Cole Henry

P Rochester Red Wings

Age 28 RHP 6'4" / 200 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	8	5	16	3.31	5.18	23.0%	18.9%	—	K 17.3% · BB 16.2% · FIP 5.88
2025	26	MIX2 levels	59	0	55	4.12	4.58	22.3%	13.5%	-0.0	K 21.6% · BB 12.9% · FIP 4.50
2026	27	MIX3 levels	34	2	36	6.81	4.75	21.7%	5.4%	-0.1	K 19.2% · BB 5.4% · FIP 4.99
2027PROJ	28	MLBWSH	47	0	49	5.01	5.12	21.0%	11.6%	-0.3
2028PROJ85% MLB	29	MLBWSH	28	0	29	5.09	5.20	20.7%	11.6%	-0.2
2029PROJ88% MLB	30	MLBWSH	18	0	19	5.21	5.34	20.2%	11.7%	-0.2

Last 3 seasons WAR -0.1 · Next 3 projected WAR -0.7Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%43

FB Velo41

xwOBA vs10

CompsSpencer Bivens (age 28) · Luis Mateo (age 27) · Wirfin Obispo (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 130122vR 114

ERA5.01

FIP5.12

K%21.0%

BB%11.6%

K-BB%9.5%

Proj IP60

Value2027 · WAR

Runs saved vs league avg · 60 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL2525

CMD3535

K†5050

Statcast Percentiles

FB Velo

p4193.9

Whiff%

p3623.3%

p4321.1%

xwOBA vs

p100.374

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)
2021	22	MIX MLE	2 levels	11	10	47	183	70	12	3	91%	4.3	29.8%	7.8%	22.0%	2.5%	2.30	2.96	—
2021	22	MIX RAW	2 levels	11	10	47	183	70	12	3	91%	4.3	38.3%	6.6%	31.7%	1.6%	2.30	1.72	—
2022	23	MIX MLE	2 levels	9	9	32	119	34	11	2	100%	3.5	26.7%	11.6%	15.0%	1.4%	1.71	3.11	—
2022	23	MIX RAW	2 levels	9	9	32	119	34	11	2	100%	3.5	28.6%	9.2%	19.3%	1.7%	1.71	2.82	—
2023	24	MIX MLE	3 levels	14	10	33	148	37	16	6	71%	2.4	18.7%	15.7%	3.0%	5.9%	6.21	6.76	—
2023	24	MIX RAW	3 levels	14	10	33	148	37	16	6	71%	2.4	25.0%	10.8%	14.2%	4.1%	6.21	4.66	—
2024	25	MIX MLE	2 levels	8	5	16	74	17	14	2	62%	2.0	17.3%	16.2%	1.0%	4.0%	3.31	5.88	—
2024	25	MIX MLE	2 levels	8	5	16	74	17	14	2	62%	2.0	17.3%	16.2%	1.0%	4.0%	3.31	5.88	—
2024	25	MIX RAW	2 levels	8	5	16	74	17	14	2	62%	2.0	23.0%	18.9%	4.1%	2.7%	3.31	5.18	—
2025	26	MIX MLE	2 levels	59	0	55	251	56	34	7	0%	0.9	21.6%	12.9%	8.7%	2.9%	4.12	4.50	+0.0
2025	26	MIX MLE	2 levels	59	0	55	251	56	34	7	0%	0.9	21.6%	12.9%	8.7%	2.9%	4.12	4.50	+0.0
2025	26	MIX RAW	2 levels	59	0	55	251	56	34	7	0%	0.9	22.3%	13.5%	8.8%	2.8%	4.12	4.58	-0.0
2026	27	MIX MLE	3 levels	34	2	36	166	36	9	8	6%	1.0	19.2%	5.4%	13.8%	5.2%	6.81	4.99	-0.2
2026	27	MIX MLE	3 levels	34	2	36	166	36	9	8	6%	1.0	19.2%	5.4%	13.8%	5.2%	6.81	4.99	-0.2
2026	27	MIX RAW	3 levels	34	2	36	166	36	9	8	6%	1.0	21.7%	5.4%	16.3%	4.8%	6.81	4.75	-0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			68	0	66	311	67	38	11	0%	1.0	21.5%	12.2%	9.3%	3.5%	5.02	4.95	-0.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	WSH	47	0	49	207	44	24	7	0%	1.0	21.0%	11.6%	9.5%	3.6%	5.01	5.12	-0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	WSH	32	0	34	141	29	16	5	0%	1.0	20.7%	11.6%	9.1%	3.6%	5.09	5.20	-0.2
2029	30	MLB MLE	WSH	20	0	21	89	18	10	3	0%	1.1	20.2%	11.7%	8.5%	3.8%	5.21	5.34	-0.2
2028	29	MLB CTX	WSH	28	0	29	122	25	14	4	0%	1.0	20.7%	11.6%	9.1%	3.6%	5.09	5.20	-0.2
2029	30	MLB CTX	WSH	18	0	19	80	16	9	3	0%	1.1	20.2%	11.7%	8.5%	3.8%	5.21	5.34	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		113	0	114	510	108	61	18	0%	1.0	21.1%	12.0%	9.2%	3.6%	5.07	4.81	-0.3
/ 200 IP	—	RAW		199	0	200	899	190	107	32	0%	1.0	21.1%	12.0%	9.2%	3.6%	5.07	4.81	-0.6
Career	—	MLE		135	36	219	941	213	105	34	27%	1.6	22.6%	11.1%	11.5%	3.6%	4.07	4.58	-0.8
/ 200 IP	—	MLE		123	33	200	861	195	96	31	27%	1.6	22.6%	11.1%	11.5%	3.6%	4.07	4.58	-1.3

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 AAARochester Red Wings · 21 IPFIP 4.01 → 4.46 (+0.45)K% 20.4% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.43%	—	×0.860	17.57%
BB% (unintentional) /BF	2.15%	—	×0.900	1.94%
HR / BF /BF	4.30%	÷1.000	×1.100	4.73%

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 100).

Result: FIP 4.01 → 4.46, 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).

2024 AAHarrisburg Senators · 14 IPFIP 4.97 → 5.88 (+0.91)K% 21.3% → 17.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.31%	—	×0.810	17.26%
BB% (unintentional) /BF	14.75%	—	×1.100	16.23%
HR / BF /BF	3.28%	÷0.990	×1.200	3.98%

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 98).

Result: FIP 4.97 → 5.88, 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).

2023 AAHarrisburg Senators · 18 IPFIP 5.98 → 6.76 (+0.78)K% 23.1% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.810	18.69%
BB% (unintentional) /BF	14.29%	—	×1.100	15.71%
HR / BF /BF	5.49%	÷1.115	×1.200	5.92%

Result: FIP 5.98 → 6.76, 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 A+Wilmington Blue Rocks · 8 IPFIP 4.73 → 5.88 (+1.15)K% 16.1% → 12.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.13%	—	×0.770	12.42%
BB% (unintentional) /BF	9.68%	—	×1.150	11.13%
HR / BF /BF	3.23%	÷0.913	×1.250	4.42%

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 83).

Result: FIP 4.73 → 5.88, 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).

2023 AFredericksburg Nationals · 7 IPFIP -0.47 → 0.46 (+0.93)K% 42.3% → 31.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	42.31%	—	×0.740	31.31%
BB% (unintentional) /BF	0.00%	—	×1.180	0.00%
HR / BF /BF	0.00%	÷0.917	×1.300	0.00%

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 83).

Result: FIP -0.47 → 0.46, 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).

2022 AAHarrisburg Senators · 24 IPFIP 2.31 → 3.11 (+0.81)K% 32.9% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.94%	—	×0.810	26.68%
BB% (unintentional) /BF	10.59%	—	×1.100	11.65%
HR / BF /BF	1.18%	÷0.979	×1.200	1.44%

Result: FIP 2.31 → 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).

2022 AAARochester Red Wings · 8 IPFIP 3.97 → 4.21 (+0.24)K% 17.6% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.65%	—	×0.880	15.53%
BB% (unintentional) /BF	5.88%	—	×1.050	6.18%
HR / BF /BF	2.94%	÷1.084	×1.100	2.98%

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 117).

Result: FIP 3.97 → 4.21, 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+Wilmington Blue Rocks · 43 IPFIP 1.70 → 2.96 (+1.26)K% 38.7% → 29.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.65%	—	×0.770	29.76%
BB% (unintentional) /BF	6.75%	—	×1.150	7.76%
HR / BF /BF	1.84%	÷0.906	×1.250	2.54%

Result: FIP 1.70 → 2.96, 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
Cole Henry (OGILVIE)	—	—	5.12	21.0%	11.6%	3.6%	—	5.25	20.5%	8.9%	54	+0.13	—	—	—
Spencer Bivens R 2022 · 4.86 FIP	28	SU	4.86	19.8%	13.5%	3.1%	.265	3.85	18.1%	10.3%	272	-1.01	3.52	391	77
Luis Mateo R 2017 · 4.60 FIP	27	SU	4.60	17.6%	11.2%	2.9%	.309	5.55	8.6%	-4.8%	43	+0.95	3.48	160	76
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	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
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	75
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	74
Cole McDonald R 2024 · 5.01 FIP	27	SU	5.01	20.9%	12.7%	3.8%	.281	—	—	—	—	—	2.81	153	74
Tyler Yates R 2006 · 4.17 FIP	28	SU	4.17	21.2%	10.6%	2.8%	.254	3.70	20.7%	11.1%	151	-0.47	3.23	248	74
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	74
Josh Lueke R 2013 · 4.09 FIP	28	SU	4.09	25.3%	11.1%	3.1%	.333	3.28	24.6%	20.9%	90	-0.81	2.29	191	73
Jeff Fulchino R 2008 · 4.62 FIP	28	SU	4.62	16.7%	11.1%	2.8%	.380	3.86	21.0%	12.4%	164	-0.76	3.36	178	73
Fernery Ozuna R 2023 · 5.65 FIP	27	SU	5.65	19.0%	11.6%	4.9%	.275	—	—	—	—	—	3.84	157	73
Arcenio Leon R 2015 · 4.73 FIP	28	SU	4.73	17.9%	12.5%	2.9%	.450	3.37	18.0%	9.1%	85	-1.36	3.00	115	73
Jose Veras R 2009 · 5.13 FIP	28	SU	5.13	17.8%	12.4%	3.6%	.228	3.57	26.3%	14.0%	186	-1.56	3.37	422	73
Carlos Fisher R 2011 · 4.33 FIP	28	SU	4.33	15.5%	9.1%	2.5%	.275	—	—	—	—	—	2.48	245	73
Mike Adams R 2022 · 5.36 FIP	27	SU	5.36	17.1%	11.2%	4.2%	.326	—	—	—	—	—	3.65	109	73
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	73
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	73
Francisco Del Rosario R 2007 · 3.93 FIP	26	SU	3.93	19.7%	9.4%	2.4%	.356	—	—	—	—	—	3.93	194	72
Ronald Peña R 2019 · 4.55 FIP	27	SU	4.55	20.5%	12.6%	2.9%	.355	4.49	16.5%	6.1%	39	-0.06	3.72	187	72

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	0.9	45	21.1%	12.0%	1.39	5.05
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Scott Proctor ('11)	1.7	57	19.0%	10.9%	1.52	4.78
John Hudek ('99)	1.0	40	23.0%	13.7%	1.30	4.43
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*