MLB Baseball

MIL vs ARI Prediction

July 5, 2026

10,000 Monte Carlo simulations

MIL vs ARI prediction for July 5, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects ARI 4.7 - MIL 4.5. ARI is favored with a 51.6% win probability. The run line is 1.5 and the total is 9.0. Model projects 9.3 total runs.

ARI
4.7
Projected Score
VS O/U 9.0
MIL
4.5
Projected Score
Win Probability
51.6%
48.4%
ARIMIL
+1.5
Run Line (ARI)
9.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 51.8% (2,777 games)

Projected Runs Range 10th – 90th percentile

MIL
346
ARI
357

Starting Pitcher Matchup

Brandon Sproat R
MIL
SI25%96 mph16% whiff
FC24%93 mph20% whiff
FF20%97 mph22% whiff
Eduardo Rodriguez L
ARI
FF40%92 mph19% whiff
CH27%86 mph20% whiff
FC13%89 mph11% whiff

Weather Impact

Chase Field
110°F3 mph windRoof: retractable
HR: 1.089 Total: 1.045
thin air

Bullpen Comparison

MIL
3.66ERA
3.52FIP
9.38K/9
3.94BB/9
1.32WHIP
ARI
3.28ERA
3.68FIP
8.28K/9
3.10BB/9
1.10WHIP

Betting Edges

RUN_LINE HOME +1.5
-28.0% EV
-156
F5_ML AWAY
-14.3% EV
-120
RUN_LINE AWAY -1.5
-13.0% EV
+129
ML AWAY
-8.8% EV
-122
TOTAL OVER 9.0
-8.7% EV
+101
F5_ML HOME
+1.5% EV
-110

First 5 Innings & NRFI

MIL F5
2.6 runs
39.8% win
ARI F5
3.0 runs
47.7% win
F5 Total
5.6
NRFI
48.3%
YRFI
51.7%
Avg 1st Inn Runs
1.18

HR Spotlight

Avg HRs
3.0
Over 0.5 HR
95%
Over 1.5 HR
79%
No HR
5%
Andrew Vaughn MIL30.0%
ISO: 0.353 | Barrel: 12.0% | vs Eduardo Rodriguez | Park: 1.06x Platoon: 1.12x
Jackson Chourio MIL30.0%
ISO: 0.275 | Barrel: 9.7% | vs Eduardo Rodriguez | Park: 1.06x Platoon: 1.12x
Corbin Carroll ARI30.0%
ISO: 0.264 | Barrel: 14.5% | vs Brandon Sproat | Park: 1.06x Platoon: 1.12x

Pitcher Strikeout Projections

Brandon Sproat
0.0 K projected
MIL | K/9: 0.0
Eduardo Rodriguez
0.0 K projected
ARI | K/9: 0.0

Injury Report

MIL8 injured
Brandon Woodruff SP15-DAY-IL
Brian Fitzpatrick RP60-DAY-IL
Logan Henderson SP15-DAY-IL
Joel Kuhnel RP15-DAY-IL
Rob Zastryzny RP15-DAY-IL
Carlos Rodriguez RP15-DAY-IL
+2 more
ARI8 injured
James McCann C10-DAY-IL
Jordan Lawlar LF10-DAY-IL
Corbin Burnes SP60-DAY-IL
Michael Soroka SP15-DAY-IL
Ryne Nelson SP60-DAY-IL
A.J. Puk RP60-DAY-IL
+2 more

AI Intelligence Analysis

NEUTRALYELLOW ZONE56.0% WR (n=156)
Eduardo Rodriguez (C+ grade, 6.7 K-rate, low stuff 18.2% score, 55.4% command) is a WEAK home pitcher vs Brandon Sproat (B- grade, 8.6 K-rate, 45.4% stuff score). Sproat is superior in both K-rate and stuff. Model shows essentially EVEN matchup: HOME ML 0.3% edge (49.9% prob), AWAY ML -8.8% edge (50.1% prob). These are MICRO-EDGES masking that the model sees this as a coin flip. Weather: 109.5F at Chase Field (highest temp on slate with +8.9% HR multiplier due to extreme heat and low 8% humidity) with retractable roof OPEN. This is an extreme run-scoring environment. Model projects 9.26 total with market at 9.0 — a 0.26 run gap, negligible. All edges are <1%. ARI has some injury concerns (James McCann 10-day IL quad, Jordan Lawlar 10-day IL hamstring) but MIL is relatively healthy. Given the extreme weather favoring overs and NO clear pitcher advantage, this is a SKIP. Market has done its homework.

Key Factors

  • Pitcher advantage: Sproat 45.4% stuff, 8.6 K-rate vs Rodriguez 18.2% stuff, 6.7 K-rate — Sproat clearly superior
  • Temperature 109.5F with 8.9% HR multiplier (extreme) and 8% humidity (dry) — run environment inflated
  • ARI injuries: James McCann (10-day IL quad), Jordan Lawlar (10-day IL hamstring) — mid-tier impact on lineup
  • Model 9.26 total nearly matches market 9.0 — market is accurate

Risk Factors

  • Extreme heat could make even elite pitchers struggle
  • Model-market disagreement <0.5 run suggests fair pricing
EXTREME WEATHERMICRO EDGESWEAK HOME PITCHER

Edge Analysis

Moneyline
ARI 51.6%
-28.0 pts
Run Line
+1.5
-28.0 pts
Total
9.0
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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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