Cardinals.
The year-round intelligence desk for St. Louis.
01 / Record
The numbers, last window.
Official BETs
27
Executable
27
archive-backed
Resolved
27
Won
19
Lost
8
Win rate
70.4%
Brier (per-resolved): 0.2158Voided: 0
02 / Calibration
Model probability vs realised rate.
- 0–20%n=0—model—realised
- 20–30%n=0—model—realised
- 30–40%n=0—model—realised
- 40–50%n=0—model—realised
- 50–60%n=356.3%model100.0%realised
- 60–70%n=2463.0%model66.7%realised
- 70–80%n=0—model—realised
- 80–90%n=0—model—realised
- 90–100%n=0—model—realised
When the model says X%, the event happened Y% of the time. Closer the two columns sit, the better calibrated the model is at that confidence band.
03 / Players
By sample size.
| Player | Official | Resolved | Won | Win rate | Brier |
|---|---|---|---|---|---|
| Alec Burleson | 8 | 8 | 5 | 63% | 0.2330 |
| Jordan Walker | 5 | 5 | 4 | 80% | 0.1858 |
| Iván Herrera | 4 | 4 | 3 | 75% | 0.2009 |
| Bryan Torres | 3 | 3 | 3 | 100% | 0.1280 |
| Everson Pereira | 1 | 1 | 1 | 100% | 0.2366 |
| Jimmy Crooks | 1 | 1 | 0 | 0% | 0.3917 |
| JJ Wetherholt | 1 | 1 | 0 | 0% | 0.3876 |
| José Fermín | 1 | 1 | 1 | 100% | 0.1319 |
| Leo Bernal | 1 | 1 | 1 | 100% | 0.1544 |
| Masyn Winn | 1 | 1 | 0 | 0% | 0.3676 |
| Thomas Saggese | 1 | 1 | 1 | 100% | 0.1756 |
04 / Mispriced
Largest edges that hit.
| Player | Market | Model | Sharp | Edge | Result |
|---|---|---|---|---|---|
| José Fermín | 1+ Hits | 63.7% | 53.1% | +10.6pp | WON |
| Bryan Torres | 1+ Hits | 67.9% | 57.3% | +10.6pp | WON |
| Jordan Walker | 1+ Hits | 62.0% | 67.9% | -5.9pp | — |
| Everson Pereira | 1+ Hits | 51.4% | 46.5% | +4.9pp | WON |
| Alec Burleson | 1+ Hits | 62.3% | 66.5% | -4.2pp | — |
| Alec Burleson | 1+ Hits | 65.2% | 61.2% | +4.0pp | WON |
| Alec Burleson | 1+ Hits | 65.6% | 68.7% | -3.1pp | — |
| Iván Herrera | 1+ Hits | 60.7% | 63.6% | -3.0pp | — |
| Jordan Walker | 1+ Hits | 66.7% | 64.7% | +2.0pp | WON |
| Iván Herrera | 1+ Hits | 64.9% | 63.5% | +1.3pp | WON |