Home / MLB Projections MLB / Padres @ Giants SD @ SF

SAN DIEGO

PADRESSD

79-68  |  Road

7
FINAL
Fri, Sep 11 • 10:15 PM ET
Oracle Park
View Odds Details →

SAN FRANCISCO

GIANTSSF

62-86  |  Home

5
Probable Pitchers
Robbie Ray
STARTING PITCHER

Robbie Ray

#38 | Starting Pitcher
@
Anthony Molina
STARTING PITCHER

Anthony Molina

#45 | Starting Pitcher
Player W-L ERA WHIP IP K
Robbie Ray 11-8 3.39 1.34 151.1 127
Anthony Molina 3-0 2.79 0.88 19.1 15
11-8 W-L 3-0
3.39 ERA Ldr 2.79
1.34 WHIP Ldr 0.88
151.1 Ldr IP (Innings Pitched) 19.1
127 Ldr K (Strikeouts) 15
AI Model Win Probability
PADRES
48%
📊
GIANTS
52%
▲ Edge: +7.90% (SF)
PADRES 58% Book Odds: -139
GIANTS 44% Book Odds: +128
Book Implied: 58.20% / 43.90%
AI Model Projected Total
AI Projection
8.0
Projected
Book Total
7.5
Over / Under Line
▲ Edge: +0.5 (Over)
Over 7.5 57%
Under 7.5 43%
AI Model Spread Expectation
AI Spread Proj
-2.0
SAN FRANCISCO
Book Spread
+1.5
Book Line
▲ Edge: +3.5 points (San Francisco)
PadresSD (-1.5) 0 GiantsSF (+1.5)
San Francisco Giants (+1.5) expected to cover
Spread Distribution
AI Model

Padres Cover

30.9%

Giants Cover

69.1%

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

SD By 1-2 runs

13.6%

SD By 3-4 runs

7.8%

SF By 1-2 runs

19.6%

SF By 3-4 runs

18.4%

AI Model Projected Score
3
SAN DIEGO
Book Implied: 4.50
5
SAN FRANCISCO
Book Implied: 3
Simulated Score
6
SAN DIEGO
Book Implied: 4.50
7
SAN FRANCISCO
Book Implied: 3
Projections Grades
Moneyline (ML)
Agreement
AI Giants Loss
52% Win Prob
D
Sim Giants Loss
59% Win Prob
C
Run Line (ATS)
Agreement 👑 Top Selection
AI Giants (+1.5) Loss
Proj Runs: -2.0
A
Sim Giants (+1.5) Loss
Proj Runs: -1.0
B
Over/Under (Total)
Agreement
AI o7.5 Win
Proj Total: 8.0
C
Sim o7.5 Win
Proj Total: 13.0
A
Head-to-Head History
Date Game Score
Sep 13, 2026 SD @ SF 6 - 4
Sep 12, 2026 SD @ SF 7 - 6
Sep 11, 2026 SD @ SF 7 - 5
Aug 2, 2026 SF @ SD 4 - 5
Aug 1, 2026 SF @ SD 5 - 6
Season Statistics Comparison
San Diego SD
vs
San Francisco SF
2
Games Played
▲ 162
6.00 ▲
Runs / Game
4.13
.328 ▲
Avg (AVG)
.245
.362 ▲
On-Base (OBP)
.306
.563 ▲
Slugging (SLG)
.400
.925 ▲
OPS
.706
4
Home Runs
▲ 178
Key Model Drivers
Home Runs (Season) +4350.0% more
San Francisco: 178.0 vs San Diego: 4.0
Errors (L5) +119.0% more
San Francisco: 1.4 vs San Diego: 0.2
Runs per Game (Season) +31.2% more
San Diego: 6.0 vs San Francisco: 4.1
Walks (L5) +29.9% more
San Diego: 3.8 vs San Francisco: 2.7
Post-Mortem Analysis
Metric Projected Actual
Score Game
SD Score 3.0 7
SF Score 5.0 5
Team Stats Splits (Home / Away)
Errors 1.4 / 0.2 1.0 / 0.0
Hits 8.4 / 9.8 6.0 / 12.0
Home Runs 1.0 / 1.3 1.0 / 0.0
Strikeouts 6.9 / 7.2 8.0 / 11.0
Total Bases 13.3 / 15.4 11.0 / 21.0
Walks 2.7 / 3.8 4.0 / 6.0
Public Market Splits
Moneyline
Open: -136 / +123 → -139 / +128 ↓
82%TICKETS18%
80%MONEY20%
Spread (ATS)
Open: -1.5 / +1.5 → -1.5 / +1.5
71%TICKETS29%
54%MONEY46%
Total (O/U)
Open: 8 → 7.5 ↓
95%TICKETS5%
86%MONEY14%
Situational Trends
📊 Win-Loss
SD Advantage
94-74-0 (56.0%)
Margin: 0.3 ATS +/-:
SF
65-97-0 (40.1%)
Margin: -0.6 ATS +/-:
🎯 ATS (Spread)
SD Advantage
(57.1%)
Margin: 0.3 ATS +/-:
SF
(51.2%)
Margin: -0.6 ATS +/-:
⚖️ Over/Under
SD
78-85-5
O: 47.9% / U: 52.2% Total +/-: +0.2
SF
76-73-13
O: 51.0% / U: 49.0% Total +/-: +0.6
Season to Date Model Accuracy
AI Model
SIM Engine
SF
SD
SF
SD
ML
49% 79-81
51% 85-83
53% 85-75
51% 85-82
ATS
62% 100-60
54% 91-77
52% 83-77
55% 92-75
TTL
55% 82-68-10
51% 82-80-6
46% 68-81-11
54% 86-74-6
Accuracy:
Elite (>60%)
Good (53-60%)
Neutral (48-52%)
Under (43-47%)
Danger (≤42%)
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