Matchup · Friday, April 17, 2026
Texas Rangers
at Seattle Mariners
9:40 PM ET · 6:40 PM PTT-Mobile Park, Seattleretractable roof
The Headline
Corey Seager enters this game with a 15.4% 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 · RHP
Jacob deGrom
HR VulnerabilityVulnerable
Contact Quality AllowedGetting barreled
ERA2.41
WHIP1.07
IP18.2
HR/91.50
K/911.6
xwOBA0.263
Barrel%14.3%
Hard-hit%45.7%
Home Starter · RHP
Logan Gilbert
HR VulnerabilityGood
Contact Quality AllowedLeague average
ERA4.28
WHIP1.21
IP27.1
HR/91.00
K/99.9
xwOBA0.253
Barrel%8.1%
Hard-hit%45.2%
The Lineups
Each batter's probability of homering in the game, ranked.
High
Medium
Low confidence
Away Lineup
Texas Rangers
Corey Seager
LHB·5 HR / 80 PA·Brl 17.4%
vs SP: 10-for-31 · .323 · 1 HR · 4 K · 34 PA
15.4%
Jake Burger
RHB·5 HR / 81 PA·Brl 13.2%
vs SP: 3-for-8 · .375 · 0 HR · 2 K · 9 PA
14.1%
Brandon Nimmo
LHB·4 HR / 88 PA·Brl 11.9%
vs SP: 1-for-8 · .125 · 1 HR · 2 K · 9 PA
13.9%
Evan Carter
LHB·2 HR / 67 PA·Brl 10.3%
vs SP: 1-for-14 · .071 · 0 HR · 7 K · 14 PA
11.7%
Wyatt Langford
RHB·1 HR / 70 PA·Brl 6.0%
vs SP: 3-for-13 · .231 · 0 HR · 5 K · 15 PA
11.4%
Joc Pederson
LHB·1 HR / 50 PA·Brl 0.0%
vs SP: 4-for-14 · .286 · 0 HR · 5 K · 15 PA
10.7%
Josh Jung
RHB·1 HR / 64 PA·Brl 0.0%
vs SP: 1-for-16 · .063 · 0 HR · 3 K · 17 PA
9.9%
Danny Jansen
RHB·1 HR / 49 PA·Brl 3.4%
vs SP: 0-for-2 · .000 · 0 HR · 1 K · 2 PA
9.9%
Josh Smith
LHB·0 HR / 66 PA·Brl 6.7%
vs SP: 4-for-22 · .182 · 0 HR · 3 K · 24 PA
8.7%
Andrew McCutchen
RHB·1 HR / 30 PA·Brl 20.0%
vs SP: 0-for-2 · .000 · 0 HR · 1 K · 3 PA
—
Ezequiel Duran
RHB·1 HR / 44 PA·Brl 3.4%
vs SP: 1-for-11 · .091 · 0 HR · 5 K · 11 PA
—
Kyle Higashioka
RHB·1 HR / 29 PA·Brl 11.8%
—
Home Lineup
Seattle Mariners
vs Jacob deGrom
Brendan Donovan
LHB·3 HR / 71 PA·Brl 4.7%
vs SP: 0-for-5 · .000 · 0 HR · 1 K · 5 PA
13.3%
Cal Raleigh
SHB·2 HR / 89 PA·Brl 10.2%
vs SP: 1-for-10 · .100 · 1 HR · 4 K · 13 PA
13.2%
Luke Raley
LHB·4 HR / 67 PA·Brl 21.6%
vs SP: 1-for-5 · .200 · 0 HR · 1 K · 7 PA
12.4%
Josh Naylor
LHB·2 HR / 85 PA·Brl 6.6%
vs SP: 0-for-5 · .000 · 0 HR · 1 K · 5 PA
11.7%
Julio Rodríguez
RHB·1 HR / 89 PA·Brl 7.7%
vs SP: 5-for-13 · .385 · 1 HR · 3 K · 14 PA
11.2%
Randy Arozarena
RHB·1 HR / 87 PA·Brl 7.0%
vs SP: 0-for-11 · .000 · 0 HR · 3 K · 13 PA
10.8%
Dominic Canzone
LHB·2 HR / 48 PA·Brl 15.2%
vs SP: 0-for-4 · .000 · 0 HR · 2 K · 5 PA
10.7%
Cole Young
LHB·2 HR / 79 PA·Brl 8.2%
vs SP: 0-for-4 · .000 · 0 HR · 2 K · 4 PA
9.9%
J.P. Crawford
LHB·0 HR / 48 PA·Brl 8.0%
vs SP: 3-for-10 · .300 · 1 HR · 3 K · 11 PA
9.3%
Mitch Garver
RHB·0 HR / 17 PA·Brl 0.0%
—
Rob Refsnyder
RHB·0 HR / 19 PA·Brl 0.0%
—
Leo Rivas
SHB·0 HR / 51 PA·Brl 0.0%
—
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.