MLB Baseball

PHI vs CIN Prediction

July 9, 2026

10,000 Monte Carlo simulations

PHI vs CIN prediction for July 9, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects CIN 3.6 - PHI 5.2. PHI is favored with a 56.5% win probability. The run line is 1.5 and the total is 9.5. Model projects 8.8 total runs.

CIN
3.6
Projected Score
VS O/U 9.5
PHI
5.2
Projected Score
Win Probability
43.5%
56.5%
CINPHI
+1.5
Run Line (CIN)
9.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 57.3% (2,789 games)

Projected Runs Range 10th – 90th percentile

PHI
357
CIN
246
FINALCIN 0 — PHI 1
Projected
CIN 3.6 — PHI 5.2
Actual
CIN 0 — PHI 1

Starting Pitcher Matchup

Jesús Luzardo L
PHI
ST36%86 mph48% whiff
FF24%97 mph12% whiff
CH20%86 mph37% whiff
Brady Singer R
CIN
SI48%91 mph13% whiff
SL30%82 mph30% whiff
ST12%81 mph39% whiff

Weather Impact

Great American Ball Park
92°F8 mph wind
HR: 1.010 Total: 1.002
thin air, 7mph in

Bullpen Comparison

PHI
4.19ERA
3.22FIP
10.30K/9
3.17BB/9
1.34WHIP
CIN
4.59ERA
5.23FIP
8.86K/9
5.87BB/9
1.53WHIP

Betting Edges

RUN_LINE HOME +1.5
-41.8% EV
-114
TOTAL OVER 9.5
-18.7% EV
-102
F5_ML HOME
-10.9% EV
+138
TOTAL UNDER 9.5
+7.8% EV
-120
ML AWAY
-6.8% EV
-164
F5_ML AWAY
-1.7% EV
-175

First 5 Innings & NRFI

PHI F5
3.0 runs
54.6% win
CIN F5
2.1 runs
31.8% win
F5 Total
5.0
NRFI
48.9%
YRFI
51.1%
Avg 1st Inn Runs
1.14

HR Spotlight

Avg HRs
2.5
Over 0.5 HR
91%
Over 1.5 HR
70%
No HR
9%
Kyle Schwarber PHI30.0%
ISO: 0.319 | Barrel: 20.8% | vs Brady Singer | Park: 1.08x Platoon: 1.12x
Bryce Harper PHI30.0%
ISO: 0.301 | Barrel: 12.3% | vs Brady Singer | Park: 1.08x Platoon: 1.12x
Brandon Marsh PHI30.0%
ISO: 0.182 | Barrel: 8.3% | vs Brady Singer | Park: 1.08x Platoon: 1.12x

Pitcher Strikeout Projections

Jesús Luzardo
0.0 K projected
PHI | K/9: 0.0
Brady Singer
0.0 K projected
CIN | K/9: 0.0

Injury Report

PHI4 injured
Tanner Banks RP15-DAY-IL
Lou Trivino RP15-DAY-IL
Johan Rojas CF60-DAY-IL
Adolis Garcia RF60-DAY-IL
CIN7 injured
Matt McLain 2BDAY-TO-DAY
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
+1 more

AI Intelligence Analysis

NEUTRALYELLOW ZONE50.1% WR (n=318)
Model heavily favors PHI (away) at 56.5% win prob vs market 62% implied (5.5% market overestimate)—yet AWAY ML edge is NEGATIVE (-6.8%), indicating market is correctly priced or overpriced. Jesús Luzardo (B, 4.05 ERA) has 1.38 ERA advantage over Brady Singer (B-, 5.43 ERA), supporting away lean, but market's -163 (62% implied) already reflects advantage. UNDER edge 7.8% is modest and YELLOW zone (50.1% WR). No strong conviction play available; better opportunities exist.

Key Factors

  • Jesús Luzardo (PHI away): B grade, 4.05 Bayesian ERA, 28.3% K rate, excellent stuff (0.672 score)—strong pitcher
  • Brady Singer (CIN home): B-, 5.43 ERA, 18.8% K rate, below-average (0.425 grade)—clear mismatch favoring away
  • Model correctly identifies PHI advantage (56.5%) but market OVERPRICES at 62%—gap is 5.5% opposite direction to normal market underestimation
  • UNDER edge 7.8% is modest; market total 9.5 vs model 8.83 (0.67 run gap) is narrow, suggesting equilibrium
  • Great American park (1.08 factor, Coors-like HR boost) partially offset by 91.7°F hot + 7.4 mph wind IN

Risk Factors

  • AWAY ML has NEGATIVE edge (-6.8%)—market is correctly valuing or overvaluing away team; recommend SKIP
  • Market at -163 confidence (62% implied) is HIGHER than model (57.9%)—unusual pattern where market is more confident than model
  • UNDER 7.8% edge with 50.1% zone WR is marginal; no compelling value proposition
Sharp MoneyAgainst ModelMarket at -163 (62% implied PHI) exceeds model 57.9% by 4.1%—market is MORE confident in PHI than model. Sharp money likely on CIN or pushing totals up (over action).
PITCHER MISMATCHMODEL MARKET CONFLICTWEAK EDGES

Edge Analysis

Moneyline
PHI 56.5%
-41.8 pts
Run Line
+1.5
-41.8 pts
Total
9.5
+7.8 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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