXUS learned from four decades of NFL economics, connecting what players did on the field with how their careers developed and what the market eventually paid them.
1985–2026
Over The Cap — contract data
2000–2025
NFL GSIS — season statistics
2016–2025
Next Gen Stats — player data
The model wasn't built around one player or one contract. The objective was to learn the underlying relationship between performance, career trajectory and future market value.
03 — THE RESULT
The number before the market
The Malik Willis prediction shows just how powerful that can be.
Broader market estimate
~$30.0M
Open-source models
~$15.0M
NEXUS prediction
$23.4M
Actual contract
$22.5M
And Willis wasn't the only test. Ahead of CeeDee Lamb's extension, NEXUS predicted $31.5M APY before he signed for $34M APY. For Ja'Marr Chase, NEXUS predicted $37.5M APY before he signed for $40.2M APY.
04 — THE IMPACT
An informational advantage.
Now the story becomes much bigger than predicting someone's next contract. If you can model future player value before the market establishes it, you can start asking entirely different questions: Who is undervalued? Who is overpriced? Where should we deploy capital? What happens to roster economics under different scenarios?
For a professional sports organization, that's not simply a better prediction. It's an informational advantage in one of the biggest investments the organization makes.
