SAN FRANCISCO
GIANTSSF
52-46 | Road
3
TORONTO
BLUE JAYSTOR
56-41 | Home
6
Probable Pitchers
STARTING PITCHER
Logan Webb
#62 | Starting Pitcher@
STARTING PITCHER
Brendon Little
#54 | Relief Pitcher| Player | W-L | ERA | WHIP | IP | K |
|---|---|---|---|---|---|
| Logan Webb | None-None | 3.08 | -- | 6.0 | 1 |
| Brendon Little | None-None | 1.96 | -- | 1.0 | 1 |
None-None
W-L
None-None
3.08
ERA
Ldr 1.96
--
WHIP
--
6.0 Ldr
IP (Innings Pitched)
1.0
1
K (Strikeouts)
1
AI Model Win Probability
GIANTS
45%
BLUE JAYS
55%
GIANTS
--
BLUE JAYS
--
AI Model Projected Total
AI Projection
9.4
Projected
Book Total
--
Over / Under Line
Over 0
45%
Under 0
55%
AI Model Spread Expectation
AI Spread Proj
-1.6
TORONTO
Book Spread
--
Book Line
▲ Edge: +1.6 points (Toronto)
Spread Distribution
AI Model
+12+8+40-4-8-12
Distribution centered around TOR -1.6 expected margin.
Margin of Victory (TOR)
SF By 1-2 runs
14.8%
SF By 3-4 runs
9.0%
TOR By 1-2 runs
19.7%
TOR By 3-4 runs
17.6%
AI Model Projected Score
San Francisco
3.91
SAN FRANCISCO
Toronto
5.49
TORONTO
Simulated Score
San Francisco
4
SAN FRANCISCO
Toronto
5
TORONTO
Projections Grades
Moneyline (ML)
Agreement
AI
Blue Jays
Win
55% Win Prob
D
Sim
Blue Jays
Win
50% Win Prob
D
Run Line (ATS)
Agreement
AI
Blue Jays (+0)
Win
Proj Runs: -1.6
A
Sim
Blue Jays (+0)
Win
Proj Runs: -1.0
D
Over/Under (Total)
No Consensus
AI
o0
Win
Proj Total: 9.4
D
Sim
u0.0
Proj Total: 9.0
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
Errors (L5)
+66.0% more
Toronto: 1.2
vs
San Francisco: 0.5
Strikeouts (L5)
+38.2% more
Toronto: 9.6
vs
San Francisco: 6.9
Home Runs (L5)
+27.0% more
Toronto: 0.8
vs
San Francisco: 0.5
Total Bases (L5)
+21.2% more
Toronto: 12.6
vs
San Francisco: 10.4
Post-Mortem Analysis
Metric
Projected
Actual
Score Game
SF Score
3.9
3
TOR Score
5.5
6
Team Stats Splits (Home / Away)
Errors
1.2 / 0.5
0.0 / 0.0
Hits
8.2 / 7.5
14.0 / 4.0
Home Runs
0.8 / 0.5
1.0 / 2.0
Strikeouts
9.6 / 6.9
9.0 / 3.0
Total Bases
12.6 / 10.4
20.0 / 11.0
Walks
2.2 / 2.9
0.0 / 1.0
Public Market Splits
Moneyline
Open: --
→
--
Spread (ATS)
Open: --
→
--
Total (O/U)
Open: --
→
--
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
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