MLB Baseball

DET vs CLE Prediction

June 13, 2026

10,000 Monte Carlo simulations

DET vs CLE prediction for June 13, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects CLE 3.9 - DET 4.2. DET is favored with a 52.5% win probability. The run line is 1.5 and the total is 7.5. Model projects 8.1 total runs.

CLE
3.9
Projected Score
VS O/U 7.5
DET
4.2
Projected Score
Win Probability
47.5%
52.5%
CLEDET
+1.5
Run Line (CLE)
7.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 57.4% (2,321 games)

Projected Runs Range 10th – 90th percentile

DET
246
CLE
246
FINALCLE 3 — DET 1
Projected
CLE 3.9 — DET 4.2
Actual
CLE 3 — DET 1

Starting Pitcher Matchup

Tarik Skubal L
DET
FF38%96 mph17% whiff
CH26%87 mph47% whiff
SI19%96 mph8% whiff
Joey Cantillo L
CLE
FF42%92 mph14% whiff
CH29%80 mph38% whiff
CU19%79 mph31% whiff

Weather Impact

Progressive Field
86°F7 mph wind
HR: 1.010 Total: 1.003
thin air, 7mph in

Bullpen Comparison

DET
4.31ERA
4.23FIP
8.88K/9
4.19BB/9
1.39WHIP
CLE
3.59ERA
3.57FIP
10.41K/9
3.47BB/9
1.23WHIP

Betting Edges

RUN_LINE HOME +1.5
-35.3% EV
-145
RUN_LINE AWAY -1.5
-11.9% EV
+120
ML AWAY
-9.4% EV
-143
TOTAL OVER 7.5
-7.5% EV
-115
F5_ML HOME
-7.0% EV
+126
F5_ML AWAY
-4.0% EV
-159

First 5 Innings & NRFI

DET F5
2.5 runs
49.3% win
CLE F5
1.9 runs
34.3% win
F5 Total
4.4
NRFI
57.3%
YRFI
42.7%
Avg 1st Inn Runs
0.89

HR Spotlight

Avg HRs
2.1
Over 0.5 HR
88%
Over 1.5 HR
63%
No HR
12%
Dillon Dingler DET30.0%
ISO: 0.243 | Barrel: 15.3% | vs Joey Cantillo | Park: 0.97x Platoon: 1.12x
Wenceel Pérez DET26.2%
ISO: 0.086 | Barrel: 8.6% | vs Joey Cantillo | Park: 0.97x Platoon: 1.12x
Spencer Torkelson DET22.6%
ISO: 0.157 | Barrel: 10.2% | vs Joey Cantillo | Park: 0.97x Platoon: 1.12x

Pitcher Strikeout Projections

Tarik Skubal
0.0 K projected
DET | K/9: 0.0
Joey Cantillo
0.0 K projected
CLE | K/9: 0.0

Injury Report

DET8 injured
Jack Flaherty SP15-DAY-IL
Casey Mize SP15-DAY-IL
Javier Baez SS60-DAY-IL
Burch Smith RP15-DAY-IL
Justin Verlander SP60-DAY-IL
Trey Sweeney SS60-DAY-IL
+2 more
CLE3 injured
Gabriel Arias SS60-DAY-IL
Erik Sabrowski RP15-DAY-IL
Carlos Hernandez RPDAY-TO-DAY

AI Intelligence Analysis

NEUTRAL -1GREEN ZONE56.6% WR (n=96)
Model leans CLE away favorite, but away ML is RED zone (43.3% WR, n=96). Pitcher mismatch (Skubal 2.92 ERA elite vs Cantillo 4.94 ERA mid-tier) supports away, but RED zone historical underperformance contradicts. Avoid to respect zone-based caution.

Key Factors

  • SP quality FAVORS AWAY: Tarik Skubal (DET away) 2.92 ERA (B-grade, 27% K-rate elite) vs Joey Cantillo (CLE home) 4.94 ERA (B- grade, 22.3% K-rate). 2.02 ERA gap is massive, suggests away should be strong favorite.
  • Model 53.3% DET win vs market 58.8% = 5.5% gap shows market AGREES with pitcher advantage, pricing away favorite heavily
  • Away ML zone is RED (43.3% WR, n=96)—despite pitcher quality advantage, away favorites historically underperform
  • Temperature 86.3F, wind 6.7 mph in = neutral environment favoring Skubal elite arm
  • Model edge 2.7% on home is marginal; negative for away favorite

Risk Factors

  • RED ZONE away ML: this is our primary blocker. Even with elite away SP (Skubal), away favorites historically lose at 43.3% WR.
  • Away favorite paradox suggests sharp money frequently opposes our model's away selections; skip to avoid trap
  • DET missing Parker Meadows (CF, 60-day IL) = reduced center field defense could allow runs; CLE pitching depth uncertain
Sharp MoneyAgainst ModelModel favoring DET away, but RED zone data contradicts. Sharp money likely on CLE home side, supporting zone bias.
RED ZONEPITCHER QUALITY AWAYAWAY FAVORITE

Edge Analysis

Moneyline
DET 52.5%
-35.3 pts
Run Line
+1.5
-35.3 pts
Total
7.5
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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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