MLB Baseball

CHC vs CIN Prediction

July 12, 2026

10,000 Monte Carlo simulations

CHC vs CIN prediction for July 12, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects CIN 4.8 - CHC 4.8. CIN is favored with a 50.4% win probability. The run line is 1.5 and the total is 9.0. Model projects 9.6 total runs.

CIN
4.8
Projected Score
VS O/U 9.0
CHC
4.8
Projected Score
Win Probability
50.4%
49.6%
CINCHC
+1.5
Run Line (CIN)
9.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 47.7% (2,790 games)

Projected Runs Range 10th – 90th percentile

CHC
357
CIN
357
FINALCIN 4 — CHC 8
Projected
CIN 4.8 — CHC 4.8
Actual
CIN 4 — CHC 8

Starting Pitcher Matchup

Matthew Boyd L
CHC
FF49%93 mph18% whiff
CH27%79 mph32% whiff
SL14%84 mph49% whiff
Andrew Abbott L
CIN
FF46%93 mph10% whiff
ST21%82 mph30% whiff
CH17%86 mph39% whiff

Weather Impact

Great American Ball Park
82°F7 mph wind
HR: 1.074 Total: 1.040
thin air, 7mph out

Bullpen Comparison

CHC
4.04ERA
5.13FIP
8.17K/9
4.04BB/9
1.34WHIP
CIN
4.59ERA
5.23FIP
8.86K/9
5.87BB/9
1.53WHIP

Betting Edges

RUN_LINE HOME +1.5
-29.7% EV
-152
F5_ML AWAY
-18.6% EV
-128
RUN_LINE AWAY -1.5
-12.0% EV
+126
F5_ML HOME
+9.6% EV
+102
ML AWAY
-8.2% EV
-127
F5 OVER 4.5
+7.0% EV
-122

First 5 Innings & NRFI

CHC F5
2.5 runs
37.8% win
CIN F5
3.1 runs
49.7% win
F5 Total
5.6
NRFI
45.8%
YRFI
54.2%
Avg 1st Inn Runs
1.21

HR Spotlight

Avg HRs
2.6
Over 0.5 HR
92%
Over 1.5 HR
73%
No HR
8%
Sal Stewart CIN30.0%
ISO: 0.284 | Barrel: 17.5% | vs Matthew Boyd | Park: 1.08x Platoon: 1.12x
Elly De La Cruz CIN30.0%
ISO: 0.343 | Barrel: 10.2% | vs Matthew Boyd | Park: 1.08x Platoon: 1.12x
Pete Crow-Armstrong CHC29.5%
ISO: 0.138 | Barrel: 13.0% | vs Andrew Abbott | Park: 1.08x

Pitcher Strikeout Projections

Matthew Boyd
0.0 K projected
CHC | K/9: 0.0
Andrew Abbott
0.0 K projected
CIN | K/9: 0.0

Injury Report

CHC8 injured
Justin Steele SP60-DAY-IL
Jameson Taillon SP15-DAY-IL
Edward Cabrera SP15-DAY-IL
Matt Shaw RF10-DAY-IL
Ethan Roberts RP15-DAY-IL
Daniel Palencia RP15-DAY-IL
+2 more
CIN7 injured
Nick Lodolo SP15-DAY-IL
Matt McLain 2B10-DAY-IL
Blake Dunn CF10-DAY-IL
Dane Myers CF10-DAY-IL
Graham Ashcraft RP60-DAY-IL
Brandon Williamson SP60-DAY-IL
+1 more

AI Intelligence Analysis

LEANYELLOW ZONE53.9% WR (n=170)
Model favors CIN home with 50.4% win prob, but market has CHC at -126 (55.9% implied). The 1.3% home ML edge is tiny. Real edge is F5_ML CIN: 54.3% model prob on CIN (edge 9.6%, market 44.5% implied), driven by Andrew Abbott (weaker) vs Matthew Boyd (B, 25.4% K-rate, elite K stuff).

Key Factors

  • F5_ML edge on CIN: 9.6% (model 54.3% vs market 44.5%) is the best edge in this game, not home ML
  • Pitcher skill gap: Boyd (25.4% K-rate, 11.6 K/9) >> Abbott (18.8% K-rate, 6.6 K/9) — elite K-rate mismatch
  • Home field + park: CIN home at 1.08 park factor adds ~0.75 runs to expected total, favoring overs
  • Bullpen: CIN 4.59 ERA (bad), CHC 4.04 ERA (mediocre) — late-game bullpen slightly favors CHC
  • Total model 9.58 vs market 9.0 = -3.0% edge on over (no value); -6.0% on under

Risk Factors

  • Home ML edge tiny (+1.3%); RED zone away ML (45.8% WR) suggests home bets often disappoint vs away
  • Park factor 1.08 inflates scoring; Boyd's K-dominance may not overcome park bias
  • F5 ML edge 9.6% — solid, but F5_ML zone shows only 50.8% WR historically (n=54, RED zone)
PITCHER MISMATCH

Edge Analysis

Moneyline
CIN 50.4%
-29.7 pts
Run Line
+1.5
-29.7 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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