Abelardo Medrano

P DSL Tigers 2

Age 21 RHP 6'2" / 180 lbs ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	19	ROKDSL Tigers 1	15	0	15	11.15	10.47	8.0%	28.7%	—	K 5.5% · BB 35.9% · FIP 8.29
2026	20	ROKDSL Tigers 2	18	1	25	7.30	4.88	21.5%	15.7%	—	K 14.6% · BB 19.6% · FIP 6.26
2027PROJ	21	MLBDET	12	0	13	6.06	6.06	18.9%	20.0%	-0.2
2028PROJ49% MLB	22	MLBDET	10	0	11	5.56	5.40	20.6%	16.6%	-0.1

Next 2 projected WAR -0.3Projected 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 100%

CompsJackson Rose (age 22) · Michael Perez (age 21) · Hudson Leach (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 148140vR 132

ERA6.06

FIP6.06

K%18.9%

BB%20.0%

K-BB%-1.1%

Proj IP13

Value2027 · WAR

Runs saved vs league avg · 13 IP

Grades · Contract

Scouting Grades

K†4550

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)
2025	19	ROK MLE	DSL Tigers 1	15	0	15	87	7	25	4	0%	1.0	5.5%	35.9%	-30.4%	2.0%	11.15	8.29	—
2025	19	ROK MLE	DSL Tigers 1	15	0	15	87	7	25	4	0%	1.0	5.5%	35.9%	-30.4%	2.0%	11.15	8.29	—
2025	19	ROK RAW	DSL Tigers 1	15	0	15	87	7	25	4	0%	1.0	8.0%	28.7%	-20.7%	4.6%	11.15	10.47	—
2026	20	ROK MLE	DSL Tigers 2	18	1	25	121	26	19	3	6%	1.4	14.6%	19.6%	-5.0%	3.5%	7.30	6.26	—
2026	20	ROK MLE	DSL Tigers 2	18	1	25	121	26	19	3	6%	1.4	14.6%	19.6%	-5.0%	3.5%	7.30	6.26	—
2026	20	ROK RAW	DSL Tigers 2	18	1	25	121	26	19	3	6%	1.4	21.5%	15.7%	5.8%	2.5%	7.30	4.88	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	21	MLB	DET	12	0	13	55	10	11	2	0%	1.1	18.9%	20.0%	-1.1%	3.0%	6.06	6.06	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	22	MLB MLE	DET	22	0	23	98	20	16	3	0%	1.1	20.6%	16.6%	3.9%	2.9%	5.63	5.47	-0.2
2028	22	MLB CTX	DET	10	0	11	46	10	8	1	0%	1.1	20.6%	16.6%	3.9%	2.8%	5.56	5.40	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		11	0	11	48	10	8	1	0%	1.0	20.6%	16.6%	3.9%	2.8%	5.56	5.02	-0.1
/ 200 IP	—	RAW		190	0	200	844	175	140	17	0%	1.1	20.6%	16.6%	3.9%	2.8%	5.56	5.02	-1.1
Career	—	MLE		33	1	40	208	22	55	6	3%	1.2	10.8%	26.4%	-15.7%	2.9%	8.78	7.11	-0.2
/ 200 IP	—	MLE		165	5	200	1040	112	275	30	3%	1.2	10.8%	26.4%	-15.7%	2.9%	8.78	7.11	-2.1

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
Abelardo Medrano (OGILVIE)	—	—	6.06	18.9%	20.0%	3.0%	—	5.47	20.6%	3.9%	23	-0.59	—	—	—
Jackson Rose R 2018 · 5.32 FIP	22	SU	5.32	17.3%	17.2%	2.8%	.267	4.77	23.5%	16.5%	56	-0.55	3.33	147	91
Michael Perez R 2024 · 5.44 FIP	21	SU	5.44	18.3%	16.1%	3.4%	.296	4.65	23.4%	7.7%	132	-0.79	4.38	153	91
Hudson Leach R 2024 · 5.37 FIP	22	SU	5.37	20.5%	20.0%	2.7%	.261	4.54	20.9%	3.1%	71	-0.83	2.77	101	90
Andrew Schultz R 2019 · 5.25 FIP	22	SU	5.25	20.9%	17.8%	3.0%	.345	4.59	23.0%	4.7%	45	-0.66	3.56	176	87
Christian Ruebeck R 2024 · 6.03 FIP	23	SU	6.03	20.6%	24.4%	2.9%	.265	4.57	21.6%	1.9%	70	-1.46	4.35	104	87
Greg Weissert R 2016 · 5.22 FIP	21	SU	5.22	19.4%	19.3%	2.4%	.382	3.80	23.0%	10.3%	126	-1.42	2.57	487	86
Marcus Crescentini R 2015 · 5.80 FIP	22	SU	5.80	21.8%	21.9%	3.2%	.365	3.95	23.3%	11.6%	123	-1.85	2.74	150	86
Elison Joseph R 2022 · 4.91 FIP	21	SU	4.91	19.6%	20.3%	1.6%	.310	4.33	24.8%	6.9%	138	-0.58	3.32	217	86
Tommy McCollum R 2021 · 6.21 FIP	22	SU	6.21	17.1%	27.2%	2.0%	.235	3.80	26.4%	10.9%	112	-2.41	2.90	219	86
Cory Thompson R 2017 · 5.42 FIP	22	SU	5.42	15.2%	15.7%	2.9%	.289	4.34	16.3%	10.6%	131	-1.08	3.59	218	86
Paul Gervase R 2022 · 4.91 FIP	22	SU	4.91	20.3%	16.2%	2.7%	.345	3.76	29.3%	16.0%	152	-1.15	3.38	211	85
Jairo Beras R 2017 · 6.07 FIP	22	SU	6.07	16.4%	16.9%	4.0%	.237	4.35	20.7%	4.5%	96	-1.72	3.48	110	85
Nick Kuzia R 2017 · 5.18 FIP	21	SU	5.18	16.5%	15.2%	2.8%	.361	5.35	17.6%	6.6%	60	+0.17	4.54	231	85
Franklyn German R 2003 · 5.17 FIP	23	SU	5.17	18.5%	18.9%	2.2%	.313	5.27	13.1%	0.1%	86	+0.10	3.37	152	85
Bryce McGowan R 2022 · 5.90 FIP	22	SU	5.90	17.0%	22.9%	2.4%	.368	4.36	20.6%	6.6%	145	-1.54	3.71	178	84
Brett Hanewich R 2017 · 5.18 FIP	22	SU	5.18	15.9%	17.6%	2.2%	.372	4.32	20.3%	2.8%	108	-0.86	4.24	134	84
Conor Grady R 2021 · 5.28 FIP	22	SU	5.28	17.2%	19.0%	2.2%	.242	4.62	16.9%	5.1%	96	-0.66	4.62	108	84
Roberto Espinosa R 2015 · 4.92 FIP	23	SU	4.92	18.9%	18.6%	1.9%	.273	4.43	14.8%	2.2%	77	-0.49	4.32	117	84
Will Varmette R 2024 · 5.06 FIP	21	SU	5.06	22.8%	19.3%	2.6%	.302	5.13	16.1%	2.3%	135	+0.07	4.69	182	83
Keith Rogalla R 2017 · 4.87 FIP	21	SU	4.87	15.9%	19.1%	1.3%	.299	3.52	21.2%	9.5%	24	-1.35	3.10	113	83