Yoendrys Gómez

P Minnesota Twins

Age 27 RHP 6'3" / 212 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	MIX2 levels	28	21	95	3.71	4.30	25.9%	11.6%	1.2	K 22.6% · BB 10.6% · FIP 4.53
2025	25	MIX2 levels	35	20	109	3.87	3.97	25.6%	10.1%	1.9	K 23.7% · BB 9.6% · FIP 3.96
2026	26	MLBMIN	65	0	67	4.30	4.13	21.9%	12.1%	0.3
2027PROJ	27	MLBMIN	50	0	52	4.74	4.80	22.4%	11.8%	-0.1
2028PROJ95% MLB	28	MLBMIN	30	0	32	4.83	4.89	22.2%	12.0%	-0.1
2029PROJ95% MLB	29	MLBMIN	21	0	22	4.96	5.05	21.6%	12.2%	-0.1

Last 3 seasons WAR 3.4 · Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo70

K%48

xwOBA vs14

Form6.52 ERA (proj 4.74) · K 23.9% (proj 22.4%) · BB 17.4% (proj 11.8%) ▼ last 90d · 19 IP through Oct 27

CompsRoberto Gómez (age 27) · Taylor Grover (age 26) · Cameron Foster (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 128120vR 112

ERA4.74

FIP4.80

K%22.4%

BB%11.8%

K-BB%10.5%

Proj IP53

Value2027 · WAR

Runs saved vs league avg · 53 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL4040

CMD4040

K†5555

Statcast Percentiles

FB Velo

p7095.9

Whiff%

p5626.2%

p4821.9%

xwOBA vs

p140.355

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)
2017	17	ROK MLE	GCL Yankees West	11	9	35	162	33	18	2	82%	3.2	13.9%	13.9%	-0.0%	1.7%	5.40	4.64	—
2017	17	ROK RAW	GCL Yankees West	11	9	35	162	33	18	2	82%	3.2	20.4%	11.1%	9.3%	1.2%	5.40	3.50	—
2018	18	ROK MLE	GCL Yankees East	12	11	48	194	50	22	1	92%	4.0	17.5%	14.2%	3.4%	0.7%	2.08	3.81	—
2018	18	ROK RAW	GCL Yankees East	12	11	48	194	50	22	1	92%	4.0	25.8%	11.3%	14.4%	0.5%	2.08	2.66	—
2019	19	A MLE	Charleston RiverDogs	6	6	27	119	25	9	2	100%	4.4	15.5%	8.9%	6.6%	2.4%	6.07	4.23	—
2019	19	A RAW	Charleston RiverDogs	6	6	27	119	25	9	2	100%	4.4	21.0%	7.6%	13.4%	1.7%	6.07	3.21	—
2021	21	A MLE	Tampa Tarpons	9	9	24	96	29	9	3	100%	2.6	22.4%	11.1%	11.3%	4.1%	3.42	4.84	—
2021	21	A RAW	Tampa Tarpons	9	9	24	96	29	9	3	100%	2.6	30.2%	9.4%	20.8%	3.1%	3.42	3.44	—
2022	22	MIX MLE	3 levels	15	15	47	191	49	18	1	100%	3.1	20.0%	11.3%	8.7%	0.6%	2.49	3.19	—
2022	22	MIX RAW	3 levels	15	15	47	191	49	18	1	100%	3.1	25.7%	9.4%	16.2%	0.5%	2.49	2.44	—
2023	23	MIX MLE	2 levels	20	19	67	282	82	37	6	95%	3.4	23.1%	14.9%	8.2%	2.5%	3.48	4.43	+0.8
2023	23	MIX RAW	2 levels	20	19	67	282	82	37	6	95%	3.4	29.1%	13.1%	16.0%	2.1%	3.48	3.47	+1.6
2024	24	MIX MLE	2 levels	28	21	95	398	103	46	14	75%	3.4	22.6%	10.6%	12.0%	3.6%	3.71	4.53	+1.0
2024	24	MIX MLE	2 levels	28	21	95	398	103	46	14	75%	3.4	22.6%	10.6%	12.0%	3.6%	3.71	4.53	+1.0
2024	24	MIX RAW	2 levels	28	21	95	398	103	46	14	75%	3.4	25.9%	11.6%	14.3%	3.5%	3.71	4.30	+1.2
2025	25	MIX MLE	2 levels	35	20	109	477	122	48	15	57%	3.1	23.7%	9.6%	14.1%	3.0%	3.87	3.96	+1.9
2025	25	MIX MLE	2 levels	35	20	109	477	122	48	15	57%	3.1	23.7%	9.6%	14.1%	3.0%	3.87	3.96	+1.9
2025	25	MIX RAW	2 levels	35	20	109	477	122	48	15	57%	3.1	25.6%	10.1%	15.5%	3.1%	3.87	3.97	+1.9
2026	26	MLB MLE	Minnesota Twins	65	0	67	297	65	36	7	0%	1.0	21.9%	12.1%	9.8%	2.3%	4.30	4.07	+0.4
2026	26	MLB MLE	Minnesota Twins	65	0	67	297	65	36	7	0%	1.0	21.9%	12.1%	9.8%	2.3%	4.30	4.07	+0.4
2026	26	MLB RAW	Minnesota Twins	65	0	67	297	65	36	7	0%	1.0	21.9%	12.1%	9.8%	2.4%	4.30	4.13	+0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			92	9	143	636	137	70	21	10%	1.6	21.5%	11.0%	10.5%	3.3%	4.59	4.56	-0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	MIN	50	0	52	220	49	26	7	0%	1.0	22.4%	11.8%	10.5%	3.1%	4.74	4.80	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	MIN	32	0	34	144	32	17	5	0%	1.1	22.2%	12.0%	10.2%	3.2%	4.83	4.89	-0.1
2029	29	MLB MLE	MIN	22	0	23	98	21	12	3	0%	1.1	21.6%	12.2%	9.4%	3.4%	4.96	5.05	-0.1
2028	28	MLB CTX	MIN	30	0	32	135	30	16	4	0%	1.1	22.2%	12.0%	10.2%	3.2%	4.83	4.89	-0.1
2029	29	MLB CTX	MIN	21	0	22	93	20	11	3	0%	1.0	21.6%	12.2%	9.4%	3.4%	4.96	5.05	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		144	9	198	866	188	98	29	6%	1.4	21.7%	11.3%	10.4%	3.3%	4.67	4.51	+0.1
/ 200 IP	—	RAW		146	9	200	877	190	99	29	6%	1.4	21.7%	11.3%	10.4%	3.3%	4.67	4.51	+0.1
Career	—	MLE		201	110	518	2216	468	259	55	55%	2.6	21.1%	11.7%	9.4%	2.5%	3.75	4.16	+1.7
/ 200 IP	—	MLE		78	42	200	855	180	100	21	55%	2.6	21.1%	11.7%	9.4%	2.5%	3.75	4.16	+1.7

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 AAACharlotte Knights · 47 IPFIP 2.55 → 2.66 (+0.11)K% 32.0% → 27.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.00%	—	×0.860	27.52%
BB% (unintentional) /BF	10.50%	—	×0.900	9.45%
HR / BF /BF	1.50%	÷1.320	×1.100	1.25%

Factors used: pitcher AAA level factors (Triple-A 2023+ robo-zone set: walks improve on promotion) — K ×0.86, BB ×0.90, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 164).

Result: FIP 2.55 → 2.66, 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 AAAScranton/Wilkes-Barre RailRiders · 83 IPFIP 4.17 → 4.45 (+0.28)K% 27.0% → 23.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.03%	—	×0.860	23.25%
BB% (unintentional) /BF	11.34%	—	×0.900	10.20%
HR / BF /BF	3.49%	÷1.045	×1.100	3.67%

Result: FIP 4.17 → 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).

2023 AASomerset Patriots · 65 IPFIP 3.61 → 4.43 (+0.82)K% 28.5% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.47%	—	×0.810	23.06%
BB% (unintentional) /BF	13.50%	—	×1.100	14.85%
HR / BF /BF	2.19%	÷1.033	×1.200	2.54%

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 107).

Result: FIP 3.61 → 4.43, 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 A+Hudson Valley Renegades · 28 IPFIP 2.43 → 3.09 (+0.67)K% 23.9% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.89%	—	×0.770	18.40%
BB% (unintentional) /BF	10.62%	—	×1.150	12.21%
HR / BF /BF	0.00%	÷1.014	×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 103).

Result: FIP 2.43 → 3.09, 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 AASomerset Patriots · 16 IPFIP 2.67 → 3.36 (+0.69)K% 27.9% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.94%	—	×0.810	22.63%
BB% (unintentional) /BF	8.82%	—	×1.100	9.71%
HR / BF /BF	1.47%	÷1.032	×1.200	1.71%

Result: FIP 2.67 → 3.36, 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 ATampa Tarpons · 24 IPFIP 3.45 → 4.84 (+1.39)K% 30.2% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.21%	—	×0.740	22.35%
BB% (unintentional) /BF	9.38%	—	×1.180	11.06%
HR / BF /BF	3.12%	÷1.000	×1.300	4.06%

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 3.45 → 4.84, 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).

2019 ACharleston RiverDogs · 27 IPFIP 3.21 → 4.23 (+1.02)K% 21.0% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.01%	—	×0.740	15.55%
BB% (unintentional) /BF	7.56%	—	×1.180	8.92%
HR / BF /BF	1.68%	÷0.916	×1.300	2.38%

Result: FIP 3.21 → 4.23, 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).

2018 ROKGCL Yankees East · 48 IPFIP 2.64 → 3.81 (+1.17)K% 25.8% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.77%	—	×0.680	17.53%
BB% (unintentional) /BF	11.34%	—	×1.250	14.18%
HR / BF /BF	0.52%	÷1.000	×1.400	0.72%

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 100).

Result: FIP 2.64 → 3.81, 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
Yoendrys Gómez (OGILVIE)	—	—	4.80	22.4%	11.8%	3.1%	—	4.95	22.0%	9.9%	57	+0.15	—	—	—
Roberto Gómez R 2017 · 3.95 FIP	27	SW	3.95	18.4%	8.9%	2.3%	.315	5.25	13.8%	4.9%	18	+1.30	3.95	115	75
Taylor Grover R 2017 · 4.93 FIP	26	SW	4.93	20.0%	10.9%	3.9%	.320	4.89	16.2%	8.9%	14	-0.04	3.68	239	73
Cameron Foster R 2024 · 4.83 FIP	25	SW	4.83	17.4%	11.5%	3.2%	.321	3.09	25.5%	17.5%	60	-1.74	2.50	213	72
Emmanuel Chapman R 2024 · 4.08 FIP	25	SW	4.08	19.7%	10.6%	2.4%	.256	4.52	17.8%	1.3%	117	+0.44	3.81	198	72
Shawn Dubin R 2023 · 4.87 FIP	27	SP-	4.87	20.0%	12.9%	3.3%	.292	3.97	21.8%	11.4%	79	-0.90	3.02	341	72
Grant Black R 2021 · 4.46 FIP	27	SW	4.46	19.0%	13.9%	2.2%	.327	5.35	15.0%	3.8%	156	+0.89	4.46	215	71
Tyler Yates R 2004 · 4.47 FIP	26	SW	4.47	15.4%	9.6%	2.6%	.333	3.64	22.5%	13.5%	116	-0.83	3.23	248	71
Britt Reames R 2001 · 4.77 FIP	27	SW	4.77	19.9%	10.4%	3.7%	.298	3.76	24.7%	14.3%	68	-1.01	3.76	204	70
Derek Gordon R 2016 · 4.62 FIP	25	SW	4.62	19.9%	9.3%	3.7%	.315	—	—	—	—	—	4.62	146	70
Jorge Reyes R 2015 · 4.58 FIP	27	SW	4.58	15.9%	8.5%	3.2%	.307	3.49	14.2%	6.2%	129	-1.09	3.39	227	69
J.P. France R 2022 · 4.44 FIP	27	SW	4.44	24.9%	10.9%	3.8%	.301	4.47	18.6%	9.0%	205	+0.03	4.04	577	69
TJ Shook R 2024 · 4.15 FIP	26	SW	4.15	23.7%	8.7%	3.5%	.317	3.92	20.0%	11.1%	107	-0.23	3.35	452	69
Logan Bawcom R 2016 · 3.73 FIP	27	SW	3.73	16.6%	9.2%	1.6%	.251	4.85	16.0%	6.7%	234	+1.12	3.73	399	69
Jake Stinnett R 2019 · 4.23 FIP	27	SW	4.23	21.1%	12.2%	2.5%	.301	—	—	—	—	—	2.88	356	69
Colby Morris R 2022 · 5.76 FIP	25	SW	5.76	16.2%	11.8%	4.6%	.268	—	—	—	—	—	4.11	105	69
Jarret Whorff R 2024 · 4.04 FIP	25	SU	4.04	18.9%	10.2%	2.3%	.271	4.52	19.6%	12.0%	123	+0.48	3.88	257	68
Cory Abbott R 2023 · 4.88 FIP	27	SW	4.88	23.5%	11.9%	4.1%	.300	5.04	22.1%	12.8%	151	+0.16	3.86	703	68
Coleman Huntley III R 2021 · 3.85 FIP	28	SW	3.85	20.2%	7.4%	2.8%	.348	3.56	23.4%	13.2%	86	-0.29	2.38	160	68
Tyler Cravy R 2016 · 3.95 FIP	27	SW	3.95	21.6%	11.0%	2.3%	.297	5.66	13.8%	3.4%	53	+1.71	3.94	276	68
Aaron Northcraft R 2016 · 4.19 FIP	26	SW	4.19	16.1%	8.3%	2.5%	.309	3.32	24.1%	13.4%	34	-0.87	3.32	252	68

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	1.3	51	21.8%	11.7%	1.26	4.69
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
David Aardsma ('15)	1.7	48	23.1%	12.4%	1.09	4.27
Bill Risley ('98)	1.1	55	21.9%	10.9%	1.26	3.98