Mets.
The year-round intelligence desk for New York.
01 / Record
The numbers, last window.
Official BETs
55
Executable
55
archive-backed
Resolved
55
Won
40
Lost
15
Win rate
72.7%
Brier (per-resolved): 0.2101Voided: 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=157.5%model0.0%realised
- 60–70%n=5463.4%model74.1%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 |
|---|---|---|---|---|---|
| Francisco Lindor | 16 | 16 | 9 | 56% | 0.2575 |
| Bo Bichette | 14 | 14 | 11 | 79% | 0.1927 |
| Carson Benge | 11 | 11 | 10 | 91% | 0.1605 |
| Juan Soto | 10 | 10 | 7 | 70% | 0.2237 |
| Jared Young | 2 | 2 | 2 | 100% | 0.1385 |
| A.J. Ewing | 1 | 1 | 1 | 100% | 0.1296 |
| Francisco Alvarez | 1 | 1 | 0 | 0% | 0.3307 |
04 / Mispriced
Largest edges that hit.
| Player | Market | Model | Sharp | Edge | Result |
|---|---|---|---|---|---|
| Jared Young | 1+ Hits | 65.3% | 61.2% | +4.0pp | WON |
| Francisco Lindor | 1+ Hits | 62.7% | 65.1% | -2.4pp | — |
| Francisco Lindor | 1+ Hits | 62.9% | 64.8% | -1.9pp | — |
| Bo Bichette | 1+ Hits | 66.3% | 67.8% | -1.6pp | — |
| Juan Soto | 1+ Hits | 64.9% | 66.5% | -1.5pp | — |
| Bo Bichette | 1+ Hits | 64.9% | 66.4% | -1.4pp | — |
| A.J. Ewing | 1+ Hits | 64.0% | 62.7% | +1.3pp | WON |
| Carson Benge | 1+ Hits | 62.8% | 61.5% | +1.3pp | WON |
| Juan Soto | 1+ Hits | 62.6% | 63.8% | -1.1pp | — |
| Carson Benge | 1+ Hits | 63.6% | 62.5% | +1.1pp | WON |