Matchup · Wednesday, April 22, 2026

Minnesota Twins
at New York Mets

7:10 PM ET · 4:10 PM PTCiti Field, Flushingopen roof

The Headline

Ryan Kreidler enters this game with a 13.5% model-estimated probability of homering at Citi Field, the strongest HR spot on the board. Below: full lineups for both teams, ranked by expected HR output, alongside detailed profiles of both probable starters.

Park Factors

LHB HR factor95

RHB HR factor96

Probable Starters

Away Starter · LHP

Connor Prielipp

HR Vulnerability—

Contact Quality Allowed—

ERA—

WHIP—

IP—

HR/9—

K/9—

xwOBA—

Barrel%undefined%

Hard-hit%undefined%

Home Starter · RHP

Clay Holmes

HR VulnerabilityElite

Contact Quality AllowedAbove average

ERA1.96

WHIP1.09

IP23.0

HR/90.80

K/96.3

xwOBA0.318

Barrel%6.0%

Hard-hit%43.3%

The Lineups

Each batter's probability of homering in the game, ranked.

High

Medium

Low confidence

Away Lineup

Minnesota Twins

vs Clay Holmes

Ryan Kreidler

RHB·2 HR / 18 PA·Brl 18.2%

13.5%

H 64·K 61

Byron Buxton

RHB·4 HR / 95 PA·Brl 13.6%

vs SP: 0-for-5 · .000 · 0 HR · 4 K · 6 PA

13.3%

H 60·K 64

Tristan Gray

LHB·2 HR / 41 PA·Brl 13.0%

12.7%

H 63·K 70

Kody Clemens

LHB·2 HR / 49 PA·Brl 21.7%

12.5%

H 62·K 70

Brooks Lee

SHB·3 HR / 74 PA·Brl 3.8%

vs SP: 0-for-1 · .000 · 0 HR · 0 K · 2 PA

12.3%

H 57·K 55

Ryan Jeffers

RHB·2 HR / 69 PA·Brl 13.6%

11.7%

H 59·K 54

Royce Lewis

RHB·2 HR / 49 PA·Brl 12.5%

11.5%

H 64·K 67

Matt Wallner

LHB·3 HR / 85 PA·Brl 10.5%

vs SP: 1-for-2 · .500 · 0 HR · 0 K · 2 PA

11.4%

H 61·K 69

Josh Bell

SHB·3 HR / 92 PA·Brl 10.2%

vs SP: 1-for-5 · .200 · 0 HR · 1 K · 5 PA

11.3%

H 63·K 50

Trevor Larnach

LHB·1 HR / 51 PA·Brl 11.1%

vs SP: 1-for-1 · 1.000 · 0 HR · 0 K · 2 PA

11.0%

H 64·K 53

Austin Martin

RHB·1 HR / 62 PA·Brl 5.6%

10.9%

H 68·K 53

James Outman

LHB·0 HR / 24 PA·Brl 0.0%

vs SP: 0-for-1 · .000 · 0 HR · 1 K · 1 PA

10.8%

H 62·K 60

Home Lineup

New York Mets

vs Connor Prielipp

Francisco Alvarez

RHB·4 HR / 72 PA·Brl 18.2%

—

Luis Robert Jr.

RHB·2 HR / 86 PA·Brl 3.7%

—

Mark Vientos

RHB·2 HR / 60 PA·Brl 4.7%

—

Francisco Lindor

SHB·2 HR / 103 PA·Brl 8.6%

—

MJ Melendez

LHB·1 HR / 18 PA·Brl 33.3%

—

Marcus Semien

RHB·1 HR / 90 PA·Brl 6.5%

—

Tyrone Taylor

RHB·1 HR / 32 PA·Brl 8.0%

—

Bo Bichette

RHB·1 HR / 102 PA·Brl 2.9%

—

Carson Benge

LHB·1 HR / 73 PA·Brl 4.4%

—

Luis Torrens

RHB·0 HR / 25 PA·Brl 0.0%

—

Tommy Pham

RHB·0 HR / 8 PA·Brl 0.0%

—

Brett Baty

LHB·0 HR / 70 PA·Brl 8.7%

—

A Note on These Numbers

HR probabilities come from our calibrated probability model combining season stats, recent form, Statcast quality, handedness splits, and park effects. Even the top pick on any given day misses 75-80% of the time — home runs are genuinely rare events. See the calibration page for how accurate these numbers have been historically.