MLB Baseball

WSH vs CLE Prediction

May 27, 2026

10,000 Monte Carlo simulations

WSH vs CLE prediction for May 27, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects CLE 5.5 - WSH 4.7. CLE is favored with a 59.4% win probability. The run line is -1.5 and the total is 8.0. Model projects 10.2 total runs.

CLE
5.5
Projected Score
VS O/U 8.0
WSH
4.7
Projected Score
Win Probability
59.4%
40.6%
CLEWSH
-1.5
Run Line (CLE)
8.0
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 58.2% (2,300 games)

Projected Runs Range 10th – 90th percentile

WSH
357
CLE
467
FINALCLE 3 — WSH 2
Projected
CLE 5.5 — WSH 4.7
Actual
CLE 3 — WSH 2

Starting Pitcher Matchup

PJ Poulin L
WSH
ST35%79 mph26% whiff
FF30%90 mph10% whiff
SI18%89 mph0% whiff
Gavin Williams R
CLE
FF27%96 mph25% whiff
ST26%87 mph45% whiff
CU21%83 mph26% whiff

Weather Impact

Progressive Field
71°F8 mph wind
HR: 0.989 Total: 0.991
thin air, 8mph in

Bullpen Comparison

WSH
4.48ERA
4.49FIP
8.33K/9
3.63BB/9
1.33WHIP
CLE
3.65ERA
3.84FIP
10.53K/9
3.93BB/9
1.27WHIP

Betting Edges

RUN_LINE AWAY +1.5
-39.0% EV
-137
TOTAL UNDER 8.0
-33.7% EV
-120
F5 OVER 4.5
+17.1% EV
+110
TOTAL OVER 8.0
+14.8% EV
-102
F5_ML HOME
-10.6% EV
-196
ML HOME
-8.0% EV
-189

First 5 Innings & NRFI

WSH F5
2.6 runs
36.9% win
CLE F5
3.2 runs
50.5% win
F5 Total
5.8
NRFI
49.3%
YRFI
50.7%
Avg 1st Inn Runs
1.12

HR Spotlight

Avg HRs
2.7
Over 0.5 HR
93%
Over 1.5 HR
75%
No HR
7%
James Wood WSH30.0%
ISO: 0.297 | Barrel: 15.8% | vs Gavin Williams | Park: 0.97x Platoon: 1.12x
CJ Abrams WSH30.0%
ISO: 0.313 | Barrel: 14.5% | vs Gavin Williams | Park: 0.97x Platoon: 1.12x
Kyle Manzardo CLE29.0%
ISO: 0.137 | Barrel: 7.2% | vs PJ Poulin | Park: 0.97x

Pitcher Strikeout Projections

PJ Poulin
0.0 K projected
WSH | K/9: 0.0
Gavin Williams
0.0 K projected
CLE | K/9: 0.0

Injury Report

WSH8 injured
Max Kranick RP60-DAY-IL
Tyler Stuart SPDAY-TO-DAY
Jake Irvin SP15-DAY-IL
DJ Herz SP60-DAY-IL
Cole Henry RP15-DAY-IL
Trevor Williams SP60-DAY-IL
+2 more
CLE3 injured
Gabriel Arias SS10-DAY-IL
Erik Sabrowski RP15-DAY-IL
Carlos Hernandez RPDAY-TO-DAY

AI Intelligence Analysis

LEAN +1YELLOW ZONE50.0% WR (n=289)
Market priced at 8.0, model projects 10.2 total (+14.8% edge on OVER). CLE's strong bullpen (3.65 ERA, 10.53 K/9, quality 1.233) vs WSH's weak pitching (PJ Poulin N/A ERA, C grade, 18.3% K-rate) creates scoring environment. Wind is 8 mph IN (headwind, -0.9 runs), but 70.9°F is neutral. OVER edge is large but TOTALS DISABLED — downgrade confidence from +2 to +1.

Key Factors

  • SP mismatch (strongly against WSH): Williams 3.51 ERA (29.1% K-rate), B grade vs Poulin unknown ERA, 18.3% K-rate, C grade. Williams ~1.5 Bayesian ERA better with elite K-rate.
  • Bullpen advantage CLE: CLE 3.65 ERA (K/9: 10.53) vs WSH 4.48 ERA (K/9: 8.33) — 0.83 ERA gap favors CLE in late innings.
  • Model total aggression: 10.2 mean runs projects to 60.9% OVER 8.0 edge, but historical OVER WR only 44.2%. High edge = likely overconfidence signal.
  • Weather slightly suppressive: 8 mph headwind (-0.9 runs), 70.9°F neutral. Reduces expected run scoring vs model baseline.
  • Away team advantage (paradox): WSH away team but model edges lean away team ML (44.1% WR) — structure unfavorable for away bets.

Risk Factors

  • TOTALS disabled: Historical F grade (45.6% WR, n=412). Betting against systemic model failure.
  • Model overconfidence signal: 14.8% edge correlates with 40-45% actual WR. High edge = trap indicator.
  • PJ Poulin unknown stats: Listed as N/A ERA (rookie or replacement level). Could pitch better than expected or blow up.
Sharp MoneyAgainst ModelMarket home -188 (65.3% prob) vs model 60.1% — market respecting CLE's superior quality. Sharp money likely on CLE moneyline, not total.
PITCHER MISMATCHTOTALS DISABLED WARNINGHIGH EDGE OVERCONFIDENCEWEATHER SLIGHT SUPPRESSBULLPEN EDGE

Edge Analysis

Moneyline
CLE 59.4%
-5.8 pts
Run Line
-1.5
-5.8 pts
Total
8.0
+14.8 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. Full methodology →

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