Domingo Germán

P Indianapolis Indians

Age 34 RHP 6'2" / 181 lbs AAA Svc 10.0 · Ctrl thru 2027 peak 0.5 · 2027

Overview

AAARPExt / FA-dealFA 2028

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	29	MIX4 levels	20	19	93	2.91	3.80	18.8%	5.4%	1.8	K 19.5% · BB 6.4% · FIP 4.16
2023	30	MLBNYY	20	19	109	4.56	4.33	25.7%	7.7%	1.4
2024	31	MIX3 levels	23	17	100	5.51	4.84	21.5%	10.7%	0.6	K 19.0% · BB 9.7% · FIP 5.14
2025	32	No MLB games played
2026	33	No MLB games played
2027PROJ	34	MLBPIT	4	4	22	4.50	4.61	21.6%	9.4%	0.2
2028PROJ	35	MLBPIT	19	19	114	4.62	4.79	20.7%	10.0%	0.6
2029PROJ	36	MLBPIT	14	14	87	4.94	5.15	19.7%	10.6%	0.1

Last 3 seasons WAR 3.8 · Next 3 projected WAR 0.9Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service10.000First FA2028

2027Ext / FA-deal$10M

Skills · percentileStatcast 2024

K%21

FB Velo10

xwOBA vs10

CompsKenshin Kawakami (age 34) · Jarrett Grube (age 34) · Manuel Flores (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 121113vR 105

ERA4.50

FIP4.61

K%21.6%

BB%9.4%

K-BB%12.2%

Proj IP154

Value2027 · WAR

Runs saved vs league avg · 154 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1090.7

Whiff%

p1520.3%

p2118.0%

xwOBA vs

p100.362

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status FA

MLB Debut 2017

Service 10.000 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$10M	+0.2	$0.8M	-$10M
Totals		$10M		$0.8M	-$10M

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	23	MIX MLE	2 levels	10	10	50	198	38	11	3	100%	5.0	14.5%	6.4%	8.1%	2.2%	3.08	3.90	—
2016	23	MIX RAW	2 levels	10	10	50	198	38	11	3	100%	5.0	19.2%	5.6%	13.6%	1.5%	3.08	3.02	—
2017	24	MIX MLE	3 levels	27	19	124	515	137	41	10	70%	4.6	23.3%	8.4%	14.9%	2.0%	2.91	3.29	+3.2
2017	24	MIX RAW	3 levels	27	19	124	515	137	41	10	70%	4.6	26.6%	8.0%	18.6%	1.9%	2.91	2.93	+3.8
2018	25	MIX MLE	4 levels	25	17	94	412	112	37	17	68%	3.8	27.2%	8.8%	18.4%	3.7%	5.74	3.97	+1.6
2018	25	MIX RAW	4 levels	25	17	94	412	112	37	17	68%	3.8	27.2%	9.0%	18.2%	4.1%	5.74	4.25	+1.3
2019	26	MIX MLE	2 levels	28	25	147	613	158	41	32	89%	5.2	25.8%	6.6%	19.2%	4.7%	4.16	4.35	+1.8
2019	26	MIX RAW	2 levels	28	25	147	613	158	41	32	89%	5.2	25.8%	6.7%	19.1%	5.2%	4.16	4.62	+1.3
2021	28	MIX MLE	2 levels	24	18	102	427	105	29	17	75%	4.3	23.9%	6.6%	17.3%	3.9%	4.49	4.05	+1.6
2021	28	MIX RAW	2 levels	24	18	102	427	105	29	17	75%	4.3	24.6%	6.8%	17.8%	4.0%	4.49	4.06	+1.6
2022	29	MIX MLE	4 levels	20	19	93	367	69	20	11	95%	4.6	19.5%	6.4%	13.1%	3.5%	2.91	4.16	+1.4
2022	29	MIX RAW	4 levels	20	19	93	367	69	20	11	95%	4.6	18.8%	5.4%	13.4%	3.0%	2.91	3.80	+1.8
2023	30	MLB MLE	New York Yankees	20	19	109	444	114	34	20	95%	5.4	25.7%	7.7%	18.0%	4.2%	4.56	4.22	+1.5
2023	30	MLB RAW	New York Yankees	20	19	109	444	114	34	20	95%	5.4	25.7%	7.7%	18.0%	4.5%	4.56	4.33	+1.4
2024	31	MIX MLE	3 levels	23	17	100	447	96	48	17	74%	4.3	19.0%	9.7%	9.3%	4.4%	5.51	5.14	+0.3
2024	31	MIX MLE	3 levels	23	17	100	447	96	48	17	74%	4.3	19.0%	9.7%	9.3%	4.4%	5.51	5.14	+0.3
2024	31	MIX RAW	3 levels	23	17	100	447	96	48	17	74%	4.3	21.5%	10.7%	10.7%	3.8%	5.51	4.84	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			119	91	543	2283	561	173	98	76%	4.6	24.6%	7.6%	17.0%	4.3%	4.54	4.34	+6.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	PIT	4	4	22	93	20	9	3	100%	5.5	21.6%	9.4%	12.2%	3.2%	4.50	4.61	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	PIT	19	19	114	481	100	48	17	100%	6.0	20.7%	10.0%	10.7%	3.6%	4.77	4.94	+0.6
2029	36	MLB MLE	PIT	15	15	87	368	72	39	14	100%	5.8	19.7%	10.6%	9.1%	3.9%	5.10	5.31	+0.1
2028	35	MLB CTX	PIT	19	19	114	481	100	48	16	100%	6.0	20.7%	10.0%	10.7%	3.3%	4.62	4.79	+0.6
2029	36	MLB CTX	PIT	14	14	87	367	72	39	13	100%	6.2	19.7%	10.6%	9.1%	3.6%	4.94	5.15	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		153	125	744	3132	733	260	127	82%	4.9	23.4%	8.3%	15.1%	4.1%	4.60	4.40	+8.7
/ 200 IP	—	RAW		41	33	200	842	197	70	34	82%	4.9	23.4%	8.3%	15.1%	4.1%	4.60	4.40	+2.3
Career	—	MLE		177	144	818	3423	791	261	127	81%	4.6	23.1%	7.6%	15.5%	3.7%	4.20	4.15	+7.4
/ 200 IP	—	MLE		43	35	200	837	194	64	31	81%	4.6	23.1%	7.6%	15.5%	3.7%	4.20	4.15	+2.0

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.

2024 AAAIndianapolis Indians · 75 IPFIP 4.47 → 5.03 (+0.56)K% 22.5% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.49%	—	×0.860	19.34%
BB% (unintentional) /BF	10.03%	—	×0.900	9.03%
HR / BF /BF	3.65%	÷0.909	×1.100	4.42%

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 82).

Result: FIP 4.47 → 5.03, 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 AAAScranton/Wilkes-Barre RailRiders · 10 IPFIP 2.23 → 2.40 (+0.17)K% 14.7% → 12.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.71%	—	×0.880	12.94%
BB% (unintentional) /BF	2.94%	—	×1.050	3.09%
HR / BF /BF	0.00%	÷1.006	×1.100	0.00%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, 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 101).

Result: FIP 2.23 → 2.40, 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 · 7 IPFIP 1.07 → 1.46 (+0.39)K% 24.0% → 19.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.00%	—	×0.810	19.44%
BB% (unintentional) /BF	0.00%	—	×1.100	0.00%
HR / BF /BF	0.00%	÷1.032	×1.200	0.00%

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 106).

Result: FIP 1.07 → 1.46, 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 A+Tampa Tarpons · 6 IPFIP 1.26 → 2.11 (+0.84)K% 34.8% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.78%	—	×0.770	26.78%
BB% (unintentional) /BF	8.70%	—	×1.150	10.00%
HR / BF /BF	0.00%	÷1.205	×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 141).

Result: FIP 1.26 → 2.11, 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).

2017 AAAScranton/Wilkes-Barre RailRiders · 76 IPFIP 2.68 → 2.88 (+0.21)K% 26.0% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.05%	—	×0.880	22.92%
BB% (unintentional) /BF	7.07%	—	×1.050	7.43%
HR / BF /BF	1.61%	÷1.247	×1.100	1.42%

Result: FIP 2.68 → 2.88, 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).

2017 AATrenton Thunder · 33 IPFIP 3.28 → 4.18 (+0.91)K% 26.8% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.76%	—	×0.810	21.68%
BB% (unintentional) /BF	7.04%	—	×1.100	7.75%
HR / BF /BF	2.82%	÷0.960	×1.200	3.52%

Result: FIP 3.28 → 4.18, 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 A+Tampa Yankees · 24 IPFIP 3.10 → 3.88 (+0.78)K% 19.2% → 14.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.23%	—	×0.770	14.81%
BB% (unintentional) /BF	8.65%	—	×1.150	9.95%
HR / BF /BF	0.96%	÷0.862	×1.250	1.39%

Result: FIP 3.10 → 3.88, 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 ACharleston RiverDogs · 26 IPFIP 2.92 → 3.92 (+1.00)K% 19.1% → 14.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.15%	—	×0.740	14.17%
BB% (unintentional) /BF	2.13%	—	×1.180	2.51%
HR / BF /BF	2.13%	÷0.895	×1.300	3.09%

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 79).

Result: FIP 2.92 → 3.92, 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
Domingo Germán (OGILVIE)	—	—	—	—	—	3.2%	—	5.10	20.2%	10.0%	201	+0.49	—	—	—
Kenshin Kawakami R 2009 · 3.97 FIP	34	SP-	3.97	15.7%	7.6%	2.2%	.277	4.06	15.1%	9.5%	87	+0.09	3.97	244	76
Jarrett Grube R 2016 · 4.74 FIP	34	SP-	4.74	18.9%	7.2%	4.2%	.280	4.41	15.8%	7.7%	134	-0.33	3.75	393	74
Manuel Flores R 2019 · 4.32 FIP	33	SP	4.32	17.1%	7.4%	3.1%	.291	—	—	—	—	—	3.46	515	70
Jorge Martinez R 2019 · 3.71 FIP	34	SP	3.71	16.3%	5.7%	2.3%	.348	—	—	—	—	—	3.53	214	63
Matt Buschmann R 2016 · 4.84 FIP	32	SP	4.84	12.8%	8.4%	3.2%	.325	—	—	—	—	—	4.03	277	63
Leo Medrano R 2016 · 4.34 FIP	33	SP	4.34	11.0%	7.3%	2.3%	.312	—	—	—	—	—	3.76	222	60
Albert Suárez R 2024 · 4.00 FIP	34	SP-	4.00	19.5%	6.8%	3.1%	.293	4.14	17.8%	10.6%	80	+0.14	3.58	616	59
Guillermo Moscoso R 2018 · 5.07 FIP	34	SP-	5.07	18.2%	8.4%	4.5%	.318	4.35	12.6%	5.9%	104	-0.72	3.56	486	59
David Buchanan R 2024 · 4.26 FIP	35	SP-	4.26	14.7%	6.5%	2.9%	.337	5.56	12.2%	4.1%	29	+1.30	3.88	560	58
Hiroki Kuroda R 2009 · 3.54 FIP	34	SP	3.54	17.9%	4.7%	2.5%	.270	3.43	19.1%	14.2%	618	-0.11	2.96	1,319	57
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	57
Ryan Vogelsong R 2011 · 3.65 FIP	34	SP	3.65	18.5%	7.3%	2.2%	.274	3.90	18.6%	11.3%	478	+0.25	3.14	1,184	56
Chris Smith R 2015 · 3.79 FIP	34	SP	3.79	20.0%	8.1%	2.5%	.306	4.41	18.4%	10.2%	285	+0.62	3.79	477	56
Paolo Espino R 2021 · 4.32 FIP	34	SP-	4.32	20.2%	5.1%	4.2%	.277	4.81	16.6%	10.9%	260	+0.49	3.42	933	56
Michael Nix R 2016 · 4.60 FIP	33	SP	4.60	11.9%	11.6%	1.9%	.322	—	—	—	—	—	3.82	234	55
Logan Duran R 2016 · 3.77 FIP	34	SP	3.77	15.3%	8.9%	1.5%	.299	3.66	15.5%	6.6%	29	-0.11	3.42	187	54
Angel Castro R 2017 · 3.51 FIP	34	SP	3.51	14.5%	7.4%	1.3%	.332	—	—	—	—	—	3.51	292	53
Orlando Hernandez R 2004 · 3.77 FIP	34	SP	3.77	23.4%	10.0%	2.5%	.278	4.34	20.5%	11.7%	438	+0.57	3.35	1,315	53
Josh Lindblom R 2021 · 3.79 FIP	34	SP-	3.79	22.7%	6.9%	3.2%	.319	5.07	20.8%	12.0%	133	+1.28	1.83	480	53
Francisco Rodriguez R 2017 · 4.43 FIP	34	SP	4.43	11.4%	8.2%	2.3%	.305	5.18	10.7%	1.4%	83	+0.75	3.16	334	52

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	4.5	100	23.1%	8.5%	1.54	4.62
Andrew Heaney ('25)	5.7	103	23.8%	7.0%	1.58	4.57
Dylan Bundy ('22)	4.6	130	21.9%	7.3%	1.61	4.74
Mike Foltynewicz ('21)	4.1	138	21.3%	7.8%	1.48	4.52
Dennis Bennett ('62-'68, 7 WAR*)	4.3	123	19.8%*	8.1%*	1.41*	4.40*
Brent Strom ('72-'77, 0 WAR*)	2.5	125	19.3%*	8.2%*	1.53*	4.78*
Paul Moskau ('77-'83, 3 WAR*)	3.2	91	19.8%*	8.9%*	1.50*	4.84*