MLB Baseball

LAD vs NYM Prediction

July 26, 2026

10,000 Monte Carlo simulations

LAD vs NYM prediction for July 26, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects NYM 3.0 - LAD 4.1. LAD is favored with a 54.8% win probability. The run line is 1.5 and the total is 8.5. Model projects 7.2 total runs.

NYM
3.0
Projected Score
VS O/U 8.5
LAD
4.1
Projected Score
Win Probability
45.2%
54.8%
NYMLAD
+1.5
Run Line (NYM)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 56.5% (2,978 games)

Projected Runs Range 10th – 90th percentile

LAD
246
NYM
135
FINALNYM 8 — LAD 3
Projected
NYM 3.0 — LAD 4.1
Actual
NYM 8 — LAD 3

Starting Pitcher Matchup

Emmet Sheehan R
LAD
FF42% · 94
SL30% · 87
CH16% · 86
usagewhiffbar labels show usage · mph
FF42%94 mph25% whiff
SL30%87 mph38% whiff
CH16%86 mph22% whiff
Freddy Peralta R
NYM
FF53% · 94
CH21% · 87
CU13% · 79
usagewhiffbar labels show usage · mph
FF53%94 mph19% whiff
CH21%87 mph25% whiff
CU13%79 mph35% whiff

Weather Impact

Citi Field
83°F5 mph wind
HR: 1.003 Total: 0.999
5mph in

Bullpen Comparison

LAD
3.58ERA
3.45FIP
10.00K/9
3.64BB/9
1.19WHIP
NYM
3.44ERA
3.69FIP
9.32K/9
3.58BB/9
1.21WHIP

Betting Edges

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Edge Analysis
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First 5 Innings & NRFI

LAD F5
2.2 runs
45.2% win
NYM F5
1.8 runs
36.4% win
F5 Total
3.9
NRFI
59.7%
YRFI
40.3%
Avg 1st Inn Runs
0.82

HR Spotlight

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Home Run Analysis
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Injury Report

LAD8 injured
Edwin Diaz RP60-DAY-IL
Enrique Hernandez 1B10-DAY-IL
Tyler Glasnow SP60-DAY-IL
Blake Snell SP60-DAY-IL
Will Smith C60-DAY-IL
Blake Treinen RP15-DAY-IL
+2 more
NYM8 injured
Juan Soto LF10-DAY-IL
Clay Holmes SP60-DAY-IL
Justin Hagenman RP60-DAY-IL
Mark Vientos 1B10-DAY-IL
Austin Warren RP15-DAY-IL
Dedniel Nunez RP60-DAY-IL
+2 more

Model Edge & Sizing

🔒The model's edge against the market, and the stake it sizes for this matchup, are premium.Unlock

Edge Analysis

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Edge Analysis
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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 →

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