Kevin Gowdy

P Binghamton Rumble Ponies

Age 29 RHP 6'4" / 205 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	27	AAATOR	33	0	36	5.25	4.79	18.6%	11.6%	—	K 16.0% · BB 10.5% · FIP 5.15
2026	28	AANYM	10	0	9	10.61	6.21	24.5%	18.4%	—	K 24.5% · BB 18.4% · FIP 5.60
2027PROJ	29	MLBNYM	—	—	0	4.83	4.83	17.8%	9.8%	—
2028PROJ31% MLB	30	MLBNYM	6	0	6	4.89	4.96	18.0%	10.0%	-0.0

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

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsWirfin Obispo (age 30) · Angel Castro (age 32) · Dustin Molleken (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 125117vR 109

ERA4.83

FIP4.83

K%17.8%

BB%9.8%

K-BB%8.0%

Proj IP23

Value2027 · WAR

Runs saved vs league avg · 23 IP

Grades · Contract

Scouting Grades

K†4045

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)
2016	18	ROK MLE	GCL Phillies	4	4	9	42	9	2	0	100%	2.2	21.4%	4.8%	16.7%	0.0%	4.00	1.89	—
2016	18	ROK RAW	GCL Phillies	4	4	9	42	9	2	0	100%	2.2	21.4%	4.8%	16.7%	0.0%	4.00	1.77	—
2019	21	A MLE	Lakewood BlueClaws	24	16	77	354	53	51	4	67%	3.2	11.1%	17.0%	-5.9%	1.8%	4.68	5.31	—
2019	21	A RAW	Lakewood BlueClaws	24	16	77	354	53	51	4	67%	3.2	15.0%	14.4%	0.6%	1.1%	4.68	4.39	—
2021	23	A+ MLE	Hickory Crawdads	20	16	90	387	89	25	9	80%	4.5	17.7%	7.4%	10.3%	3.3%	4.20	4.36	—
2021	23	A+ RAW	Hickory Crawdads	20	16	90	387	89	25	9	80%	4.5	23.0%	6.5%	16.5%	2.3%	4.20	3.26	—
2022	24	AA MLE	Frisco RoughRiders	32	3	40	201	33	31	11	9%	1.2	13.3%	17.0%	-3.7%	7.2%	9.90	8.07	—
2022	24	AA RAW	Frisco RoughRiders	32	3	40	201	33	31	11	9%	1.2	16.4%	15.4%	1.0%	5.5%	9.90	7.35	—
2023	25	AA MLE	Tulsa Drillers	31	0	38	168	41	20	4	0%	1.2	19.8%	13.1%	6.7%	2.6%	4.93	4.54	—
2023	25	AA RAW	Tulsa Drillers	31	0	38	168	41	20	4	0%	1.2	24.4%	11.9%	12.5%	2.4%	4.93	3.88	—
2024	26	AAA MLE	Oklahoma City Baseball Club	42	1	51	231	45	23	1	2%	1.2	16.8%	9.0%	7.8%	0.5%	4.38	3.11	—
2024	26	AAA MLE	Oklahoma City Baseball Club	42	1	51	231	45	23	1	2%	1.2	16.8%	9.0%	7.8%	0.5%	4.38	3.11	—
2024	26	AAA RAW	Oklahoma City Baseball Club	42	1	51	231	45	23	1	2%	1.2	19.5%	10.0%	9.5%	0.4%	4.38	2.94	—
2025	27	AAA MLE	Buffalo Bisons	33	0	36	172	32	20	5	0%	1.1	16.0%	10.5%	5.5%	3.8%	5.25	5.15	—
2025	27	AAA MLE	Buffalo Bisons	33	0	36	172	32	20	5	0%	1.1	16.0%	10.5%	5.5%	3.8%	5.25	5.15	—
2025	27	AAA RAW	Buffalo Bisons	33	0	36	172	32	20	5	0%	1.1	18.6%	11.6%	7.0%	2.9%	5.25	4.79	—
2026	28	AA MLE	Binghamton Rumble Ponies	10	0	9	49	12	9	2	0%	0.9	24.5%	18.4%	6.1%	4.1%	10.61	5.60	—
2026	28	AA MLE	Binghamton Rumble Ponies	10	0	9	49	12	9	2	0%	0.9	24.5%	18.4%	6.1%	4.1%	10.61	5.60	—
2026	28	AA RAW	Binghamton Rumble Ponies	10	0	9	49	12	9	2	0%	0.9	24.5%	18.4%	6.1%	4.1%	10.61	6.21	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	NYM	—	—	0	—	—	—	—	—	—	17.8%	9.8%	8.0%	3.0%	4.83	4.83	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	NYM	17	0	18	75	13	7	2	0%	1.0	18.0%	10.0%	8.0%	3.2%	4.89	4.96	-0.1
2028	30	MLB CTX	NYM	6	0	6	25	5	3	1	0%	1.0	18.0%	10.0%	8.0%	3.2%	4.89	4.96	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		5	0	6	23	4	2	1	0%	1.1	18.0%	10.0%	8.0%	3.2%	4.89	4.58	-0.0
/ 200 IP	—	RAW		190	0	200	844	144	72	36	0%	1.1	18.0%	10.0%	8.0%	3.2%	4.89	4.58	-0.1
Career	—	MLE		196	40	351	1604	255	195	48	20%	1.8	15.9%	12.1%	3.8%	3.0%	5.33	4.93	-0.1
/ 200 IP	—	MLE		112	23	200	914	145	111	27	20%	1.8	15.9%	12.1%	3.8%	3.0%	5.33	4.93	-1.0

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.

2026 AABinghamton Rumble Ponies · 9 IPFIP 5.60 → 6.67 (+1.07)K% 24.5% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.49%	—	×0.810	19.84%
BB% (unintentional) /BF	18.37%	—	×1.100	20.20%
HR / BF /BF	4.08%	÷1.000	×1.200	4.90%

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 5.60 → 6.67, 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 AAABuffalo Bisons · 36 IPFIP 4.60 → 5.15 (+0.55)K% 18.6% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.60%	—	×0.860	16.00%
BB% (unintentional) /BF	11.63%	—	×0.900	10.47%
HR / BF /BF	2.91%	÷0.847	×1.100	3.78%

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 69).

Result: FIP 4.60 → 5.15, 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 AAAOklahoma City Baseball Club · 51 IPFIP 2.95 → 3.11 (+0.16)K% 19.5% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.48%	—	×0.860	16.75%
BB% (unintentional) /BF	9.96%	—	×0.900	8.96%
HR / BF /BF	0.43%	÷0.896	×1.100	0.53%

Result: FIP 2.95 → 3.11, 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 AATulsa Drillers · 38 IPFIP 3.85 → 4.54 (+0.68)K% 24.4% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.40%	—	×0.810	19.77%
BB% (unintentional) /BF	11.90%	—	×1.100	13.10%
HR / BF /BF	2.38%	÷1.083	×1.200	2.64%

Result: FIP 3.85 → 4.54, 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 AAFrisco RoughRiders · 40 IPFIP 6.67 → 8.07 (+1.40)K% 16.4% → 13.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.42%	—	×0.810	13.30%
BB% (unintentional) /BF	15.42%	—	×1.100	16.97%
HR / BF /BF	5.47%	÷0.915	×1.200	7.18%

Result: FIP 6.67 → 8.07, 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 A+Hickory Crawdads · 90 IPFIP 3.25 → 4.36 (+1.10)K% 23.0% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.00%	—	×0.770	17.71%
BB% (unintentional) /BF	6.46%	—	×1.150	7.43%
HR / BF /BF	2.33%	÷0.881	×1.250	3.30%

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 76).

Result: FIP 3.25 → 4.36, 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).

2019 ALakewood BlueClaws · 77 IPFIP 4.28 → 5.31 (+1.03)K% 15.0% → 11.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.97%	—	×0.740	11.08%
BB% (unintentional) /BF	14.41%	—	×1.180	17.00%
HR / BF /BF	1.13%	÷0.809	×1.300	1.81%

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 62).

Result: FIP 4.28 → 5.31, 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).

2016 ROKGCL Phillies · 9 IPFIP 1.89 → 2.62 (+0.73)K% 21.4% → 14.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.43%	—	×0.680	14.57%
BB% (unintentional) /BF	4.76%	—	×1.250	5.95%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

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 1.89 → 2.62, 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
Kevin Gowdy (OGILVIE)	—	—	4.83	17.8%	9.8%	3.0%	—	4.96	18.0%	8.0%	18	+0.13	—	—	—
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	81
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	81
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	80
Diego Moreno R 2016 · 3.75 FIP	29	SU	3.75	21.0%	8.2%	2.5%	.347	3.13	17.8%	11.9%	54	-0.62	2.29	187	80
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	79
Thad Weber R 2013 · 5.18 FIP	28	SU	5.18	16.4%	13.1%	3.3%	.244	4.52	12.2%	6.0%	308	-0.66	4.40	378	79
Carlos Fisher R 2011 · 4.33 FIP	28	SU	4.33	15.5%	9.1%	2.5%	.275	—	—	—	—	—	2.48	245	78
Yoanner Negrin R 2015 · 3.79 FIP	31	SW	3.79	15.1%	7.5%	1.9%	.256	3.29	15.0%	8.5%	270	-0.50	3.15	485	78
Gregory Infante R 2016 · 4.47 FIP	29	SU	4.47	19.0%	12.3%	2.6%	.333	3.43	22.5%	15.8%	120	-1.04	2.97	230	77
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	77
Willie Eyre R 2007 · 4.53 FIP	29	SU	4.53	13.7%	9.1%	2.6%	.306	2.87	11.1%	5.5%	18	-1.66	2.87	164	77
Mike Adams R 2022 · 5.36 FIP	27	SU	5.36	17.1%	11.2%	4.2%	.326	—	—	—	—	—	3.65	109	76
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	76
Drew Hayes R 2016 · 3.99 FIP	28	SU	3.99	13.8%	10.1%	1.4%	.302	—	—	—	—	—	3.35	117	76
Ryan Doolittle R 2016 · 4.38 FIP	28	SU	4.38	13.9%	7.1%	2.8%	.269	—	—	—	—	—	4.03	101	76
Fredy Quintero R 2017 · 4.45 FIP	29	SW	4.45	14.0%	8.7%	2.6%	.335	4.62	17.2%	3.5%	43	+0.17	4.29	241	76
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	76
Brian Sanches R 2008 · 4.74 FIP	29	SU	4.74	18.5%	9.3%	3.7%	.378	4.01	20.5%	10.8%	182	-0.73	3.39	229	75
Santiago Casilla R 2009 · 4.44 FIP	29	SU	4.44	15.0%	9.4%	2.6%	.324	3.29	22.1%	13.0%	170	-1.15	2.76	647	75
Ronald Peña R 2021 · 4.49 FIP	29	SU	4.49	16.5%	10.4%	2.7%	.288	—	—	—	—	—	3.72	187	75