Home / MLB Projections MLB / Giants @ Mets SF @ NYM

SAN FRANCISCO

GIANTSSF

59-85  |  Road

2
FINAL
Sun, Sep 6 • 1:40 PM ET
Citi Field
View Odds Details →

NEW YORK

METSNYM

65-78  |  Home

4
Probable Pitchers
👤
STARTING PITCHER

Cesar Perdomo

#83 | Relief Pitcher
@
Christian Scott
STARTING PITCHER

Christian Scott

#45 | Starting Pitcher
Player W-L ERA WHIP IP K
Cesar Perdomo 0-0 2.25 1.00 4.0 4
Christian Scott 4-4 3.80 1.31 94.2 113
0-0 W-L 4-4
2.25 Ldr ERA 3.80
1.00 Ldr WHIP 1.31
4.0 IP (Innings Pitched) Ldr 94.2
4 K (Strikeouts) Ldr 113
AI Model Win Probability
GIANTS
52%
📊
METS
48%
▲ Edge: +8.40% (SF)
GIANTS 44% Book Odds: +130
METS 61% Book Odds: -157
Book Implied: 43.50% / 61.10%
AI Model Projected Total
AI Projection
9.0
Projected
Book Total
8.0
Over / Under Line
▲ Edge: +1.0 (Over)
Over 8.0 60%
Under 8.0 40%
AI Model Spread Expectation
AI Spread Proj
-1.4
SAN FRANCISCO
Book Spread
+1.5
Book Line
▲ Edge: +2.9 points (San Francisco)
GiantsSF (+1.5) 0 MetsNYM (-1.5)
San Francisco Giants (+1.5) expected to cover
Spread Distribution
AI Model

Giants Cover

63.7%

Mets Cover

36.3%

-12-8-40+4+8+12
Distribution centered around SF -1.4 expected margin.
Margin of Victory (SF)

SF By 1-2 runs

19.7%

SF By 3-4 runs

17.2%

NYM By 1-2 runs

15.3%

NYM By 3-4 runs

9.5%

AI Model Projected Score
5.2
SAN FRANCISCO
Book Implied: 3.20
3.8
NEW YORK
Book Implied: 4.80
Simulated Score
5
SAN FRANCISCO
Book Implied: 3.20
6
NEW YORK
Book Implied: 4.80
Projections Grades
Moneyline (ML)
Divergence
AI Giants Loss
52% Win Prob
C
Sim Mets Win
59% Win Prob
C
Run Line (ATS)
Agreement
AI Giants (+1.5) Loss
Proj Runs: -1.4
A
Sim Giants (+1.5) Loss
Proj Runs: +1.0
C
Over/Under (Total)
Agreement 👑 Top Selection
AI o8.0 Loss
Proj Total: 9.0
B
Sim o8.0 Loss
Proj Total: 11.0
A
Head-to-Head History
Date Game Score
Sep 6, 2026 SF @ NYM 2 - 4
Sep 5, 2026 SF @ NYM 9 - 5
Sep 4, 2026 SF @ NYM 6 - 10
Apr 5, 2026 NYM @ SF 5 - 2
Apr 4, 2026 NYM @ SF 9 - 0
Season Statistics Comparison
San Francisco SF
vs
New York NYM
162
Games Played
162
4.13
Runs / Game
▲ 4.31
.245 ▲
Avg (AVG)
.239
.306
On-Base (OBP)
▲ .310
.400 ▲
Slugging (SLG)
.395
.706 ▲
OPS
.705
178
Home Runs
▲ 204
Key Model Drivers
Errors (L5) +55.0% more
San Francisco: 0.9 vs New York: 0.3
Home Runs (L5) +28.2% more
San Francisco: 2.6 vs New York: 1.9
Total Bases (L5) +21.8% more
San Francisco: 18.7 vs New York: 14.6
Hits (L5) +16.1% more
San Francisco: 9.1 vs New York: 7.6
Post-Mortem Analysis
Metric Projected Actual
Score Game
SF Score 5.2 2
NYM Score 3.8 4
Team Stats Splits (Home / Away)
Errors 0.3 / 0.9 1.0 / 0.0
Hits 7.6 / 9.1 7.0 / 5.0
Home Runs 1.9 / 2.6 2.0 / 0.0
Strikeouts 8.7 / 6.7 12.0 / 4.0
Total Bases 14.6 / 18.7 14.0 / 5.0
Walks 3.6 / 3.8 0.0 / 2.0
Public Market Splits
Moneyline
Open: +153 / -186 → +130 / -157 ↓
26%TICKETS74%
36%MONEY64%
Spread (ATS)
Open: +1.5 / -1.5 → +1.5 / -1.5
26%TICKETS74%
16%MONEY84%
Total (O/U)
Open: 8 → 8
86%TICKETS14%
77%MONEY23%
Situational Trends
📊 Win-Loss
SF
65-97-0 (40.1%)
Margin: -0.6 ATS +/-:
NYM Advantage
74-88-0 (45.7%)
Margin: -0.2 ATS +/-:
🎯 ATS (Spread)
SF Advantage
(51.2%)
Margin: -0.6 ATS +/-:
NYM
(46.3%)
Margin: -0.2 ATS +/-:
⚖️ Over/Under
SF
76-73-13
O: 51.0% / U: 49.0% Total +/-: +0.6
NYM
77-73-12
O: 51.3% / U: 48.7% Total +/-: +0.7
Season to Date Model Accuracy
AI Model
SIM Engine
NYM
SF
NYM
SF
ML
50% 79-80
49% 79-81
48% 76-83
53% 85-75
ATS
58% 93-66
62% 100-60
49% 78-81
52% 83-77
TTL
55% 80-66-13
55% 82-68-10
51% 74-72-13
46% 68-81-11
Accuracy:
Elite (>60%)
Good (53-60%)
Neutral (48-52%)
Under (43-47%)
Danger (≤42%)
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