Simulation Calibration
31
Races Learned
0.145
Avg Rank Correlation (ρ)
1.0 = perfect · 0 = random
1.0 = perfect · 0 = random
-0.9
Worst Race ρ
0.893
Best Race ρ
Current Factor Weights
Starts at 1.00 (unchanged). Increases when the factor successfully predicted better finishers; decreases when it led the model astray. Learning rate: 0.08 per race. Clamped between 0.15 and 4.00.
| Factor | Weight | Visual | Races | Signal | Description | Last Updated |
|---|---|---|---|---|---|---|
| Best speed ceiling | 0.9199 ↓ |
|
31 | -1 | Current avg BSR vs best Brisnet speed figure this year — horses near their proven ceiling get a boost | May 21, 2026 |
| Career form | 0.7564 ↓ |
|
31 | -3.04 | Career win% quality + current-year momentum vs prior years | May 21, 2026 |
| Jockey local wins | 0.7146 ↓ |
|
31 | -3.57 | Jockey win history in our own recorded races — proven winning jockeys at this level get a boost | May 21, 2026 |
| Jockey trainer combo | 0.8631 ↓ |
|
31 | -1.71 | Jockey + Trainer partnership win rate — certain duos consistently outperform each individually (×1.5 coefficient) | May 21, 2026 |
| Local db wins | 1.0000 |
|
31 | 0 | Actual wins recorded in our own race results — strongest verified evidence (×2 coefficient) | May 21, 2026 |
| Morning line | 1.0000 |
|
31 | 0 | Track handicapper ML odds — soft secondary endorsement (±1.5 pts) | May 21, 2026 |
| Track affinity | 0.6312 ↓ |
|
31 | -4.61 | Win% at this exact track vs 16% national avg (career stat blocks) | May 21, 2026 |
Recalibrate = reset weights then replay every recorded result through the engine — use this to make all your results weigh in.
Reset = wipe weights only (no replay). Use after a major engine change.
Reset = wipe weights only (no replay). Use after a major engine change.
Race Feedback History
| Race | Date | Horses | Rank ρ | Top Factor Adjustments | Analyzed |
|---|---|---|---|---|---|
| Laurel Park R6 | May 16, 2026 | 6 | 0.371 |
form +0.746 jockey trainer combo +0.522 bsr trajectory +0.443 |
May 21 4:53pm |
| Laurel Park R7 | May 16, 2026 | 7 | 0.893 |
beaten lengths +0.602 bsr trajectory +0.402 jockey trainer combo +0.348 |
May 21 4:53pm |
| Laurel Park R8 | May 16, 2026 | 7 | -0.214 |
freshness +0.737 bounce +0.478 post position +0.397 |
May 21 4:53pm |
| Laurel Park R9 | May 16, 2026 | 7 | 0.286 |
weight +0.725 jockey +0.518 beaten lengths +0.229 |
May 21 4:53pm |
| Laurel Park R10 | May 16, 2026 | 5 | -0.6 |
best speed ceiling +0.395 bounce +0.395 bsr ability +0.142 |
May 21 4:53pm |
| Laurel Park R11 | May 16, 2026 | 8 | 0.167 |
class change +0.304 trainer +0.207 career form +0.184 |
May 21 4:53pm |
| Laurel Park R12 | May 16, 2026 | 5 | 0.1 |
form +0.879 trainer +0.846 bsr trajectory +0.59 |
May 21 4:53pm |
| Laurel Park R13 | May 16, 2026 | 5 | -0.9 |
form +0.912 bounce +0.79 trainer +0.669 |
May 21 4:53pm |
| Woodbine R4 | May 3, 2026 | 8 | 0.048 |
jockey local wins +0.575 post position +0.49 distance +0.327 |
May 21 4:53pm |
| Woodbine R5 | May 3, 2026 | 7 | 0.714 |
freshness +0.299 jockey local wins +0.282 best speed ceiling +0.27 |
May 21 4:53pm |
| Woodbine R6 | May 3, 2026 | 8 | -0.357 |
form +0.418 beaten lengths +0.311 pace scenario +0.067 |
May 21 4:53pm |
| Woodbine R7 | May 3, 2026 | 6 | 0.829 |
jockey trainer combo +0.515 jockey +0.447 beaten lengths +0.417 |
May 21 4:53pm |
| Woodbine R8 | May 3, 2026 | 6 | 0.486 |
form +0.861 class change +0.716 pace scenario +0.544 |
May 21 4:53pm |
| Woodbine R9 | May 3, 2026 | 11 | 0.225 |
jockey +0.72 jockey local wins +0.497 career form +0.49 |
May 21 4:53pm |
| Laurel Park R1 | May 16, 2026 | 10 | 0.103 |
bsr trajectory +0.477 jockey trainer combo +0.347 jockey local wins +0.297 |
May 21 4:53pm |
| Laurel Park R2 | May 16, 2026 | 9 | 0.483 |
post position +0.636 surface +0.539 class change +0.326 |
May 21 4:53pm |
| Laurel Park R3 | May 16, 2026 | 11 | 0.627 |
bsr trajectory +0.319 jockey local wins +0.265 jockey +0.168 |
May 21 4:53pm |
| Laurel Park R4 | May 16, 2026 | 5 | -0.5 |
best speed ceiling +0.612 weight +0.408 career form +0.271 |
May 21 4:53pm |
| Laurel Park R5 | May 16, 2026 | 14 | 0.398 |
jockey local wins +0.331 class change +0.199 surface +0.172 |
May 21 4:53pm |
| Tampa Bay Downs R1 | May 3, 2026 | 6 | 0.657 |
surface +0.446 weight +0.316 jockey trainer combo +0.316 |
May 21 4:53pm |
| Tampa Bay Downs R2 | May 3, 2026 | 7 | 0.429 |
jockey trainer combo +0.74 bsr ability +0.174 best speed ceiling +0.125 |
May 21 4:53pm |
| Tampa Bay Downs R3 | May 3, 2026 | 3 | -0.5 |
post position +0.995 distance +0.995 freshness +0.585 |
May 21 4:53pm |
| Tampa Bay Downs R4 | May 3, 2026 | 8 | 0.524 |
bounce +0.557 freshness +0.376 best speed ceiling +0.335 |
May 21 4:53pm |
| Tampa Bay Downs R5 | May 3, 2026 | 9 | -0.367 |
bsr trajectory +0.234 surface +0.083 freshness +0.05 |
May 21 4:53pm |
| Tampa Bay Downs R6 | May 3, 2026 | 6 | 0.243 |
bounce +0.87 class change +0.618 form +0.399 |
May 21 4:53pm |
| Tampa Bay Downs R7 | May 3, 2026 | 9 | 0.25 |
best speed ceiling +0.496 post position +0.375 jockey trainer combo +0.373 |
May 21 4:53pm |
| Tampa Bay Downs R8 | May 3, 2026 | 5 | -0.9 |
beaten lengths +0.401 post position +0.391 freshness +0.29 |
May 21 4:53pm |
| Tampa Bay Downs R9 | May 3, 2026 | 9 | 0.3 |
bsr trajectory +0.366 career form +0.245 beaten lengths +0.228 |
May 21 4:53pm |
| Woodbine R1 | May 3, 2026 | 7 | -0.357 |
post position +0.559 freshness +0.248 jockey +0.222 |
May 21 4:53pm |
| Woodbine R2 | May 3, 2026 | 7 | 0.464 |
weight +0.592 class change +0.43 jockey local wins +0.226 |
May 21 4:53pm |
| Woodbine R3 | May 3, 2026 | 6 | 0.6 |
bsr trajectory +0.875 weight +0.463 class change +0.463 |
May 21 4:53pm |
How the Learning Works
- You enter actual results on any race page after the race is run.
- The engine compares each horse's predicted rank (by simulation win%) to their actual finish position.
- For each scoring factor (BSR, trajectory, bounce, etc.) it computes the Pearson correlation between that factor's values across the field and the prediction errors.
- Factors that consistently pointed at the right horses have their weight increased ↑. Factors that led the model astray get decreased ↓.
- The Spearman rank correlation (ρ) measures how well the simulation ranked the field overall — closer to 1.0 = better predictions.
- After enough races, the weights converge to reflect what actually matters most in your data set.