Colin Rea

P Chicago Cubs

Age 37 RHP 6'5" / 220 lbs MLB peak 0.6 · 2027

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR
2024	34	MLBMIL	32	27	168	4.29	4.49	18.9%	5.9%	1.8
2025	35	MLBCHC	32	27	159	3.95	3.97	19.2%	6.6%	2.7
2026	36	MLBCHC	34	19	137	4.34	4.65	17.2%	8.0%	1.2
2027PROJ	37	MLBCHC	14	14	87	4.61	4.80	17.9%	7.4%	0.6
2028PROJ	38	MLBCHC	8	8	45	4.99	5.24	16.8%	8.1%	0.1
2029PROJ	39	MLBCHC	4	4	21	5.40	5.67	15.7%	8.8%	-0.1

Last 3 seasons WAR 5.7 · Next 3 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo40

xwOBA vs17

K%16

Form2.84 ERA (proj 4.61) · K 17.8% (proj 17.9%) · BB 6.9% (proj 7.4%) · last 90d · 25 IP through Oct 27

CompsMasato Yoshii (age 37) · Kenshin Kawakami (age 35) · Hiroki Kuroda (age 37)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 127119vR 111

ERA4.61

FIP4.80

K%17.9%

BB%7.4%

K-BB%10.6%

Proj IP87

Value2027 · WAR

Runs saved vs league avg · 87 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p4093.8

Whiff%

p1119.8%

p1617.2%

xwOBA vs

p170.351

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	25	MIX MLE	3 levels	24	24	133	536	106	33	5	100%	5.6	17.2%	6.5%	10.7%	1.1%	2.50	3.05	+3.9
2015	25	MIX RAW	3 levels	24	24	133	536	106	33	5	100%	5.6	19.8%	6.2%	13.6%	0.9%	2.50	2.74	+4.5
2016	26	MIX MLE	2 levels	21	20	104	459	82	41	12	95%	4.9	17.6%	8.8%	8.8%	2.8%	4.86	4.26	+1.4
2016	26	MIX RAW	2 levels	21	20	104	459	82	41	12	95%	4.9	17.9%	8.9%	8.9%	2.6%	4.86	4.21	+1.5
2018	28	MIX MLE	2 levels	18	15	75	341	70	36	14	83%	4.2	17.6%	11.3%	6.4%	4.7%	5.73	5.61	—
2018	28	MIX RAW	2 levels	18	15	75	341	70	36	14	83%	4.2	20.5%	10.6%	10.0%	4.1%	5.73	5.09	—
2019	29	AAA MLE	Iowa Cubs	26	26	148	626	120	57	17	100%	5.7	16.9%	9.6%	7.3%	2.8%	3.95	4.45	—
2019	29	AAA RAW	Iowa Cubs	26	26	148	626	120	57	17	100%	5.7	19.2%	9.1%	10.1%	2.7%	3.95	4.13	—
2020	30	MLB MLE	Chicago Cubs	9	2	14	62	10	2	3	22%	1.6	16.1%	3.2%	12.9%	5.0%	5.79	4.91	-0.1
2020	30	MLB RAW	Chicago Cubs	9	2	14	62	10	2	3	22%	1.6	16.1%	3.2%	12.9%	4.8%	5.79	4.89	-0.1
2021	31	MIX MLE	2 levels	8	7	42	166	40	4	4	88%	5.2	21.7%	3.0%	18.7%	1.7%	3.02	2.57	+1.5
2021	31	MIX RAW	2 levels	8	7	42	166	40	4	4	88%	5.2	24.1%	2.4%	21.7%	2.4%	3.02	2.72	+1.4
2023	33	MIX MLE	2 levels	30	26	143	587	131	39	24	87%	4.8	21.8%	6.6%	15.2%	3.9%	4.29	4.26	+1.9
2023	33	MIX RAW	2 levels	30	26	143	587	131	39	24	87%	4.8	22.3%	6.6%	15.7%	4.1%	4.29	4.27	+1.9
2024	34	MLB MLE	Milwaukee Brewers	32	27	168	714	135	42	29	84%	5.2	18.9%	5.9%	13.0%	3.9%	4.29	4.37	+2.0
2024	34	MLB MLE	Milwaukee Brewers	32	27	168	714	135	42	29	84%	5.2	18.9%	5.9%	13.0%	3.9%	4.29	4.37	+2.0
2024	34	MLB RAW	Milwaukee Brewers	32	27	168	714	135	42	29	84%	5.2	18.9%	5.9%	13.0%	4.1%	4.29	4.49	+1.8
2025	35	MLB MLE	Chicago Cubs	32	27	159	662	127	44	20	84%	5.0	19.2%	6.6%	12.5%	3.1%	3.95	4.04	+2.6
2025	35	MLB MLE	Chicago Cubs	32	27	159	662	127	44	20	84%	5.0	19.2%	6.6%	12.5%	3.1%	3.95	4.04	+2.6
2025	35	MLB RAW	Chicago Cubs	32	27	159	662	127	44	20	84%	5.0	19.2%	6.6%	12.5%	3.0%	3.95	3.97	+2.7
2026	36	MLB MLE	Chicago Cubs	34	19	137	587	101	47	21	56%	4.0	17.2%	8.0%	9.2%	3.7%	4.34	4.70	+1.1
2026	36	MLB MLE	Chicago Cubs	34	19	137	587	101	47	21	56%	4.0	17.2%	8.0%	9.2%	3.7%	4.34	4.70	+1.1
2026	36	MLB RAW	Chicago Cubs	34	19	137	587	101	47	21	56%	4.0	17.2%	8.0%	9.2%	3.6%	4.34	4.65	+1.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			160	122	743	3153	594	224	112	76%	4.6	18.8%	7.1%	11.7%	3.6%	4.40	4.37	+9.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	37	MLB	CHC	14	14	87	367	66	27	13	100%	6.2	17.9%	7.4%	10.6%	3.5%	4.61	4.80	+0.6
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	38	MLB MLE	CHC	7	7	45	190	32	15	7	100%	6.4	16.8%	8.1%	8.7%	3.9%	4.99	5.24	+0.1
2029	39	MLB MLE	CHC	3	3	21	87	14	8	4	100%	6.9	15.7%	8.8%	6.9%	4.4%	5.40	5.67	-0.1
2028	38	MLB CTX	CHC	8	8	45	190	32	15	7	100%	5.6	16.8%	8.1%	8.7%	3.9%	4.99	5.24	+0.1
2029	39	MLB CTX	CHC	4	4	21	89	14	8	4	100%	5.2	15.7%	8.8%	6.9%	4.4%	5.40	5.67	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		171	133	809	3430	640	247	123	78%	4.7	18.6%	7.2%	11.4%	3.6%	4.46	4.41	+9.4
/ 200 IP	—	RAW		42	33	200	848	158	61	30	78%	4.7	18.6%	7.2%	11.4%	3.6%	4.46	4.41	+2.3
Career	—	MLE		234	193	1123	4740	876	352	151	82%	4.8	18.5%	7.4%	11.0%	3.2%	4.11	4.24	+9.0
/ 200 IP	—	MLE		42	34	200	844	156	63	27	82%	4.8	18.5%	7.4%	11.0%	3.2%	4.11	4.24	+2.2

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.

2023 AAANashville Sounds · 18 IPFIP 1.53 → 2.04 (+0.51)K% 30.0% → 25.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.00%	—	×0.860	25.80%
BB% (unintentional) /BF	1.43%	—	×0.900	1.29%
HR / BF /BF	1.43%	÷0.905	×1.100	1.74%

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 81).

Result: FIP 1.53 → 2.04, 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 AAANashville Sounds · 36 IPFIP 2.15 → 2.57 (+0.42)K% 24.6% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.65%	—	×0.880	21.69%
BB% (unintentional) /BF	2.82%	—	×1.050	2.96%
HR / BF /BF	1.41%	÷0.915	×1.100	1.69%

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 83).

Result: FIP 2.15 → 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).

2019 AAAIowa Cubs · 148 IPFIP 4.13 → 4.45 (+0.32)K% 19.2% → 16.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.17%	—	×0.880	16.87%
BB% (unintentional) /BF	9.11%	—	×1.050	9.56%
HR / BF /BF	2.72%	÷1.050	×1.100	2.84%

Result: FIP 4.13 → 4.45, 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 · 51 IPFIP 5.25 → 5.68 (+0.43)K% 21.9% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.88%	—	×0.880	19.25%
BB% (unintentional) /BF	10.27%	—	×1.050	10.78%
HR / BF /BF	4.91%	÷1.045	×1.100	5.17%

Result: FIP 5.25 → 5.68, 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 AASan Antonio Missions · 24 IPFIP 4.40 → 5.47 (+1.07)K% 17.9% → 14.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.95%	—	×0.810	14.54%
BB% (unintentional) /BF	11.11%	—	×1.100	12.22%
HR / BF /BF	2.56%	÷0.824	×1.200	3.73%

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 65).

Result: FIP 4.40 → 5.47, 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).

2015 AASan Antonio Missions · 75 IPFIP 2.00 → 2.45 (+0.46)K% 21.2% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.20%	—	×0.810	17.17%
BB% (unintentional) /BF	3.89%	—	×1.100	4.28%
HR / BF /BF	0.35%	÷0.885	×1.200	0.48%

Result: FIP 2.00 → 2.45, 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).

2015 AAAEl Paso Chihuahuas · 27 IPFIP 3.77 → 4.18 (+0.41)K% 16.7% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.67%	—	×0.880	14.67%
BB% (unintentional) /BF	9.17%	—	×1.050	9.62%
HR / BF /BF	1.67%	÷0.919	×1.100	2.00%

Result: FIP 3.77 → 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).

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
Colin Rea (OGILVIE)	—	—	—	—	—	3.5%	—	5.38	16.4%	8.1%	66	+0.58	—	—	—
Masato Yoshii R 2002 · 4.15 FIP	37	SP-	4.15	13.4%	5.4%	2.7%	.295	—	—	—	—	—	4.15	757	76
Kenshin Kawakami R 2010 · 4.06 FIP	35	SP	4.06	15.1%	5.6%	2.8%	.293	—	—	—	—	—	3.97	244	56
Hiroki Kuroda R 2012 · 3.66 FIP	37	SP	3.66	18.7%	5.5%	2.6%	.277	3.42	18.0%	13.3%	400	-0.24	2.96	1,319	54
Jarrett Grube R 2017 · 4.41 FIP	35	SP	4.41	15.8%	8.1%	3.0%	.296	—	—	—	—	—	3.75	393	46
Yasutomo Kubo R 2019 · 3.98 FIP	38	SP	3.98	20.4%	4.7%	3.6%	.327	—	—	—	—	—	3.98	152	43
Walter Silva R 2015 · 4.15 FIP	38	SP	4.15	14.8%	7.4%	2.5%	.311	3.91	10.4%	3.7%	209	-0.24	3.67	453	42
Jose Oyervides R 2019 · 5.66 FIP	37	SP	5.66	16.3%	11.2%	4.6%	.320	—	—	—	—	—	3.01	407	41
Pablo Ortega R 2015 · 4.52 FIP	38	SP	4.52	8.6%	7.3%	2.2%	.291	4.24	11.5%	6.0%	236	-0.28	4.01	375	40
Ivan Maldonado R 2016 · 5.41 FIP	36	SP	5.41	6.4%	9.7%	3.0%	.325	—	—	—	—	—	4.60	172	34
Jon Leicester R 2015 · 3.76 FIP	36	SP	3.76	12.3%	5.9%	1.7%	.333	—	—	—	—	—	3.76	113	32
Jonathan Castellanos R 2019 · 5.24 FIP	37	SW	5.24	11.0%	9.0%	3.5%	.348	—	—	—	—	—	3.40	394	27
Logan Duran R 2019 · 3.66 FIP	37	SP-	3.66	15.5%	8.9%	1.4%	.427	—	—	—	—	—	3.42	187	24
Jorge Castillo L 2019 · 4.91 FIP	37	SP	4.91	19.6%	8.1%	4.5%	.316	—	—	—	—	—	4.50	408	21
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	21
Arturo Lopez L 2019 · 5.46 FIP	36	SP	5.46	12.2%	6.8%	4.6%	.320	—	—	—	—	—	4.34	445	20
Mauricio Lara L 2016 · 3.68 FIP	37	SP-	3.68	12.1%	7.6%	1.1%	.294	4.34	12.2%	5.6%	219	+0.66	3.62	444	20
Jason Lane L 2015 · 5.56 FIP	38	SP	5.56	8.4%	6.2%	4.3%	.307	—	—	—	—	—	5.56	164	16
Chris Michalak L 2006 · 5.71 FIP	35	SP-	5.71	6.2%	8.6%	3.7%	.273	—	—	—	—	—	4.71	186	10
Oscar Rivera L 2017 · 5.80 FIP	36	SP	5.80	9.8%	7.8%	4.6%	.252	—	—	—	—	—	3.68	237	10

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	4.5	99	18.6%	7.4%	1.39	4.47
Mark Leiter ('90-'01, 5 WAR*)	5.9	118	20.7%*	7.8%*	1.36*	4.61*
Chase Anderson ('24)	5.5	101	19.7%	8.1%	1.48	4.41
Eddie Solomon ('73-'82, 3 WAR*)	3.6	103	15.8%*	8.0%*	1.51*	4.33*
Jerry Garvin ('77-'82, 4 WAR*)	3.0	101	19.3%*	8.4%*	1.44*	4.52*
Wade LeBlanc ('21)	4.7	72	16.9%	7.1%	1.45	4.54
Jaime Barria ('23)	2.3	77	17.9%	7.7%	1.61	4.38