Alexander Padilla

P DSL Tigers 1

Age 18 RHP ROK peak 0.1 · 2028

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	17	ROKDSL Tigers 1	6	6	13	6.39	3.02	27.0%	17.5%	—	K 18.3% · BB 21.8% · FIP 4.32
2027PROJ	18	MLBDET	1	1	8	5.28	5.28	22.4%	16.4%	-0.0
2028PROJ49% MLB	19	MLBDET	2	2	10	5.03	4.93	22.9%	14.2%	-0.0

Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0 WAR median (P10 0 / P90 0, comp-based) · star 0% · didn't stick 98%

CompsJustin Lange (age 19) · Edgar Leon (age 18) · Omar Gonzalez (age 18)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 133125vR 117

ERA5.28

FIP5.28

K%22.4%

BB%16.4%

K-BB%6.0%

Proj IP8

Value2027 · WAR

Runs saved vs league avg · 8 IP

Grades · Contract

Scouting Grades

K†5555

Contract

No contract data on file. Pre-MLB players and minor-league free agents do not yet have salary projections — entries are added at first 40-man roster placement.

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral

Methodology▸ how WAR & MLE are computed

Stats are park-neutral MLB equivalents. The "TEAM" column shows current org affiliation only — we do NOT project at that team's park.
Rates (K%, BB%, HR-BF) are park-stripped; MiLB stat lines are translated to their MLB-equivalent via per-level MLE factors.
WAR is computed from projected runs prevented vs a replacement pitcher (the marginal arm a team would call up if this pitcher were unavailable) — calibrated to industry-standard fWAR.

Year	Age	Lvl	Team	G	GS	IP	BF	K	BB	HR	GS%	IP/G	K%	BB%	K-BB%	HR%	ERA	FIP	WAR
▸ Career — actual stats, one row per year (as recorded, no adjustments)
▸ Career — adjusted (each season translated to a park/league-neutral MLB-equivalent line; levels combined per year)
▸ Model inputs — neutral MLE (past 3 seasons + 2027 so far)
2026	17	ROK MLE	DSL Tigers 1	6	6	13	63	17	11	0	100%	2.1	18.3%	21.8%	-3.5%	0.0%	6.39	4.32	—
2026	17	ROK MLE	DSL Tigers 1	6	6	13	63	17	11	0	100%	2.1	18.3%	21.8%	-3.5%	0.0%	6.39	4.32	—
2026	17	ROK RAW	DSL Tigers 1	6	6	13	63	17	11	0	100%	2.1	27.0%	17.5%	9.5%	0.0%	6.39	3.02	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	18	MLB	DET	1	1	8	34	8	6	1	100%	8.0	22.4%	16.4%	6.0%	2.9%	5.28	5.28	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	19	MLB MLE	DET	4	4	20	84	19	12	2	100%	5.0	22.9%	14.2%	8.7%	2.9%	5.03	4.93	-0.0
2028	19	MLB CTX	DET	2	2	10	42	10	6	1	100%	5.0	22.9%	14.2%	8.7%	2.9%	5.03	4.93	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		2	2	10	42	9	6	1	100%	4.9	22.9%	14.2%	8.7%	2.9%	5.03	4.55	+0.0
/ 200 IP	—	RAW		46	46	200	844	183	122	20	100%	4.3	22.9%	14.2%	8.7%	2.9%	5.03	4.55	+0.8
Career	—	MLE		6	6	13	63	12	14	0	100%	2.1	18.3%	21.8%	-3.5%	0.0%	6.39	4.32	-0.0
/ 200 IP	—	MLE		95	95	200	995	183	217	0	100%	2.1	18.3%	21.8%	-3.5%	0.0%	6.39	4.32	-0.1

Career Path Comps

What happened to similar pitchers from this age · Y-axis: ERA+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

			Profile at Match Age					Next 3 Yrs				Career
Comp	Age	Role	FIP	K%	BB%	HR/BF	BABIP	FIP	K%	K-BB%	IP	ΔFIP	Low FIP	IP	Match
Alexander Padilla (OGILVIE)	—	—	5.28	22.4%	16.4%	2.9%	—	4.93	22.9%	8.7%	20	-0.35	—	—	—
Justin Lange R 2021 · 4.55 FIP	19	SP	4.55	19.3%	18.4%	1.4%	.298	4.81	23.4%	3.7%	122	+0.26	4.55	144	82
Edgar Leon R 2023 · 4.36 FIP	18	SP	4.36	18.2%	15.4%	1.5%	.268	4.93	17.6%	-3.0%	83	+0.57	4.13	144	79
Omar Gonzalez R 2023 · 5.10 FIP	18	SP	5.10	24.3%	24.6%	1.7%	.375	5.69	15.1%	-2.0%	106	+0.59	2.25	137	77
Jharold Clemente R 2023 · 4.97 FIP	20	SP	4.97	17.5%	13.6%	3.0%	.258	5.11	13.3%	4.3%	92	+0.14	4.09	116	77
Alexander Almonte R 2024 · 5.69 FIP	17	SP	5.69	16.2%	13.8%	4.0%	.250	4.82	12.6%	-2.8%	75	-0.87	4.27	100	76
Mick Abel R 2021 · 4.95 FIP	19	SP	4.95	25.8%	16.9%	3.5%	.242	4.86	21.1%	7.6%	326	-0.09	2.24	528	76
Gio Arriera R 2017 · 5.41 FIP	19	SP	5.41	15.1%	13.9%	3.3%	.333	4.34	15.5%	2.0%	79	-1.07	4.34	185	76
Eddy Peralta R 2023 · 4.65 FIP	20	SP-	4.65	22.0%	19.8%	1.6%	.342	3.96	21.0%	1.7%	86	-0.69	3.73	117	76
Dylan Lesko R 2023 · 4.34 FIP	19	SP	4.34	26.8%	18.3%	2.2%	.333	6.78	17.8%	-7.7%	124	+2.44	4.34	152	75
Biembenido Brito R 2022 · 4.64 FIP	19	SP	4.64	24.7%	18.5%	2.3%	.301	5.37	18.7%	-1.3%	91	+0.73	3.58	130	74
Waylin Santana R 2021 · 5.12 FIP	18	SP	5.12	15.1%	15.0%	2.5%	.377	6.18	13.5%	1.0%	94	+1.06	4.88	117	74
Grayson Long R 2015 · 4.38 FIP	21	SP	4.38	17.6%	14.7%	1.7%	.346	3.91	19.0%	9.9%	192	-0.47	3.46	211	74
Randry De Leon R 2023 · 6.45 FIP	18	SP-	6.45	17.7%	20.2%	4.2%	.308	4.83	18.4%	3.3%	123	-1.62	4.37	153	74
Carson Fulmer R 2015 · 4.15 FIP	21	SP	4.15	21.4%	11.5%	2.5%	.259	4.96	17.1%	4.0%	364	+0.81	3.88	910	74
Michell Miliano R 2018 · 4.93 FIP	18	SP	4.93	16.3%	16.7%	2.0%	.379	5.90	24.3%	-1.8%	71	+0.97	4.42	205	73
Jared Kelley R 2021 · 5.33 FIP	19	SP	5.33	16.5%	23.2%	1.2%	.312	5.14	16.5%	-1.2%	174	-0.19	4.25	250	73
Victor Mederos R 2022 · 4.69 FIP	21	SP	4.69	15.6%	14.0%	2.1%	.286	5.19	16.4%	5.7%	301	+0.50	3.73	394	72
Ryan Harbin R 2021 · 4.79 FIP	19	SP	4.79	15.8%	15.4%	2.0%	.391	4.57	21.8%	6.2%	107	-0.22	3.82	185	72
Tanner McDougal R 2023 · 4.96 FIP	20	SP	4.96	19.7%	16.9%	2.5%	.285	4.81	21.3%	8.0%	253	-0.15	3.82	323	71
Moises Castillo R 2024 · 4.58 FIP	19	SP-	4.58	18.1%	11.7%	2.8%	.269	4.06	19.4%	4.9%	67	-0.52	3.76	104	71