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

SAN FRANCISCO

GIANTSSF

52-47  |  Road

6
FINAL
Sun, Jul 20 • 12:05 PM ET
Rogers Centre
View Odds Details →

TORONTO

BLUE JAYSTOR

57-41  |  Home

8
Probable Pitchers
Willy Adames
STARTING PITCHER

Willy Adames

#2 | Shortstop
@
Braydon Fisher
STARTING PITCHER

Braydon Fisher

#63 | Relief Pitcher
Player W-L ERA WHIP IP K
Willy Adames None-None -- -- -- --
Braydon Fisher None-None 2.86 -- -- --
None-None W-L None-None
-- ERA 2.86
-- WHIP --
-- IP (Innings Pitched) --
-- K (Strikeouts) --
AI Model Win Probability
GIANTS
44%
📊
BLUE JAYS
56%
GIANTS --
BLUE JAYS --
AI Model Projected Total
AI Projection
9.6
Projected
Book Total
--
Over / Under Line
Over 0 40%
Under 0 60%
AI Model Spread Expectation
AI Spread Proj
-1.8
TORONTO
Book Spread
--
Book Line
▲ Edge: +1.8 points (Toronto)
GiantsSF (-3.5) 0 Blue JaysTOR (+3.5)
Model Expected Spread
Spread Distribution
AI Model

Giants Cover

32.9%

Blue Jays Cover

67.1%

+12+8+40-4-8-12
Distribution centered around TOR -1.8 expected margin.
Margin of Victory (TOR)

SF By 1-2 runs

14.2%

SF By 3-4 runs

8.4%

TOR By 1-2 runs

19.7%

TOR By 3-4 runs

18.0%

AI Model Projected Score
3.92
SAN FRANCISCO
5.69
TORONTO
Simulated Score
3
SAN FRANCISCO
5
TORONTO
Projections Grades
Moneyline (ML)
Agreement
AI Blue Jays Win
56% Win Prob
D
Sim Blue Jays Win
50% Win Prob
D
Run Line (ATS)
Agreement
AI Blue Jays (+0) Win
Proj Runs: -1.8
D
Sim Blue Jays (+0) Win
Proj Runs: -2.0
D
Over/Under (Total)
No Consensus
AI o0 Win
Proj Total: 9.6
D
Sim u0.0
Proj Total: 8.0
D
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
San Francisco SF
vs
Toronto TOR
162
Games Played
162
4.13 ▲
Runs / Game
4.00
.245
Avg (AVG)
▲ .247
.306
On-Base (OBP)
▲ .310
.400 ▲
Slugging (SLG)
.381
.706 ▲
OPS
.692
178 ▲
Home Runs
152
Key Model Drivers
Strikeouts (L5) +67.1% more
Toronto: 9.4 vs San Francisco: 5.6
Hits (L5) +59.5% more
Toronto: 10.1 vs San Francisco: 6.4
Errors (L5) +43.0% more
Toronto: 0.8 vs San Francisco: 0.4
Total Bases (L5) +42.2% more
Toronto: 15.1 vs San Francisco: 10.6
Post-Mortem Analysis
Metric Projected Actual
Score Game
SF Score 3.9 6
TOR Score 5.7 8
Team Stats Splits (Home / Away)
Errors 0.8 / 0.4 0.0 / 0.0
Hits 10.1 / 6.4 9.0 / 12.0
Home Runs 0.9 / 1.0 3.0 / 1.0
Strikeouts 9.4 / 5.6 9.0 / 7.0
Total Bases 15.1 / 10.6 22.0 / 18.0
Walks 1.5 / 2.3 2.0 / 5.0
Public Market Splits
Moneyline
Open: -- → --
46%TICKETS54%
54%MONEY46%
Spread (ATS)
Open: -- → --
22%TICKETS78%
58%MONEY42%
Total (O/U)
Open: -- → --
43%TICKETS57%
33%MONEY67%
Situational Trends
📊 Win-Loss
SF
65-97-0 (40.1%)
Margin: -0.6 ATS +/-:
TOR Advantage
79-83-0 (48.8%)
Margin: -0.3 ATS +/-:
🎯 ATS (Spread)
SF Advantage
(51.2%)
Margin: -0.6 ATS +/-:
TOR
(46.9%)
Margin: -0.3 ATS +/-:
⚖️ Over/Under
SF
76-73-13
O: 51.0% / U: 49.0% Total +/-: +0.6
TOR
81-76-5
O: 51.6% / U: 48.4% Total +/-: +0.3
Season to Date Model Accuracy
AI Model
SIM Engine
TOR
SF
TOR
SF
ML
46% 74-87
49% 79-81
50% 80-80
53% 85-75
ATS
56% 90-71
62% 100-60
49% 79-81
52% 83-77
TTL
51% 80-76-5
55% 82-68-10
45% 70-85-5
46% 68-81-11
Accuracy:
Elite (>60%)
Good (53-60%)
Neutral (48-52%)
Under (43-47%)
Danger (≤42%)
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