MIL vs SF prediction for July 30, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects SF 2.6 - MIL 3.5. MIL is favored with a 56.1% win probability. The run line is 1.5 and the total is 7.5. Model projects 6.1 total runs.
SF
2.6
Projected Score
VS
O/U 7.5
MIL
3.5
Projected Score
Win Probability
SFMIL
+1.5
Run Line (SF)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 56.8% (2,978 games)
Projected Runs Range 10th – 90th percentile
MIL
245
SF
135
Starting Pitcher Matchup
Thomas Pannone L
MIL
Logan Webb R
SF
usagewhiffbar labels show usage · mph
SI31%92 mph10% whiff
CH26%86 mph27% whiff
ST19%84 mph21% whiff
Weather Impact
Oracle Park
70°F12 mph wind
HR: 1.076 Total: 1.043
11mph out
Bullpen Comparison
MIL
3.42ERA
3.74FIP
9.21K/9
3.89BB/9
1.26WHIP
SF
4.42ERA
4.39FIP
8.28K/9
4.54BB/9
1.43WHIP
Betting Edges
First 5 Innings & NRFI
MIL F5
1.7 runs
42.0% win
SF F5
1.4 runs
35.8% win
F5 Total
3.1
NRFI
67.7%
YRFI
32.4%
Avg 1st Inn Runs
0.62
HR Spotlight
Injury Report
MIL8 injured
Jake Bauers 1BDAY-TO-DAY
Kyle Harrison SP15-DAY-IL
Sal Frelick RF10-DAY-IL
Brandon Lockridge LF60-DAY-IL
Joel Kuhnel RP15-DAY-IL
DL Hall RP15-DAY-IL
+2 more
SF8 injured
Trevor McDonald SP15-DAY-IL
Harrison Bader CF10-DAY-IL
Casey Schmitt LF10-DAY-IL
Matt Chapman 3B10-DAY-IL
Victor Bericoto RF10-DAY-IL
Jonah Cox CF10-DAY-IL
+2 more
AI Intelligence Analysis
Edge Analysis
More Projections Today
How this prediction was generated: This page shows output from the Olympus Bets MLB Baseball Monte Carlo engine. Each game is simulated 10,000 times using real-time team data, injury reports, and current odds. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →