MLB Baseball

LAD vs PHI Prediction

July 22, 2026

10,000 Monte Carlo simulations

LAD vs PHI prediction for July 22, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects PHI 6.0 - LAD 5.4. PHI is favored with a 53.8% win probability. The run line is 1.5 and the total is 9.5. Model projects 11.4 total runs.

PHI
6.0
Projected Score
VS O/U 9.5
LAD
5.4
Projected Score
Win Probability
53.8%
46.2%
PHILAD
+1.5
Run Line (PHI)
9.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 55.7% (2,978 games)

Projected Runs Range 10th – 90th percentile

LAD
357
PHI
468
FINALPHI 5 — LAD 9
Projected
PHI 6.0 — LAD 5.4
Actual
PHI 5 — LAD 9

Starting Pitcher Matchup

Eric Lauer L
LAD
FF44% · 91
FC19% · 87
CH16% · 84
usagewhiffbar labels show usage · mph
FF44%91 mph17% whiff
FC19%87 mph18% whiff
CH16%84 mph11% whiff
Aaron Nola R
PHI
KC34% · 78
FF24% · 92
SI20% · 92
usagewhiffbar labels show usage · mph
KC34%78 mph39% whiff
FF24%92 mph12% whiff
SI20%92 mph10% whiff

Weather Impact

Citizens Bank Park
79°F6 mph wind
HR: 1.061 Total: 1.033
thin air, 6mph out

Bullpen Comparison

LAD
3.58ERA
3.45FIP
10.00K/9
3.64BB/9
1.19WHIP
PHI
4.19ERA
3.22FIP
10.30K/9
3.17BB/9
1.34WHIP

Betting Edges

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Edge Analysis
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First 5 Innings & NRFI

LAD F5
3.2 runs
37.0% win
PHI F5
3.9 runs
51.9% win
F5 Total
7.1
NRFI
41.3%
YRFI
58.7%
Avg 1st Inn Runs
1.51

HR Spotlight

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Home Run Analysis
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Injury Report

LAD8 injured
Edwin Diaz RP60-DAY-IL
Will Smith C60-DAY-IL
Enrique Hernandez 1B10-DAY-IL
Tyler Glasnow SP60-DAY-IL
Blake Snell SP60-DAY-IL
Blake Treinen RP15-DAY-IL
+2 more
PHI6 injured
Garrett Stubbs C10-DAY-IL
Brad Keller RP15-DAY-IL
Tanner Banks RP15-DAY-IL
Lou Trivino RP15-DAY-IL
Johan Rojas CF60-DAY-IL
Adolis Garcia RF60-DAY-IL

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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