MLB Baseball

MIA vs NYM Prediction

July 30, 2026

10,000 Monte Carlo simulations

MIA vs NYM prediction for July 30, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects NYM 4.3 - MIA 4.0. NYM is favored with a 54.6% win probability. The run line is -1.5 and the total is 7.0. Model projects 8.2 total runs.

NYM
4.3
Projected Score
VS O/U 7.0
MIA
4.0
Projected Score
Win Probability
54.6%
45.4%
NYMMIA
-1.5
Run Line (NYM)
7.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 56.5% (2,978 games)

Projected Runs Range 10th – 90th percentile

MIA
246
NYM
246

Starting Pitcher Matchup

Eury Pérez R
MIA
FF43% · 98
SL15% · 88
ST14% · 84
usagewhiffbar labels show usage · mph
FF43%98 mph20% whiff
SL15%88 mph41% whiff
ST14%84 mph36% whiff
Nolan McLean R
NYM
SI33% · 95
FF20% · 96
ST15% · 85
usagewhiffbar labels show usage · mph
SI33%95 mph13% whiff
FF20%96 mph25% whiff
ST15%85 mph23% whiff

Weather Impact

Citi Field
72°F6 mph wind
HR: 0.995 Total: 0.995
6mph in

Bullpen Comparison

MIA
4.10ERA
3.72FIP
9.49K/9
4.04BB/9
1.21WHIP
NYM
3.56ERA
3.85FIP
9.31K/9
3.52BB/9
1.23WHIP

Betting Edges

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Edge Analysis
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First 5 Innings & NRFI

MIA F5
2.0 runs
33.6% win
NYM F5
2.7 runs
50.5% win
F5 Total
4.6
NRFI
57.8%
YRFI
42.2%
Avg 1st Inn Runs
0.88

HR Spotlight

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Home Run Analysis
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Injury Report

MIA8 injured
Andrew Nardi RP60-DAY-IL
Leo Jimenez 3BDAY-TO-DAY
Owen Caissie RF10-DAY-IL
Michael Petersen RPDAY-TO-DAY
Max Meyer SP15-DAY-IL
Josh Ekness RP60-DAY-IL
+2 more
NYM7 injured
Clay Holmes SP60-DAY-IL
Juan Soto LF10-DAY-IL
Justin Hagenman RP60-DAY-IL
Mark Vientos 1B10-DAY-IL
Dedniel Nunez RP60-DAY-IL
Reed Garrett RP60-DAY-IL
+1 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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