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BALTIMORE

ORIOLESBAL

61-75  |  Road

2
FINAL
Sun, Aug 31 • 4:05 PM ET
Oracle Park
View Odds Details →

SAN FRANCISCO

GIANTSSF

67-69  |  Home

13
Probable Pitchers
Yennier Cano
STARTING PITCHER

Yennier Cano

#78 | Relief Pitcher
@
Drew Gilbert
STARTING PITCHER

Drew Gilbert

#0 | Center Field
Player W-L ERA WHIP IP K
Yennier Cano None-None 5.18 -- 1.1 --
Drew Gilbert None-None -- -- -- --
None-None W-L None-None
5.18 ERA --
-- WHIP --
1.1 IP (Innings Pitched) --
-- K (Strikeouts) --
AI Model Win Probability
ORIOLES
46%
📊
GIANTS
54%
ORIOLES --
GIANTS --
AI Model Projected Total
AI Projection
9.1
Projected
Book Total
--
Over / Under Line
Over 0 35%
Under 0 65%
AI Model Spread Expectation
AI Spread Proj
-0.3
SAN FRANCISCO
Book Spread
--
Book Line
▲ Edge: +0.3 points (San Francisco)
OriolesBAL (-3.5) 0 GiantsSF (+3.5)
Model Expected Spread
Spread Distribution
AI Model

Orioles Cover

46.9%

Giants Cover

53.1%

+12+8+40-4-8-12
Distribution centered around SF -0.3 expected margin.
Margin of Victory (SF)

BAL By 1-2 runs

17.9%

BAL By 3-4 runs

12.7%

SF By 1-2 runs

18.9%

SF By 3-4 runs

14.5%

AI Model Projected Score
4.38
BALTIMORE
4.69
SAN FRANCISCO
Simulated Score
3
BALTIMORE
5
SAN FRANCISCO
Projections Grades
Moneyline (ML)
Agreement
AI Giants Win
54% Win Prob
D
Sim Giants Win
50% Win Prob
D
Run Line (ATS)
Agreement
AI Giants (+0) Win
Proj Runs: -0.3
B
Sim Giants (+0) Win
Proj Runs: -2.0
D
Over/Under (Total)
No Consensus
AI o0 Win
Proj Total: 9.1
D
Sim u0.0
Proj Total: 8.0
D
Head-to-Head History
Date Game Score
Apr 12, 2026 SF @ BAL 2 - 6
Apr 11, 2026 SF @ BAL 2 - 6
Apr 10, 2026 SF @ BAL 6 - 3
Aug 31, 2025 BAL @ SF 2 - 13
Aug 30, 2025 BAL @ SF 11 - 1
Season Statistics Comparison
Baltimore BAL
vs
San Francisco SF
161
Games Played
▲ 162
4.46 ▲
Runs / Game
4.13
.234
Avg (AVG)
▲ .245
.314 ▲
On-Base (OBP)
.306
.396
Slugging (SLG)
▲ .400
.711 ▲
OPS
.706
199 ▲
Home Runs
178
Key Model Drivers
Walks (L5) +64.0% more
San Francisco: 3.1 vs Baltimore: 1.9
Home Runs (L5) +14.7% more
San Francisco: 1.8 vs Baltimore: 1.6
Strikeouts (L5) +12.1% more
San Francisco: 8.9 vs Baltimore: 7.9
Batting Avg (Season) +1.1%
San Francisco: 24.5% vs Baltimore: 23.4%
Post-Mortem Analysis
Metric Projected Actual
Score Game
BAL Score 4.4 2
SF Score 4.7 13
Team Stats Splits (Home / Away)
Errors 0.5 / 0.8 1.0 / 3.0
Hits 9.6 / 9.9 16.0 / 9.0
Home Runs 1.8 / 1.6 1.0 / 0.0
Strikeouts 8.9 / 7.9 10.0 / 6.0
Total Bases 16.0 / 18.0 24.0 / 10.0
Walks 3.1 / 1.9 6.0 / 7.0
Public Market Splits
Moneyline
Open: -- → --
43%TICKETS57%
46%MONEY54%
Spread (ATS)
Open: -- → --
67%TICKETS33%
40%MONEY60%
Total (O/U)
Open: -- → --
73%TICKETS27%
79%MONEY21%
Situational Trends
📊 Win-Loss
BAL Advantage
79-82-0 (49.1%)
Margin: -0.1 ATS +/-:
SF
65-97-0 (40.1%)
Margin: -0.6 ATS +/-:
🎯 ATS (Spread)
BAL Advantage
(52.8%)
Margin: -0.1 ATS +/-:
SF
(51.2%)
Margin: -0.6 ATS +/-:
⚖️ Over/Under
BAL
80-77-4
O: 51.0% / U: 49.0% Total +/-: +0.5
SF
76-73-13
O: 51.0% / U: 49.0% Total +/-: +0.6
Season to Date Model Accuracy
AI Model
SIM Engine
SF
BAL
SF
BAL
ML
49% 79-81
53% 83-73
53% 85-75
57% 90-69
ATS
62% 100-60
61% 95-60-1
52% 83-77
57% 90-68-1
TTL
55% 82-68-10
54% 81-70-5
46% 68-81-11
51% 78-75-6
Accuracy:
Elite (>60%)
Good (53-60%)
Neutral (48-52%)
Under (43-47%)
Danger (≤42%)
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