Vol. I · Issue 24
Friday, April 24, 2026

The Dinger Almanac
··· Baseball Statistics & Analysis ···


Matchup · Friday, April 24, 2026

Seattle Mariners
at St. Louis Cardinals

8:15 PM ET · 5:15 PM PTBusch Stadium, St. Louisopen roof

The Headline

Jordan Walker enters this game with a 15.7% 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

George Kirby

HR VulnerabilityAverage
Contact Quality AllowedElite suppression
ERA2.97
WHIP1.05
IP33.1
HR/91.10
K/97.3
xwOBA0.274
Barrel%5.4%
Hard-hit%47.3%
Home Starter · RHP

Andre Pallante

HR VulnerabilityGood
Contact Quality AllowedLeague average
ERA4.05
WHIP1.45
IP20.0
HR/90.90
K/95.4
xwOBA0.363
Barrel%9.1%
Hard-hit%43.9%

The Lineups

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


Away Lineup

Seattle Mariners

Cal Raleigh
SHB·5 HR / 114 PA·Brl 13.0%
14.3%
H 61·K 55
Luke Raley
LHB·5 HR / 79 PA·Brl 20.9%
13.5%
H 66·K 69
Dominic Canzone
LHB·3 HR / 60 PA·Brl 18.6%
vs SP: 0-for-1 · .000 · 0 HR · 0 K · 1 PA
12.4%
H 65·K 61
Rob Refsnyder
RHB·1 HR / 32 PA·Brl 9.1%
vs SP: 2-for-5 · .400 · 0 HR · 0 K · 6 PA
11.8%
H 62·K 60
Brendan Donovan
LHB·0 HR / 0 PA
11.8%
H 64·K 60
Randy Arozarena
RHB·2 HR / 109 PA·Brl 8.1%
vs SP: 1-for-1 · 1.000 · 0 HR · 0 K · 1 PA
11.4%
H 69·K 62
Will Wilson
RHB·0 HR / 0 PA
11.4%
H 64·K 60
Connor Joe
RHB·0 HR / 9 PA·Brl 20.0%
vs SP: 1-for-9 · .111 · 0 HR · 3 K · 10 PA
11.0%
H 64·K 60
Josh Naylor
LHB·2 HR / 104 PA·Brl 5.2%
vs SP: 1-for-6 · .167 · 0 HR · 0 K · 8 PA
11.0%
H 69·K 56
J.P. Crawford
LHB·1 HR / 74 PA·Brl 10.9%
10.5%
H 63·K 51
Mitch Garver
RHB·0 HR / 29 PA·Brl 6.7%
10.3%
H 63·K 60
Julio Rodríguez
RHB·1 HR / 112 PA·Brl 5.6%
10.1%
H 70·K 58
Home Lineup

St. Louis Cardinals

Jordan Walker
RHB·8 HR / 98 PA·Brl 22.4%
vs SP: 1-for-2 · .500 · 0 HR · 1 K · 2 PA
15.7%
H 62·K 71
Iván Herrera
RHB·3 HR / 111 PA·Brl 9.7%
vs SP: 0-for-3 · .000 · 0 HR · 0 K · 3 PA
12.6%
H 65·K 53
Alec Burleson
LHB·3 HR / 103 PA·Brl 11.5%
vs SP: 2-for-5 · .400 · 0 HR · 0 K · 5 PA
12.1%
H 66·K 53
Nathan Church
LHB·2 HR / 61 PA·Brl 5.1%
11.9%
H 66·K 63
Ramón Urías
RHB·2 HR / 51 PA·Brl 11.8%
vs SP: 1-for-4 · .250 · 0 HR · 1 K · 5 PA
11.7%
H 62·K 54
José Fermín
RHB·1 HR / 29 PA·Brl 0.0%
vs SP: 1-for-2 · .500 · 0 HR · 0 K · 2 PA
11.5%
H 63·K 61
JJ Wetherholt
LHB·3 HR / 110 PA·Brl 6.1%
11.4%
H 58·K 60
Nolan Gorman
LHB·3 HR / 88 PA·Brl 3.8%
vs SP: 1-for-4 · .250 · 0 HR · 3 K · 4 PA
11.2%
H 60·K 68
Pedro Pagés
RHB·1 HR / 55 PA·Brl 5.1%
vs SP: 1-for-2 · .500 · 0 HR · 0 K · 2 PA
10.9%
H 61·K 63
Yohel Pozo
RHB·0 HR / 16 PA·Brl 0.0%
10.7%
H 63·K 61
Masyn Winn
RHB·1 HR / 82 PA·Brl 3.7%
10.2%
H 69·K 60
Thomas Saggese
RHB·0 HR / 54 PA·Brl 3.0%
vs SP: 1-for-1 · 1.000 · 0 HR · 0 K · 2 PA
9.6%
H 57·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.