Evidence
29 Aug 2026, 17:27 UTCOver 25 paired rounds, the model does NOT beat the baseline (grid order).
| Baseline | Race | Rounds | Model | Baseline | Gain | Verdict |
|---|---|---|---|---|---|---|
| Grid order | race | 25 | 9.62 | 9.11 | -0.51 | does NOT beat the baseline |
| Last race order | race | 24 | 9.40 | 10.09 | +0.69 | beats the baseline |
Paired bootstrap on the round-by-round difference: -0.510, 95% CI [-0.975, -0.010] in positions gained. Positive means the model is closer to the real finishing order than grid order is; the whole interval is BELOW zero, so the shortfall is measured, not noise.
forward evaluation — each round was forecast before it ran and scored afterwards; not a backtest. Historical replays and the forward record are computed separately and never merged.
- The model does not beat grid order on every measured comparison. That is stated rather than hidden.
- Some comparisons straddle zero: a difference has not been demonstrated, in either direction.
- Metrics are only comparable within this series. A position error over this field size means nothing next to another series' number.
NASCAR Cup Series · Season 2026
Model accuracy
How the NASCAR model’s pre-race forecasts have scored against the actual results, over 25 completed rounds of the season. Every number is scored against the full official classification (every car is classified in Cup racing), using only data available before each race.
Winner hit rate
20%
Podium hit rate
21%
Mean position error
9.62
NDCG@5
0.73
Per-round accuracy
Podium-weighted race accuracy per round. Tap a cell for the breakdown.
Per round
| Round | Winner | Podium hits | Mean error | NDCG@5 | Win Brier |
|---|---|---|---|---|---|
| R1 · Daytona International Speedway | miss | 0/3 | 15 | 0.52 | 0.0238 |
| R2 · Atlanta Motor Speedway | ✓ hit | 1/3 | 11.474 | 0.69 | 0.0222 |
| R3 · Circuit of The Americas | ✓ hit | 1/3 | 10.486 | 0.80 | 0.0186 |
| R4 · Phoenix Raceway | miss | 0/3 | 8.432 | 0.65 | 0.0286 |
| R5 · Las Vegas Motor Speedway | miss | 1/3 | 6.778 | 0.85 | 0.0274 |
| R6 · Darlington Raceway | ✓ hit | 1/3 | 9.73 | 0.71 | 0.0196 |
| R7 · Martinsville Speedway | miss | 1/3 | 6.595 | 0.84 | 0.0277 |
| R8 · Bristol Motor Speedway | miss | 0/3 | 8.757 | 0.75 | 0.0237 |
| R9 · Kansas Speedway | ✓ hit | 1/3 | 7.243 | 0.86 | 0.0182 |
| R10 · Talladega Superspeedway | miss | 0/3 | 14.2 | 0.72 | 0.0260 |
| R11 · Texas Motor Speedway | miss | 1/3 | 8.579 | 0.86 | 0.0245 |
| R12 · Watkins Glen International | miss | 0/3 | 10.789 | 0.70 | 0.0288 |
| R13 · Charlotte Motor Speedway | miss | 1/3 | 11.077 | 0.61 | 0.0271 |
| R14 · Nashville Superspeedway | miss | 1/3 | 9.526 | 0.83 | 0.0209 |
| R15 · Michigan International Speedway | miss | 1/3 | 11.838 | 0.43 | 0.0179 |
| R16 · Pocono Raceway | ✓ hit | 2/3 | 7.579 | 0.93 | 0.0092 |
| R17 · San Diego Street Course | miss | 0/3 | 10.154 | 0.66 | 0.0284 |
| R18 · Sonoma Raceway | miss | 0/3 | 9.667 | 0.44 | 0.0302 |
| R19 · Chicagoland Speedway | miss | 1/3 | 8.526 | 0.64 | 0.0259 |
| R20 · Atlanta Motor Speedway | miss | 0/3 | 9.211 | 0.65 | 0.0245 |
| R21 · North Wilkesboro Speedway | miss | 1/3 | 7.73 | 0.78 | 0.0285 |
| R22 · Indianapolis Motor Speedway | miss | 0/3 | 9.692 | 0.81 | 0.0266 |
| R23 · Iowa Speedway | miss | 2/3 | 10.333 | 0.84 | 0.0235 |
| R24 · Richmond Raceway | miss | 0/3 | 8.27 | 0.84 | 0.0292 |
| R25 · New Hampshire Motor Speedway | miss | 0/3 | 8.889 | 0.79 | 0.0275 |
Win Brier scores the model’s win probabilities against who actually won — lower is sharper and better calibrated.
Walk-forward validation
Model vs the naive baselines
Every completed round is re-forecast using only earlier rounds, then scored against two trivial predictors — one that replays the previous result, one that assumes the grid finishes in order. Yellow marks the best column. Beating these baselines is the bar the model has to clear.
Cup Race
25 rounds · model vs naive baselines| Metric | Model | Last-race | Grid order |
|---|---|---|---|
| Mean position error | 9.62 | 10.09 | 9.11 |
| Top-5 ranking | 0.728 | 0.672 | 0.726 |
| Order agreement | 0.364 | 0.286 | 0.410 |
| Podium hits / round | 0.64 | 0.54 | 0.80 |
Candidate model
A shadow model runs alongside the live one
position-head candidate · gated behind NASCAR_USE_POSITION_HEAD
Comparison basis: race mean_position_error
Production error
9.34
mean positions off
Candidate error
9.45
mean positions off
Gap
+0.11
candidate minus production
candidate within ±2% of production (mean change -1.9%). The candidate only gets promoted once it beats the live model on enough real rounds — until then the site keeps serving the production forecast.
Probability calibration
How trustworthy the probabilities are
A well-calibrated model assigns probabilities that match how often things actually happen. The forecasts are tuned against the season’s real classified results — separately for each of the four track types, because Talladega and Sonoma race nothing alike — so a stated 30% podium chance means roughly 3-in-10 over the long run.
Training rounds
25
real completed rounds
Status
superspeedway stratumroad stratumshort stratumintermediate stratum
Calibrated on real NASCAR Cup results, stratified by track type (superspeedway / intermediate / short / road).
Generated 8/30/2026, 12:00:50 PM
Calibration samples per market
Win
941
observations
Podium
941
observations
Top 6
941
observations
Top 10
941
observations
Each figure is how many prior driver-outcomes fed the calibrator for that market. More samples means a steadier probability estimate.
Historical performance
Backtest across 6,045 driver-rounds
Predicted finishing order scored against the official classification for the 2026 season — every round, every driver. Each round was replayed using only signals available before lights-out, so nothing here is hindsight.
Rounds Evaluated
36
Mean Position Error
9.49 pos
Within 3 Positions
26.5%
Within 5 Positions
37.7%
Podium Hit Rate
14.8%
Winner Hit Rate
5.6%
Order Agreement
0.340
Top-5 Ranking
0.619
Model Health
WatchA self-check on the live model: whether recent forecasts are still landing as well as they should, and whether the numbers feeding the model have drifted from what it was tuned on.
Forecast quality
▲ 14%
higher error than the season benchmark
Rounds monitored
25
recent rounds in the rolling check
Input drift
6/6
model inputs that moved vs baseline
Input drift by feature
Win-market Brier, Round by Round
How far the model's win probabilities sat from who actually won — lower is a better-calibrated forecast.
Some model inputs have drifted from their reference range — normal across a season as the field moves between superspeedways, short tracks, intermediates and road courses. It is flagged here for transparency, but the rolling forecast-quality check above shows whether the predictions themselves are being watched closely.
Diagnostics
- ⚠ pWin: PSI 0.288 (significant drift vs baseline)
- ⚠ pPodium: PSI 0.287 (significant drift vs baseline)
- ⚠ pDnf: PSI 0.572 (significant drift vs baseline)
- • predictedValue: PSI 0.135 (moderate drift vs baseline)
- • meanFinish: PSI 0.135 (moderate drift vs baseline)
- • finishRangeHigh: PSI 0.241 (moderate drift vs baseline)
- • rolling Brier regression +14.4%