Brent Headrick

P New York Yankees

Age 29 LHP 6'6" / 235 lbs MLB Svc 1.0 · Ctrl thru 2031 peak 0.9 · 2027

Overview

MLBRP40-MANPre-ArbFA 2032

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX3 levels	8	5	22	2.01	4.13	29.5%	9.5%	0.3	K 26.7% · BB 7.3% · FIP 4.12
2025	27	MIX2 levels	37	0	47	2.87	3.29	28.4%	6.8%	0.7	K 26.7% · BB 6.5% · FIP 3.35
2026	28	MLBNYY	81	0	78	2.18	2.42	30.1%	8.0%	2.0
2027PROJ	29	MLBNYY	66	0	69	3.12	3.26	29.3%	6.9%	1.1
2028PROJ95% MLB	30	MLBNYY	56	0	59	3.43	3.57	28.6%	7.2%	0.8
2029PROJ95% MLB	31	MLBNYY	49	0	51	3.66	3.81	27.9%	7.5%	0.5

Last 3 seasons WAR 3.0 · Next 3 projected WAR 2.5Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2031Service1.994First FA2032

2027Pre-Arb$0.8M2028Pre-Arb$0.8M2029Arb-1$1M2030Ext$4M2031Ext$6M

Skills · percentileStatcast 2026

K%90

xwOBA vs90

FB Velo44

Form4.12 ERA (proj 3.12) · K 32.7% (proj 29.3%) · BB 9.3% (proj 6.9%) · last 90d · 24 IP through Oct 27

CompsHideki Okajima (age 31) · Adam Liberatore (age 29) · Kyle Regnault (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 7381vR 89

ERA3.12

FIP3.26

K%29.3%

BB%6.9%

K-BB%22.4%

Proj IP72

Value2027 · WAR

Runs saved vs league avg · 72 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit+$17M ctrl surplus

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL5050

CMD6565

K†6565

Statcast Percentiles

FB Velo

p4494.1

Whiff%

p9031.8%

p9030.1%

xwOBA vs

p900.271

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

Status Pre-Arb

MLB Debut 2023

Service 1.994 yrs.days

Team Control Through 2031

First FA Year 2032

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+1.1	$9M	+$8M
2028	Pre-Arb	$0.8M	+0.8	$3M	+$2M
2029	Arb-1	$1M	+0.5	$2M	+$0.8M
2030	Ext	beyond projection horizon · no WAR estimate
2031	Ext	beyond projection horizon · no WAR estimate
Totals		$3M		$14M	+$11M

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	23	MIX MLE	2 levels	16	15	63	286	88	35	5	94%	3.9	22.9%	14.0%	8.9%	2.6%	3.71	4.36	—
2021	23	MIX RAW	2 levels	16	15	63	286	88	35	5	94%	3.9	30.8%	12.2%	18.5%	1.7%	3.71	3.00	—
2022	24	MIX MLE	2 levels	25	23	108	439	136	25	18	92%	4.3	24.4%	6.4%	18.0%	5.2%	3.32	4.68	—
2022	24	MIX RAW	2 levels	25	23	108	439	136	25	18	92%	4.3	31.0%	5.7%	25.3%	4.1%	3.32	3.44	—
2023	25	MIX MLE	2 levels	33	12	101	438	113	36	18	36%	3.1	23.1%	7.6%	15.5%	4.3%	5.10	4.49	+0.1
2023	25	MIX RAW	2 levels	33	12	101	438	113	36	18	36%	3.1	25.8%	8.2%	17.6%	4.1%	5.10	4.25	+0.4
2024	26	MIX MLE	3 levels	8	5	22	95	28	9	4	62%	2.8	26.7%	7.3%	19.4%	4.3%	2.01	4.12	+0.3
2024	26	MIX MLE	3 levels	8	5	22	95	28	9	4	62%	2.8	26.7%	7.3%	19.4%	4.3%	2.01	4.12	+0.3
2024	26	MIX RAW	3 levels	8	5	22	95	28	9	4	62%	2.8	29.5%	9.5%	20.0%	4.2%	2.01	4.13	+0.3
2025	27	MIX MLE	2 levels	37	0	47	190	54	13	6	0%	1.3	26.7%	6.5%	20.2%	3.1%	2.87	3.35	+0.7
2025	27	MIX MLE	2 levels	37	0	47	190	54	13	6	0%	1.3	26.7%	6.5%	20.2%	3.1%	2.87	3.35	+0.7
2025	27	MIX RAW	2 levels	37	0	47	190	54	13	6	0%	1.3	28.4%	6.8%	21.6%	3.2%	2.87	3.29	+0.7
2026	28	MLB MLE	New York Yankees	81	0	78	326	98	26	5	0%	1.0	30.1%	8.0%	22.1%	1.4%	2.18	2.36	+2.1
2026	28	MLB MLE	New York Yankees	81	0	78	326	98	26	5	0%	1.0	30.1%	8.0%	22.1%	1.4%	2.18	2.36	+2.1
2026	28	MLB RAW	New York Yankees	81	0	78	326	98	26	5	0%	1.0	30.1%	8.0%	22.1%	1.5%	2.18	2.42	+2.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			113	0	130	548	163	44	17	0%	1.2	29.7%	8.0%	21.7%	3.1%	3.18	3.31	+1.9
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	NYY	66	0	69	291	85	20	7	0%	1.0	29.3%	6.9%	22.4%	2.5%	3.12	3.26	+1.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	NYY	59	0	62	262	75	19	7	0%	1.1	28.6%	7.2%	21.4%	2.7%	3.33	3.47	+0.8
2029	31	MLB MLE	NYY	51	0	53	225	63	17	7	0%	1.0	27.9%	7.5%	20.3%	2.9%	3.55	3.70	+0.6
2028	30	MLB CTX	NYY	56	0	59	249	71	18	7	0%	1.1	28.6%	7.2%	21.4%	2.9%	3.43	3.57	+0.8
2029	31	MLB CTX	NYY	49	0	51	215	60	16	7	0%	1.0	27.9%	7.5%	20.3%	3.1%	3.66	3.81	+0.5
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		217	0	240	1011	294	78	31	0%	1.1	29.1%	7.7%	21.4%	3.1%	3.35	3.30	+3.6
/ 200 IP	—	RAW		181	0	200	844	245	65	26	0%	1.1	29.1%	7.7%	21.4%	3.1%	3.35	3.30	+3.0
Career	—	MLE		200	55	420	1774	448	147	64	28%	2.1	25.3%	8.3%	17.0%	3.6%	3.47	3.98	+3.3
/ 200 IP	—	MLE		95	26	200	845	213	70	30	28%	2.1	25.3%	8.3%	17.0%	3.6%	3.47	3.98	+2.7

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 AAAScranton/Wilkes-Barre RailRiders · 24 IPFIP 3.06 → 3.29 (+0.23)K% 24.5% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.49%	—	×0.860	21.06%
BB% (unintentional) /BF	7.14%	—	×0.900	6.43%
HR / BF /BF	2.04%	÷1.070	×1.100	2.10%

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 114).

Result: FIP 3.06 → 3.29, 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 AAASt. Paul Saints · 18 IPFIP 3.73 → 4.12 (+0.40)K% 31.1% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.08%	—	×0.860	26.73%
BB% (unintentional) /BF	8.11%	—	×0.900	7.30%
HR / BF /BF	4.05%	÷1.039	×1.100	4.29%

Result: FIP 3.73 → 4.12, 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 AAASt. Paul Saints · 75 IPFIP 3.82 → 4.20 (+0.37)K% 25.9% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.86%	—	×0.860	22.24%
BB% (unintentional) /BF	8.10%	—	×0.900	7.29%
HR / BF /BF	3.43%	÷1.009	×1.100	3.74%

Result: FIP 3.82 → 4.20, 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+Cedar Rapids Kernels · 65 IPFIP 2.70 → 3.87 (+1.17)K% 30.3% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.31%	—	×0.770	23.34%
BB% (unintentional) /BF	5.12%	—	×1.150	5.89%
HR / BF /BF	2.76%	÷0.948	×1.250	3.64%

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 90).

Result: FIP 2.70 → 3.87, 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).

2022 AAWichita Wind Surge · 43 IPFIP 4.49 → 5.80 (+1.31)K% 31.9% → 25.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.89%	—	×0.810	25.83%
BB% (unintentional) /BF	6.49%	—	×1.100	7.14%
HR / BF /BF	5.95%	÷0.985	×1.200	7.24%

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 97).

Result: FIP 4.49 → 5.80, 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 AFort Myers Mighty Mussels · 61 IPFIP 2.98 → 4.36 (+1.38)K% 30.9% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.94%	—	×0.740	22.89%
BB% (unintentional) /BF	11.87%	—	×1.180	14.01%
HR / BF /BF	1.80%	÷0.908	×1.300	2.58%

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 82).

Result: FIP 2.98 → 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).

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
Brent Headrick (OGILVIE)	—	—	3.26	29.3%	6.9%	2.5%	—	3.58	28.3%	20.9%	115	+0.32	—	—	—
Hideki Okajima L 2007 · 3.05 FIP	31	SU	3.05	23.2%	5.5%	2.2%	.234	3.87	20.2%	12.6%	169	+0.82	3.05	238	69
Adam Liberatore L 2016 · 2.38 FIP	29	SU	2.38	26.7%	7.4%	1.1%	.281	4.28	18.6%	9.5%	30	+1.90	2.38	124	69
Kyle Regnault L 2018 · 3.82 FIP	29	SU	3.82	27.6%	9.7%	3.3%	.367	—	—	—	—	—	2.88	204	68
Yuki Matsui L 2024 · 3.63 FIP	28	SU	3.63	26.8%	8.9%	3.0%	.242	4.25	23.9%	12.6%	140	+0.62	3.63	203	67
Mike Dunn L 2014 · 2.82 FIP	29	SU	2.82	27.3%	8.6%	1.7%	.281	3.92	25.3%	14.8%	147	+1.10	2.82	432	66
Tony Watson L 2014 · 2.45 FIP	29	SU	2.45	26.6%	4.9%	1.8%	.289	3.54	20.3%	14.6%	210	+1.09	2.21	648	66
Zac Rosscup L 2017 · 2.85 FIP	29	SU	2.85	29.5%	7.8%	2.3%	.275	4.42	26.4%	5.9%	35	+1.57	2.56	173	66
Glen Perkins L 2012 · 2.90 FIP	29	SU	2.90	27.8%	4.6%	2.8%	.269	2.93	26.9%	22.5%	181	+0.03	2.16	611	65
Ryan Buchter L 2016 · 2.74 FIP	29	SU	2.74	31.6%	11.3%	1.6%	.219	4.30	24.8%	15.3%	150	+1.56	2.37	296	65
Tim Mayza L 2021 · 2.84 FIP	29	SU	2.84	27.1%	5.7%	2.4%	.257	3.31	21.0%	15.2%	145	+0.47	2.24	584	65
Andrew Chafin L 2019 · 3.11 FIP	29	SU	3.11	30.2%	8.0%	2.8%	.346	2.88	25.7%	18.4%	126	-0.23	2.42	545	65
Brian Fuentes L 2005 · 2.92 FIP	29	SU	2.92	28.3%	9.3%	1.9%	.273	3.08	26.9%	18.5%	189	+0.16	2.08	602	64
Tyler Holton L 2024 · 2.97 FIP	28	SU	2.97	21.8%	4.5%	2.1%	.197	4.34	19.4%	13.8%	151	+1.37	2.97	439	64
Matt Thornton L 2006 · 3.43 FIP	29	SU	3.43	21.6%	7.5%	2.2%	.263	2.61	27.2%	20.5%	196	-0.82	1.71	663	64
Armando Almanza L 2002 · 4.34 FIP	29	SU	4.34	30.0%	11.6%	4.2%	.272	5.01	21.8%	12.0%	62	+0.67	2.90	211	64
Ryan O'Rourke L 2016 · 3.05 FIP	28	SU	3.05	23.4%	6.7%	1.9%	.284	4.08	22.1%	7.8%	56	+1.03	3.05	145	64
Zach Phillips L 2016 · 3.01 FIP	29	SU	3.01	27.4%	11.9%	1.3%	.370	3.20	19.2%	10.6%	86	+0.19	2.33	202	64
Scott Sauerbeck L 2001 · 3.04 FIP	29	SU	3.04	28.1%	12.1%	1.4%	.348	3.64	23.6%	11.9%	119	+0.60	2.79	386	63
Sammy Solís L 2018 · 4.39 FIP	29	SU	4.39	24.9%	9.6%	4.0%	.330	4.05	26.2%	17.3%	23	-0.34	2.51	190	63
Josh Smoker L 2018 · 3.66 FIP	29	SU	3.66	22.1%	8.4%	2.5%	.318	6.58	14.2%	3.4%	14	+2.92	2.71	230	62

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	1.6	53	29.1%	7.7%	1.11	3.26
Giovanny Gallegos ('24)	1.7	56	29.6%	6.6%	1.18	3.49
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*
Keone Kela ('21)	1.1	45	29.9%	9.2%	1.03	3.33
Blake Parker ('21)	1.7	58	26.7%	7.9%	1.30	3.47
Joe Sambito ('76-'87, 8 WAR*)	3.1	70	26.8%*	7.5%*	1.06*	3.65*
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*