Tim Hill

P New York Yankees

Age 37 LHP 6'4" / 210 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR
2024	34	MLBNYY	62	67	3.36	3.32	10.7%	5.8%	1.0
2025	35	MLBNYY	70	67	3.09	4.13	13.8%	4.8%	0.3
2026	36	MLBNYY	67	59	4.60	5.47	10.4%	4.6%	-0.6
2027PROJ	37	MLBNYY	38	40	4.51	5.05	10.8%	5.2%	-0.2
2028PROJ	38	MLBNYY	13	14	5.08	5.45	10.0%	5.9%	-0.1

Last 3 seasons WAR 0.7 · Next 2 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs39

FB Velo10

K%10

Form5.50 ERA (proj 4.51) · K 8.3% (proj 10.8%) · BB 4.2% (proj 5.2%) · last 90d · 18 IP through Oct 27

CompsBrian Shouse (age 37) · Hisanori Takahashi (age 37) · Brian Sweeney (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 108116vR 124

ERA4.51

FIP5.05

K%10.8%

BB%5.2%

K-BB%5.6%

Proj IP40

Value2027 · WAR

Runs saved vs league avg · 40 IP

Grades · Statcast · Contract

Scouting Grades

STUF3030

CTRL6060

CMD3030

K†3030

Statcast Percentiles

FB Velo

p1089.2

Whiff%

p1013.1%

p1010.4%

xwOBA vs

p390.325

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	26	MIX MLE	2 levels	44	0	63	266	62	24	9	0%	1.4	18.7%	10.1%	8.6%	4.3%	3.43	5.14	—
2016	26	MIX RAW	2 levels	44	0	63	266	62	24	9	0%	1.4	23.3%	9.0%	14.3%	3.4%	3.43	4.13	—
2017	27	MIX MLE	2 levels	40	0	74	322	84	22	2	0%	1.9	20.5%	6.3%	14.2%	0.7%	4.26	2.57	—
2017	27	MIX RAW	2 levels	40	0	74	322	84	22	2	0%	1.9	26.1%	6.8%	19.3%	0.6%	4.26	2.07	—
2018	28	MLB MLE	Kansas City Royals	70	0	46	198	42	14	4	0%	0.7	21.2%	7.1%	14.1%	2.2%	4.53	3.40	+0.6
2018	28	MLB RAW	Kansas City Royals	70	0	46	198	42	14	4	0%	0.7	21.2%	7.1%	14.1%	2.0%	4.53	3.32	+0.7
2019	29	MIX MLE	2 levels	73	0	69	280	69	17	6	0%	0.9	23.4%	6.2%	17.2%	2.3%	2.99	3.18	+1.1
2019	29	MIX RAW	2 levels	73	0	69	280	69	17	6	0%	0.9	24.6%	6.1%	18.6%	2.1%	2.99	2.97	+1.3
2020	30	MLB MLE	San Diego Padres	23	0	18	79	20	5	3	0%	0.8	25.3%	6.3%	19.0%	3.7%	4.50	3.80	+0.2
2020	30	MLB RAW	San Diego Padres	23	0	18	79	20	5	3	0%	0.8	25.3%	6.3%	19.0%	3.8%	4.50	3.88	+0.1
2021	31	MLB MLE	San Diego Padres	78	0	60	255	56	18	9	0%	0.8	22.0%	7.1%	14.9%	3.4%	3.62	4.03	+0.4
2021	31	MLB RAW	San Diego Padres	78	0	60	255	56	18	9	0%	0.8	22.0%	7.1%	14.9%	3.5%	3.62	4.09	+0.3
2022	32	MLB MLE	San Diego Padres	55	0	48	199	25	13	1	0%	0.9	12.6%	6.5%	6.0%	0.5%	3.56	3.14	+0.8
2022	32	MLB RAW	San Diego Padres	55	0	48	199	25	13	1	0%	0.9	12.6%	6.5%	6.0%	0.5%	3.56	3.14	+0.8
2023	33	MIX MLE	3 levels	50	0	46	214	28	14	7	0%	0.9	12.9%	6.9%	5.9%	3.4%	6.26	4.75	-0.1
2023	33	MIX RAW	3 levels	50	0	46	214	28	14	7	0%	0.9	13.1%	6.5%	6.5%	3.3%	6.26	4.77	-0.1
2024	34	MLB MLE	New York Yankees	62	0	67	291	31	17	2	0%	1.1	10.7%	5.8%	4.8%	0.6%	3.36	3.29	+1.0
2024	34	MLB MLE	New York Yankees	62	0	67	291	31	17	2	0%	1.1	10.7%	5.8%	4.8%	0.6%	3.36	3.29	+1.0
2024	34	MLB RAW	New York Yankees	62	0	67	291	31	17	2	0%	1.1	10.7%	5.8%	4.8%	0.7%	3.36	3.32	+1.0
2025	35	MLB MLE	New York Yankees	70	0	67	269	37	13	8	0%	1.0	13.8%	4.8%	8.9%	2.8%	3.09	4.08	+0.4
2025	35	MLB MLE	New York Yankees	70	0	67	269	37	13	8	0%	1.0	13.8%	4.8%	8.9%	2.8%	3.09	4.08	+0.4
2025	35	MLB RAW	New York Yankees	70	0	67	269	37	13	8	0%	1.0	13.8%	4.8%	8.9%	3.0%	3.09	4.13	+0.3
2026	36	MLB MLE	New York Yankees	67	0	59	241	25	11	12	0%	0.9	10.4%	4.6%	5.8%	4.7%	4.60	5.36	-0.6
2026	36	MLB MLE	New York Yankees	67	0	59	241	25	11	12	0%	0.9	10.4%	4.6%	5.8%	4.7%	4.60	5.36	-0.6
2026	36	MLB RAW	New York Yankees	67	0	59	241	25	11	12	0%	0.9	10.4%	4.6%	5.8%	5.0%	4.60	5.47	-0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			519	0	448	1895	301	116	50	0%	0.9	15.9%	6.1%	9.8%	2.6%	3.94	3.98	+3.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	37	MLB	NYY	38	0	40	169	18	9	6	0%	1.1	10.8%	5.2%	5.6%	3.3%	4.51	5.05	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	38	MLB MLE	NYY	14	0	14	60	6	4	2	0%	1.0	10.0%	5.9%	4.1%	3.8%	5.08	5.45	-0.1
2028	38	MLB CTX	NYY	13	0	14	59	6	3	2	0%	1.1	10.0%	5.9%	4.1%	3.8%	5.08	5.45	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		533	0	462	1955	307	120	52	0%	0.9	15.7%	6.1%	9.6%	2.7%	3.97	4.02	+2.9
/ 200 IP	—	RAW		230	0	200	846	133	52	22	0%	0.9	15.7%	6.1%	9.6%	2.7%	3.97	4.02	+1.3
Career	—	MLE		632	0	616	2614	445	170	65	0%	1.0	17.0%	6.5%	10.5%	2.5%	3.90	3.85	+2.8
/ 200 IP	—	MLE		205	0	200	848	144	55	21	0%	1.0	17.0%	6.5%	10.5%	2.5%	3.90	3.85	+1.2

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.

2019 AAAOmaha Storm Chasers · 30 IPFIP 2.53 → 2.89 (+0.36)K% 25.2% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.21%	—	×0.880	22.18%
BB% (unintentional) /BF	5.04%	—	×1.050	5.29%
HR / BF /BF	1.68%	÷1.023	×1.100	1.81%

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 105).

Result: FIP 2.53 → 2.89, 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 AANorthwest Arkansas Naturals · 69 IPFIP 2.06 → 2.57 (+0.51)K% 25.3% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.34%	—	×0.810	20.52%
BB% (unintentional) /BF	5.74%	—	×1.100	6.32%
HR / BF /BF	0.68%	÷1.114	×1.200	0.73%

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 123).

Result: FIP 2.06 → 2.57, 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 A+Wilmington Blue Rocks · 5 IPFIP 2.61 → 3.65 (+1.04)K% 34.6% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.62%	—	×0.770	26.65%
BB% (unintentional) /BF	19.23%	—	×1.150	22.12%
HR / BF /BF	0.00%	÷0.810	×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 62).

Result: FIP 2.61 → 3.65, 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 AANorthwest Arkansas Naturals · 45 IPFIP 3.86 → 4.82 (+0.97)K% 26.1% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.09%	—	×0.810	21.13%
BB% (unintentional) /BF	9.24%	—	×1.100	10.16%
HR / BF /BF	3.26%	÷0.967	×1.200	4.04%

Result: FIP 3.86 → 4.82, 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+Wilmington Blue Rocks · 18 IPFIP 4.75 → 5.87 (+1.12)K% 17.1% → 13.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.07%	—	×0.770	13.15%
BB% (unintentional) /BF	8.54%	—	×1.150	9.82%
HR / BF /BF	3.66%	÷0.954	×1.250	4.79%

Result: FIP 4.75 → 5.87, 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).

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
Tim Hill (OGILVIE)	—	—	5.05	10.8%	5.2%	3.3%	—	5.45	10.0%	4.1%	14	+0.40	—	—	—
Brian Shouse L 2006 · 4.19 FIP	37	SU	4.19	13.2%	7.5%	2.3%	.269	3.37	15.3%	11.0%	127	-0.82	2.32	339	69
Hisanori Takahashi L 2012 · 4.04 FIP	37	SU	4.04	24.5%	6.1%	4.1%	.295	—	—	—	—	—	3.50	240	46
Brian Sweeney R 2010 · 4.63 FIP	36	SU	4.63	9.5%	3.4%	3.5%	.226	—	—	—	—	—	3.03	108	31
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	31
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	31
Yoshihisa Hirano R 2020 · 5.02 FIP	36	SU	5.02	17.5%	12.7%	3.3%	.381	—	—	—	—	—	3.45	132	29
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	29
Seunghwan Oh R 2019 · 5.75 FIP	37	SU	5.75	18.2%	6.8%	6.0%	.383	—	—	—	—	—	1.87	226	27
Pete Walker R 2006 · 4.45 FIP	37	SU	4.45	19.6%	8.0%	3.6%	.337	—	—	—	—	—	4.45	327	26
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	25
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	25
Francisco Del Rosario R 2017 · 4.15 FIP	36	SU	4.15	16.4%	10.0%	2.1%	.267	6.35	11.9%	-0.6%	77	+2.20	3.93	194	24
Jonathan Castellanos R 2019 · 5.24 FIP	37	SW	5.24	11.0%	9.0%	3.5%	.348	—	—	—	—	—	3.40	394	15

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	2.5	50	15.3%	6.8%	1.06	4.02
Shawn Camp ('14)	3.0	59	15.6%	6.8%	0.99	4.41
Todd Coffey ('12)	2.2	63	17.2%	7.2%	1.01	4.10
Manny Corpas ('13)	1.9	53	16.6%	7.0%	0.91	4.14
Larry Casian ('90-'98, 0 WAR*)	1.2	40	14.7%*	6.8%*	1.25*	4.37*
Tony Castillo ('88-'98, 4 WAR*)	2.6	59	18.5%*	7.3%*	0.98*	3.76*
Donn Pall ('88-'98, 3 WAR*)	2.5	63	17.1%*	6.2%*	1.20*	3.86*