Home / MLB Projections MLB / Giants @ Red Sox SF @ BOS

SAN FRANCISCO

GIANTSSF

52-78  |  Road

4
FINAL
Sun, Aug 23 • 3:15 PM ET
Fenway Park
View Odds Details →

BOSTON

RED SOXBOS

71-59  |  Home

5
Probable Pitchers
👤
STARTING PITCHER

Matt Wilkinson

#71 | Starting Pitcher
@
Jake Bennett
STARTING PITCHER

Jake Bennett

#64 | Starting Pitcher
Player W-L ERA WHIP IP K
Matt Wilkinson 0-0 0.00 0.50 2.0 --
Jake Bennett 7-6 3.46 1.07 80.2 61
0-0 W-L 7-6
0.00 Ldr ERA 3.46
0.50 Ldr WHIP 1.07
2.0 IP (Innings Pitched) Ldr 80.2
-- K (Strikeouts) Ldr 61
AI Model Win Probability
GIANTS
77%
📊
RED SOX
23%
▲ Edge: +42.70% (SF)
GIANTS 35% Book Odds: +189
RED SOX 67% Book Odds: -204
Book Implied: 34.60% / 67.10%
AI Model Projected Total
AI Projection
9.0
Projected
Book Total
8.5
Over / Under Line
▲ Edge: +0.5 (Over)
Over 8.5 57%
Under 8.5 43%
AI Model Spread Expectation
AI Spread Proj
-3.2
SAN FRANCISCO
Book Spread
+1.5
Book Line
▲ Edge: +4.7 points (San Francisco)
GiantsSF (+1.5) 0 Red SoxBOS (-1.5)
San Francisco Giants (+1.5) expected to cover
Spread Distribution
AI Model

Giants Cover

78.8%

Red Sox Cover

21.2%

-12-8-40+4+8+12
Distribution centered around SF -3.2 expected margin.
Margin of Victory (SF)

SF By 1-2 runs

18.1%

SF By 3-4 runs

19.7%

BOS By 1-2 runs

10.0%

BOS By 3-4 runs

5.0%

AI Model Projected Score
6.1
SAN FRANCISCO
Book Implied: 3.50
2.9
BOSTON
Book Implied: 5
Simulated Score
3
SAN FRANCISCO
Book Implied: 3.50
4
BOSTON
Book Implied: 5
Projections Grades
Moneyline (ML)
Divergence
AI Giants Loss
77% Win Prob
A
Sim Red Sox Win
59% Win Prob
C
Run Line (ATS)
Agreement
AI Giants (+1.5) Win
Proj Runs: -3.2
A
Sim Giants (+1.5) Win
Proj Runs: +1.0
C
Over/Under (Total)
Divergence
AI o8.5 Win
Proj Total: 9.0
C
Sim u8.5 Loss
Proj Total: 7.0
B
Head-to-Head History
Date Game Score
Aug 23, 2026 SF @ BOS 4 - 5
Aug 22, 2026 SF @ BOS 2 - 3
Aug 21, 2026 SF @ BOS 4 - 6
Jun 22, 2025 BOS @ SF 5 - 9
Jun 21, 2025 BOS @ SF 2 - 3
Season Statistics Comparison
San Francisco SF
vs
Boston BOS
162 ▲
Games Played
2
4.13 ▲
Runs / Game
1.00
.245 ▲
Avg (AVG)
.117
.306 ▲
On-Base (OBP)
.159
.400 ▲
Slugging (SLG)
.250
.706 ▲
OPS
.409
178 ▲
Home Runs
2
Key Model Drivers
Home Runs (Season) +98.9% more
San Francisco: 178.0 vs Boston: 2.0
Runs per Game (Season) +75.8% more
San Francisco: 4.1 vs Boston: 1.0
OPS (Season) +29.7%
San Francisco: 70.6% vs Boston: 40.9%
Strikeouts (L5) +29.6% more
San Francisco: 9.6 vs Boston: 6.8
Post-Mortem Analysis
Metric Projected Actual
Score Game
SF Score 6.1 4
BOS Score 2.9 5
Team Stats Splits (Home / Away)
Errors 0.5 / 0.6 2.0 / 0.0
Hits 9.8 / 7.3 11.0 / 8.0
Home Runs 1.1 / 1.4 1.0 / 1.0
Strikeouts 6.8 / 9.6 5.0 / 7.0
Total Bases 15.5 / 12.6 20.0 / 11.0
Walks 5.2 / 3.8 1.0 / 1.0
Public Market Splits
Moneyline
Open: +185 / -203 → +189 / -204
6%TICKETS94%
9%MONEY91%
Spread (ATS)
Open: +1.5 / -1.5 → +1.5 / -1.5
16%TICKETS84%
11%MONEY89%
Total (O/U)
Open: 8 → 8.5 ↑
73%TICKETS27%
70%MONEY30%
Situational Trends
📊 Win-Loss
SF
65-97-0 (40.1%)
Margin: -0.6 ATS +/-:
BOS Advantage
87-77-0 (53.1%)
Margin: 0.4 ATS +/-:
🎯 ATS (Spread)
SF Advantage
(51.2%)
Margin: -0.6 ATS +/-:
BOS
(46.3%)
Margin: 0.4 ATS +/-:
⚖️ Over/Under
SF
76-73-13
O: 51.0% / U: 49.0% Total +/-: +0.6
BOS
74-86-4
O: 46.3% / U: 53.8% Total +/-: 0.0
Season to Date Model Accuracy
AI Model
SIM Engine
BOS
SF
BOS
SF
ML
50% 80-80
49% 79-81
47% 76-87
53% 85-75
ATS
58% 93-67
62% 100-60
48% 79-84
52% 83-77
TTL
46% 72-83-5
55% 82-68-10
47% 74-83-6
46% 68-81-11
Accuracy:
Elite (>60%)
Good (53-60%)
Neutral (48-52%)
Under (43-47%)
Danger (≤42%)
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