Matchup · Sunday, April 19, 2026
Texas Rangers
at Seattle Mariners
4:10 PM EDTT-Mobile Park, Seattleretractable roof
The Headline
Corey Seager enters this game with a 13.4% model-estimated probability of homering at T-Mobile Park, 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 factor92
RHB HR factor89
Probable Starters
Away Starter · LHP
MacKenzie Gore
HR VulnerabilityGood
Contact Quality AllowedLeague average
ERA3.00
WHIP1.10
IP21.0
HR/90.90
K/912.9
xwOBA0.281
Barrel%9.3%
Hard-hit%41.9%
Home Starter · RHP
Bryan Woo
HR VulnerabilityElite
Contact Quality AllowedElite suppression
ERA2.16
WHIP0.92
IP25.0
HR/90.00
K/97.2
xwOBA0.239
Barrel%4.2%
Hard-hit%39.4%
The Lineups
Each batter's probability of homering in the game, ranked.
High
Medium
Low confidence
Away Lineup
Texas Rangers
vs Bryan Woo
Corey Seager
LHB·5 HR / 88 PA·Brl 18.0%
vs SP: 6-for-10 · .600 · 2 HR · 0 K · 15 PA
13.4%
Jake Burger
RHB·5 HR / 89 PA·Brl 12.3%
vs SP: 0-for-8 · .000 · 0 HR · 2 K · 8 PA
12.1%
Brandon Nimmo
LHB·4 HR / 97 PA·Brl 13.1%
vs SP: 3-for-5 · .600 · 0 HR · 0 K · 6 PA
11.7%
Andrew McCutchen
RHB·1 HR / 32 PA·Brl 18.8%
vs SP: 0-for-3 · .000 · 0 HR · 2 K · 3 PA
10.8%
Evan Carter
LHB·2 HR / 75 PA·Brl 9.3%
vs SP: 1-for-7 · .143 · 0 HR · 2 K · 7 PA
10.7%
Kyle Higashioka
RHB·1 HR / 34 PA·Brl 11.8%
vs SP: 0-for-6 · .000 · 0 HR · 3 K · 6 PA
10.4%
Joc Pederson
LHB·1 HR / 54 PA·Brl 0.0%
vs SP: 0-for-10 · .000 · 0 HR · 2 K · 10 PA
10.1%
Sam Haggerty
SHB·0 HR / 13 PA·Brl 0.0%
9.9%
Danny Jansen
RHB·1 HR / 52 PA·Brl 6.3%
vs SP: 1-for-3 · .333 · 0 HR · 1 K · 4 PA
9.9%
Wyatt Langford
RHB·1 HR / 78 PA·Brl 5.7%
vs SP: 1-for-8 · .125 · 1 HR · 4 K · 9 PA
9.8%
Josh Jung
RHB·2 HR / 72 PA·Brl 0.0%
vs SP: 3-for-13 · .231 · 0 HR · 5 K · 13 PA
9.6%
Ezequiel Duran
RHB·1 HR / 49 PA·Brl 3.4%
vs SP: 3-for-6 · .500 · 0 HR · 1 K · 6 PA
9.6%
Home Lineup
Seattle Mariners
Luke Raley
LHB·5 HR / 72 PA·Brl 21.1%
12.3%
Brendan Donovan
LHB·3 HR / 71 PA·Brl 4.4%
vs SP: 3-for-15 · .200 · 0 HR · 5 K · 16 PA
11.4%
Cal Raleigh
SHB·2 HR / 96 PA·Brl 9.6%
vs SP: 1-for-7 · .143 · 0 HR · 2 K · 8 PA
11.2%
Dominic Canzone
LHB·2 HR / 53 PA·Brl 14.3%
11.2%
Josh Naylor
LHB·2 HR / 91 PA·Brl 6.3%
11.1%
Connor Joe
RHB·0 HR / 5 PA·Brl 33.3%
vs SP: 1-for-8 · .125 · 0 HR · 2 K · 10 PA
10.7%
Cole Young
LHB·2 HR / 86 PA·Brl 7.8%
vs SP: 0-for-1 · .000 · 0 HR · 0 K · 1 PA
10.5%
Rob Refsnyder
RHB·0 HR / 21 PA·Brl 0.0%
vs SP: 1-for-7 · .143 · 0 HR · 3 K · 8 PA
10.3%
Mitch Garver
RHB·0 HR / 19 PA·Brl 0.0%
vs SP: 1-for-5 · .200 · 0 HR · 1 K · 5 PA
10.2%
Randy Arozarena
RHB·1 HR / 93 PA·Brl 6.7%
vs SP: 0-for-5 · .000 · 0 HR · 4 K · 5 PA
10.2%
Julio Rodríguez
RHB·1 HR / 95 PA·Brl 7.4%
vs SP: 0-for-7 · .000 · 0 HR · 2 K · 8 PA
9.9%
J.P. Crawford
LHB·0 HR / 56 PA·Brl 7.1%
vs SP: 2-for-8 · .250 · 1 HR · 3 K · 8 PA
9.6%
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.