Evidence
9 Jul 2026, 10:10 UTCOver 11 paired rounds, the model no difference demonstrated (grid order).
| Baseline | Race | Rounds | Model | Baseline | Gain | Verdict |
|---|---|---|---|---|---|---|
| Grid order | race | 11 | 6.11 | 5.73 | -0.38 | no difference demonstrated |
| Last race order | race | 10 | 6.10 | 7.70 | +1.60 | beats the baseline |
Paired bootstrap on the round-by-round difference: -0.380, 95% CI [-1.079, 0.291] in positions gained. Positive means the model is closer to the real finishing order than grid order is; the interval covers zero, so no difference has been demonstrated.
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.
- 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.
NTT IndyCar Series · Season 2026
Model accuracy
How the IndyCar model’s pre-race forecasts have scored against the actual results, over 11 completed rounds of the season. Every number is scored against the full official classification (every car is classified in IndyCar racing), using only data available before each race.
Winner hit rate
27%
Podium hit rate
42%
Mean position error
6.11
NDCG@5
0.76
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 · Streets of St. Petersburg | ✓ hit | 2/3 | 6.16 | 0.66 | 0.0121 |
| R2 · Phoenix Raceway | miss | 1/3 | 5.92 | 0.63 | 0.0435 |
| R3 · Streets of Arlington | ✓ hit | 2/3 | 5.2 | 0.92 | 0.0315 |
| R4 · Barber Motorsports Park | miss | 1/3 | 4.48 | 0.83 | 0.0362 |
| R5 · Streets of Long Beach | miss | 1/3 | 6.4 | 0.71 | 0.0286 |
| R6 · Indianapolis Motor Speedway Road Course | miss | 1/3 | 6.24 | 0.77 | 0.0491 |
| R7 · Indianapolis Motor Speedway | miss | 1/3 | 9.091 | 0.62 | 0.0335 |
| R8 · Streets of Detroit | ✓ hit | 2/3 | 5.04 | 0.73 | 0.0175 |
| R9 · World Wide Technology Raceway | miss | 0/3 | 7.04 | 0.68 | 0.0445 |
| R10 · Road America | miss | 1/3 | 6.4 | 0.85 | 0.0428 |
| R11 · Mid-Ohio Sports Car Course | miss | 2/3 | 5.2 | 0.94 | 0.0461 |
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.
IndyCar Race
11 rounds · model vs naive baselines| Metric | Model | Last-race | Grid order |
|---|---|---|---|
| Mean position error | 6.11 | 7.70 | 5.73 |
| Top-5 ranking | 0.757 | 0.616 | 0.793 |
| Order agreement | 0.430 | 0.192 | 0.496 |
| Podium hits / round | 1.27 | 0.50 | 1.18 |
Candidate model
A shadow model runs alongside the live one
position-head candidate · gated behind INDYCAR_USE_POSITION_HEAD
Comparison basis: race mean_position_error
Production error
6.24
mean positions off
Candidate error
6.30
mean positions off
Gap
+0.07
candidate minus production
candidate within ±2% of production (mean change +1.1%). 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
11
real completed rounds
Status
street stratumoval stratumroad stratum
Calibrated on real IndyCar results, stratified by track type (oval / road / street).
Generated 8/30/2026, 12:01:04 PM
Calibration samples per market
Win
283
observations
Podium
283
observations
Top 6
283
observations
Top 10
283
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 3,286 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
17
Mean Position Error
6.08 pos
Within 3 Positions
37.8%
Within 5 Positions
54.4%
Podium Hit Rate
37.3%
Winner Hit Rate
5.9%
Order Agreement
0.355
Top-5 Ranking
0.719
Model health
Win-market Brier trend
Lower is better · 11 rounds
Diagnostics
- ⚠ pPodium: PSI 0.334 (significant drift vs baseline)
- ⚠ pDnf: PSI 0.647 (significant drift vs baseline)
- ⚠ meanFinish: PSI 0.504 (significant drift vs baseline)
- ⚠ finishRangeHigh: PSI 2.667 (significant drift vs baseline)
- • pWin: PSI 0.243 (moderate drift vs baseline)
Feature drift and rolling-Brier are tracked round-to-round; a spike flags where the field behaved unlike the rounds the model learned from.