goal hazard curves: minute profile of scoring
← lab · n games 5,521 · n goals 17,000 · share after 75 0.243 · ran 7/6/2026
What this is: A one-off study — its numbers below are exactly what the run reported.
| note | share_after_75 vs uniform (20/95≈0.21) quantifies the late-game spike; price_window() turns a match's lambda into P(goal in window). |
| n games | 5,521 |
| n goals | 17,000 |
| share after 75 | 0.243 |
| share after 85 | 0.1375 |
| share first 15 | 0.1167 |
| n games with goals | 5,521 |
| uniform share after 75 | 0.2105 |
| goal in both halves given any | 0.6283 |
profile by bucket
| 0 | 0.0275 |
| 5 | 0.0439 |
| 10 | 0.0453 |
| 15 | 0.0462 |
| 20 | 0.0461 |
| 25 | 0.0466 |
| 30 | 0.0493 |
| 35 | 0.0463 |
| 40 | 0.0502 |
| 45 | 0.0789 |
| 50 | 0.0572 |
| 55 | 0.0562 |
first goal profile
| 0 | 0.0831 |
| 5 | 0.1213 |
| 10 | 0.1087 |
| 15 | 0.0976 |
| 20 | 0.0819 |
| 25 | 0.077 |
| 30 | 0.0656 |
| 35 | 0.054 |
| 40 | 0.0496 |
| 45 | 0.0638 |
| 50 | 0.0379 |
| 55 | 0.0357 |
Reading the columnswhat each number actually means
| AUC | predictability: 0.50 = coin flip, ~0.70 = ceiling for sports |
| Importance | how much the model leans on this factor (permutation importance) |
| Direction | sign of the raw correlation with the outcome |
| Survives all eras | effect points the same way in every historical era |
Spec · the reproducible recipe
{
"kind": "hazard_curves",
"bucket_minutes": 5
}