Who is predicted to win DET vs NYY on July 1, 2026?

Based on 10,000 Pitch Sim v5.3 Monte Carlo simulations, NYY is favored with a 50.7% win probability. The simulation's mean projected score is NYY 5.3 - DET 5.5.

How does Olympus Bets generate sports predictions?

Every projection is produced by a league-specific Monte Carlo simulation engine (10,000+ iterations per game), Platt-scaled and isotonic-calibrated against historical outcomes, then sized with the Kelly Criterion plus a 15% Bayesian probability shrinkage. The full methodology is documented at https://app.olympus-bets.com/methodology.

DET vs NYY Prediction & Picks — July 1, 2026

DET vs NYY prediction for July 1, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects NYY 5.3 - DET 5.5. NYY is favored with a 50.7% win probability. The run line is -1.5 and the total is 9.5. Model projects 10.8 total runs.

NYY

5.3

Projected Score

VS O/U 9.5

DET

5.5

Projected Score

Win Probability

50.7%

49.3%

NYYDET

-1.5

Run Line (NYY)

9.5

Total Line

10,000

Simulations

☑ Calibrated accuracy at this confidence: 55.1% (2,559 games)

Projected Runs Range 10th – 90th percentile

DET

467

NYY

357

Starting Pitcher Matchup

Troy Melton R

DET

FF40%96 mph12% whiff

SL21%86 mph26% whiff

FC18%92 mph22% whiff

Will Warren R

NYY

FF40%94 mph20% whiff

SI27%93 mph19% whiff

ST21%84 mph21% whiff

Weather Impact

Yankee Stadium

96°F10 mph wind

HR: 1.008 Total: 1.002

thin air, 7mph in

Bullpen Comparison

DET

4.22ERA

4.23FIP

8.86K/9

4.10BB/9

1.37WHIP

NYY

3.36ERA

3.71FIP

8.80K/9

3.56BB/9

1.27WHIP

Betting Edges

RUN_LINE AWAY +1.5

-33.0% EV

-185

F5_ML HOME

-13.3% EV

-132

TOTAL UNDER 9.5

-12.6% EV

-112

RUN_LINE HOME -1.5

-8.5% EV

+152

ML HOME

-7.7% EV

-132

F5_ML AWAY

+4.5% EV

+106

First 5 Innings & NRFI

DET F5

3.0 runs

45.6% win

NYY F5

2.9 runs

41.4% win

F5 Total

5.8

NRFI

51.1%

YRFI

48.9%

Avg 1st Inn Runs

1.05

HR Spotlight

Avg HRs

3.0

Over 0.5 HR

95%

Over 1.5 HR

79%

No HR

Dillon Dingler DET30.0%

ISO: 0.294 | Barrel: 15.8% | vs Will Warren | Park: 1.10x

Kerry Carpenter DET30.0%

ISO: 0.270 | Barrel: 14.3% | vs Will Warren | Park: 1.10x Platoon: 1.12x

Spencer Torkelson DET30.0%

ISO: 0.227 | Barrel: 12.1% | vs Will Warren | Park: 1.10x

Pitcher Strikeout Projections

Troy Melton

0.0 K projected

DET | K/9: 0.0

Will Warren

0.0 K projected

NYY | K/9: 0.0

Injury Report

DET8 injured

Will Vest RP15-DAY-IL

Matt Seelinger RPDEVELOPMENTAL LIST

Jackson Jobe SP60-DAY-IL

Wenceel Perez RF60-DAY-IL

Parker Meadows CF60-DAY-IL

Burch Smith RP60-DAY-IL

+2 more

NYY8 injured

Spencer Jones CFDAY-TO-DAY

Max Fried SP15-DAY-IL

Ryan McMahon 3B10-DAY-IL

Trent Grisham CF10-DAY-IL

Giancarlo Stanton DH10-DAY-IL

David Bednar RPPATERNITY

+2 more

AI Intelligence Analysis

23.6% OVER edge at Yankee Stadium? Model overheating.

YELLOW ZONE50.1% WR (n=281)Sharp Money: Against Model

Will Warren vs Troy Melton — both rookies with unknown Bayesian ERAs, both mediocre stuff grades. Model projects 13.47 total on 9.5 market. 23.6% edge on OVER. Yankee Stadium is offensive (+10% HR factor) and it's 96°F, but the pitching is NOT elite. This is textbook model overconfidence in a high-edge, YELLOW-zone spot. The model just threw 4.0 units away on identical high-edge patterns. Don't repeat it.

Pitchers unknown quality: Will Warren (Bayesian ERA N/A, 9.5 K/9, B-) and Troy Melton (Bayesian ERA N/A, 5.0 K/9, B+) both lack established ERA baseline
Model edge 23.6% on OVER in YELLOW zone — fits worst-performing pattern (high edge + YELLOW, not GREEN)
+ 2 more factors with Premium

HIGH EDGE WARNINGTBD PITCHER QUALITYYELLOW ZONE TRAP

🔒Full analysis, risk factors, and recommended action available with PremiumUnlock

Edge Analysis

Moneyline

NYY 50.7%

-8.5 pts

Run Line

-1.5

-8.5 pts

Total

9.5

+3.8 pts

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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 →

DET vs NYY Prediction