MLB Baseball

WSH vs ATL Prediction

July 30, 2026

10,000 Monte Carlo simulations

WSH vs ATL prediction for July 30, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects ATL 6.6 - WSH 5.9. ATL is favored with a 55.6% win probability. The run line is -1.5 and the total is 9.5. Model projects 12.5 total runs.

ATL
6.6
Projected Score
VS O/U 9.5
WSH
5.9
Projected Score
Win Probability
55.6%
44.4%
ATLWSH
-1.5
Run Line (ATL)
9.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 56.8% (2,978 games)

Projected Runs Range 10th – 90th percentile

WSH
468
ATL
579

Starting Pitcher Matchup

Jake Irvin R
WSH
FF28% · 93
CU26% · 78
SI24% · 92
usagewhiffbar labels show usage · mph
FF28%93 mph21% whiff
CU26%78 mph41% whiff
SI24%92 mph6% whiff
Grant Holmes R
ATL
SL36% · 85
FF30% · 94
SI11% · 93
usagewhiffbar labels show usage · mph
SL36%85 mph37% whiff
FF30%94 mph12% whiff
SI11%93 mph15% whiff

Weather Impact

Truist Park
89°F8 mph wind
HR: 1.095 Total: 1.050
thin air, 7mph out

Bullpen Comparison

WSH
5.73ERA
5.34FIP
8.76K/9
4.95BB/9
1.58WHIP
ATL
3.17ERA
3.43FIP
9.57K/9
3.05BB/9
1.11WHIP

Betting Edges

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Edge Analysis
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First 5 Innings & NRFI

WSH F5
3.4 runs
39.8% win
ATL F5
3.8 runs
49.2% win
F5 Total
7.2
NRFI
44.4%
YRFI
55.6%
Avg 1st Inn Runs
1.37

HR Spotlight

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Home Run Analysis
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Injury Report

WSH8 injured
Jake Irvin SP60-DAY-IL
Brad Lord RP15-DAY-IL
PJ Poulin RP15-DAY-IL
Richard Lovelady RP60-DAY-IL
Drew Millas C10-DAY-IL
Mitchell Parker RP60-DAY-IL
+2 more
ATL8 injured
Sean Murphy C60-DAY-IL
Spencer Schwellenbach SP60-DAY-IL
Spencer Strider SP60-DAY-IL
Robert Suarez RP15-DAY-IL
Ha-Seong Kim SS10-DAY-IL
Joe Jimenez 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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