SAN FRANCISCO
GIANTSSF
58-83 | Road
2
PITTSBURGH
PIRATESPIT
69-72 | Home
5
Probable Pitchers
STARTING PITCHER
Blade Tidwell
#46 | Relief Pitcher@
STARTING PITCHER
Lake Bachar
#71 | Relief Pitcher| Player | W-L | ERA | WHIP | IP | K |
|---|---|---|---|---|---|
| Blade Tidwell | 0-1 | 4.54 | 1.22 | 37.2 | 31 |
| Lake Bachar | 1-3 | 3.70 | 1.09 | 75.1 | 77 |
0-1
W-L
1-3
4.54
ERA
Ldr 3.70
1.22
WHIP
Ldr 1.09
37.2
IP (Innings Pitched)
Ldr 75.1
31
K (Strikeouts)
Ldr 77
AI Model Win Probability
GIANTS
52%
PIRATES
48%
▲ Edge: +10.90% (SF)
GIANTS
42%
Book Odds: +141
PIRATES
63%
Book Odds: -171
AI Model Projected Total
AI Projection
9.5
Projected
Book Total
9.0
Over / Under Line
▲
Edge: +0.5 (Over)
Over 9.0
55%
Under 9.0
45%
AI Model Spread Expectation
AI Spread Proj
-1.5
SAN FRANCISCO
Book Spread
+1.5
Book Line
▲ Edge: +3.0 points (San Francisco)
Spread Distribution
AI Model
-12-8-40+4+8+12
Distribution centered around SF -1.5 expected margin.
Margin of Victory (SF)
SF By 1-2 runs
19.7%
SF By 3-4 runs
17.5%
PIT By 1-2 runs
15.0%
PIT By 3-4 runs
9.2%
AI Model Projected Score
San Francisco
5.5
SAN FRANCISCO
Book Implied: 3.80
Pittsburgh
4
PITTSBURGH
Book Implied: 5.20
Simulated Score
San Francisco
3
SAN FRANCISCO
Book Implied: 3.80
Pittsburgh
6
PITTSBURGH
Book Implied: 5.20
Projections Grades
Moneyline (ML)
Divergence
AI
Giants
Loss
52% Win Prob
C
Sim
Pirates
Win
77% Win Prob
A
Run Line (ATS)
Divergence
👑 Top Selection
AI
Giants (+1.5)
Loss
Proj Runs: -1.5
B
Sim
Pirates (-1.5)
Win
Proj Runs: -3.0
B
Over/Under (Total)
Divergence
AI
o9.0
Loss
Proj Total: 9.5
C
Sim
o9.0
Loss
Proj Total: 9.0
D
Head-to-Head History
Date
Game
Score
Sep 3, 2026
SF @ PIT
2 - 5
Sep 2, 2026
SF @ PIT
5 - 4
Sep 1, 2026
SF @ PIT
12 - 13
May 10, 2026
PIT @ SF
6 - 7
May 9, 2026
PIT @ SF
13 - 3
Season Statistics Comparison
San Francisco
SF
vs
Pittsburgh
PIT
162
Games Played
162
4.13
Runs / Game
▲
4.73
.245
Avg (AVG)
▲
.253
.306
On-Base (OBP)
▲
.330
.400
Slugging (SLG)
▲
.404
.706
OPS
▲
.734
178
Home Runs
▲
186
Key Model Drivers
Home Runs (L5)
+40.6% more
San Francisco: 1.3
vs
Pittsburgh: 0.8
Runs per Game (Season)
+14.5% more
Pittsburgh: 4.7
vs
San Francisco: 4.1
Strikeouts (L5)
+11.5% more
Pittsburgh: 8.4
vs
San Francisco: 7.6
Hits (L5)
+10.2% more
Pittsburgh: 10.3
vs
San Francisco: 9.4
Post-Mortem Analysis
Metric
Projected
Actual
Score Game
SF Score
5.5
2
PIT Score
4.0
5
Team Stats Splits (Home / Away)
Errors
0.6 / 0.6
0.0 / 1.0
Hits
10.3 / 9.4
5.0 / 2.0
Home Runs
0.8 / 1.3
0.0 / 0.0
Strikeouts
8.4 / 7.6
9.0 / 6.0
Total Bases
14.4 / 15.4
5.0 / 3.0
Walks
4.0 / 4.2
5.0 / 7.0
Public Market Splits
Moneyline
Open: +129 / -156
→
+141 / -171
↑
Spread (ATS)
Open: +1.5 / -1.5
→
+1.5 / -1.5
Total (O/U)
Open: 8.5
→
9
↑
Situational Trends
📊 Win-Loss
SF
65-97-0
(40.1%)
Margin: -0.6
ATS +/-:
PIT
Advantage
82-80-0
(50.6%)
Margin: 0.2
ATS +/-:
🎯 ATS (Spread)
SF
Advantage
(51.2%)
Margin: -0.6
ATS +/-:
PIT
(49.4%)
Margin: 0.2
ATS +/-:
⚖️ Over/Under
SF
76-73-13
O: 51.0% / U: 49.0%
Total +/-: +0.6
PIT
81-74-7
O: 52.3% / U: 47.7%
Total +/-: +1.0
Season to Date Model Accuracy
AI Model
SIM Engine
PIT
SF
PIT
SF
ML
52%
82-77
49%
79-81
52%
85-78
53%
85-75
ATS
54%
86-73
62%
100-60
50%
81-82
52%
83-77
TTL
47%
72-81-6
55%
82-68-10
50%
79-78-6
46%
68-81-11
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