FINAL: DET 3 — TOR 2. Our Monte Carlo simulation projected DET 3.9 - TOR 2.9 (DET at 63.4% win probability). The run line is 1.5 and the total is 8.0. Model projects 6.8 total runs.
DET
3.9
Projected Score
VS
O/U 8.0
TOR
2.9
Projected Score
Win Probability
DETTOR
+1.5
Run Line (DET)
8.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 63.8% (2,085 games)
Projected Runs Range 10th – 90th percentile
TOR
135
DET
246
Projected
DET 3.9 — TOR 2.9
Actual
DET 3 — TOR 2
Pick Results
DET MLmlWIN+2.12u
Starting Pitcher Matchup
Trey Yesavage R
TOR
FF49%94 mph16% whiff
FS37%82 mph38% whiff
SL15%88 mph40% whiff
Brenan Hanifee R
DET
SI62%95 mph10% whiff
SL21%88 mph29% whiff
FF11%96 mph10% whiff
Weather Impact
Comerica Park
70°F9 mph wind
HR: 0.991 Total: 0.993
7mph in
Bullpen Comparison
TOR
3.65ERA
3.19FIP
10.06K/9
3.39BB/9
1.29WHIP
DET
4.39ERA
4.24FIP
9.05K/9
4.37BB/9
1.43WHIP
Betting Edges
RUN_LINE AWAY -1.5
-37.7% EV
+134
TOTAL OVER 8.0
-33.2% EV
-110
F5_ML AWAY
-32.3% EV
-128
ML AWAY
-26.2% EV
-123
F5_ML HOME
+25.2% EV
+102
RUN_LINE HOME +1.5
-23.1% EV
-161
First 5 Innings & NRFI
TOR F5
1.3 runs
26.3% win
DET F5
2.2 runs
53.6% win
F5 Total
3.5
NRFI
69.4%
YRFI
30.6%
Avg 1st Inn Runs
0.58
HR Spotlight
Avg HRs
2.0
Over 0.5 HR
87%
Over 1.5 HR
60%
No HR
13%
Kazuma Okamoto TOR30.0%
ISO: 0.250 | Barrel: 12.6% | vs Brenan Hanifee | Park: 0.97x
Dillon Dingler DET30.0%
ISO: 0.290 | Barrel: 13.9% | vs Trey Yesavage | Park: 0.97x
Daulton Varsho TOR24.3%
ISO: 0.159 | Barrel: 7.6% | vs Brenan Hanifee | Park: 0.97x Platoon: 1.12x
Pitcher Strikeout Projections
Trey Yesavage
0.0 K projected
TOR | K/9: 0.0
Brenan Hanifee
0.0 K projected
DET | K/9: 0.0
Injury Report
TOR8 injured
Nathan Lukes RF10-DAY-IL
Jose Berrios SP15-DAY-IL
Max Scherzer SP15-DAY-IL
Yimi Garcia RP60-DAY-IL
Addison Barger RF10-DAY-IL
Fernando Perez PDEVELOPMENTAL LIST
+2 more
DET8 injured
Gleyber Torres 2B10-DAY-IL
Will Vest RP15-DAY-IL
Casey Mize SP15-DAY-IL
Tarik Skubal SP15-DAY-IL
Justin Verlander SP60-DAY-IL
Kerry Carpenter RF10-DAY-IL
+2 more
AI Intelligence Analysis
STRONG BET +2GREEN ZONE54.5% WR (n=152)
HOME team (DET) has legitimate +22.0% ML edge despite road favorite being heavily favored. Brenan Hanifee (1.17 ERA, elite command A-) dominates Trey Yesavage (0.73 ERA, B- stuff) in a pitcher mismatch that favors the home UNDERDOG. Model gives DET 59.2% despite market pricing at 48.5% (implied). This is RARE +2 territory: home underdog with ace-level ERA performance, GREEN zone confirmation, and pitcher quality backed by data.
Key Factors
- SP mismatch heavily favors HOME (DET): Hanifee 1.17 ERA, A- command (elite), 14.9% K rate + Yesavage 0.73 ERA but B- stuff and road context = DET's low ERA better setup for home success
- Home underdog in GREEN zone: 54.5% WR (n=152) on MLB|ml|home — this is profitable historical bucket. DET is +106 home dog (48.5% implied) but model says 59.2%.
- F5_ML (first 5 innings) shows 25.2% edge for DET (62% model) — starting pitching advantage shows up strongest early
- UNDER edge: 6.83 model vs 8.0 market = 14.1% UNDER edge. Two quality SPs suppress runs. Weather 70.4°F + 7mph wind blowing in supports low-scoring game.
- Weather factor: 70°F temperature neutral but 7mph wind suppression helps under. NRFI 14.2% edge (65.6% model) suggests slow starts from both teams.
Risk Factors
- 22% edge is HUGE but falls in GREEN zone, not in high-edge trap. Historical 20-25% edge range on home ML shows 54.5% WR, which is our baseline, so edge is calibrated correctly. Not a confidence trap here.
- Yesavage elite 0.73 ERA could be sustainable — if he's genuinely that good, game might be closer than model suggests. But staff quality (TOR bullpen 3.65 ERA vs DET 4.39) slightly favors DET.
- Home underdog can fail to attract enough sharp money if public respects the away favorite's SP. But DET at +1.06 is actually well-priced; market isn't egregiously off.
PITCHER MISMATCHGREEN ZONEHOME UNDERDOG EDGESTRONG BET
Edge Analysis
Moneyline
DET 63.4%
-23.1 pts
Run Line
+1.5
-23.1 pts
Total
8.0
+14.1 pts
How this prediction was generated: This page shows output from the Olympus Bets MLB Baseball Monte Carlo engine. Each game is simulated 10,000 times using real-time team data, injury reports, and current odds. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →