MLB Baseball

TOR vs BOS Prediction

June 17, 2026

10,000 Monte Carlo simulations

TOR vs BOS prediction for June 17, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects BOS 5.9 - TOR 5.7. BOS is favored with a 53.3% win probability. The run line is 1.5 and the total is 9.5. Model projects 11.6 total runs.

BOS
5.9
Projected Score
VS O/U 9.5
TOR
5.7
Projected Score
Win Probability
53.3%
46.7%
BOSTOR
+1.5
Run Line (BOS)
9.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 55.7% (2,410 games)

Projected Runs Range 10th – 90th percentile

TOR
468
BOS
468
FINALBOS 0 — TOR 3
Projected
BOS 5.9 — TOR 5.7
Actual
BOS 0 — TOR 3

Starting Pitcher Matchup

Braydon Fisher R
TOR
SL49%89 mph31% whiff
CU29%81 mph21% whiff
FF17%95 mph20% whiff
Jake Bennett L
BOS
FF30%92 mph20% whiff
SI30%92 mph5% whiff
CH25%84 mph31% whiff

Weather Impact

Fenway Park
77°F8 mph wind
HR: 1.068 Total: 1.037
8mph out

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

RUN_LINE HOME +1.5
-30.9% EV
-200
TOTAL UNDER 9.5
-21.2% EV
-112
TOTAL OVER 9.5
+12.5% EV
-108
F5 OVER 5.5
+9.8% EV
-102
RUN_LINE AWAY -1.5
-8.4% EV
+164
F5_ML AWAY
-6.0% EV
+108

First 5 Innings & NRFI

TOR F5
3.2 runs
40.2% win
BOS F5
3.6 runs
48.7% win
F5 Total
6.9
NRFI
43.3%
YRFI
56.7%
Avg 1st Inn Runs
1.36

HR Spotlight

Avg HRs
3.1
Over 0.5 HR
95%
Over 1.5 HR
81%
No HR
5%
Kazuma Okamoto TOR30.0%
ISO: 0.226 | Barrel: 12.2% | vs Jake Bennett | Park: 1.08x Platoon: 1.12x
George Springer TOR30.0%
ISO: 0.216 | Barrel: 7.3% | vs Jake Bennett | Park: 1.08x Platoon: 1.12x
Alejandro Kirk TOR30.0%
ISO: 0.092 | Barrel: 9.2% | vs Jake Bennett | Park: 1.08x Platoon: 1.12x

Pitcher Strikeout Projections

Braydon Fisher
0.0 K projected
TOR | K/9: 0.0
Jake Bennett
0.0 K projected
BOS | K/9: 0.0

Injury Report

TOR8 injured
Max Scherzer SP15-DAY-IL
Daulton Varsho CF10-DAY-IL
Shane Bieber SP60-DAY-IL
Yimi Garcia RP60-DAY-IL
Addison Barger RF10-DAY-IL
Lazaro Estrada RP60-DAY-IL
+2 more
BOS8 injured
Romy Gonzalez 1B60-DAY-IL
Roman Anthony LF10-DAY-IL
Garrett Crochet SP60-DAY-IL
Noah Song SPDEVELOPMENTAL LIST
Nick Sogard 3B10-DAY-IL
Patrick Sandoval SP60-DAY-IL
+2 more

AI Intelligence Analysis

NEUTRAL -1YELLOW ZONE43.4% WR (n=12)
TOR @ BOS is a SKIP due to both major lineup uncertainty (Max Scherzer TOR SP now on IL with back spasms, Jake Bennett C+/D stuff taking the start) and weak edge profiles. BOS OVER 9.5 at 12.5% edge is marginal; zone history shows OVER plays at 53.2% WR. Bennett (C+/D stuff) is such a downgrade that game projection is unreliable.

Key Factors

  • LINEUP CHANGE CRITICAL: Max Scherzer (TOR SP) 10-day IL back spasms → Jake Bennett (C+/D stuff, 4.8 K/9 mean, 12.3% K rate) = ~3pt swing in TOR win prob (53.4% → ~49-50%)
  • Bennett profile weak: C+ overall grade, D stuff score (0.034), 6th-round SP quality. Braydon Fisher (TOR away SP, B grade, 26.97% K rate) now the pitching advantage to BOS
  • Weather: 77.1°F at Fenway, 8 mph wind BLOWING OUT = +1.0 run boost from environment (1.037 total mult). Should push OVER higher, but SP downgrade negates it
  • Fenway park factor: 1.068 HR multiplier, 1.037 total multiplier (wind out) = run-heavy environment normally. But TOR's ace swap kills offensive projection reliability
  • Zone: OVER in 10-15% edge, 55-60% prob bucket has only 43.4% WR (n=12 bets) — worst bucket on board for OVER

Risk Factors

  • DATA INTEGRITY FAILURE: Model doesn't reflect Scherzer IL news. All projections (win prob, run totals, edges) are unreliable
  • Market line may not have updated yet; line posted pre-Scherzer IL news (likely). Expect sharp repricing if news spreads
  • BOS ML likely moves from -126 to -140+ as TOR win prob drops; OVER/UNDER edge structure changes entirely
DATA INTEGRITYLINEUP CHANGEPITCHER DOWNGRADESKIP

Edge Analysis

Moneyline
BOS 53.3%
-30.9 pts
Run Line
+1.5
-30.9 pts
Total
9.5
+12.5 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. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →

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