Juan Mendez

P Cedar Rapids Kernels

Age 28 RHP 6'4" / 240 lbs A+

Overview

A+PROSPECT

MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	A+MIN	33	0	36	4.79	2.93	26.8%	8.9%	—	K 20.6% · BB 10.3% · FIP 3.69
2025	26	A+MIN	6	0	7	15.43	4.96	10.0%	17.5%	—	K 10.0% · BB 17.5% · FIP 4.47
2027PROJ	28	MLBMIN	—	—	0	4.41	4.41	22.7%	9.6%	—
2028PROJ30% MLB	29	MLBMIN	6	0	6	4.48	4.53	22.5%	9.8%	0.0

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

Contract

No contract data on file.

CompsMatt Ramsey (age 28) · Neil Wagner (age 29) · Joe Nelson (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 117109vR 101

ERA4.41

FIP4.41

K%22.7%

BB%9.6%

K-BB%13.1%

Proj IP21

Value2027 · WAR

Runs saved vs league avg · 21 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 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)
2021	22	ROK MLE	FCL Twins	12	5	28	123	37	14	2	42%	2.3	20.5%	14.2%	6.2%	2.3%	3.58	4.45	—
2021	22	ROK RAW	FCL Twins	12	5	28	123	37	14	2	42%	2.3	30.1%	11.4%	18.7%	1.6%	3.58	2.88	—
2022	23	A MLE	Fort Myers Mighty Mussels	32	0	46	204	58	31	4	0%	1.4	21.0%	17.9%	3.1%	2.5%	5.05	4.99	—
2022	23	A RAW	Fort Myers Mighty Mussels	32	0	46	204	58	31	4	0%	1.4	28.4%	15.2%	13.2%	2.0%	5.05	3.73	—
2023	24	A MLE	Fort Myers Mighty Mussels	34	0	46	204	66	31	8	0%	1.4	23.9%	17.9%	6.0%	5.2%	4.89	6.22	—
2023	24	A RAW	Fort Myers Mighty Mussels	34	0	46	204	66	31	8	0%	1.4	32.4%	15.2%	17.2%	3.9%	4.89	4.51	—
2024	25	A+ MLE	Cedar Rapids Kernels	33	0	36	168	45	15	3	0%	1.1	20.6%	10.3%	10.4%	1.9%	4.79	3.69	—
2024	25	A+ MLE	Cedar Rapids Kernels	33	0	36	168	45	15	3	0%	1.1	20.6%	10.3%	10.4%	1.9%	4.79	3.69	—
2024	25	A+ RAW	Cedar Rapids Kernels	33	0	36	168	45	15	3	0%	1.1	26.8%	8.9%	17.9%	1.8%	4.79	2.93	—
2025	26	A+ MLE	Cedar Rapids Kernels	6	0	7	40	4	7	0	0%	1.2	10.0%	17.5%	-7.5%	0.0%	15.43	4.47	—
2025	26	A+ MLE	Cedar Rapids Kernels	6	0	7	40	4	7	0	0%	1.2	10.0%	17.5%	-7.5%	0.0%	15.43	4.47	—
2025	26	A+ RAW	Cedar Rapids Kernels	6	0	7	40	4	7	0	0%	1.2	10.0%	17.5%	-7.5%	0.0%	15.43	4.96	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	MIN	—	—	0	—	—	—	—	—	—	22.7%	9.6%	13.1%	3.0%	4.41	4.41	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	MIN	17	0	18	77	17	8	2	0%	1.1	22.5%	9.8%	12.7%	3.1%	4.48	4.53	+0.0
2028	29	MLB CTX	MIN	6	0	6	25	6	2	1	0%	1.0	22.5%	9.8%	12.7%	3.1%	4.48	4.53	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		5	0	6	23	5	2	1	0%	1.1	22.5%	9.8%	12.7%	3.1%	4.48	4.15	+0.0
/ 200 IP	—	RAW		190	0	200	844	182	73	36	0%	1.1	22.5%	9.8%	12.7%	3.1%	4.48	4.15	+0.9
Career	—	MLE		117	5	163	739	156	115	22	4%	1.4	21.1%	15.5%	5.5%	3.0%	5.15	4.92	+0.0
/ 200 IP	—	MLE		144	6	200	909	191	141	27	4%	1.4	21.1%	15.5%	5.5%	3.0%	5.15	4.92	+0.0

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 A+Cedar Rapids Kernels · 7 IPFIP 4.47 → 5.00 (+0.53)K% 10.0% → 7.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	10.00%	—	×0.770	7.70%
BB% (unintentional) /BF	17.50%	—	×1.150	20.12%
HR / BF /BF	0.00%	÷0.962	×1.250	0.00%

Factors used: pitcher A+ level factors — K ×0.77, BB ×1.15, HR ×1.25. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 92).

Result: FIP 4.47 → 5.00, 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 A+Cedar Rapids Kernels · 36 IPFIP 2.95 → 3.69 (+0.74)K% 26.8% → 20.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.79%	—	×0.770	20.62%
BB% (unintentional) /BF	8.93%	—	×1.150	10.27%
HR / BF /BF	1.79%	÷1.191	×1.250	1.87%

Result: FIP 2.95 → 3.69, 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 AFort Myers Mighty Mussels · 46 IPFIP 4.45 → 6.22 (+1.77)K% 32.4% → 23.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.35%	—	×0.740	23.94%
BB% (unintentional) /BF	15.20%	—	×1.180	17.93%
HR / BF /BF	3.92%	÷0.976	×1.300	5.23%

Factors used: pitcher A level factors — K ×0.74, BB ×1.18, HR ×1.30. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 95).

Result: FIP 4.45 → 6.22, 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).

2022 AFort Myers Mighty Mussels · 46 IPFIP 3.70 → 4.99 (+1.29)K% 28.4% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.43%	—	×0.740	21.04%
BB% (unintentional) /BF	15.20%	—	×1.180	17.93%
HR / BF /BF	1.96%	÷1.000	×1.300	2.55%

Result: FIP 3.70 → 4.99, 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).

2021 ROKFCL Twins · 28 IPFIP 2.89 → 4.45 (+1.55)K% 30.1% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.08%	—	×0.680	20.46%
BB% (unintentional) /BF	11.38%	—	×1.250	14.23%
HR / BF /BF	1.63%	÷0.982	×1.400	2.32%

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 96).

Result: FIP 2.89 → 4.45, 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
Juan Mendez (OGILVIE)	—	—	4.41	22.7%	9.6%	3.0%	—	4.53	22.5%	12.7%	18	+0.12	—	—	—
Matt Ramsey R 2018 · 3.78 FIP	28	SU	3.78	24.9%	8.8%	3.0%	.276	2.42	21.7%	12.6%	34	-1.36	2.42	125	87
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	87
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	85
Tyler Sturdevant R 2015 · 4.37 FIP	29	SU	4.37	21.3%	8.5%	3.6%	.241	3.97	18.5%	11.9%	118	-0.40	3.44	149	85
Gerardo Sanchez R 2017 · 3.47 FIP	28	SU	3.47	21.6%	8.4%	2.1%	.355	3.58	20.5%	15.1%	56	+0.11	2.65	137	84
Josh Lueke R 2013 · 4.09 FIP	28	SU	4.09	25.3%	11.1%	3.1%	.333	3.28	24.6%	20.9%	90	-0.81	2.29	191	84
Marcos Mateo R 2011 · 3.40 FIP	27	SU	3.40	25.5%	10.2%	2.1%	.361	—	—	—	—	—	3.12	104	82
Tyler Yates R 2006 · 4.17 FIP	28	SU	4.17	21.2%	10.6%	2.8%	.254	3.70	20.7%	11.1%	151	-0.47	3.23	248	82
Jason Bulger R 2008 · 4.60 FIP	29	SU	4.60	27.4%	12.3%	4.1%	.293	3.94	25.1%	13.3%	90	-0.66	3.78	106	82
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	82
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	82
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	81
Francisco Del Rosario R 2007 · 3.93 FIP	26	SU	3.93	19.7%	9.4%	2.4%	.356	—	—	—	—	—	3.93	194	81
Michael Dimock R 2018 · 3.37 FIP	28	SU	3.37	23.5%	10.7%	1.6%	.346	—	—	—	—	—	3.08	166	81
Santiago Casilla R 2008 · 3.71 FIP	28	SU	3.71	18.8%	7.9%	2.2%	.337	3.37	20.6%	10.4%	155	-0.34	2.76	647	81
Matt Pushard R 2024 · 3.87 FIP	26	SU	3.87	24.1%	8.9%	3.0%	.242	3.29	22.2%	14.0%	115	-0.58	2.84	220	80
Brandon Cunniff R 2017 · 4.79 FIP	28	SU	4.79	20.1%	11.6%	3.5%	.275	6.80	13.9%	-1.9%	30	+2.01	3.89	180	80
Zach Franklin R 2024 · 3.24 FIP	25	SU	3.24	26.4%	10.9%	1.8%	.301	4.15	27.5%	18.3%	117	+0.91	3.24	158	80
Greg Aquino R 2006 · 4.41 FIP	28	SU	4.41	23.2%	10.0%	3.6%	.331	4.39	17.4%	5.6%	30	-0.02	4.10	154	80
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	80