Mets.
The year-round intelligence desk for New York.
01 / Record
The numbers, last window.
Official BETs
3
Executable
3
archive-backed
Resolved
3
Won
1
Lost
2
Win rate
33.3%
Brier (per-resolved): 0.1814Voided: 0
02 / Calibration
Model probability vs realised rate.
- 0–20%n=0—model—realised
- 20–30%n=120.2%model0.0%realised
- 30–40%n=0—model—realised
- 40–50%n=0—model—realised
- 50–60%n=258.0%model50.0%realised
- 60–70%n=0—model—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 Alvarez | 3 | 3 | 1 | 33% | 0.1814 |
04 / Mispriced
Largest edges that hit.
| Player | Market | Model | Sharp | Edge | Result |
|---|---|---|---|---|---|
| Francisco Alvarez | 1+ Hits | 58.4% | 54.3% | +4.1pp | WON |