Wuilberth Mendez

P FCL Tigers

Age 23 RHP 6'3" / 150 lbs ROK peak 0.5 · 2028

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	19	ROKDSL Tigers 2	11	9	36	6.44	3.76	17.5%	3.1%	—	K 11.9% · BB 3.9% · FIP 4.97
2024	20	ROKDSL Tigers 2	12	12	54	2.65	2.92	17.1%	4.1%	—	K 11.6% · BB 5.1% · FIP 3.80
2025	21	MIX2 levels	13	9	47	5.32	3.48	19.0%	7.0%	—	K 13.2% · BB 8.9% · FIP 4.90
2026	22	No MLB games played
2027PROJ	23	MLBDET	—	—	0	5.18	5.18	14.2%	9.9%	—
2028PROJ43% MLB	24	MLBDET	4	4	22	5.01	4.96	16.2%	9.6%	0.1
2029PROJ66% MLB	25	MLBDET	4	4	26	4.89	4.84	17.3%	9.4%	0.2

Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff30Control45Command35

CompsRyan Atkinson (age 23) · Bradley Brehmer (age 23) · Michael Matuella (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 132123vR 115

ERA5.18

FIP5.18

K%14.2%

BB%9.9%

K-BB%4.3%

Proj IP52

Value2027 · WAR

Runs saved vs league avg · 52 IP

Grades · Contract

Scouting Grades

STUF3030

CTRL4545

CMD3535

K†3045

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 the standard WAR scale.

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)
2023	19	ROK MLE	DSL Tigers 2	11	9	36	160	28	5	5	82%	3.3	11.9%	3.9%	8.0%	4.3%	6.44	4.97	—
2023	19	ROK RAW	DSL Tigers 2	11	9	36	160	28	5	5	82%	3.3	17.5%	3.1%	14.4%	3.1%	6.44	3.76	—
2024	20	ROK MLE	DSL Tigers 2	12	12	54	222	38	9	3	100%	4.5	11.6%	5.1%	6.6%	1.9%	2.65	3.80	—
2024	20	ROK MLE	DSL Tigers 2	12	12	54	222	38	9	3	100%	4.5	11.6%	5.1%	6.6%	1.9%	2.65	3.80	—
2024	20	ROK RAW	DSL Tigers 2	12	12	54	222	38	9	3	100%	4.5	17.1%	4.1%	13.1%	1.4%	2.65	2.92	—
2025	21	MIX MLE	2 levels	13	9	47	200	38	14	4	69%	3.6	13.2%	8.9%	4.3%	3.2%	5.32	4.90	—
2025	21	MIX MLE	2 levels	13	9	47	200	38	14	4	69%	3.6	13.2%	8.9%	4.3%	3.2%	5.32	4.90	—
2025	21	MIX RAW	2 levels	13	9	47	200	38	14	4	69%	3.6	19.0%	7.0%	12.0%	2.0%	5.32	3.48	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	23	MLB	DET	—	—	0	—	—	—	—	—	—	14.2%	9.9%	4.3%	3.0%	5.18	5.18	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	24	MLB MLE	DET	9	9	52	221	36	21	7	100%	5.8	16.2%	9.6%	6.6%	3.0%	5.01	4.96	+0.3
2029	25	MLB MLE	DET	7	7	39	164	28	16	5	100%	5.6	17.3%	9.4%	7.9%	3.0%	4.89	4.84	+0.3
2030	26	MLB MLE	DET	6	6	38	161	29	15	5	100%	6.4	17.9%	9.4%	8.5%	3.0%	4.81	4.78	+0.3
2031	27	MLB MLE	DET	6	6	37	156	28	15	5	100%	6.2	18.0%	9.5%	8.5%	3.0%	4.81	4.81	+0.3
2028	24	MLB CTX	DET	4	4	22	93	15	9	3	100%	5.5	16.2%	9.6%	6.6%	3.0%	5.01	4.96	+0.1
2029	25	MLB CTX	DET	4	4	26	110	19	10	3	100%	6.5	17.3%	9.4%	7.9%	3.0%	4.89	4.84	+0.2
2030	26	MLB CTX	DET	5	5	30	127	23	12	4	100%	6.0	17.9%	9.4%	8.5%	3.0%	4.81	4.78	+0.2
2031	27	MLB CTX	DET	5	5	32	135	24	13	4	100%	6.4	18.0%	9.5%	8.5%	3.0%	4.81	4.81	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		19	19	110	464	81	44	14	100%	5.8	17.4%	9.5%	8.0%	3.0%	4.87	4.46	+1.2
/ 200 IP	—	RAW		34	34	200	844	147	80	25	100%	5.9	17.4%	9.5%	8.0%	3.0%	4.87	4.46	+2.2
Career	—	MLE		36	30	138	582	71	35	18	83%	3.8	12.2%	6.1%	6.2%	3.0%	4.57	4.50	+1.0
/ 200 IP	—	MLE		52	43	200	843	103	51	26	83%	3.8	12.2%	6.1%	6.2%	3.0%	4.57	4.50	+1.3

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2025 ROKFCL Tigers · 47 IPFIP 3.49 → 4.90 (+1.41)K% 19.4% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.39%	—	×0.680	13.18%
BB% (unintentional) /BF	7.14%	—	×1.250	8.93%
HR / BF /BF	2.04%	÷0.880	×1.400	3.25%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 76).

Result: FIP 3.49 → 4.90, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2024 ROKDSL Tigers 2 · 54 IPFIP 2.91 → 3.80 (+0.89)K% 17.1% → 11.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.12%	—	×0.680	11.64%
BB% (unintentional) /BF	4.05%	—	×1.250	5.07%
HR / BF /BF	1.35%	÷0.995	×1.400	1.90%

Result: FIP 2.91 → 3.80, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2023 ROKDSL Tigers 2 · 36 IPFIP 3.73 → 4.97 (+1.24)K% 17.5% → 11.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.50%	—	×0.680	11.90%
BB% (unintentional) /BF	3.12%	—	×1.250	3.91%
HR / BF /BF	3.12%	÷1.009	×1.400	4.34%

Result: FIP 3.73 → 4.97, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

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
Wuilberth Mendez (OGILVIE)	—	—	5.18	14.2%	9.9%	3.0%	—	4.87	17.0%	7.5%	130	-0.31	—	—	—
Ryan Atkinson R 2016 · 4.58 FIP	23	SP-	4.58	18.4%	11.3%	2.9%	.315	4.48	21.6%	9.0%	305	-0.10	4.14	338	86
Bradley Brehmer R 2023 · 4.43 FIP	23	SP	4.43	14.6%	9.5%	2.5%	.349	3.27	20.0%	11.5%	94	-1.16	2.83	165	86
Michael Matuella R 2017 · 4.28 FIP	23	SP	4.28	13.5%	8.2%	2.3%	.342	4.66	16.5%	3.4%	94	+0.38	3.60	169	85
Jeremy Lee R 2024 · 4.17 FIP	22	SP-	4.17	16.8%	11.5%	1.9%	.318	5.21	11.2%	-0.5%	46	+1.04	4.17	125	85
Garrett Burhenn R 2023 · 4.39 FIP	23	SP-	4.39	13.5%	8.4%	2.5%	.312	4.36	18.1%	10.2%	247	-0.03	4.30	433	84
Cole Wiper R 2015 · 5.41 FIP	23	SP	5.41	14.6%	10.5%	4.0%	.343	4.52	15.6%	5.2%	136	-0.89	3.97	170	84
Tommy Mace R 2022 · 5.47 FIP	23	SP	5.47	16.0%	12.1%	4.0%	.261	5.04	14.7%	2.7%	376	-0.43	4.86	501	83
Caleb Boushley R 2017 · 4.11 FIP	23	SP	4.11	14.2%	10.0%	1.7%	.351	3.21	18.3%	14.2%	163	-0.90	3.05	790	82
Brandon White R 2023 · 4.93 FIP	23	SP	4.93	16.7%	10.3%	3.5%	.264	4.05	17.5%	10.6%	280	-0.88	3.90	299	82
Levi Thomas R 2021 · 5.22 FIP	23	SP-	5.22	18.1%	11.9%	3.9%	.328	5.16	20.8%	3.3%	31	-0.06	5.16	116	82
Bryce Warrecker R 2024 · 5.43 FIP	22	SP	5.43	11.3%	11.7%	3.3%	.271	3.82	20.1%	9.6%	91	-1.61	2.47	154	82
Sergio Mitre R 2004 · 4.16 FIP	23	SP-	4.16	15.2%	7.8%	2.5%	.357	4.16	13.2%	6.5%	250	+0.00	3.55	602	82
Tanner Hall R 2024 · 4.67 FIP	22	SP-	4.67	18.8%	11.2%	3.2%	.295	5.33	10.1%	-4.6%	72	+0.66	4.67	137	82
Andrew Quezada R 2021 · 4.40 FIP	24	SP-	4.40	18.1%	8.1%	3.3%	.312	4.86	14.6%	6.1%	291	+0.46	4.40	412	81
Spencer Schwellenbach R 2023 · 4.00 FIP	23	SP	4.00	14.5%	8.5%	1.9%	.273	3.09	24.5%	19.9%	266	-0.91	3.05	318	81
Robbie Peto R 2021 · 5.81 FIP	23	SP	5.81	16.6%	10.7%	5.0%	.303	5.57	15.5%	-1.0%	161	-0.24	5.39	232	81
Cade Kuehler R 2024 · 4.22 FIP	22	SP	4.22	15.5%	11.2%	1.8%	.266	7.37	12.2%	-2.2%	109	+3.15	4.22	159	81
Cha Seung Baek R 2004 · 4.77 FIP	24	SP-	4.77	14.4%	7.2%	3.6%	.288	3.95	15.7%	10.0%	108	-0.82	3.35	280	81
Chris Kachmar R 2021 · 4.29 FIP	24	SP	4.29	16.1%	11.4%	2.0%	.309	4.61	18.4%	9.4%	172	+0.32	4.29	360	81
Jordan Geber R 2022 · 5.03 FIP	23	SP-	5.03	15.3%	10.7%	3.4%	.341	4.39	15.5%	7.8%	176	-0.64	4.26	241	81

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 historical, 1901-2023), also matched on career-to-date at the same age. * Historical (Lahman) careers: rates era-adjusted to 2001-24 league levels; WAR is an OGILVIE proxy.

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	1.1	44	16.5%	9.6%	1.15	4.96
Vic Darensbourg ('05)	1.5	50	17.0%	9.3%	1.01	4.96
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Tom Martin ('07)	1.6	53	15.8%	10.1%	1.02	4.92
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Dave Leiper ('84-'96, 0 WAR*)	1.4	46	15.6%*	9.1%*	0.94*	4.28*