MLB Baseball

TOR vs BOS Prediction

July 26, 2026

10,000 Monte Carlo simulations

TOR vs BOS prediction for July 26, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects BOS 4.3 - TOR 4.0. BOS is favored with a 52.6% win probability. The run line is -1.5 and the total is 7.5. Model projects 8.3 total runs.

BOS
4.3
Projected Score
VS O/U 7.5
TOR
4.0
Projected Score
Win Probability
52.6%
47.4%
BOSTOR
-1.5
Run Line (BOS)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 54.6% (2,978 games)

Projected Runs Range 10th – 90th percentile

TOR
246
BOS
246
FINALBOS 6 — TOR 1
Projected
BOS 4.3 — TOR 4.0
Actual
BOS 6 — TOR 1

Starting Pitcher Matchup

Kevin Gausman R
TOR
FF52% · 94
FS38% · 84
SL10% · 84
usagewhiffbar labels show usage · mph
FF52%94 mph13% whiff
FS38%84 mph39% whiff
SL10%84 mph32% whiff
Ranger Suarez L
BOS
SI24% · 90
FF22% · 92
FC21% · 88
usagewhiffbar labels show usage · mph
SI24%90 mph12% whiff
FF22%92 mph16% whiff
FC21%88 mph15% whiff

Weather Impact

Fenway Park
73°F9 mph wind
HR: 0.978 Total: 0.985
8mph in

Bullpen Comparison

TOR
3.92ERA
3.64FIP
9.10K/9
3.46BB/9
1.29WHIP
BOS
3.90ERA
4.18FIP
9.00K/9
3.45BB/9
1.30WHIP

Betting Edges

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Edge Analysis
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First 5 Innings & NRFI

TOR F5
2.0 runs
33.9% win
BOS F5
2.6 runs
49.9% win
F5 Total
4.6
NRFI
56.2%
YRFI
43.8%
Avg 1st Inn Runs
0.93

HR Spotlight

🔒
Home Run Analysis
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Injury Report

TOR8 injured
Yimi Garcia RP60-DAY-IL
Addison Barger RF60-DAY-IL
Jesus Sanchez RF10-DAY-IL
Max Scherzer SP15-DAY-IL
Patrick Corbin SP15-DAY-IL
Jonatan Clase LF10-DAY-IL
+2 more
BOS8 injured
Marcelo Mayer 2B10-DAY-IL
Garrett Crochet SP60-DAY-IL
Zack Kelly RP60-DAY-IL
Trevor Story SS60-DAY-IL
Isiah Kiner-Falefa 2B10-DAY-IL
Tanner Houck SP60-DAY-IL
+2 more

Model Edge & Sizing

🔒The model's edge against the market, and the stake it sizes for this matchup, are premium.Unlock

Edge Analysis

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Edge Analysis
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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. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →

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