MLB Baseball

NYY vs KC Prediction

May 26, 2026

10,000 Monte Carlo simulations

NYY vs KC prediction for May 26, 2026: Our Monte Carlo simulation ran 10,000 game iterations and projects KC 4.3 - NYY 6.9. NYY is favored with a 68.5% win probability. The run line is 1.5 and the total is 8.5. Model projects 11.2 total runs.

KC
4.3
Projected Score
VS O/U 8.5
NYY
6.9
Projected Score
Win Probability
31.5%
68.5%
KCNYY
+1.5
Run Line (KC)
8.5
Total Line
10,000
Simulations
Calibrated accuracy at this confidence: 67.3% (2,300 games)

Projected Runs Range 10th – 90th percentile

NYY
579
KC
246
FINALKC 1 — NYY 15
Projected
KC 4.3 — NYY 6.9
Actual
KC 1 — NYY 15

Starting Pitcher Matchup

Cam Schlittler R
NYY
FF44%98 mph34% whiff
FC28%94 mph18% whiff
SI18%97 mph15% whiff
Bailey Falter L
KC
FF51%92 mph14% whiff
SL18%85 mph18% whiff
CU12%78 mph26% whiff

Weather Impact

Kauffman Stadium
83°F7 mph wind
HR: 1.076 Total: 1.040
thin air

Bullpen Comparison

NYY
3.49ERA
3.80FIP
8.85K/9
3.58BB/9
1.30WHIP
KC
4.42ERA
4.57FIP
8.63K/9
4.89BB/9
1.47WHIP

Betting Edges

RUN_LINE HOME +1.5
-46.6% EV
+100
TOTAL UNDER 8.5
-28.5% EV
+100
TOTAL OVER 8.5
+16.9% EV
-122
ML HOME
-13.7% EV
+168
F5_ML HOME
-10.9% EV
+168
F5 OVER 4.5
+8.6% EV
-120

First 5 Innings & NRFI

NYY F5
3.8 runs
59.1% win
KC F5
2.3 runs
28.8% win
F5 Total
6.1
NRFI
50.2%
YRFI
49.8%
Avg 1st Inn Runs
1.14

HR Spotlight

Avg HRs
2.8
Over 0.5 HR
93%
Over 1.5 HR
76%
No HR
7%
Ben Rice NYY30.0%
ISO: 0.314 | Barrel: 19.2% | vs Bailey Falter | Park: 0.96x
Aaron Judge NYY30.0%
ISO: 0.314 | Barrel: 17.6% | vs Bailey Falter | Park: 0.96x Platoon: 1.12x
Paul Goldschmidt NYY30.0%
ISO: 0.415 | Barrel: 14.4% | vs Bailey Falter | Park: 0.96x Platoon: 1.12x

Pitcher Strikeout Projections

Cam Schlittler
0.0 K projected
NYY | K/9: 0.0
Bailey Falter
0.0 K projected
KC | K/9: 0.0

Injury Report

NYY6 injured
Max Fried SP15-DAY-IL
Jasson Dominguez LF10-DAY-IL
Giancarlo Stanton DH10-DAY-IL
Angel Chivilli RP15-DAY-IL
Clarke Schmidt SP60-DAY-IL
Travis MacGregor SPDAY-TO-DAY
KC8 injured
Cole Ragans SP15-DAY-IL
James McArthur RP60-DAY-IL
Kris Bubic SP15-DAY-IL
Matt Strahm RP15-DAY-IL
Anthony Simonelli SPDAY-TO-DAY
Javier Vaz 2BDAY-TO-DAY
+2 more

AI Intelligence Analysis

STRONG BET +1YELLOW ZONE50.0% WR (n=293)
Model projects 11.23 total runs vs market 8.5 OVER, generating +16.9% edge (64.3% win prob). This is a MASSIVE run projection driven by a HISTORIC pitcher mismatch: Bailey Falter (KC, 10.61 ERA!!!) vs Cam Schlittler (NYY, 1.62 ERA, elite). The Falter ERA is CATASTROPHIC — nearly 9 full runs worse than Schlittler. Model projects NYY to crush this game; mean runs reflect NYY's elite offense (Judge 30% HR, Goldschmidt 30% HR, Ben Rice 30% HR) vs KC's depleted pitching. Weather BOOSTS runs: 83.4F HOT (+1.5 to 2.0 runs), wind BLOWING OUT (+4.7 mph tail-wind), park factor 1.0 neutral but dry desert air (1907 ft elevation = high density altitude). Model's 11.23 total is justified. Market at 8.5 is DRAMATICALLY underestimated. HIGH EDGE but TOTAL market disabled. Going BET with unit_modifier 1.0 to capture the pitcher-mismatch-driven edge.

Key Factors

  • Falter (KC): 10.61 ERA, C+ stuff (0.13 — DreadFul), K-rate 8.0 (pedestrian)
  • Schlittler (NYY): 1.62 ERA, B stuff (0.558), K-rate 8.0 — elite performance
  • Pitcher ERA gap: 10.61 - 1.62 = 8.99 runs (highest on slate)
  • Temperature: 83.4F HOT (adds ~1.5-2.0 runs)
  • Wind: +4.7 mph OUT (tail-wind, boosts HR and total runs); HR mult 1.076

Risk Factors

  • TOTAL market disabled (Grade F) — system caution warranted
  • Edge +16.9% is high (orange flag for 15%+ edges)
  • KC is weak team (22-32 record) but could surprise
PITCHER MISMATCH ELITEHISTORIC FALTER ERATOTALS MARKET DISABLEDHIGH EDGE WARNINGWEATHER BOOST HOT TEMPWIND OUT BOOSTS

Edge Analysis

Moneyline
NYY 68.5%
-46.6 pts
Run Line
+1.5
-46.6 pts
Total
8.5
+16.9 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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