Home / MLB Projections MLB / Giants @ Dodgers SF @ LAD

SAN FRANCISCO

GIANTSSF

64-92  |  Road

1
FINAL
Sun, Sep 20 • 4:10 PM ET
Dodger Stadium
View Odds Details →

LOS ANGELES

DODGERSLAD

96-60  |  Home

3
Probable Pitchers
👤
STARTING PITCHER

Matt Wilkinson

#71 | Starting Pitcher
@
Jack Dreyer
STARTING PITCHER

Jack Dreyer

#86 | Relief Pitcher
Player W-L ERA WHIP IP K
Matt Wilkinson 1-3 4.58 1.12 19.2 12
Jack Dreyer 5-2 3.19 1.13 59.1 68
1-3 W-L 5-2
4.58 ERA Ldr 3.19
1.12 Ldr WHIP 1.13
19.2 IP (Innings Pitched) Ldr 59.1
12 K (Strikeouts) Ldr 68
AI Model Win Probability
GIANTS
31%
📊
DODGERS
69%
▲ Edge: +0.60% (SF)
GIANTS 30% Book Odds: +229
DODGERS 74% Book Odds: -287
Book Implied: 30.40% / 74.20%
AI Model Projected Total
AI Projection
9.0
Projected
Book Total
8.5
Over / Under Line
▲ Edge: +0.5 (Over)
Over 8.5 56%
Under 8.5 44%
AI Model Spread Expectation
AI Spread Proj
-2.0
LOS ANGELES
Book Spread
-1.5
Book Line
▲ Edge: +0.5 points (Los Angeles)
GiantsSF (+1.5) 0 DodgersLAD (-1.5)
Los Angeles Dodgers (-1.5) expected to cover
Spread Distribution
AI Model

Giants Cover

30.9%

Dodgers Cover

69.1%

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

SF By 1-2 runs

13.6%

SF By 3-4 runs

7.8%

LAD By 1-2 runs

19.6%

LAD By 3-4 runs

18.4%

AI Model Projected Score
3.5
SAN FRANCISCO
Book Implied: 3.50
5.5
LOS ANGELES
Book Implied: 5
Simulated Score
6
SAN FRANCISCO
Book Implied: 3.50
5
LOS ANGELES
Book Implied: 5
Projections Grades
Moneyline (ML)
Divergence
AI Dodgers Win
69% Win Prob
A
Sim Giants Loss
61% Win Prob
C
Run Line (ATS)
Divergence
AI Dodgers (-1.5) Win
Proj Runs: -2.0
D
Sim Giants (+1.5) Loss
Proj Runs: -1.0
A
Over/Under (Total)
Agreement
AI o8.5 Loss
Proj Total: 9.0
C
Sim o8.5 Loss
Proj Total: 11.0
A
Head-to-Head History
Date Game Score
Sep 27, 2026 LAD @ SF 5 - 1
Sep 26, 2026 LAD @ SF 4 - 3
Sep 25, 2026 LAD @ SF 2 - 0
Sep 20, 2026 SF @ LAD 1 - 3
Sep 19, 2026 SF @ LAD 4 - 10
Season Statistics Comparison
San Francisco SF
vs
Los Angeles LAD
162
Games Played
162
4.13
Runs / Game
▲ 4.94
.245
Avg (AVG)
▲ .257
.306
On-Base (OBP)
▲ .338
.400
Slugging (SLG)
▲ .424
.706
OPS
▲ .762
178
Home Runs
▲ 204
Key Model Drivers
Home Runs (L5) +86.6% more
Los Angeles: 2.1 vs San Francisco: 1.1
Total Bases (L5) +50.4% more
Los Angeles: 20.2 vs San Francisco: 13.4
Walks (L5) +37.8% more
Los Angeles: 4.6 vs San Francisco: 3.3
Hits (L5) +34.6% more
Los Angeles: 11.3 vs San Francisco: 8.4
Post-Mortem Analysis
Metric Projected Actual
Score Game
SF Score 3.5 1
LAD Score 5.5 3
Team Stats Splits (Home / Away)
Errors 0.0 / 1.1 2.0 / 0.0
Hits 11.3 / 8.4 11.0 / 2.0
Home Runs 2.1 / 1.1 1.0 / 0.0
Strikeouts 5.3 / 9.9 7.0 / 14.0
Total Bases 20.2 / 13.4 17.0 / 2.0
Walks 4.6 / 3.3 0.0 / 3.0
Public Market Splits
Moneyline
Open: +273 / -349 → +229 / -287 ↓
5%TICKETS95%
12%MONEY88%
Spread (ATS)
Open: +1.5 / -1.5 → +1.5 / -1.5
12%TICKETS88%
15%MONEY85%
Total (O/U)
Open: 7 → 8.5 ↑
90%TICKETS10%
92%MONEY8%
Situational Trends
📊 Win-Loss
SF
65-97-0 (40.1%)
Margin: -0.6 ATS +/-:
LAD Advantage
103-67-0 (60.6%)
Margin: 1.2 ATS +/-:
🎯 ATS (Spread)
SF Advantage
(51.2%)
Margin: -0.6 ATS +/-:
LAD
(42.4%)
Margin: 1.2 ATS +/-:
⚖️ Over/Under
SF
76-73-13
O: 51.0% / U: 49.0% Total +/-: +0.6
LAD
75-90-5
O: 45.5% / U: 54.6% Total +/-: +0.1
Season to Date Model Accuracy
AI Model
SIM Engine
LAD
SF
LAD
SF
ML
54% 92-77
49% 79-81
48% 81-89
53% 85-75
ATS
58% 98-71
62% 100-60
44% 75-95
52% 83-77
TTL
49% 80-83-6
55% 82-68-10
45% 73-91-6
46% 68-81-11
Accuracy:
Elite (>60%)
Good (53-60%)
Neutral (48-52%)
Under (43-47%)
Danger (≤42%)
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