Colten Brewer

P Scranton/Wilkes-Barre RailRiders

Age 34 RHP 6'4" / 222 lbs AAA peak 0.1 · 2027

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	30	MIX2 levels	18	2	28	2.22	4.44	24.3%	8.1%	0.0	K 25.7% · BB 7.0% · FIP 3.36
2024	31	MIX2 levels	32	0	39	3.96	3.26	24.6%	9.9%	0.6	K 22.9% · BB 9.5% · FIP 3.35
2025	32	AAAScranton/Wilk…	22	0	30	3.94	3.77	27.1%	12.7%	—	K 23.3% · BB 11.4% · FIP 4.01
2026	33	No MLB games played
2027PROJ	34	MLBNYY	13	0	14	4.44	4.48	23.8%	10.8%	0.0
2028PROJ6% MLB	35	MLBNYY	5	0	5	4.67	4.82	22.8%	11.3%	-0.0
2029PROJMLE	36	MLBNYY	—	—	0	4.98	5.19	21.8%	11.9%	—

Last 3 seasons WAR 0.6 · Next 3 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

K%55

FB Velo47

xwOBA vs42

CompsFernando Rodriguez Jr. (age 34) · Keiichi Yabu (age 36) · Scott McGough (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 118110vR 102

ERA4.44

FIP4.48

K%23.8%

BB%10.8%

K-BB%13.0%

Proj IP139

Value2027 · WAR

Runs saved vs league avg · 139 IP

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL3535

CMD4040

K†5555

Statcast Percentiles

FB Velo

p4794.3

Whiff%

p5626.3%

p5523.2%

xwOBA vs

p420.321

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)
2015	22	A MLE	West Virginia Power	22	22	119	511	99	37	9	100%	5.4	14.3%	8.5%	5.8%	2.0%	4.90	4.08	—
2015	22	A RAW	West Virginia Power	22	22	119	511	99	37	9	100%	5.4	19.4%	7.2%	12.1%	1.8%	4.90	3.35	—
2016	23	A+ MLE	Bradenton Marauders	18	13	70	322	66	27	5	72%	3.9	15.8%	9.6%	6.1%	1.8%	4.09	3.96	—
2016	23	A+ RAW	Bradenton Marauders	18	13	70	322	66	27	5	72%	3.9	20.5%	8.4%	12.1%	1.6%	4.09	3.30	—
2017	24	MIX MLE	3 levels	41	0	61	262	69	15	2	0%	1.5	19.6%	6.7%	12.9%	0.8%	2.82	2.72	—
2017	24	MIX RAW	3 levels	41	0	61	262	69	15	2	0%	1.5	26.3%	5.7%	20.6%	0.8%	2.82	2.00	—
2018	25	MIX MLE	2 levels	48	0	58	243	73	21	3	0%	1.2	28.6%	7.6%	21.0%	1.6%	4.06	2.54	+1.4
2018	25	MIX RAW	2 levels	48	0	58	243	73	21	3	0%	1.2	30.0%	8.6%	21.4%	1.2%	4.06	2.34	+1.5
2019	26	MIX MLE	2 levels	67	0	66	309	62	40	8	0%	1.0	19.7%	13.1%	6.6%	2.7%	4.25	4.56	-0.0
2019	26	MIX RAW	2 levels	67	0	66	309	62	40	8	0%	1.0	20.1%	12.9%	7.1%	2.6%	4.25	4.62	-0.1
2020	27	MLB MLE	Boston Red Sox	11	4	26	122	25	14	6	36%	2.3	20.5%	11.5%	9.0%	5.0%	5.61	5.59	-0.3
2020	27	MLB RAW	Boston Red Sox	11	4	26	122	25	14	6	36%	2.3	20.5%	11.5%	9.0%	4.9%	5.61	5.83	-0.4
2021	28	MIX MLE	3 levels	16	1	26	119	28	15	2	6%	1.6	20.6%	12.3%	8.3%	2.2%	5.47	4.11	+0.1
2021	28	MIX RAW	3 levels	16	1	26	119	28	15	2	6%	1.6	23.5%	12.6%	10.9%	1.7%	5.47	3.67	+0.3
2022	29	AAA MLE	Omaha Storm Chasers	36	0	40	169	42	18	7	0%	1.1	21.9%	11.2%	10.7%	4.6%	4.76	5.21	—
2022	29	AAA RAW	Omaha Storm Chasers	36	0	40	169	42	18	7	0%	1.1	24.9%	10.7%	14.2%	4.1%	4.76	4.64	—
2023	30	MIX MLE	2 levels	18	2	28	111	27	9	5	11%	1.6	25.7%	7.0%	18.7%	2.8%	2.22	3.36	+0.4
2023	30	MIX RAW	2 levels	18	2	28	111	27	9	5	11%	1.6	24.3%	8.1%	16.2%	4.5%	2.22	4.44	+0.0
2024	31	MIX MLE	2 levels	32	0	39	171	42	17	3	0%	1.2	22.9%	9.5%	13.5%	1.8%	3.96	3.35	+0.6
2024	31	MIX MLE	2 levels	32	0	39	171	42	17	3	0%	1.2	22.9%	9.5%	13.5%	1.8%	3.96	3.35	+0.6
2024	31	MIX RAW	2 levels	32	0	39	171	42	17	3	0%	1.2	24.6%	9.9%	14.6%	1.8%	3.96	3.26	+0.6
2025	32	AAA MLE	Scranton/Wilkes-Barre RailRiders	22	0	30	118	32	15	3	0%	1.3	23.3%	11.4%	11.9%	2.6%	3.94	4.01	—
2025	32	AAA MLE	Scranton/Wilkes-Barre RailRiders	22	0	30	118	32	15	3	0%	1.3	23.3%	11.4%	11.9%	2.6%	3.94	4.01	—
2025	32	AAA RAW	Scranton/Wilkes-Barre RailRiders	22	0	30	118	32	15	3	0%	1.3	27.1%	12.7%	14.4%	2.5%	3.94	3.77	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			100	4	120	562	114	69	16	4%	1.2	20.3%	12.3%	8.0%	2.8%	5.10	4.66	-0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	NYY	13	0	14	59	14	6	2	0%	1.1	23.8%	10.8%	13.0%	3.0%	4.44	4.48	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	NYY	95	0	100	422	96	48	14	0%	1.1	22.8%	11.3%	11.5%	3.3%	4.67	4.82	-0.3
2029	36	MLB MLE	NYY	71	0	75	317	69	38	12	0%	1.1	21.8%	11.9%	9.9%	3.7%	4.98	5.19	-0.5
2028	35	MLB CTX	NYY	5	0	5	21	5	2	1	0%	1.0	22.8%	11.3%	11.5%	3.3%	4.67	4.82	-0.0
2029	36	MLB CTX	NYY	—	—	0	—	—	—	—	—	—	21.8%	11.9%	9.9%	3.7%	4.98	5.19	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		105	4	125	585	119	72	17	4%	1.2	20.4%	12.2%	8.1%	2.9%	5.08	4.50	+0.1
/ 200 IP	—	RAW		168	6	200	933	190	115	27	4%	1.2	20.4%	12.2%	8.1%	2.9%	5.08	4.50	+0.1
Career	—	MLE		331	42	562	2457	487	236	56	13%	1.7	19.8%	9.6%	10.2%	2.3%	4.21	3.89	-1.0
/ 200 IP	—	MLE		118	15	200	874	173	84	20	13%	1.7	19.8%	9.6%	10.2%	2.3%	4.21	3.89	-0.7

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 · 30 IPFIP 3.82 → 4.01 (+0.20)K% 27.1% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.12%	—	×0.860	23.32%
BB% (unintentional) /BF	12.71%	—	×0.900	11.44%
HR / BF /BF	2.54%	÷1.070	×1.100	2.61%

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 3.82 → 4.01, 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 AAAIowa Cubs · 18 IPFIP 3.66 → 3.86 (+0.21)K% 26.3% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.32%	—	×0.860	22.63%
BB% (unintentional) /BF	10.53%	—	×0.900	9.47%
HR / BF /BF	2.63%	÷1.079	×1.100	2.68%

Result: FIP 3.66 → 3.86, 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 AAAScranton/Wilkes-Barre RailRiders · 20 IPFIP 2.99 → 3.36 (+0.37)K% 29.9% → 25.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.87%	—	×0.860	25.69%
BB% (unintentional) /BF	7.79%	—	×0.900	7.01%
HR / BF /BF	2.60%	÷1.017	×1.100	2.81%

Result: FIP 2.99 → 3.36, 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).

2022 AAAOmaha Storm Chasers · 40 IPFIP 4.62 → 5.21 (+0.59)K% 24.9% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.85%	—	×0.880	21.87%
BB% (unintentional) /BF	10.65%	—	×1.050	11.18%
HR / BF /BF	4.14%	÷0.984	×1.100	4.63%

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 97).

Result: FIP 4.62 → 5.21, 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 AAAWorcester Red Sox · 18 IPFIP 4.03 → 4.11 (+0.08)K% 23.4% → 20.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.38%	—	×0.880	20.57%
BB% (unintentional) /BF	11.69%	—	×1.050	12.27%
HR / BF /BF	2.60%	÷1.318	×1.100	2.17%

Result: FIP 4.03 → 4.11, 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).

2021 ROKFCL Red Sox · 7 IPFIP 1.95 → 2.97 (+1.02)K% 27.3% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.27%	—	×0.680	18.55%
BB% (unintentional) /BF	9.09%	—	×1.250	11.36%
HR / BF /BF	0.00%	÷0.951	×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 90).

Result: FIP 1.95 → 2.97, 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 AAAPawtucket Red Sox · 11 IPFIP 5.14 → 5.51 (+0.38)K% 17.9% → 15.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.86%	—	×0.880	15.71%
BB% (unintentional) /BF	12.50%	—	×1.050	13.12%
HR / BF /BF	3.57%	÷1.038	×1.100	3.79%

Result: FIP 5.14 → 5.51, 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 AAAEl Paso Chihuahuas · 48 IPFIP 2.12 → 2.54 (+0.42)K% 32.5% → 28.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.47%	—	×0.880	28.58%
BB% (unintentional) /BF	7.22%	—	×1.050	7.58%
HR / BF /BF	1.55%	÷1.045	×1.100	1.63%

Result: FIP 2.12 → 2.54, 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).

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
Colten Brewer (OGILVIE)	—	—	4.48	23.8%	10.8%	3.0%	—	4.98	22.4%	10.8%	175	+0.50	—	—	—
Fernando Rodriguez Jr. R 2018 · 4.07 FIP	34	SW	4.07	23.7%	9.9%	3.1%	.253	5.11	25.0%	13.8%	32	+1.04	3.34	335	64
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	63
Scott McGough R 2024 · 4.56 FIP	34	SU	4.56	18.6%	12.2%	2.7%	.289	3.82	20.3%	13.1%	57	-0.74	3.55	429	62
Giovanni Carrara R 2002 · 4.78 FIP	34	SU	4.78	14.5%	7.2%	3.6%	.239	3.83	17.1%	7.9%	158	-0.95	2.50	462	61
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	61
Chris Jakubauskas R 2011 · 4.42 FIP	32	SW	4.42	15.7%	7.9%	3.0%	.339	—	—	—	—	—	4.42	165	61
Jean Machi R 2016 · 4.36 FIP	34	SU	4.36	18.3%	6.6%	3.6%	.282	4.12	18.6%	12.0%	67	-0.24	2.16	306	60
Yoshihisa Hirano R 2018 · 3.45 FIP	34	SU	3.45	22.5%	7.3%	2.4%	.242	3.97	24.6%	15.2%	65	+0.52	3.45	132	60
Blake Parker R 2019 · 4.65 FIP	34	SU	4.65	25.5%	8.6%	4.8%	.258	4.26	24.9%	15.4%	87	-0.39	2.52	406	59
Brendan Donnelly R 2005 · 4.02 FIP	34	SU	4.02	19.6%	5.9%	3.3%	.264	4.02	17.6%	8.5%	98	-0.00	2.23	385	57
Tiago Da Silva R 2019 · 3.95 FIP	34	SW	3.95	15.0%	7.2%	2.2%	.365	—	—	—	—	—	2.21	287	57
Ivan Maldonado R 2015 · 4.60 FIP	35	SW	4.60	12.8%	8.7%	2.7%	.269	5.41	6.4%	-3.3%	104	+0.81	4.60	172	57
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	57
Greg Burke R 2015 · 3.61 FIP	32	SU	3.61	22.1%	7.3%	2.7%	.241	—	—	—	—	—	3.61	139	57
Juan Sandoval R 2015 · 3.82 FIP	34	SU	3.82	15.4%	6.0%	2.3%	.294	3.33	17.4%	8.8%	116	-0.49	3.24	225	56
Josh Lueke R 2019 · 4.11 FIP	34	SU	4.11	20.4%	6.4%	3.5%	.311	—	—	—	—	—	2.29	191	56
Zack Segovia R 2016 · 3.33 FIP	33	SU	3.33	20.2%	5.9%	2.2%	.312	4.55	17.6%	4.0%	57	+1.22	3.33	144	56
Rafael Martín R 2017 · 3.40 FIP	33	SU	3.40	20.4%	5.1%	2.5%	.305	4.71	22.5%	16.5%	47	+1.31	2.94	227	56
Diego Moreno R 2021 · 4.75 FIP	34	SU	4.75	18.6%	9.4%	3.7%	.232	—	—	—	—	—	2.29	187	55
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	54

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	2.2	72	22.2%	11.6%	1.22	4.77
Tim Birtsas ('85-'90, -0 WAR*)	1.6	82	21.4%*	11.7%*	1.31*	4.63*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
David West ('88-'98, 1 WAR*)	2.8	71	22.1%*	12.1%*	1.28*	4.79*
Britt Reames ('06)	1.1	73	20.7%	12.0%	1.32	5.28
Jake Faria ('23)	1.0	68	20.9%	10.3%	1.32	4.87
Justin Miller ('10)	1.9	63	18.1%	11.3%	1.17	4.82