Colin Poche

P Syracuse Mets

Age 33 LHP 6'3" / 225 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	29	MLBTB	66	0	61	2.23	3.08	24.8%	9.3%	1.1
2024	30	MIX2 levels	46	0	40	4.05	4.58	20.6%	7.3%	-0.0	K 21.6% · BB 7.2% · FIP 4.77
2025	31	MIX2 levels	31	1	28	7.39	5.92	20.3%	20.3%	-0.4	K 18.6% · BB 19.3% · FIP 5.56
2026	32	No MLB games played
2027PROJ	33	MLBNYM	6	0	6	4.49	4.92	20.8%	12.0%	-0.0
2028PROJ6% MLB	34	MLBNYM	2	0	2	4.93	5.23	19.9%	12.5%	-0.0
2029PROJMLE	35	MLBNYM	—	—	0	5.31	5.56	19.0%	13.0%	—

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.

Scouting grades · 20-80

Stuff45Control50Command45FB velo35

CompsBrandon Mann (age 33) · Doug Creek (age 33) · Ryan O'Rourke (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 110119vR 127

ERA4.49

FIP4.92

K%20.8%

BB%12.0%

K-BB%8.8%

Proj IP57

Value2027 · WAR

Runs saved vs league avg · 57 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL5050

CMD4545

K†5050

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)
2017	23	MIX MLE	2 levels	31	0	50	194	81	16	0	0%	1.6	31.5%	9.6%	21.9%	0.0%	1.25	1.65	—
2017	23	MIX RAW	2 levels	31	0	50	194	81	16	0	0%	1.6	41.8%	8.2%	33.5%	0.0%	1.25	0.84	—
2018	24	MIX MLE	2 levels	40	2	66	241	110	19	2	5%	1.6	39.2%	8.3%	30.9%	0.9%	0.82	1.36	—
2018	24	MIX RAW	2 levels	40	2	66	241	110	19	2	5%	1.6	45.6%	7.9%	37.8%	0.8%	0.82	1.02	—
2019	25	MIX MLE	2 levels	71	2	79	329	120	27	13	3%	1.1	34.7%	8.3%	26.4%	4.0%	5.24	3.42	+1.1
2019	25	MIX RAW	2 levels	71	2	79	329	120	27	13	3%	1.1	36.5%	8.2%	28.3%	4.0%	5.24	3.23	+1.2
2022	28	MIX MLE	2 levels	71	0	65	266	75	24	11	0%	0.9	26.1%	9.0%	17.1%	4.6%	3.62	4.57	-0.0
2022	28	MIX RAW	2 levels	71	0	65	266	75	24	11	0%	0.9	28.2%	9.0%	19.2%	4.1%	3.62	4.11	+0.3
2023	29	MLB MLE	Tampa Bay Rays	66	0	61	246	61	23	4	0%	0.9	24.8%	9.3%	15.4%	1.7%	2.23	3.11	+1.0
2023	29	MLB RAW	Tampa Bay Rays	66	0	61	246	61	23	4	0%	0.9	24.8%	9.3%	15.4%	1.6%	2.23	3.08	+1.1
2024	30	MIX MLE	2 levels	46	0	40	165	34	12	7	0%	0.9	21.6%	7.2%	14.4%	4.7%	4.05	4.77	-0.1
2024	30	MIX MLE	2 levels	46	0	40	165	34	12	7	0%	0.9	21.6%	7.2%	14.4%	4.7%	4.05	4.77	-0.1
2024	30	MIX RAW	2 levels	46	0	40	165	34	12	7	0%	0.9	20.6%	7.3%	13.3%	4.2%	4.05	4.58	-0.0
2025	31	MIX MLE	2 levels	31	1	28	133	27	27	4	3%	0.9	18.6%	19.3%	-0.7%	2.9%	7.39	5.56	-0.3
2025	31	MIX MLE	2 levels	31	1	28	133	27	27	4	3%	0.9	18.6%	19.3%	-0.7%	2.9%	7.39	5.56	-0.3
2025	31	MIX RAW	2 levels	31	1	28	133	27	27	4	3%	0.9	20.3%	20.3%	0.0%	3.0%	7.39	5.92	-0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			239	0	218	903	241	88	32	0%	0.9	26.7%	9.7%	16.9%	3.5%	4.01	4.01	+1.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	NYM	6	0	6	25	5	3	1	0%	1.0	20.8%	12.0%	8.8%	3.1%	4.49	4.92	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	NYM	38	0	40	168	33	21	6	0%	1.0	19.9%	12.5%	7.4%	3.4%	4.93	5.23	-0.3
2029	35	MLB MLE	NYM	28	0	30	126	24	16	5	0%	1.1	19.0%	13.0%	5.9%	3.7%	5.31	5.56	-0.3
2030	36	MLB MLE	NYM	23	0	24	100	18	14	4	0%	1.0	17.9%	13.6%	4.3%	4.1%	5.68	5.93	-0.4
2028	34	MLB CTX	NYM	2	0	2	8	2	1	0	0%	1.0	19.9%	12.5%	7.4%	3.4%	4.93	5.23	-0.0
2029	35	MLB CTX	NYM	—	—	0	—	—	—	—	—	—	19.0%	13.0%	5.9%	3.7%	5.31	5.56	—
2030	36	MLB CTX	NYM	—	—	0	—	—	—	—	—	—	17.9%	13.6%	4.3%	4.1%	5.68	5.93	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		241	0	220	913	243	89	32	0%	0.9	26.6%	9.8%	16.8%	3.5%	4.02	4.04	+1.3
/ 200 IP	—	RAW		219	0	200	830	221	81	29	0%	0.9	26.6%	9.8%	16.8%	3.5%	4.02	4.04	+1.2
Career	—	MLE		356	5	389	1574	461	150	43	1%	1.1	29.3%	9.6%	19.7%	2.8%	3.27	3.35	+0.3
/ 200 IP	—	MLE		183	3	200	810	237	77	22	1%	1.1	29.3%	9.6%	19.7%	2.8%	3.27	3.35	+0.2

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.

2025 AAASyracuse Mets · 19 IPFIP 5.50 → 5.41 (−0.09)K% 19.8% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.75%	—	×0.860	16.99%
BB% (unintentional) /BF	16.05%	—	×0.900	14.44%
HR / BF /BF	3.70%	÷1.167	×1.100	3.49%

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 133).

Result: FIP 5.50 → 5.41, 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 AAADurham Bulls · 6 IPFIP -0.12 → 0.47 (+0.59)K% 52.4% → 46.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	52.38%	—	×0.880	46.10%
BB% (unintentional) /BF	9.52%	—	×1.050	10.00%
HR / BF /BF	0.00%	÷1.034	×1.100	0.00%

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 107).

Result: FIP -0.12 → 0.47, 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).

2019 AAADurham Bulls · 27 IPFIP 2.51 → 2.91 (+0.40)K% 39.3% → 34.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.34%	—	×0.880	34.62%
BB% (unintentional) /BF	7.38%	—	×1.050	7.75%
HR / BF /BF	3.28%	÷1.128	×1.100	3.20%

Result: FIP 2.51 → 2.91, 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 AAADurham Bulls · 50 IPFIP 1.33 → 1.88 (+0.56)K% 41.5% → 36.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.49%	—	×0.880	36.51%
BB% (unintentional) /BF	9.04%	—	×1.050	9.49%
HR / BF /BF	1.06%	÷0.970	×1.100	1.21%

Result: FIP 1.33 → 1.88, 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).

2018 AAMontgomery Biscuits · 16 IPFIP -1.52 → -0.50 (+1.02)K% 60.4% → 48.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	60.38%	—	×0.810	48.91%
BB% (unintentional) /BF	3.77%	—	×1.100	4.15%
HR / BF /BF	0.00%	÷0.984	×1.200	0.00%

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 -1.52 → -0.50, 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+Visalia Rawhide · 26 IPFIP 1.39 → 2.30 (+0.92)K% 36.6% → 28.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.63%	—	×0.770	28.21%
BB% (unintentional) /BF	10.89%	—	×1.150	12.52%
HR / BF /BF	0.00%	÷1.048	×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 110).

Result: FIP 1.39 → 2.30, 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 AKane County Cougars · 25 IPFIP -0.21 → 0.95 (+1.16)K% 47.3% → 35.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	47.31%	—	×0.740	35.01%
BB% (unintentional) /BF	5.38%	—	×1.180	6.34%
HR / BF /BF	0.00%	÷0.899	×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 80).

Result: FIP -0.21 → 0.95, 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 Poche (OGILVIE)	—	—	4.92	20.8%	12.0%	3.1%	—	5.51	19.1%	6.1%	93	+0.59	—	—	—
Brandon Mann L 2017 · 4.24 FIP	33	SU	4.24	19.8%	11.3%	2.5%	.286	3.59	17.8%	6.4%	52	-0.65	3.59	190	81
Doug Creek L 2002 · 4.99 FIP	33	SU	4.99	21.4%	12.6%	3.8%	.288	5.79	17.1%	7.9%	36	+0.80	4.48	277	80
Ryan O'Rourke L 2019 · 4.08 FIP	31	SU	4.08	22.1%	14.3%	1.9%	.290	—	—	—	—	—	3.05	145	80
Adam Liberatore L 2018 · 4.28 FIP	31	SU	4.28	18.6%	9.1%	2.9%	.354	—	—	—	—	—	2.38	124	78
Kelly Wunsch L 2005 · 3.82 FIP	33	SU	3.82	21.0%	11.4%	1.9%	.261	—	—	—	—	—	3.36	175	78
Hideki Okajima L 2009 · 3.95 FIP	33	SU	3.95	20.5%	7.0%	3.1%	.268	4.27	15.5%	8.5%	46	+0.32	3.05	238	76
Brian Shouse L 2002 · 5.54 FIP	33	SU	5.54	15.5%	11.3%	4.2%	.245	3.31	16.3%	10.7%	159	-2.23	2.32	339	74
Ryan Sherriff L 2023 · 3.78 FIP	33	SU	3.78	21.9%	11.0%	2.1%	.297	—	—	—	—	—	2.96	245	73
Scott Sauerbeck L 2005 · 3.75 FIP	33	SU	3.75	22.3%	8.9%	2.5%	.298	5.05	14.0%	0.0%	25	+1.30	2.79	386	71
Brian Moran L 2022 · 4.20 FIP	33	SU	4.20	21.7%	7.0%	3.7%	.304	3.72	21.5%	14.5%	152	-0.48	1.80	421	71
Clay Rapada L 2015 · 3.84 FIP	34	SU	3.84	14.3%	8.0%	1.7%	.299	—	—	—	—	—	3.00	120	71
Tommy Phelps L 2005 · 3.98 FIP	31	SU	3.98	13.2%	7.5%	1.9%	.280	—	—	—	—	—	3.39	120	68
Tom Martin L 2003 · 3.82 FIP	33	SU	3.82	24.3%	9.5%	2.9%	.226	3.99	16.2%	8.6%	106	+0.17	3.40	303	67
Grant Dayton L 2021 · 4.00 FIP	33	SU	4.00	23.0%	8.2%	3.3%	.325	3.80	23.2%	13.5%	49	-0.20	1.63	277	66
Anthony Gose L 2024 · 3.78 FIP	33	SU	3.78	26.4%	11.3%	2.7%	.279	5.07	21.5%	10.1%	97	+1.29	3.78	233	66
Alejandro Soto L 2019 · 4.03 FIP	33	SW	4.03	17.1%	6.9%	2.7%	.376	—	—	—	—	—	3.96	280	65
Edward Paredes L 2019 · 5.10 FIP	32	SU	5.10	21.5%	7.3%	5.3%	.364	—	—	—	—	—	2.36	130	65
Joey Eischen L 2003 · 4.00 FIP	33	SU	4.00	18.1%	5.4%	3.2%	.309	3.44	19.6%	10.3%	69	-0.56	2.13	294	65
Marlon Arias L 2017 · 3.73 FIP	32	SU	3.73	17.2%	7.7%	2.0%	.443	4.83	19.8%	8.6%	74	+1.10	3.73	154	64
Edwin Escobar L 2024 · 5.12 FIP	32	SU	5.12	19.6%	14.0%	3.5%	.275	—	—	—	—	—	4.28	218	61

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	1.8	46	23.8%	11.2%	1.35	4.40
Chasen Shreve ('24)	1.8	45	25.2%	10.8%	1.54	3.96
Dominic Leone ('24)	2.1	54	23.9%	10.4%	1.26	3.94
Jorge Julio ('09)	2.3	58	21.7%	11.3%	1.25	4.43
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Bill Scherrer ('82-'88, 1 WAR*)	1.6	62	20.7%*	10.2%*	1.19*	4.44*