MLB Baseball

MIL vs STL Prediction

July 8, 2026

10,000 Monte Carlo simulations

MIL vs STL prediction for July 8, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects STL 2.7 - MIL 3.6. MIL is favored with a 54.7% win probability. The run line is 1.5 and the total is 8.0. Model projects 6.2 total runs.

STL
2.7
Projected Score
VS O/U 8.0
MIL
3.6
Projected Score
Win Probability
45.3%
54.7%
STLMIL
+1.5
Run Line (STL)
8.0
Total Line
10,000
Simulations
MIL W5STL W4
Calibrated accuracy at this confidence: 56.5% (2,780 games)

Projected Runs Range 10th – 90th percentile

MIL
246
STL
135
FINALSTL 5 — MIL 1
Projected
STL 2.7 — MIL 3.6
Actual
STL 5 — MIL 1

Pick Results

Kyle Harrison OVER 5.5 Ksk_propsLOSS-0.50u

Starting Pitcher Matchup

Kyle Harrison L
MIL
FF59%95 mph29% whiff
SV30%82 mph27% whiff
CH10%86 mph23% whiff
Michael McGreevy R
STL
FF26%92 mph11% whiff
CH21%87 mph26% whiff
SI16%90 mph10% whiff

Weather Impact

Busch Stadium
86°F2 mph wind
HR: 1.040 Total: 1.020
thin air

Bullpen Comparison

MIL
3.66ERA
3.52FIP
9.38K/9
3.94BB/9
1.32WHIP
STL
4.30ERA
4.29FIP
8.27K/9
4.08BB/9
1.36WHIP

Betting Edges

RUN_LINE HOME +1.5
-43.3% EV
-133
TOTAL OVER 8.0
-30.6% EV
-114
TOTAL UNDER 8.0
+22.4% EV
-106
F5 UNDER 4.5
+13.7% EV
-125
F5_ML HOME
-11.7% EV
+122
ML AWAY
-6.9% EV
-152

First 5 Innings & NRFI

MIL F5
1.9 runs
49.0% win
STL F5
1.4 runs
31.2% win
F5 Total
3.3
NRFI
61.6%
YRFI
38.5%
Avg 1st Inn Runs
0.75

HR Spotlight

Avg HRs
1.8
Over 0.5 HR
83%
Over 1.5 HR
52%
No HR
17%
Jake Bauers MIL30.0%
ISO: 0.268 | Barrel: 13.6% | vs Michael McGreevy | Park: 0.98x Platoon: 1.12x
Jackson Chourio MIL30.0%
ISO: 0.241 | Barrel: 9.7% | vs Michael McGreevy | Park: 0.98x
Jordan Walker STL30.0%
ISO: 0.318 | Barrel: 10.9% | vs Kyle Harrison | Park: 0.98x Platoon: 1.12x

Pitcher Strikeout Projections

Kyle Harrison
0.0 K projected
MIL | K/9: 0.0
Michael McGreevy
0.0 K projected
STL | K/9: 0.0

Injury Report

MIL8 injured
Logan Henderson SP15-DAY-IL
Brandon Lockridge LF60-DAY-IL
David Hamilton 3B10-DAY-IL
Brandon Woodruff SP15-DAY-IL
Brian Fitzpatrick RP60-DAY-IL
Joel Kuhnel RP15-DAY-IL
+2 more
STL3 injured
Ryne Stanek RPDAY-TO-DAY
Max Rajcic RP60-DAY-IL
Ramon Urias 3B60-DAY-IL

AI Intelligence Analysis

LEANYELLOW ZONE49.8% WR (n=156)
Model projects 6.22 total vs market 8.0 = 1.78 run under-edge, +22.4% value (63.1% WR) — exceptionally strong UNDER signal. Away SP Harrison (B+, 3.05 ERA, 8.0 K/9, 0.677 grade) dominates home McGreevy (C+, 3.37 ERA, 8.0 K/9, 0.371 grade) — ace vs mediocre matchup rare. Weather 86.5F neutral, park factor 1.0. Home MIL underdog at +127 is market-disrespected. This game features UNDER as cleanest play: +22.4% edge with F5 UNDER at +13.7% cross-validation. BET UNDER not MIL ML.

Key Factors

  • Model total 6.22 vs market 8.0 = 1.78 run swing; +22.4% edge (63.1% WR) is THE second-strongest UNDER on slate (after SEA @ MIA)
  • SP mismatch: Kyle Harrison (B+, 0.677 grade, 3.05 ERA, 8.0 K/9) vs McGreevy (C+, 0.371 grade, 3.37 ERA, 8.0 K/9) — Harrison elite, McGreevy mediocre. Clear advantage away.
  • Scoring projection: MIL 3.56 runs away vs STL 2.66 runs home — inverted home/away scoring (away superior), rare and valid
  • F5 UNDER: 3.29 model vs 4.5 market, +13.7% edge (63.2% WR) — cross-validates daily, suggests early-inning dominance by STL's weak starter

Risk Factors

  • MIL +127 underdog away is sharp-disrespected at true 54.7% model win prob for away team; but ML and UNDER are different bets
  • Harrison (B+) is elite but not guaranteed dominant — weather neutral, no extreme park effects
  • STL has legitimate lineup (Walker) but McGreevy's 0.371 grade is severe liability early
EXCEPTIONAL UNDER EDGEPITCHER MISMATCH AWAYAWAY FAVORITE UNDERDOG MLF5 UNDER STRONG

Edge Analysis

Moneyline
MIL 54.7%
-43.3 pts
Run Line
+1.5
-43.3 pts
Total
8.0
+22.4 pts
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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