MLB Baseball

BAL vs CIN Prediction

July 5, 2026

10,000 Monte Carlo simulations

BAL vs CIN prediction for July 5, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects CIN 4.2 - BAL 3.9. CIN is favored with a 54.2% win probability. The run line is 1.5 and the total is 9.5. Model projects 8.1 total runs.

CIN
4.2
Projected Score
VS O/U 9.5
BAL
3.9
Projected Score
Win Probability
54.2%
45.8%
CINBAL
+1.5
Run Line (CIN)
9.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 52.1% (2,777 games)

Projected Runs Range 10th – 90th percentile

BAL
246
CIN
246
FINALCIN 3 — BAL 2
Projected
CIN 4.2 — BAL 3.9
Actual
CIN 3 — BAL 2

Starting Pitcher Matchup

Kyle Bradish R
BAL
SI33%95 mph9% whiff
SL27%87 mph34% whiff
CU22%84 mph42% whiff
Nick Lodolo L
CIN
SI27%94 mph8% whiff
CU25%82 mph36% whiff
FF24%94 mph20% whiff

Weather Impact

Great American Ball Park
85°F4 mph wind
HR: 1.024 Total: 1.011
thin air

Bullpen Comparison

BAL
4.34ERA
4.01FIP
8.76K/9
3.44BB/9
1.30WHIP
CIN
4.59ERA
5.23FIP
8.86K/9
5.87BB/9
1.53WHIP

Betting Edges

RUN_LINE HOME +1.5
-29.4% EV
-175
TOTAL OVER 9.5
-27.6% EV
-118
TOTAL UNDER 9.5
+19.9% EV
-103
RUN_LINE AWAY -1.5
-13.8% EV
+143
F5_ML AWAY
-12.0% EV
-110
ML AWAY
-9.3% EV
-110

First 5 Innings & NRFI

BAL F5
2.0 runs
38.4% win
CIN F5
2.4 runs
46.8% win
F5 Total
4.4
NRFI
57.0%
YRFI
43.0%
Avg 1st Inn Runs
0.89

HR Spotlight

Avg HRs
2.5
Over 0.5 HR
91%
Over 1.5 HR
70%
No HR
9%
Pete Alonso BAL30.0%
ISO: 0.148 | Barrel: 18.9% | vs Nick Lodolo | Park: 1.08x Platoon: 1.12x
Gunnar Henderson BAL30.0%
ISO: 0.259 | Barrel: 8.5% | vs Nick Lodolo | Park: 1.08x
Coby Mayo BAL30.0%
ISO: 0.423 | Barrel: 10.1% | vs Nick Lodolo | Park: 1.08x Platoon: 1.12x

Pitcher Strikeout Projections

Kyle Bradish
0.0 K projected
BAL | K/9: 0.0
Nick Lodolo
0.0 K projected
CIN | K/9: 0.0

Injury Report

BAL8 injured
Ryan Helsley RP15-DAY-IL
Keegan Akin RP15-DAY-IL
Yaramil Hiraldo RP60-DAY-IL
Felix Bautista RP60-DAY-IL
Colin Selby RP60-DAY-IL
Chris Bassitt SP15-DAY-IL
+2 more
CIN6 injured
Blake Dunn CF10-DAY-IL
Dane Myers CF10-DAY-IL
Ke'Bryan Hayes 3B10-DAY-IL
Graham Ashcraft RP60-DAY-IL
Brandon Williamson SP60-DAY-IL
Tony Santillan RP15-DAY-IL

AI Intelligence Analysis

LEAN +1YELLOW ZONE50.1% WR (n=302)
Nick Lodolo (5.45 ERA, C+ grade, 8.0 K/9) is a WEAK home pitcher facing Kyle Bradish (4.07 ERA, C+ grade, 8.0 K/9 but higher stuff score). Despite matching K-rate, Bradish's 4.07 ERA and B- stuff (425 stuff score) vs Lodolo's 5.45 ERA suggests modest away pitcher advantage. However, the real edge is UNDER 9.5 at 19.9% edge (60.9% model prob) with YELLOW zone historical WR 50.1% BUT the home park (Great American Ball Park, +8-10% HR multiplier) and 85F temperature with tight location (Great American) compress runs slightly. Market at 9.5 seems too high. Coors normally inflates, but this park suppresses slightly. Lean UNDER given weather-adjusted baseline and pitcher quality. Avoid ML due to close matchup; totals are cleaner.

Key Factors

  • Pitcher quality: Bradish 4.07 ERA (C+ stuff, B- command, 8.0 K/9) vs Lodolo 5.45 ERA (C stuff) — Bradish slight advantage on ERA
  • Park factor: Great American 1.08 is neutral-favorable to offense; not a suppression park
  • Temperature 85.3F at high humidity (69%) slightly reduces fly ball distance but not dramatic
  • CIN home field worth ~0.5-1pt baseline, offset by weaker starter (Lodolo 5.45 vs visiting ace standards)

Risk Factors

  • 19.9% edge in YELLOW zone (50.1% historical WR) suggests 8-10% true edge after calibration
  • BAL offensive lineup (Pete Alonso, Gunnar Henderson, Coby Mayo) all projecting 30% HR prob each — power is present if BP blows up
  • CIN recent bullpen fatigue unknown
PITCHER MISMATCHWEATHER IMPACTYELLOW ZONEMODERATE EDGE WARNING

Edge Analysis

Moneyline
CIN 54.2%
-29.4 pts
Run Line
+1.5
-29.4 pts
Total
9.5
+19.9 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 →

Want Premium Predictions?

Get full access to all picks, detailed game-by-game analysis, and Kelly-optimized unit sizing across 9 leagues.

Go Premium Free Picks