MARKET LAB
Powered by machine learning, our breakout model identifies year 2 and year 3 players primed for a massive leap based on underlying efficiency.
ML Breakout Engine
The model predicts the probability of a player taking a massive statistical leap into the Elite tier based on underlying efficiency metrics from their previous season.
Year 2 Candidates: Evaluated primarily on their rookie season efficiency (e.g., Target Share, EPA/Play). High efficiency on limited snaps strongly predicts a sophomore breakout.
Year 3 Candidates: Evaluated on their sophomore season efficiency. Historically, players who haven't broken out by Year 3 have a drastically lower success rate, so the model requires exceptional sophomore metrics to project a leap.
Raw vs Adj Prob: The Raw ML Prob is the pure algorithmic likelihood of a breakout based entirely on efficiency. However, efficiency doesn't matter without volume. The Adj Breakout Prob penalizes this raw probability if the player's market value (Redraft ADP) indicates they are buried on the depth chart and unlikely to see the field.
SH Metrics: "SH" stands for Second Half. The model often uses Second Half metrics (like SH Tgt Share) for rookies, as late-season rookie performance is a much stronger predictor of future success than full-season averages.
Powered by XGBoost algorithms trained on 10 years of NFL history, this model predicts the probability a player jumps into an Elite or Blue Chip tier based on their underlying rookie/sophomore efficiency metrics. Probabilities are market-adjusted based on current KTC values.
| Player | Class | Primary Metric | Secondary Metric | Raw ML Prob | Adj Breakout Prob | Redraft ADP |
|---|---|---|---|---|---|---|
No players found matching your criteria. | ||||||