MLB Baseball

DET vs BOS Prediction

April 19, 2026

10,000 Monte Carlo simulations

DET vs BOS prediction for April 19, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects BOS 3.0 - DET 4.1. DET is favored with a 59.7% win probability. The run line is -1.5 and the total is 7.0. Model projects 7.1 total runs.

BOS
3.0
Projected Score
VS O/U 7.0
DET
4.1
Projected Score
Win Probability
40.3%
59.7%
BOSDET
-1.5
Run Line (BOS)
7.0
Total Line
10,000
Simulations
DETBOS L5
Calibrated accuracy at this confidence: 60.7% (2,040 games)

Projected Runs Range 10th – 90th percentile

DET
246
BOS
135

Pick Results

Jahmai Jones OVER 0.5 Hitsbatter_hitsWIN+0.96u

Starting Pitcher Matchup

Framber Valdez L
DET
SI49%94 mph9% whiff
CU30%78 mph23% whiff
CH20%89 mph12% whiff
Garrett Crochet L
BOS
FC31%91 mph21% whiff
FF26%96 mph20% whiff
SI23%95 mph18% whiff

Weather Impact

Fenway Park
46°F14 mph wind
HR: 0.966 Total: 0.980
6mph in

Bullpen Comparison

DET
3.27ERA
4.44FIP
8.45K/9
4.95BB/9
1.32WHIP
BOS
4.14ERA
5.51FIP
8.76K/9
4.50BB/9
1.21WHIP

Betting Edges

RUN_LINE HOME -1.5
-28.5% EV
+159
F5_ML AWAY
+27.2% EV
+122
F5_ML HOME
-27.0% EV
-152
RUN_LINE AWAY +1.5
-25.6% EV
-192
ML HOME
-23.7% EV
-143
ML AWAY
+23.1% EV
+119

First 5 Innings & NRFI

DET F5
2.3 runs
49.9% win
BOS F5
1.6 runs
31.3% win
F5 Total
3.9
NRFI
62.6%
YRFI
37.4%
Avg 1st Inn Runs
0.73

HR Spotlight

Avg HRs
1.4
Over 0.5 HR
74%
Over 1.5 HR
39%
No HR
26%
Dillon Dingler DET30.0%
ISO: 0.148 | Barrel: 14.8% | vs Garrett Crochet | Park: 1.08x Platoon: 1.12x
Willson Contreras BOS27.4%
ISO: 0.086 | Barrel: 8.6% | vs Framber Valdez | Park: 1.08x Platoon: 1.12x
Jahmai Jones DET23.3%
ISO: 0.093 | Barrel: 9.3% | vs Garrett Crochet | Park: 1.08x Platoon: 1.12x

Pitcher Strikeout Projections

Framber Valdez
0.0 K projected
DET | K/9: 0.0
Garrett Crochet
0.0 K projected
BOS | K/9: 0.0

Injury Report

DET8 injured
Zach McKinstry 3B10-DAY-IL
Justin Verlander SP15-DAY-IL
Bailey Horn RP15-DAY-IL
Troy Melton RP60-DAY-IL
Beau Brieske RP60-DAY-IL
Parker Meadows CF60-DAY-IL
+2 more
BOS8 injured
Kutter Crawford SP15-DAY-IL
Justin Slaten RP15-DAY-IL
Triston Casas 1B10-DAY-IL
Johan Oviedo SP60-DAY-IL
Patrick Sandoval SP15-DAY-IL
Brendan Rodgers 2BOUT
+2 more

AI Intelligence Analysis

STRONG BET +1RED ZONE45.5% WR (n=390)
DET @ BOS is a strong AWAY FAVORITE play (away dogs are RED zone, but this game has +23.1% edge offsetting curse). Garrett Crochet (8.19 ERA, C+/B- grade, 21.4% K-rate) is a disaster. Framber Valdez (4.05 ERA, C+/D grade, 13.3% K-rate, elite control 0.654) is weak but better than Crochet. Model projects DET 59.7% win prob at 23.1% edge on away ML. Market prices BOS -142 (58.8% implied), favoring home. But DET model 56.2% > market 45.7% = +23.1% edge (AWAY FAVORITE bias ignored). Take DET ML at +119 as away favorite with strong pitcher edge (Valdez clearly better than Crochet). F5 dominance: DET 57.3% F5 win prob, 27.2% F5_ML edge = early control.

Key Factors

  • Pitcher advantage EXTREME: Valdez 4.05 ERA (weak) vs Crochet 8.19 ERA (disaster) = 4.14 ERA gap, DET +14pt swing
  • Model DET 59.7% vs market BOS 58.8% implies = 14% edge away ML (high-conviction away favorite)
  • F5 dominance: DET 57.3% F5 prob, 27.2% F5_ML edge = early-inning control (FLAGS: DIRECTION_CONFIRMED)
  • Cold weather (45.8°F, 6mph in) suppresses BOS home advantage; limits run scoring

Risk Factors

  • Away favorite curse (RED zone 45.5% WR) is real; high edge (+23.1%) suggests model overconfidence (25%+ edges = 75% WR historically)
  • Crochet disaster ERA (8.19) might be regression candidate; could stabilize unexpectedly
  • BOS bullpen (4.14 ERA) is functional; late-game blowout less likely than projection suggests
PITCHER MISMATCHRED ZONEDIRECTION CONFIRMEDCOLD WEATHER

Edge Analysis

Moneyline
DET 59.7%
-28.5 pts
Run Line
-1.5
-28.5 pts
Total
7.0
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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. Full methodology →

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