CIN vs NYM prediction for May 25, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects NYM 4.5 - CIN 4.8. CIN is favored with a 51.7% win probability. The run line is -1.5 and the total is 7.5. Model projects 9.3 total runs.
NYM
4.5
Projected Score
VS
O/U 7.5
CIN
4.8
Projected Score
Win Probability
NYMCIN
-1.5
Run Line (NYM)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 53.6% (2,610 games)
Projected Runs Range 10th – 90th percentile
CIN
357
NYM
346
Projected
NYM 4.5 — CIN 4.8
Actual
NYM 2 — CIN 7
Starting Pitcher Matchup
Nick Lodolo L
CIN
CH27%89 mph19% whiff
CU26%82 mph36% whiff
SI25%94 mph10% whiff
Nolan McLean R
NYM
SI36%95 mph14% whiff
FF18%96 mph17% whiff
ST15%85 mph15% whiff
Weather Impact
Citi Field
68°F7 mph wind
HR: 1.005 Total: 1.002
neutral
Bullpen Comparison
CIN
4.82ERA
5.44FIP
9.15K/9
6.18BB/9
1.52WHIP
NYM
4.06ERA
3.88FIP
8.98K/9
3.76BB/9
1.32WHIP
Betting Edges
RUN_LINE AWAY +1.5
-31.8% EV
-179
TOTAL UNDER 7.5
-22.0% EV
-115
ML HOME
-16.7% EV
-152
RUN_LINE HOME -1.5
-14.5% EV
+146
ML AWAY
+13.6% EV
+128
TOTAL OVER 7.5
+13.6% EV
-105
First 5 Innings & NRFI
CIN F5
2.5 runs
36.6% win
NYM F5
2.9 runs
49.1% win
F5 Total
5.4
NRFI
53.0%
YRFI
47.0%
Avg 1st Inn Runs
1.01
HR Spotlight
Avg HRs
2.6
Over 0.5 HR
93%
Over 1.5 HR
73%
No HR
7%
Tyrone Taylor NYM25.6%
ISO: 0.209 | Barrel: 6.9% | vs Nick Lodolo | Park: 0.96x Platoon: 1.12x
JJ Bleday CIN23.9%
ISO: 0.338 | Barrel: 17.5% | vs Nolan McLean | Park: 0.96x Platoon: 1.12x
Bo Bichette NYM21.2%
ISO: 0.268 | Barrel: 4.9% | vs Nick Lodolo | Park: 0.96x Platoon: 1.12x
Pitcher Strikeout Projections
Nick Lodolo
0.0 K projected
CIN | K/9: 0.0
Nolan McLean
0.0 K projected
NYM | K/9: 0.0
Injury Report
CIN8 injured
Ke'Bryan Hayes 3B10-DAY-IL
Rhett Lowder SP15-DAY-IL
Emilio Pagan RP15-DAY-IL
Jose Trevino C10-DAY-IL
Hunter Greene SP60-DAY-IL
Connor Burns CDAY-TO-DAY
+2 more
NYM8 injured
Francisco Lindor SS10-DAY-IL
Jorge Polanco 1B10-DAY-IL
Juan Soto LFDAY-TO-DAY
Kodai Senga SP15-DAY-IL
A.J. Minter RP60-DAY-IL
Clay Holmes SP60-DAY-IL
+2 more
AI Intelligence Analysis
LEAN +1
Model projects 9.31 total runs (OVER 7.5, +13.6% edge, 58.3% model prob). Pitcher matchup heavily favors NYM: Nolan McLean (B pitcher, 3.86 ERA, 0.588 grade) vs Nick Lodolo (C pitcher, 7.78 ERA (!), 0.274 grade) — Lodolo is one of the worst SPs on the slate. Even though model projects CIN underdog (51.7% win prob), the high-ERA Lodolo makes CIN lineup face severe disadvantage. Low-scoring environment unlikely; NYM will score, CIN will need to keep up = over bet.
Key Factors
- Pitcher mismatch: Lodolo 7.78 ERA (C grade, 0.274 overall_score) is bottom-5 arm on slate. McLean 3.86 ERA (B grade, 0.588 score) is solid. ~3.9 ERA gap translates to ~2-3 run difference in game total prediction. Model projects 9.31 runs (vs 7.5 market) largely due to Lodolo's vulnerability.
- Weather neutral (68.1F, 7.1 mph wind slightly in, humidity 88%). Park factor 1.0 (neutral). No environmental amplification.
- NYM bullpen (4.06 ERA, quality 1.108) is solid; CIN bullpen (4.82 ERA, quality 0.934) below average. If game stays close through 6 innings, NYM's relief edge helps them extend lead.
- Model edge only 13.6% on total (modest) but paired with clear SP advantage for NYM side (McLean 3.86 vs Lodolo 7.78) = reasonable corner play.
Risk Factors
- Totals are DISABLED (grade F, 44.9% WR). Caution on all total edges, even 13.6%. Market may be efficiently pricing runs despite Lodolo weakness.
- CIN underdog (51.7%, market 43.9%) offers underdog value play on ML instead of chasing total edge. If CIN can get to Lodolo early for runs, game could go over without requiring big-scoring framework.
- historically mixed on totals is not compelling; edge only 13.6% (modest); recommend LEAN (0.75u) vs full bet.
PITCHER MISMATCHTOTALS VALUE
Edge Analysis
Moneyline
CIN 51.7%
-14.5 pts
Run Line
-1.5
-14.5 pts
Total
7.5
+13.6 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 →