FINAL: CIN 11 — PHI 5. Our Monte Carlo simulation projected CIN 2.8 - PHI 4.8 (PHI at 59.5% win probability). The run line is -1.5 and the total is 9.0. Model projects 7.6 total runs.
CIN
2.8
Projected Score
VS
O/U 9.0
PHI
4.8
Projected Score
Win Probability
CINPHI
-1.5
Run Line (CIN)
9.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 59.5% (2,780 games)
Projected Runs Range 10th – 90th percentile
PHI
357
CIN
135
Projected
CIN 2.8 — PHI 4.8
Actual
CIN 11 — PHI 5
Pick Results
PHI F5 MLf5_mlLOSS-0.50u
Starting Pitcher Matchup
Alan Rangel R
PHI
FF35%93 mph8% whiff
CH34%81 mph41% whiff
SL16%84 mph26% whiff
Chase Burns R
CIN
FF57%98 mph16% whiff
SL37%91 mph51% whiff
CH6%90 mph27% whiff
Weather Impact
Great American Ball Park
90°F2 mph wind
HR: 1.041 Total: 1.020
thin air
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
-41.9% EV
+146
F5_ML AWAY
+36.1% EV
+124
F5_ML HOME
-35.6% EV
-156
TOTAL OVER 9.0
-24.0% EV
-105
ML HOME
-20.3% EV
-143
ML AWAY
+16.8% EV
+120
First 5 Innings & NRFI
PHI F5
2.5 runs
56.2% win
CIN F5
1.5 runs
27.6% win
F5 Total
4.0
NRFI
54.4%
YRFI
45.6%
Avg 1st Inn Runs
0.91
HR Spotlight
Avg HRs
2.1
Over 0.5 HR
87%
Over 1.5 HR
62%
No HR
13%
Kyle Schwarber PHI30.0%
ISO: 0.319 | Barrel: 20.8% | vs Chase Burns | Park: 1.08x Platoon: 1.12x
Bryce Harper PHI30.0%
ISO: 0.301 | Barrel: 12.3% | vs Chase Burns | Park: 1.08x Platoon: 1.12x
JJ Bleday CIN30.0%
ISO: 0.350 | Barrel: 7.8% | vs Alan Rangel | Park: 1.08x Platoon: 1.12x
Pitcher Strikeout Projections
Alan Rangel
0.0 K projected
PHI | K/9: 0.0
Chase Burns
0.0 K projected
CIN | K/9: 0.0
Injury Report
PHI3 injured
Brad Keller RP15-DAY-IL
Johan Rojas CF60-DAY-IL
Adolis Garcia RF60-DAY-IL
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
NEUTRAL -2RED ZONE44.9% WR (n=164)
Model shows PHI away ML at +16.8% edge (53.1% win prob). RED ZONE away-ML trap (44.9% WR). Combined with high edge (>15%), this is historically worst-performing combination. Market prices CIN -142 (heavily favored) despite Burns (B, 0.604 grade, 10.7 K/9) being legitimate starter. PHI's Alan Rangel (B-, 0.45 grade, 15.0 K/9) is B-minus, creating SP matchup debate. But model's 16.8% edge with <55% prob is unreliable signal. UNDER 9.0 at +14.1% (61.0% WR) is THE edge here, not PHI ML. Avoid away underdog traps; focus on totals.
Key Factors
- PHI away ML: +16.8% edge with 53.1% win prob triggers RED zone away-ML 44.9% WR. Historically this combination loses money.
- SP match: Burns (B, 0.604) vs Rangel (B-, 0.45) favors CIN at home, but Rangel's 15.0 K/9 (elite) is interesting; however, Burns' overall grade superior
- Great American Ball Park: 1.08 park factor (inflates runs ~8%) suggests overs, yet model projects UNDER. Contradiction suggests model uncertainty.
- UNDER 9.0: +14.1% edge (61.0% WR) is legitimate and away from RED zone trap. This is the actual play, not PHI ML.
- Market CIN -142 reflects heavy home favoritism; sharp action likely respects Burns over Rangel
Risk Factors
- Great American factor 1.08 is significant; heat (90.5F) + thin air fuels overs, yet model projects UNDER. Model may overestimate pitching dominance.
- Rangel's 15.0 K/9 is elite and could suppress scoring early; PHI lineup (Schwarber, Harper) has power but weak deep bench
- High edge (16.8%) with modest win prob (53.1%) is classic underdog trap; market correct at -142
RED ZONE AWAY MLHIGH EDGE WARNING 15%+PARK FACTOR INFLATION 1.08UNDER IS REAL EDGEMARKET FAVORS HOME
Edge Analysis
Moneyline
PHI 59.5%
-41.9 pts
Run Line
-1.5
-41.9 pts
Total
9.0
+14.1 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 →