Matchup · Saturday, April 25, 2026
Seattle Mariners
at St. Louis Cardinals
2:15 PM ET · 11:15 AM PTBusch Stadium, St. Louisopen roof
The Headline
Cal Raleigh enters this game with a 15.2% model-estimated probability of homering at Busch Stadium, 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 factor94
Probable Starters
Away Starter · RHP
Bryan Woo
HR VulnerabilityElite
Contact Quality AllowedElite suppression
ERA2.25
WHIP0.88
IP32.0
HR/90.00
K/97.3
xwOBA0.253
Barrel%5.6%
Hard-hit%43.8%
Home Starter · LHP
Matthew Liberatore
HR VulnerabilityVery HR-prone
Contact Quality AllowedAbove average
ERA3.67
WHIP1.41
IP27.0
HR/91.70
K/95.3
xwOBA0.342
Barrel%7.7%
Hard-hit%40.7%
The Lineups
Each batter's probability of homering in the game, ranked.
High
Medium
Low confidence
Away Lineup
Seattle Mariners
Cal Raleigh
SHB·5 HR / 118 PA·Brl 13.0%
vs SP: 0-for-3 · .000 · 0 HR · 0 K · 3 PA
15.2%
H 67·K 56
Luke Raley
LHB·5 HR / 81 PA·Brl 20.9%
vs SP: 0-for-1 · .000 · 0 HR · 0 K · 1 PA
14.3%
H 66·K 68
Dominic Canzone
LHB·3 HR / 64 PA·Brl 18.6%
13.0%
H 66·K 59
Josh Naylor
LHB·3 HR / 108 PA·Brl 5.2%
vs SP: 2-for-8 · .250 · 1 HR · 0 K · 8 PA
12.6%
H 69·K 59
Rob Refsnyder
RHB·1 HR / 34 PA·Brl 9.1%
vs SP: 1-for-2 · .500 · 0 HR · 1 K · 2 PA
12.5%
H 63·K 58
Brendan Donovan
LHB·0 HR / 0 PA
12.4%
H 65·K 59
Will Wilson
RHB·0 HR / 0 PA
12.1%
H 65·K 59
Randy Arozarena
RHB·2 HR / 113 PA·Brl 8.1%
vs SP: 2-for-5 · .400 · 1 HR · 0 K · 6 PA
12.1%
H 69·K 61
Connor Joe
RHB·0 HR / 9 PA·Brl 20.0%
vs SP: 1-for-2 · .500 · 0 HR · 0 K · 3 PA
11.7%
H 64·K 59
J.P. Crawford
LHB·1 HR / 78 PA·Brl 10.9%
vs SP: 2-for-2 · 1.000 · 0 HR · 0 K · 3 PA
11.1%
H 60·K 51
Mitch Garver
RHB·0 HR / 29 PA·Brl 6.7%
vs SP: 1-for-2 · .500 · 0 HR · 0 K · 4 PA
10.9%
H 64·K 59
Julio Rodríguez
RHB·1 HR / 116 PA·Brl 5.6%
vs SP: 0-for-2 · .000 · 0 HR · 0 K · 2 PA
10.7%
H 70·K 57
Home Lineup
St. Louis Cardinals
vs Bryan Woo
Jordan Walker
RHB·8 HR / 102 PA·Brl 22.4%
vs SP: 0-for-2 · .000 · 0 HR · 1 K · 2 PA
14.5%
H 61·K 71
Iván Herrera
RHB·3 HR / 115 PA·Brl 9.7%
vs SP: 1-for-3 · .333 · 0 HR · 0 K · 3 PA
11.6%
H 65·K 53
Alec Burleson
LHB·3 HR / 107 PA·Brl 11.5%
vs SP: 1-for-3 · .333 · 1 HR · 1 K · 3 PA
11.1%
H 61·K 55
Nathan Church
LHB·2 HR / 65 PA·Brl 5.1%
10.9%
H 65·K 63
Ramón Urías
RHB·2 HR / 55 PA·Brl 11.8%
10.7%
H 61·K 52
José Fermín
RHB·1 HR / 32 PA·Brl 0.0%
10.5%
H 62·K 61
JJ Wetherholt
LHB·3 HR / 114 PA·Brl 6.1%
10.5%
H 57·K 59
Nolan Gorman
LHB·3 HR / 92 PA·Brl 3.8%
vs SP: 0-for-2 · .000 · 0 HR · 2 K · 2 PA
10.3%
H 60·K 68
Pedro Pagés
RHB·1 HR / 55 PA·Brl 5.1%
10.1%
H 61·K 63
Yohel Pozo
RHB·0 HR / 16 PA·Brl 0.0%
9.8%
H 62·K 61
Masyn Winn
RHB·1 HR / 86 PA·Brl 3.7%
vs SP: 0-for-2 · .000 · 0 HR · 1 K · 2 PA
9.3%
H 69·K 61
Thomas Saggese
RHB·0 HR / 54 PA·Brl 3.0%
vs SP: 0-for-2 · .000 · 0 HR · 2 K · 2 PA
8.8%
H 56·K 70
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.