Home / MLB Projections MLB / Blue Jays @ Giants TOR @ SF

TORONTO

BLUE JAYSTOR

42-49  |  Road

1
FINAL
Mon, Jul 6 • 9:45 PM ET
Oracle Park
View Odds Details →

SAN FRANCISCO

GIANTSSF

38-52  |  Home

10
Probable Pitchers
Andres Gimenez
STARTING PITCHER

Andres Gimenez

#0 | Shortstop
@
Landen Roupp
STARTING PITCHER

Landen Roupp

#65 | Starting Pitcher
Player W-L ERA WHIP IP K
Andres Gimenez None-None -- -- -- --
Landen Roupp None-None 4.27 -- 8.0 5
None-None W-L None-None
-- ERA 4.27
-- WHIP --
-- IP (Innings Pitched) 8.0
-- K (Strikeouts) 5
AI Model Win Probability
BLUE JAYS
67%
📊
GIANTS
33%
BLUE JAYS --
GIANTS --
AI Model Projected Total
AI Projection
11.2
Projected
Book Total
--
Over / Under Line
Over 0 81%
Under 0 19%
AI Model Spread Expectation
AI Spread Proj
-2.0
TORONTO
Book Spread
--
Book Line
▲ Edge: +2.0 points (Toronto)
Blue JaysTOR (-3.5) 0 GiantsSF (+3.5)
Model Expected Spread
Spread Distribution
AI Model

Blue Jays Cover

69.1%

Giants Cover

30.9%

-12-8-40+4+8+12
Distribution centered around TOR -2.0 expected margin.
Margin of Victory (TOR)

TOR By 1-2 runs

19.6%

TOR By 3-4 runs

18.4%

SF By 1-2 runs

13.6%

SF By 3-4 runs

7.8%

AI Model Projected Score
6.6
TORONTO
4.6
SAN FRANCISCO
Simulated Score
4
TORONTO
5
SAN FRANCISCO
Projections Grades
Moneyline (ML)
Divergence
AI Blue Jays Loss
67% Win Prob
B
Sim Giants Win
59% Win Prob
C
Run Line (ATS)
Divergence
AI Blue Jays (+1.5) Loss
Proj Runs: -2.0
C
Sim Giants (-1.5) Win
Proj Runs: -1.0
A
Over/Under (Total)
No Consensus 👑 Top Selection
AI o7.5 Win
Proj Total: 11.2
A
Sim o7.5 Win
Proj Total: 9.0
B
Head-to-Head History
Date Game Score
Jul 8, 2026 TOR @ SF 10 - 0
Jul 7, 2026 TOR @ SF 9 - 3
Jul 6, 2026 TOR @ SF 1 - 10
Jul 20, 2025 SF @ TOR 6 - 8
Jul 19, 2025 SF @ TOR 3 - 6
Season Statistics Comparison
Toronto TOR
vs
San Francisco SF
162
Games Played
162
4.00
Runs / Game
▲ 4.13
.247 ▲
Avg (AVG)
.245
.310 ▲
On-Base (OBP)
.306
.381
Slugging (SLG)
▲ .400
.692
OPS
▲ .706
152
Home Runs
▲ 178
Key Model Drivers
Strikeouts (L5) +26.1% more
Toronto: 10.0 vs San Francisco: 7.4
Errors (L5) +9.0% more
Toronto: 0.7 vs San Francisco: 0.6
On-Base Pct (Season) +0.4%
Toronto: 31.0% vs San Francisco: 30.6%
Batting Avg (Season) +0.2%
Toronto: 24.7% vs San Francisco: 24.5%
Post-Mortem Analysis
Metric Projected Actual
Score Game
TOR Score 6.6 1
SF Score 4.6 10
Team Stats Splits (Home / Away)
Errors 0.6 / 0.7 1.0 / 3.0
Hits 10.1 / 4.6 8.0 / 3.0
Home Runs 2.2 / 0.3 2.0 / 1.0
Strikeouts 7.4 / 10.0 8.0 / 7.0
Total Bases 19.1 / 6.6 16.0 / 6.0
Walks 3.0 / 2.6 6.0 / 2.0
Public Market Splits
Moneyline
Open: -- → --
66%TICKETS34%
62%MONEY38%
Spread (ATS)
Open: -- → --
64%TICKETS36%
82%MONEY18%
Total (O/U)
Open: -- → --
58%TICKETS42%
76%MONEY24%
Situational Trends
📊 Win-Loss
TOR Advantage
79-83-0 (48.8%)
Margin: -0.3 ATS +/-:
SF
65-97-0 (40.1%)
Margin: -0.6 ATS +/-:
🎯 ATS (Spread)
TOR
(46.9%)
Margin: -0.3 ATS +/-:
SF Advantage
(51.2%)
Margin: -0.6 ATS +/-:
⚖️ Over/Under
TOR
81-76-5
O: 51.6% / U: 48.4% Total +/-: +0.3
SF
76-73-13
O: 51.0% / U: 49.0% Total +/-: +0.6
Season to Date Model Accuracy
AI Model
SIM Engine
SF
TOR
SF
TOR
ML
49% 79-81
46% 74-87
53% 85-75
50% 80-80
ATS
62% 100-60
56% 90-71
52% 83-77
49% 79-81
TTL
55% 82-68-10
51% 80-76-5
46% 68-81-11
45% 70-85-5
Accuracy:
Elite (>60%)
Good (53-60%)
Neutral (48-52%)
Under (43-47%)
Danger (≤42%)
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