Blue Jays.
The year-round intelligence desk for Toronto.
01 / Record
The numbers, last window.
Official BETs
44
Executable
44
archive-backed
Resolved
44
Won
32
Lost
12
Win rate
72.7%
Brier (per-resolved): 0.2028Voided: 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=559.6%model60.0%realised
- 60–70%n=3964.2%model74.4%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 |
|---|---|---|---|---|---|
| George Springer | 9 | 9 | 8 | 89% | 0.1568 |
| Alejandro Kirk | 6 | 6 | 4 | 67% | 0.2189 |
| Vladimir Guerrero Jr. | 6 | 6 | 4 | 67% | 0.2233 |
| Kazuma Okamoto | 5 | 5 | 2 | 40% | 0.2928 |
| Nathan Lukes | 5 | 5 | 5 | 100% | 0.1258 |
| Andrés Giménez | 3 | 3 | 2 | 67% | 0.2205 |
| Brett Bateman | 3 | 3 | 3 | 100% | 0.1129 |
| Ernie Clement | 3 | 3 | 1 | 33% | 0.3127 |
| Myles Straw | 2 | 2 | 1 | 50% | 0.2639 |
| Charles McAdoo | 1 | 1 | 1 | 100% | 0.1390 |
| Josh Smith | 1 | 1 | 1 | 100% | 0.1598 |
04 / Mispriced
Largest edges that hit.
| Player | Market | Model | Sharp | Edge | Result |
|---|---|---|---|---|---|
| Myles Straw | 1+ Hits | 59.0% | 52.0% | +7.0pp | WON |
| Nathan Lukes | 1+ Hits | 59.8% | 53.0% | +6.8pp | WON |
| Charles McAdoo | 1+ Hits | 62.7% | 56.4% | +6.4pp | WON |
| Kazuma Okamoto | 1+ Hits | 60.6% | 66.2% | -5.6pp | — |
| Kazuma Okamoto | 1+ Hits | 62.4% | 68.0% | -5.5pp | — |
| Kazuma Okamoto | 1+ Hits | 59.3% | 55.0% | +4.2pp | WON |
| Andrés Giménez | 1+ Hits | 59.9% | 63.9% | -3.9pp | — |
| Andrés Giménez | 1+ Hits | 62.0% | 58.3% | +3.7pp | WON |
| Vladimir Guerrero Jr. | 1+ Hits | 67.0% | 70.5% | -3.5pp | — |
| Vladimir Guerrero Jr. | 1+ Hits | 63.9% | 66.6% | -2.7pp | — |