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

LOS ANGELES

DODGERSLAD

100-62  |  Road

5
FINAL
Sun, Sep 27 • 3:05 PM ET
Oracle Park
View Odds Details →

SAN FRANCISCO

GIANTSSF

65-97  |  Home

1
Probable Pitchers
Jack Dreyer
STARTING PITCHER

Jack Dreyer

#86 | Relief Pitcher
@
Carson Seymour
STARTING PITCHER

Carson Seymour

#77 | Relief Pitcher
Player W-L ERA WHIP IP K
Jack Dreyer 5-2 3.16 1.10 62.2 71
Carson Seymour 0-2 4.70 1.53 30.2 22
5-2 W-L 0-2
3.16 Ldr ERA 4.70
1.10 Ldr WHIP 1.53
62.2 Ldr IP (Innings Pitched) 30.2
71 Ldr K (Strikeouts) 22
AI Model Win Probability
DODGERS
61%
📊
GIANTS
39%
▲ Edge: +5.70% (SF)
DODGERS 71% Book Odds: -249
GIANTS 33% Book Odds: +201
Book Implied: 71.30% / 33.20%
AI Model Projected Total
AI Projection
8.5
Projected
Book Total
8.5
Over / Under Line
Over 8.5 50%
Under 8.5 50%
AI Model Spread Expectation
AI Spread Proj
+1.5
SAN FRANCISCO
Book Spread
+1.5
Book Line
DodgersLAD (-1.5) 0 GiantsSF (+1.5)
Line aligns with book spread (+1.5)
Spread Distribution
AI Model

Dodgers Cover

35.4%

Giants Cover

64.6%

-12-8-40+4+8+12
Distribution centered around SF +1.5 expected margin.
Margin of Victory (SF)

LAD By 1-2 runs

19.7%

LAD By 3-4 runs

17.5%

SF By 1-2 runs

15.0%

SF By 3-4 runs

9.2%

AI Model Projected Score
5
LOS ANGELES
Book Implied: 5
3.5
SAN FRANCISCO
Book Implied: 3.50
Simulated Score
5
LOS ANGELES
Book Implied: 5
6
SAN FRANCISCO
Book Implied: 3.50
Projections Grades
Moneyline (ML)
Divergence
AI Dodgers Win
61% Win Prob
C
Sim Giants Loss
59% Win Prob
C
Run Line (ATS)
Agreement
AI Giants (-1.5) Win
Proj Runs: +1.5
D
Sim Giants (+1.5) Loss
Proj Runs: -1.0
A
Over/Under (Total)
Divergence
AI u8.5 Win
Proj Total: 8.5
D
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
Los Angeles LAD
vs
San Francisco SF
162
Games Played
162
4.94 ▲
Runs / Game
4.13
.257 ▲
Avg (AVG)
.245
.338 ▲
On-Base (OBP)
.306
.424 ▲
Slugging (SLG)
.400
.762 ▲
OPS
.706
204 ▲
Home Runs
178
Key Model Drivers
Home Runs (L5) +89.1% more
Los Angeles: 1.5 vs San Francisco: 0.2
Total Bases (L5) +34.5% more
Los Angeles: 14.4 vs San Francisco: 9.4
Walks (L5) +33.2% more
Los Angeles: 2.7 vs San Francisco: 1.8
Hits (L5) +25.0% more
Los Angeles: 8.6 vs San Francisco: 6.5
Post-Mortem Analysis
Metric Projected Actual
Score Game
LAD Score 5.0 5
SF Score 3.5 1
Team Stats Splits (Home / Away)
Errors 0.6 / 0.3 1.0 / 0.0
Hits 6.5 / 8.6 5.0 / 8.0
Home Runs 0.2 / 1.5 0.0 / 1.0
Strikeouts 10.8 / 9.1 16.0 / 6.0
Total Bases 9.4 / 14.4 5.0 / 14.0
Walks 1.8 / 2.7 2.0 / 6.0
Public Market Splits
Moneyline
Open: -334 / +263 → -249 / +201 ↑
94%TICKETS6%
85%MONEY15%
Spread (ATS)
Open: -1.5 / +1.5 → -1.5 / +1.5
79%TICKETS21%
82%MONEY18%
Total (O/U)
Open: 7.5 → 8.5 ↑
72%TICKETS28%
81%MONEY19%
Situational Trends
📊 Win-Loss
LAD Advantage
103-63-0 (62.1%)
Margin: 1.2 ATS +/-:
SF
65-97-0 (40.1%)
Margin: -0.6 ATS +/-:
🎯 ATS (Spread)
LAD
(43.4%)
Margin: 1.2 ATS +/-:
SF Advantage
(51.2%)
Margin: -0.6 ATS +/-:
⚖️ Over/Under
LAD
72-89-5
O: 44.7% / U: 55.3% Total +/-: 0.0
SF
76-73-13
O: 51.0% / U: 49.0% Total +/-: +0.6
Season to Date Model Accuracy
AI Model
SIM Engine
SF
LAD
SF
LAD
ML
49% 79-81
56% 92-73
53% 85-75
48% 79-87
ATS
62% 100-60
59% 98-67
52% 83-77
43% 72-94
TTL
55% 82-68-10
48% 77-82-6
46% 68-81-11
44% 70-90-6
Accuracy:
Elite (>60%)
Good (53-60%)
Neutral (48-52%)
Under (43-47%)
Danger (≤42%)
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