Blue Jays.
The year-round intelligence desk for Toronto.
01 / Record
The numbers, last window.
Official BETs
18
Executable
18
archive-backed
Resolved
18
Won
13
Lost
5
Win rate
72.2%
Brier (per-resolved): 0.2003Voided: 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=0—model—realised
- 60–70%n=1865.2%model72.2%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 | 5 | 5 | 4 | 80% | 0.1821 |
| Nathan Lukes | 3 | 3 | 3 | 100% | 0.1159 |
| Vladimir Guerrero Jr. | 3 | 3 | 2 | 67% | 0.2291 |
| Alejandro Kirk | 2 | 2 | 2 | 100% | 0.1242 |
| Brett Bateman | 2 | 2 | 2 | 100% | 0.1166 |
| Ernie Clement | 2 | 2 | 0 | 0% | 0.3962 |
| Kazuma Okamoto | 1 | 1 | 0 | 0% | 0.3850 |
04 / Mispriced
Largest edges that hit.
| Player | Market | Model | Sharp | Edge | Result |
|---|---|---|---|---|---|
| Vladimir Guerrero Jr. | 1+ Hits | 67.0% | 70.5% | -3.5pp | — |
| George Springer | 1+ Hits | 64.5% | 62.5% | +2.1pp | WON |
| Ernie Clement | 1+ Hits | 63.2% | 65.2% | -2.0pp | — |
| Nathan Lukes | 1+ Hits | 68.3% | 67.0% | +1.4pp | WON |
| Ernie Clement | 1+ Hits | 62.7% | 64.0% | -1.3pp | — |
| Nathan Lukes | 1+ Hits | 65.5% | 64.8% | +0.8pp | WON |
| George Springer | 1+ Hits | 66.7% | 66.3% | +0.4pp | WON |
| Brett Bateman | 1+ Hits | 67.8% | 67.6% | +0.2pp | WON |