Cold-Start Exposure Gate
This study separates two questions that were previously conflated in the draft-informed cold-start prior: what rate should a player have if he earns rotation exposure, and how likely is a first-NBA-season player to earn enough exposure to avoid the pooled replacement group?
The pooled replacement-token study answers the first question for the low-exposure pool. This page addresses the second question for first-NBA-season players only. Returning players keep their lagged RAPM prior; a low minute count in a returning season never activates this gate.
Model Contract
For historical first-NBA-season player \(i\), define realized regular-season team-opportunity share as
The binary label is \(r_i = \mathbb{1}[s_i < 0.05]\), so a positive label means the player fell in the low-exposure population used by the shared replacement token. The logistic gate estimates
where \(x_i\) contains centered linear and quadratic draft pick, draft-status indicators (undrafted, pick above 60, or unknown), draft age, listed height, listed body-mass index, and the draft-pick-by-draft-age interaction. Features are standardized and the model uses L2-regularized logistic regression.
Draft age is reported season age adjusted back to the draft year. As with the draft RAPM prior, this is conditional on recording a first NBA season: drafted players with no NBA appearance are absent. The gate is a conditional rotation/exposure model, not a general draft-prospect model.
2025-26 Diagnostic
The current immutable run is
artifacts/models/cold_start_exposure/2025-26/cold-start-exposure-2025-26-20260806T013228Z-6072bdd3/.
It trains on 2,299 first-NBA-season players from 1996-97 through 2024-25 and
produces 100 preseason-only 2025-26 profiles. The target profile artifact
excludes target RAPM, possessions, realized exposure share, and the
replacement-candidate label.
The selected inverse L2 penalty was C = 10.0, based on six expanding
validation seasons from 2019-20 through 2024-25. The profile features are
meaningfully predictive:
| Model | Out-of-fold players | Log loss | Brier score | ROC AUC |
|---|---|---|---|---|
| Draft-profile gate | 611 | 0.5415 | 0.1850 | 0.7889 |
| Constant historical candidate rate | 611 | 0.6930 | 0.2499 | 0.5000 |
The left panel gives the partial draft-pick relationship at the historical reference draft age and body profile; the right panel is calibration over the six forward folds. The fitted probability rises from 2.8% for pick 1 to 60.3% for pick 60 at that reference profile. Rocco Zikarsky's low-exposure probability is 71.7%, correcting the earlier draft RAPM-rate artifact where the pick-age interaction made him appear unusually favorable.
The gate does not make a hard 5% probability decision. That would throw away useful uncertainty. The exposure-gated cold-start prior uses the probability continuously:
It is evaluated with the full 2025-26 regular-season and playoff holdouts, while this study remains independently inspectable for calibration.
2025-26 Cold-Start Rankings
These sortable rankings are predicted rotation probability, not player
quality or retrospective RAPM. A lower low-exposure probability means the
player is less likely to receive the replacement component in a future blended
prior. The complete 100-player table is target_exposure_predictions.parquet
in the immutable run.
Top 25 Predicted Rotation Rankings
| Rank | Player | Pos. | Draft status | Pick | Draft age | P(low exposure) | P(rotation) |
|---|---|---|---|---|---|---|---|
| 1 | Dylan Harper | G | Drafted 1-60 | 2 | 20 | 2.2% | 97.8% |
| 2 | Cooper Flagg | F | Drafted 1-60 | 1 | 19 | 2.4% | 97.6% |
| 3 | VJ Edgecombe | G | Drafted 1-60 | 3 | 20 | 2.5% | 97.5% |
| 4 | Kon Knueppel | G-F | Drafted 1-60 | 4 | 20 | 3.0% | 97.0% |
| 5 | Jeremiah Fears | G | Drafted 1-60 | 7 | 19 | 3.5% | 96.5% |
| 6 | Tre Johnson | G | Drafted 1-60 | 6 | 20 | 3.8% | 96.2% |
| 7 | Ace Bailey | F | Drafted 1-60 | 5 | 19 | 3.9% | 96.1% |
| 8 | Collin Murray-Boyles | F | Drafted 1-60 | 9 | 21 | 5.6% | 94.4% |
| 9 | Egor Demin | G | Drafted 1-60 | 8 | 20 | 5.6% | 94.4% |
| 10 | Cedric Coward | G | Drafted 1-60 | 11 | 22 | 6.9% | 93.1% |
| 11 | Khaman Maluach | C | Drafted 1-60 | 10 | 19 | 8.1% | 91.9% |
| 12 | Noa Essengue | F | Drafted 1-60 | 12 | 19 | 8.3% | 91.7% |
| 13 | Carter Bryant | F | Drafted 1-60 | 14 | 20 | 8.8% | 91.2% |
| 14 | Derik Queen | C | Drafted 1-60 | 13 | 21 | 9.3% | 90.7% |
| 15 | Walter Clayton Jr. | G | Drafted 1-60 | 18 | 23 | 12.0% | 88.0% |
| 16 | Nolan Traore | G | Drafted 1-60 | 19 | 20 | 12.5% | 87.5% |
| 17 | Yang Hansen | C | Drafted 1-60 | 16 | 21 | 14.8% | 85.2% |
| 18 | Kasparas Jakucionis | G | Drafted 1-60 | 20 | 20 | 14.8% | 85.2% |
| 19 | Joan Beringer | F | Drafted 1-60 | 17 | 19 | 15.2% | 84.8% |
| 20 | Drake Powell | G-F | Drafted 1-60 | 22 | 20 | 17.5% | 82.5% |
| 21 | Jase Richardson | G | Drafted 1-60 | 25 | 20 | 18.1% | 81.9% |
| 22 | Nique Clifford | G | Drafted 1-60 | 24 | 24 | 19.2% | 80.8% |
| 23 | Will Riley | F | Drafted 1-60 | 21 | 20 | 20.9% | 79.1% |
| 24 | Asa Newell | F | Drafted 1-60 | 23 | 20 | 23.6% | 76.4% |
| 25 | Ben Saraf | G | Drafted 1-60 | 26 | 20 | 24.4% | 75.6% |
Artifacts
| File | Contents |
|---|---|
training_first_nba_season_exposure.parquet |
Historical first-year labels, exposure shares, and preseason features |
target_first_nba_season_profiles.parquet |
Outcome-free target-season player profiles |
cross_validation.parquet |
Six expanding-fold candidates and scores |
cross_validated_predictions.parquet |
One forward prediction per validation player |
calibration_deciles.parquet |
Out-of-fold calibration bins |
target_exposure_predictions.parquet |
2025-26 cold-start probabilities and ranks |
model.joblib |
Final logistic gate fit through 2024-25 |
metadata.json / manifest.json |
Scope, temporal boundary, source hashes, and integrity records |