Nelfy Ynfante

P Palm Beach Cardinals

Age 22 RHP 6'3" / 168 lbs A

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	19	MIX2 levels	21	11	65	3.17	2.53	26.4%	8.6%	—	K 18.2% · BB 10.5% · FIP 3.70
2025	20	ASTL	24	13	90	4.60	3.88	20.3%	10.8%	—	K 15.0% · BB 12.7% · FIP 4.87
2026	21	MIX3 levels	37	1	70	4.50	4.26	23.6%	8.8%	—	K 17.8% · BB 10.1% · FIP 5.44
2027PROJ	22	MLBSTL	—	—	0	5.68	5.68	14.9%	13.0%	—
2028PROJ49% MLB	23	MLBSTL	29	0	30	5.42	5.34	16.8%	11.8%	-0.3
2029PROJ70% MLB	24	MLBSTL	40	0	42	5.21	5.13	17.9%	11.2%	-0.3

Next 3 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control35Command35

Career WAR0.0 WAR median (P10 -0.3 / P90 0.0, comp-based) · star 0% · didn't stick 96%

CompsJustin Ferrell (age 22) · Yunior Montero (age 22) · Josh White (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 141133vR 125

ERA5.68

FIP5.68

K%14.9%

BB%13.0%

K-BB%1.9%

Proj IP53

Value2027 · WAR

Runs saved vs league avg · 53 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL3535

CMD3535

K†3050

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)
2022	17	ROK MLE	DSL Cardinals	11	8	41	175	39	19	1	73%	3.8	15.2%	13.6%	1.6%	0.8%	1.96	3.96	—
2022	17	ROK RAW	DSL Cardinals	11	8	41	175	39	19	1	73%	3.8	22.3%	10.9%	11.4%	0.6%	1.96	2.91	—
2023	18	ROK MLE	DSL Cardinals	9	9	30	128	34	11	2	100%	3.3	18.1%	10.7%	7.3%	2.3%	4.50	4.22	—
2023	18	ROK RAW	DSL Cardinals	9	9	30	128	34	11	2	100%	3.3	26.6%	8.6%	18.0%	1.6%	4.50	2.80	—
2024	19	MIX MLE	2 levels	21	11	65	280	74	24	3	52%	3.1	18.2%	10.5%	7.7%	1.5%	3.17	3.70	—
2024	19	MIX MLE	2 levels	21	11	65	280	74	24	3	52%	3.1	18.2%	10.5%	7.7%	1.5%	3.17	3.70	—
2024	19	MIX RAW	2 levels	21	11	65	280	74	24	3	52%	3.1	26.4%	8.6%	17.9%	1.1%	3.17	2.53	—
2025	20	A MLE	Palm Beach Cardinals	24	13	90	409	83	44	8	54%	3.8	15.0%	12.7%	2.3%	2.6%	4.60	4.87	—
2025	20	A MLE	Palm Beach Cardinals	24	13	90	409	83	44	8	54%	3.8	15.0%	12.7%	2.3%	2.6%	4.60	4.87	—
2025	20	A RAW	Palm Beach Cardinals	24	13	90	409	83	44	8	54%	3.8	20.3%	10.8%	9.5%	2.0%	4.60	3.88	—
2026	21	MIX MLE	3 levels	37	1	70	296	70	26	11	3%	1.9	17.8%	10.1%	7.8%	4.7%	4.50	5.44	—
2026	21	MIX MLE	3 levels	37	1	70	296	70	26	11	3%	1.9	17.8%	10.1%	7.8%	4.7%	4.50	5.44	—
2026	21	MIX RAW	3 levels	37	1	70	296	70	26	11	3%	1.9	23.6%	8.8%	14.9%	3.7%	4.50	4.26	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	22	MLB	STL	—	—	0	—	—	—	—	—	—	14.9%	13.0%	1.9%	3.3%	5.68	5.68	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	23	MLB MLE	STL	58	0	61	256	43	30	8	0%	1.0	16.8%	11.8%	4.9%	3.2%	5.42	5.34	-0.5
2029	24	MLB MLE	STL	58	0	61	256	46	29	8	0%	1.0	17.9%	11.2%	6.7%	3.2%	5.21	5.13	-0.4
2030	25	MLB MLE	STL	49	0	52	218	40	24	7	0%	1.1	18.4%	10.8%	7.6%	3.2%	5.09	5.03	-0.3
2031	26	MLB MLE	STL	49	0	51	215	40	23	7	0%	1.0	18.7%	10.7%	8.0%	3.2%	5.02	4.99	-0.3
2032	27	MLB MLE	STL	47	0	50	209	39	23	7	0%	1.1	18.7%	10.8%	8.0%	3.2%	5.02	5.02	-0.3
2033	28	MLB MLE	STL	45	0	47	200	37	22	7	0%	1.1	18.6%	10.9%	7.7%	3.3%	5.07	5.11	-0.3
2034	29	MLB MLE	STL	44	0	46	196	40	20	7	0%	1.1	20.4%	10.3%	10.0%	3.5%	5.01	4.97	-0.2
2035	30	MLB MLE	STL	40	0	42	179	36	19	7	0%	1.1	20.0%	10.7%	9.4%	3.7%	5.09	5.15	-0.3
2028	23	MLB CTX	STL	29	0	30	127	21	15	4	0%	1.0	16.8%	11.8%	4.9%	3.2%	5.42	5.34	-0.3
2029	24	MLB CTX	STL	40	0	42	177	32	20	6	0%	1.1	17.9%	11.2%	6.7%	3.2%	5.21	5.13	-0.3
2030	25	MLB CTX	STL	40	0	42	177	33	19	6	0%	1.1	18.4%	10.8%	7.6%	3.2%	5.09	5.03	-0.2
2031	26	MLB CTX	STL	43	0	45	190	36	20	6	0%	1.0	18.7%	10.7%	8.0%	3.2%	5.02	4.99	-0.2
2032	27	MLB CTX	STL	43	0	45	190	36	20	6	0%	1.0	18.7%	10.8%	8.0%	3.2%	5.02	5.02	-0.2
2033	28	MLB CTX	STL	42	0	44	186	35	20	6	0%	1.0	18.6%	10.9%	7.7%	3.3%	5.07	5.11	-0.3
2034	29	MLB CTX	STL	41	0	43	182	37	19	6	0%	1.0	20.4%	10.3%	10.0%	3.5%	5.01	4.97	-0.2
2035	30	MLB CTX	STL	38	0	40	169	34	18	6	0%	1.1	20.0%	10.7%	9.4%	3.7%	5.09	5.15	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		314	0	330	1394	261	151	46	0%	1.1	18.8%	10.9%	7.9%	3.3%	5.10	4.70	-0.6
/ 200 IP	—	RAW		190	0	200	844	158	91	28	0%	1.1	18.8%	10.9%	7.9%	3.3%	5.10	4.70	-0.4
Career	—	MLE		102	42	297	1288	215	149	33	41%	2.9	16.7%	11.5%	5.1%	2.6%	3.88	4.56	-2.6
/ 200 IP	—	MLE		69	28	200	868	145	100	22	41%	2.9	16.7%	11.5%	5.1%	2.6%	3.88	4.56	-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.

2026 APalm Beach Cardinals · 43 IPFIP 3.60 → 4.86 (+1.26)K% 25.4% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.42%	—	×0.740	18.81%
BB% (unintentional) /BF	6.21%	—	×1.180	7.33%
HR / BF /BF	3.39%	÷1.000	×1.300	4.41%

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 100).

Result: FIP 3.60 → 4.86, 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).

2026 A+Peoria Chiefs · 14 IPFIP 2.76 → 3.73 (+0.97)K% 29.0% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.03%	—	×0.770	22.35%
BB% (unintentional) /BF	9.68%	—	×1.150	11.13%
HR / BF /BF	1.61%	÷1.000	×1.250	2.02%

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 100).

Result: FIP 2.76 → 3.73, 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).

2026 AASpringfield Cardinals · 13 IPFIP 7.91 → 9.08 (+1.17)K% 12.3% → 9.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.28%	—	×0.810	9.95%
BB% (unintentional) /BF	15.79%	—	×1.100	17.37%
HR / BF /BF	7.02%	÷1.000	×1.200	8.42%

Factors used: pitcher AA level factors — K ×0.81, BB ×1.10, HR ×1.20. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 100).

Result: FIP 7.91 → 9.08, 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).

2025 APalm Beach Cardinals · 90 IPFIP 3.82 → 4.87 (+1.05)K% 20.3% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.29%	—	×0.740	15.02%
BB% (unintentional) /BF	10.76%	—	×1.180	12.69%
HR / BF /BF	1.96%	÷0.973	×1.300	2.61%

Result: FIP 3.82 → 4.87, 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 ROKFCL Cardinals · 52 IPFIP 2.19 → 3.42 (+1.23)K% 28.3% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.31%	—	×0.680	19.25%
BB% (unintentional) /BF	7.76%	—	×1.250	9.70%
HR / BF /BF	0.91%	÷0.975	×1.400	1.31%

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 95).

Result: FIP 2.19 → 3.42, 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 APalm Beach Cardinals · 13 IPFIP 3.79 → 4.72 (+0.92)K% 19.7% → 14.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.67%	—	×0.740	14.56%
BB% (unintentional) /BF	11.48%	—	×1.180	13.54%
HR / BF /BF	1.64%	÷1.036	×1.300	2.06%

Result: FIP 3.79 → 4.72, 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 Cardinals · 30 IPFIP 2.80 → 4.22 (+1.42)K% 26.6% → 18.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.56%	—	×0.680	18.06%
BB% (unintentional) /BF	8.59%	—	×1.250	10.74%
HR / BF /BF	1.56%	÷0.932	×1.400	2.35%

Result: FIP 2.80 → 4.22, 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 ROKDSL Cardinals · 41 IPFIP 2.91 → 3.96 (+1.06)K% 22.3% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.29%	—	×0.680	15.15%
BB% (unintentional) /BF	10.86%	—	×1.250	13.57%
HR / BF /BF	0.57%	÷1.039	×1.400	0.77%

Result: FIP 2.91 → 3.96, 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
Nelfy Ynfante (OGILVIE)	—	—	5.68	14.9%	13.0%	3.3%	—	5.17	17.7%	6.4%	173	-0.51	—	—	—
Justin Ferrell R 2016 · 5.30 FIP	22	SW	5.30	14.9%	14.0%	3.1%	.261	4.34	20.4%	9.1%	173	-0.96	3.83	300	91
Yunior Montero R 2015 · 4.82 FIP	22	SW	4.82	16.9%	14.1%	2.5%	.276	4.58	21.5%	6.2%	91	-0.24	3.65	127	88
Josh White R 2023 · 5.12 FIP	22	SW	5.12	17.7%	13.9%	3.2%	.244	3.15	27.7%	17.2%	182	-1.97	1.84	247	86
Seth McClung R 2003 · 5.63 FIP	22	SW	5.63	15.0%	14.4%	3.6%	.241	5.29	15.3%	2.8%	212	-0.34	2.52	430	86
Blake Quinn R 2017 · 5.41 FIP	23	SW	5.41	16.9%	15.3%	3.3%	.328	4.42	17.1%	3.3%	48	-0.99	4.42	122	85
Chance Huff R 2023 · 5.57 FIP	23	SW	5.57	11.8%	11.4%	3.7%	.312	5.08	15.7%	0.2%	155	-0.49	4.31	238	85
Garrett Nuss R 2015 · 5.71 FIP	22	SW	5.71	14.1%	14.9%	3.5%	.352	4.58	15.0%	5.3%	92	-1.13	4.57	174	85
Axel Rios R 2016 · 4.70 FIP	23	SW	4.70	13.1%	13.5%	1.8%	.333	4.06	15.2%	3.2%	97	-0.64	3.50	153	85
Hunter Hayes R 2023 · 4.53 FIP	22	SW	4.53	13.3%	9.7%	2.4%	.307	4.49	16.5%	4.0%	155	-0.04	3.34	216	84
Luis Rujano R 2024 · 4.54 FIP	21	SW	4.54	17.0%	12.3%	2.4%	.361	4.80	17.9%	-0.8%	97	+0.26	4.54	203	84
Cooper Adams R 2024 · 5.42 FIP	24	SW	5.42	13.0%	12.2%	3.4%	.275	4.32	21.7%	10.4%	141	-1.10	3.05	221	84
Anyelo Gómez R 2016 · 4.66 FIP	23	SW	4.66	17.1%	12.2%	2.7%	.292	2.66	24.2%	15.6%	68	-2.00	2.66	145	83
Wirkin Estevez R 2016 · 5.39 FIP	24	SW	5.39	10.7%	13.4%	2.7%	.316	4.46	12.3%	3.5%	179	-0.93	4.37	238	82
Victor Santos R 2001 · 4.97 FIP	24	SW	4.97	15.5%	13.4%	2.7%	.231	4.38	16.4%	7.4%	206	-0.59	4.09	602	82
Nick Lockhart R 2023 · 4.63 FIP	22	SW	4.63	16.1%	10.6%	2.8%	.274	—	—	—	—	—	4.44	140	82
Kelvin Vasquez R 2015 · 5.03 FIP	22	SU	5.03	14.8%	13.8%	2.6%	.248	5.38	15.0%	-3.0%	103	+0.35	5.01	180	82
Zach Mort R 2019 · 5.01 FIP	22	SW	5.01	10.7%	12.3%	2.3%	.240	5.35	17.0%	8.8%	176	+0.34	4.95	237	81
Paulshawn Pasqualotto R 2024 · 4.84 FIP	23	SW	4.84	15.6%	9.5%	3.4%	.354	3.77	20.2%	10.8%	111	-1.07	3.73	186	81
Daniel Concepcion R 2016 · 5.87 FIP	22	SW	5.87	13.0%	10.6%	4.6%	.271	—	—	—	—	—	3.84	110	81
Trent Fennell R 2018 · 4.48 FIP	22	SP-	4.48	14.5%	12.5%	1.9%	.317	4.46	20.9%	7.5%	89	-0.02	4.08	163	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	2.3	51	18.2%	11.2%	1.27	5.19
Will Cunnane ('04)	1.4	46	18.9%	10.4%	1.25	5.26
Buck Farmer ('24)	2.6	51	21.6%	10.5%	1.24	4.71
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Dennis Powell ('85-'93, -2 WAR*)	1.7	49	17.6%*	10.1%*	1.18*	5.31*