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Blue Jays.

The year-round intelligence desk for Toronto.

Window7 d14 d30 d60 d90 d· 15 official BETs released
01 / Record

The numbers, last window.

Official BETs
15
Executable
15
archive-backed
Resolved
15
Won
10
Lost
5
Win rate
66.7%
Brier (per-resolved): 0.2176Voided: 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=15
    65.0%
    model
    66.7%
    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.

PlayerOfficialResolvedWonWin rateBrier
George Springer44375%0.2000
Nathan Lukes333100%0.1159
Vladimir Guerrero Jr.33267%0.2291
Ernie Clement2200%0.3962
Alejandro Kirk111100%0.1223
Brett Bateman111100%0.1296
Kazuma Okamoto1100%0.3850
04 / Mispriced

Largest edges that hit.

PlayerMarketModelSharpEdgeResult
Vladimir Guerrero Jr.1+ Hits67.0%70.5%-3.5pp—
George Springer1+ Hits64.5%62.5%+2.1ppWON
Ernie Clement1+ Hits63.2%65.2%-2.0pp—
Nathan Lukes1+ Hits68.3%67.0%+1.4ppWON
Ernie Clement1+ Hits62.7%64.0%-1.3pp—
Nathan Lukes1+ Hits65.5%64.8%+0.8ppWON