BAL vs TOR prediction for June 7, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects TOR 4.7 - BAL 5.5. BAL is favored with a 55.8% win probability. The run line is -1.5 and the total is 8.0. Model projects 10.1 total runs.
TOR
4.7
Projected Score
VS
O/U 8.0
BAL
5.5
Projected Score
Win Probability
TORBAL
-1.5
Run Line (TOR)
8.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 55.8% (2,193 games)
Projected Runs Range 10th – 90th percentile
BAL
467
TOR
357
Projected
TOR 4.7 — BAL 5.5
Actual
TOR 6 — BAL 4
Starting Pitcher Matchup
Shane Baz R
BAL
FF34%96 mph13% whiff
KC34%85 mph28% whiff
FC18%90 mph15% whiff
Kevin Gausman R
TOR
FF53%94 mph14% whiff
FS38%84 mph36% whiff
SL9%84 mph32% whiff
Weather Impact
Rogers Centre
75°F8 mph windRoof: retractable
HR: 1.009 Total: 1.003
neutral
Bullpen Comparison
BAL
4.39ERA
3.82FIP
8.94K/9
3.57BB/9
1.32WHIP
TOR
4.06ERA
3.72FIP
8.94K/9
3.50BB/9
1.34WHIP
Betting Edges
TOTAL UNDER 8.0
-27.5% EV
-102
RUN_LINE AWAY +1.5
-27.1% EV
-185
RUN_LINE HOME -1.5
-20.5% EV
+152
ML HOME
-18.6% EV
-135
F5_ML HOME
-16.0% EV
-139
ML AWAY
+15.0% EV
+116
First 5 Innings & NRFI
BAL F5
2.9 runs
45.8% win
TOR F5
2.6 runs
40.1% win
F5 Total
5.5
NRFI
53.3%
YRFI
46.7%
Avg 1st Inn Runs
1.03
HR Spotlight
Avg HRs
2.5
Over 0.5 HR
92%
Over 1.5 HR
71%
No HR
8%
Pete Alonso BAL23.7%
ISO: 0.229 | Barrel: 11.8% | vs Kevin Gausman | Park: 1.01x
Jackson Holliday BAL21.9%
ISO: 0.200 | Barrel: 7.6% | vs Kevin Gausman | Park: 1.01x Platoon: 1.12x
Adley Rutschman BAL17.4%
ISO: 0.257 | Barrel: 11.4% | vs Kevin Gausman | Park: 1.01x Platoon: 1.12x
Pitcher Strikeout Projections
Shane Baz
0.0 K projected
BAL | K/9: 0.0
Kevin Gausman
0.0 K projected
TOR | K/9: 0.0
Injury Report
BAL8 injured
Samuel Basallo CDAY-TO-DAY
Ryan Helsley RP15-DAY-IL
Dean Kremer SP60-DAY-IL
Chris Bassitt SPDAY-TO-DAY
Levi Wells PDAY-TO-DAY
Dylan Beavers RF10-DAY-IL
+2 more
TOR8 injured
Daulton Varsho CFDAY-TO-DAY
Max Scherzer SP15-DAY-IL
Dylan Cease SP15-DAY-IL
Yimi Garcia RP60-DAY-IL
Joe Mantiply RP60-DAY-IL
Alejandro Kirk C60-DAY-IL
+2 more
AI Intelligence Analysis
LEAN +1YELLOW ZONE47.1% WR (n=201)
Model shows 15.0% away ML edge (BAL 53.2% vs market 46.3%), but this is a HIGH EDGE (>10%) in a historically weak zone (away ML 47.1% WR). HOWEVER, external factors support the lean: (1) Kevin Gausman (TOR home, 3.63 ERA) is WORSE than Shane Baz (BAL away, 4.63 ERA) — but only by 1.0 ERA, (2) BAL has superior bullpen (BAL 4.39 vs TOR 4.06 — actually TOR bullpen slightly better), (3) weather is cool (74.6F, neutral), (4) MAJOR factor: TOR missing Vladmir Guerrero Jr. (suspended? trade?) + BAL missing key bats but lineup still intact. The 15% edge is high, but OVER 8.0 total has 6.0% edge (60.5% model prob) — this is the TRUE play. BAL lineup edge + TOR pitcher advantage wash. LEAN on OVER 8.0 instead of ML, or light ML at 1.0 unit.
Key Factors
- SP quality: Gausman 3.63 ERA (B- stuff, B command) vs Baz 4.63 ERA (C+ stuff, B command) — only 1.0 ERA gap, favors home by ~0.5 runs max
- Bullpen: TOR 4.06 ERA slightly better than BAL 4.39 ERA — ~0.33 run advantage TOR
- MAJOR: TOR missing Guerrero Jr. (critical bat), Kirk 60-day C, Varsho DTD — BAL roster more intact
- Model total 10.14 vs market 8.0 = 6.0% OVER edge (60.5% model prob). This is the real edge, under 10%, in YELLOW zone at 49.7% WR
- Weather: 74.6F, neutral, no tail wind. Retractable roof (Rogers Centre) = neutral baseline
Risk Factors
- Away ML 15% edge is historically overconfident (calibration warning: 47.1% WR on away ML n=201). Model likely overestimating BAL moneyline.
- Gausman slight home pitcher advantage not fully reflected in market, but size of edge (15%) is outsized
- TOR lineup depth loss significant but not fully quantifiable without full lineup cards
HIGH EDGE WARNINGAWAY ML RED ZONETOTALS EDGE LEGITIMATELINEUP IMPACT SIGNIFICANTPIVOT TO TOTAL RECOMMENDED
Edge Analysis
Moneyline
BAL 55.8%
-20.5 pts
Run Line
-1.5
-20.5 pts
Total
8.0
+6.0 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 →