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

TORONTO

BLUE JAYSTOR

44-49  |  Road

10
FINAL
Wed, Jul 8 • 3:45 PM ET
Oracle Park
View Odds Details →

SAN FRANCISCO

GIANTSSF

38-54  |  Home

0
Probable Pitchers
Tyler Rogers
STARTING PITCHER

Tyler Rogers

#71 | Relief Pitcher
@
Logan Webb
STARTING PITCHER

Logan Webb

#62 | Starting Pitcher
Player W-L ERA WHIP IP K
Tyler Rogers None-None 1.73 -- 1.0 --
Logan Webb None-None 3.86 -- 7.0 2
None-None W-L None-None
1.73 Ldr ERA 3.86
-- WHIP --
1.0 IP (Innings Pitched) Ldr 7.0
-- K (Strikeouts) Ldr 2
AI Model Win Probability
BLUE JAYS
68%
📊
GIANTS
32%
BLUE JAYS --
GIANTS --
AI Model Projected Total
AI Projection
7.6
Projected
Book Total
--
Over / Under Line
Over 0 57%
Under 0 43%
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
4.8
TORONTO
2.8
SAN FRANCISCO
Simulated Score
4
TORONTO
5
SAN FRANCISCO
Projections Grades
Moneyline (ML)
Divergence
AI Blue Jays Win
68% Win Prob
B
Sim Giants Loss
59% Win Prob
C
Run Line (ATS)
Divergence
AI Blue Jays (+1.5) Win
Proj Runs: -2.0
D
Sim Giants (-1.5) Loss
Proj Runs: -1.0
A
Over/Under (Total)
No Consensus
AI o7.0 Win
Proj Total: 7.6
C
Sim o7.0 Win
Proj Total: 9.0
A
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
Errors (L5) +48.0% more
Toronto: 1.0 vs San Francisco: 0.5
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%
Home Runs (L5) +71.0% more
San Francisco: 1.4 vs Toronto: 0.7
Post-Mortem Analysis
Metric Projected Actual
Score Game
TOR Score 4.8 10
SF Score 2.8 0
Team Stats Splits (Home / Away)
Errors 0.5 / 1.0 3.0 / 0.0
Hits 9.2 / 7.0 1.0 / 11.0
Home Runs 1.4 / 0.7 0.0 / 3.0
Strikeouts 7.1 / 7.7 11.0 / 3.0
Total Bases 15.4 / 9.9 1.0 / 20.0
Walks 2.6 / 2.3 3.0 / 4.0
Public Market Splits
Moneyline
Open: -- → --
75%TICKETS25%
66%MONEY34%
Spread (ATS)
Open: -- → --
59%TICKETS41%
77%MONEY23%
Total (O/U)
Open: -- → --
95%TICKETS5%
85%MONEY15%
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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