MLB Baseball

CLE vs CIN Prediction

July 27, 2026

10,000 Monte Carlo simulations

CLE vs CIN prediction for July 27, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects CIN 5.2 - CLE 5.1. CIN is favored with a 52.2% win probability. The run line is -1.5 and the total is 8.5. Model projects 10.3 total runs.

CIN
5.2
Projected Score
VS O/U 8.5
CLE
5.1
Projected Score
Win Probability
52.2%
47.8%
CINCLE
-1.5
Run Line (CIN)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 54.1% (2,978 games)

Projected Runs Range 10th – 90th percentile

CLE
357
CIN
357

Starting Pitcher Matchup

Slade Cecconi R
CLE
FF27% · 93
FC25% · 88
SI21% · 93
usagewhiffbar labels show usage · mph
FF27%93 mph16% whiff
FC25%88 mph19% whiff
SI21%93 mph8% whiff
Chase Burns R
CIN
FF57% · 98
SL37% · 90
CH5% · 90
usagewhiffbar labels show usage · mph
FF57%98 mph15% whiff
SL37%90 mph49% whiff
CH5%90 mph27% whiff

Weather Impact

Great American Ball Park
94°F8 mph wind
HR: 1.094 Total: 1.050
thin air, 8mph out

Bullpen Comparison

CLE
3.52ERA
3.55FIP
10.51K/9
3.50BB/9
1.23WHIP
CIN
4.59ERA
5.23FIP
8.86K/9
5.87BB/9
1.53WHIP

Betting Edges

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Edge Analysis
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First 5 Innings & NRFI

CLE F5
2.8 runs
39.5% win
CIN F5
3.1 runs
47.4% win
F5 Total
5.8
NRFI
46.3%
YRFI
53.7%
Avg 1st Inn Runs
1.19

HR Spotlight

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Home Run Analysis
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Injury Report

CLE1 injured
Shawn Armstrong RP15-DAY-IL
CIN7 injured
Spencer Steer 1B10-DAY-IL
Matt McLain 2B10-DAY-IL
Tony Santillan RP15-DAY-IL
Blake Dunn CF10-DAY-IL
Nick Lodolo SP15-DAY-IL
Brandon Williamson SP60-DAY-IL
+1 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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