Matchup · Friday, April 24, 2026
Los Angeles Angels
at Kansas City Royals
7:40 PM ET · 4:40 PM PTKauffman Stadium, Kansas Cityopen roof
The Headline
Mike Trout enters this game with a 17.6% model-estimated probability of homering at Kauffman 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 factor97
RHB HR factor98
Probable Starters
Away Starter · LHP
Yusei Kikuchi
HR VulnerabilityAverage
Contact Quality AllowedLeague average
ERA5.63
WHIP1.63
IP24.0
HR/91.10
K/910.1
xwOBA0.353
Barrel%8.3%
Hard-hit%44.4%
Home Starter · LHP
Noah Cameron
HR VulnerabilityVery HR-prone
Contact Quality AllowedGetting barreled
ERA5.40
WHIP1.45
IP20.0
HR/92.30
K/97.7
xwOBA0.403
Barrel%15.2%
Hard-hit%48.5%
The Lineups
Each batter's probability of homering in the game, ranked.
High
Medium
Low confidence
Away Lineup
Los Angeles Angels
vs Noah Cameron
Mike Trout
RHB·8 HR / 115 PA·Brl 24.6%
vs SP: 0-for-1 · .000 · 0 HR · 0 K · 3 PA
17.6%
H 65·K 55
Jorge Soler
RHB·5 HR / 95 PA·Brl 12.2%
15.1%
H 60·K 69
Oswald Peraza
RHB·4 HR / 76 PA·Brl 9.6%
vs SP: 0-for-1 · .000 · 0 HR · 1 K · 2 PA
14.3%
H 71·K 55
Yoán Moncada
SHB·3 HR / 85 PA·Brl 7.5%
13.3%
H 62·K 72
Josh Lowe
LHB·3 HR / 72 PA·Brl 6.7%
13.1%
H 62·K 61
Zach Neto
RHB·5 HR / 121 PA·Brl 11.9%
vs SP: 1-for-3 · .333 · 0 HR · 2 K · 3 PA
12.9%
H 61·K 72
Jo Adell
RHB·3 HR / 112 PA·Brl 4.8%
vs SP: 0-for-2 · .000 · 0 HR · 0 K · 3 PA
12.9%
H 60·K 57
Logan O'Hoppe
RHB·1 HR / 86 PA·Brl 9.8%
vs SP: 1-for-2 · .500 · 0 HR · 0 K · 2 PA
11.8%
H 61·K 69
Travis d'Arnaud
RHB·0 HR / 18 PA·Brl 20.0%
11.7%
H 59·K 62
Adam Frazier
LHB·1 HR / 47 PA·Brl 3.8%
11.5%
H 62·K 69
Nolan Schanuel
LHB·3 HR / 104 PA·Brl 2.6%
11.3%
H 66·K 55
Bryce Teodosio
RHB·0 HR / 27 PA·Brl 6.7%
vs SP: 0-for-2 · .000 · 0 HR · 1 K · 2 PA
11.1%
H 60·K 62
Home Lineup
Kansas City Royals
Carter Jensen
LHB·6 HR / 79 PA·Brl 14.6%
16.3%
H 70·K 66
Vinnie Pasquantino
LHB·3 HR / 109 PA·Brl 8.1%
vs SP: 1-for-5 · .200 · 0 HR · 3 K · 5 PA
13.0%
H 56·K 65
Tyler Tolbert
RHB·0 HR / 0 PA
vs SP: 0-for-2 · .000 · 0 HR · 1 K · 2 PA
12.1%
H 64·K 65
Jonathan India
RHB·0 HR / 0 PA
vs SP: 0-for-2 · .000 · 0 HR · 0 K · 2 PA
12.0%
H 64·K 65
Salvador Perez
RHB·3 HR / 99 PA·Brl 9.6%
vs SP: 4-for-17 · .235 · 0 HR · 6 K · 17 PA
11.8%
H 58·K 71
Elias Díaz
RHB·0 HR / 4 PA·Brl 0.0%
vs SP: 2-for-10 · .200 · 0 HR · 3 K · 10 PA
11.7%
H 64·K 65
Michael Massey
LHB·1 HR / 35 PA·Brl 8.0%
vs SP: 0-for-2 · .000 · 0 HR · 0 K · 2 PA
11.6%
H 66·K 68
Kyle Isbel
LHB·3 HR / 71 PA·Brl 6.1%
vs SP: 1-for-4 · .250 · 0 HR · 3 K · 4 PA
11.4%
H 63·K 70
Jac Caglianone
LHB·1 HR / 83 PA·Brl 16.0%
vs SP: 0-for-1 · .000 · 0 HR · 0 K · 2 PA
11.3%
H 62·K 74
Nick Loftin
RHB·0 HR / 16 PA·Brl 8.3%
vs SP: 0-for-5 · .000 · 0 HR · 2 K · 5 PA
11.2%
H 64·K 65
Starling Marte
RHB·0 HR / 24 PA·Brl 12.5%
vs SP: 1-for-4 · .250 · 0 HR · 0 K · 4 PA
11.0%
H 64·K 65
Maikel Garcia
RHB·2 HR / 110 PA·Brl 8.9%
vs SP: 1-for-10 · .100 · 1 HR · 2 K · 10 PA
10.8%
H 65·K 66
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.