Reed Garrett

P New York Mets

Age 34 RHP 6'2" / 195 lbs MLB peak 0.4 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	30	MIX2 levels	42	0	55	4.25	4.12	22.5%	10.2%	0.3	K 20.3% · BB 9.5% · FIP 4.25
2024	31	MIX3 levels	56	0	61	4.01	2.92	34.3%	11.7%	1.2	K 33.6% · BB 11.7% · FIP 3.09
2025	32	MIX2 levels	59	2	56	3.83	3.19	27.3%	9.9%	0.9	K 26.9% · BB 10.1% · FIP 3.26
2026	33	No MLB games played
2027PROJ	34	MLBNYM	36	0	38	3.72	3.64	30.9%	10.2%	0.4
2028PROJ95% MLB	35	MLBNYM	45	0	47	3.87	3.98	29.9%	10.7%	0.3
2029PROJ86% MLB	36	MLBNYM	29	0	30	4.16	4.35	28.9%	11.3%	0.1

Last 3 seasons WAR 2.4 · Next 3 projected WAR 0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo90

K%75

xwOBA vs71

CompsKazuhiro Sasaki (age 34) · Jumbo Diaz (age 34) · Fernando Cruz (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9991vR 82

ERA3.72

FIP3.64

K%30.9%

BB%10.2%

K-BB%20.7%

Proj IP38

Value2027 · WAR

Runs saved vs league avg · 38 IP

Grades · Statcast · Contract

Scouting Grades

STUF6565

CTRL3535

CMD6060

K†7070

Statcast Percentiles

FB Velo

p9097.9

Whiff%

p8330.5%

p7526.9%

xwOBA vs

p710.292

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	MIX MLE	2 levels	25	25	140	594	96	48	18	100%	5.6	12.3%	9.4%	2.9%	3.7%	4.58	5.26	—
2015	22	MIX RAW	2 levels	25	25	140	594	96	48	18	100%	5.6	16.2%	8.1%	8.1%	3.0%	4.58	4.43	—
2016	23	MIX MLE	3 levels	29	18	110	490	86	50	13	62%	3.8	14.7%	11.6%	3.1%	3.1%	6.24	5.02	—
2016	23	MIX RAW	3 levels	29	18	110	490	86	50	13	62%	3.8	17.6%	10.2%	7.3%	2.7%	6.24	4.44	—
2017	24	AA MLE	Frisco RoughRiders	44	4	69	296	70	29	10	9%	1.6	19.2%	10.8%	8.4%	3.7%	4.98	4.89	—
2017	24	AA RAW	Frisco RoughRiders	44	4	69	296	70	29	10	9%	1.6	23.6%	9.8%	13.9%	3.4%	4.98	4.22	—
2018	25	MIX MLE	2 levels	51	0	62	250	61	17	3	0%	1.2	20.2%	7.4%	12.8%	1.3%	2.04	3.06	—
2018	25	MIX RAW	2 levels	51	0	62	250	61	17	3	0%	1.2	24.4%	6.8%	17.6%	1.2%	2.04	2.58	—
2019	26	MIX MLE	2 levels	47	0	56	260	50	31	7	0%	1.2	17.4%	12.3%	5.1%	2.9%	5.82	4.78	-0.1
2019	26	MIX RAW	2 levels	47	0	56	260	50	31	7	0%	1.2	19.2%	11.9%	7.3%	2.7%	5.82	4.61	-0.0
2022	29	MIX MLE	3 levels	50	0	58	249	59	24	6	0%	1.2	23.8%	9.1%	14.7%	2.6%	3.59	3.66	+0.6
2022	29	MIX RAW	3 levels	50	0	58	249	59	24	6	0%	1.2	23.7%	9.6%	14.1%	2.4%	3.59	3.65	+0.6
2023	30	MIX MLE	2 levels	42	0	55	244	55	25	7	0%	1.3	20.3%	9.5%	10.8%	3.0%	4.25	4.25	+0.2
2023	30	MIX RAW	2 levels	42	0	55	244	55	25	7	0%	1.3	22.5%	10.2%	12.3%	2.9%	4.25	4.12	+0.3
2024	31	MIX MLE	3 levels	56	0	61	265	91	31	6	0%	1.1	33.6%	11.7%	21.9%	2.4%	4.01	3.09	+1.1
2024	31	MIX MLE	3 levels	56	0	61	265	91	31	6	0%	1.1	33.6%	11.7%	21.9%	2.4%	4.01	3.09	+1.1
2024	31	MIX RAW	3 levels	56	0	61	265	91	31	6	0%	1.1	34.3%	11.7%	22.6%	2.3%	4.01	2.92	+1.2
2025	32	MIX MLE	2 levels	59	2	56	242	66	24	5	3%	1.0	26.9%	10.1%	16.8%	2.1%	3.83	3.26	+0.9
2025	32	MIX MLE	2 levels	59	2	56	242	66	24	5	3%	1.0	26.9%	10.1%	16.8%	2.1%	3.83	3.26	+0.9
2025	32	MIX RAW	2 levels	59	2	56	242	66	24	5	3%	1.0	27.3%	9.9%	17.4%	2.1%	3.83	3.19	+0.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			142	1	157	698	179	80	18	1%	1.1	25.6%	11.5%	14.2%	2.6%	4.76	3.84	+1.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	NYM	36	0	38	160	49	16	4	0%	1.1	30.9%	10.2%	20.7%	2.7%	3.72	3.64	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	NYM	47	0	49	209	62	22	6	0%	1.1	29.9%	10.7%	19.2%	3.0%	3.87	3.98	+0.3
2029	36	MLB MLE	NYM	33	0	35	148	43	17	5	0%	1.1	28.9%	11.3%	17.6%	3.4%	4.16	4.35	+0.1
2030	37	MLB MLE	NYM	21	0	22	92	26	11	4	0%	1.0	27.8%	12.0%	15.8%	3.8%	4.51	4.75	-0.1
2028	35	MLB CTX	NYM	45	0	47	198	59	21	6	0%	1.0	29.9%	10.7%	19.2%	3.0%	3.87	3.98	+0.3
2029	36	MLB CTX	NYM	29	0	30	127	37	14	4	0%	1.0	28.9%	11.3%	17.6%	3.4%	4.16	4.35	+0.1
2030	37	MLB CTX	NYM	16	0	17	72	20	9	3	0%	1.1	27.8%	12.0%	15.8%	3.8%	4.51	4.75	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		232	1	251	1096	295	124	31	0%	1.1	26.9%	11.3%	15.6%	2.8%	4.50	3.82	+2.2
/ 200 IP	—	RAW		184	1	200	872	235	99	25	0%	1.1	26.9%	11.3%	15.6%	2.8%	4.50	3.82	+1.7
Career	—	MLE		403	49	665	2890	560	296	84	12%	1.7	19.4%	10.2%	9.1%	2.9%	4.53	4.36	+1.7
/ 200 IP	—	MLE		121	15	200	869	168	89	25	12%	1.7	19.4%	10.2%	9.1%	2.9%	4.53	4.36	+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.

2023 AAASyracuse Mets · 35 IPFIP 3.85 → 4.14 (+0.28)K% 24.8% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.84%	—	×0.860	21.36%
BB% (unintentional) /BF	11.46%	—	×0.900	10.32%
HR / BF /BF	2.55%	÷1.003	×1.100	2.79%

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 101).

Result: FIP 3.85 → 4.14, 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 · 47 IPFIP 3.32 → 3.66 (+0.35)K% 27.0% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.04%	—	×0.880	23.80%
BB% (unintentional) /BF	8.67%	—	×1.050	9.11%
HR / BF /BF	2.55%	÷1.084	×1.100	2.59%

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 3.32 → 3.66, 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 AAANashville Sounds · 40 IPFIP 3.70 → 4.11 (+0.41)K% 21.9% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.86%	—	×0.880	19.23%
BB% (unintentional) /BF	9.84%	—	×1.050	10.33%
HR / BF /BF	2.19%	÷0.998	×1.100	2.41%

Result: FIP 3.70 → 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).

2018 AAFrisco RoughRiders · 43 IPFIP 2.32 → 2.94 (+0.62)K% 28.4% → 23.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.40%	—	×0.810	23.00%
BB% (unintentional) /BF	7.41%	—	×1.100	8.15%
HR / BF /BF	1.23%	÷1.088	×1.200	1.36%

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 118).

Result: FIP 2.32 → 2.94, 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 AAARound Rock Express · 19 IPFIP 3.00 → 3.29 (+0.29)K% 17.0% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.05%	—	×0.880	15.00%
BB% (unintentional) /BF	5.68%	—	×1.050	5.97%
HR / BF /BF	1.14%	÷0.978	×1.100	1.28%

Result: FIP 3.00 → 3.29, 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 AAFrisco RoughRiders · 69 IPFIP 4.20 → 4.89 (+0.69)K% 23.6% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.65%	—	×0.810	19.16%
BB% (unintentional) /BF	9.80%	—	×1.100	10.78%
HR / BF /BF	3.38%	÷1.089	×1.200	3.72%

Result: FIP 4.20 → 4.89, 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).

2016 AAFrisco RoughRiders · 94 IPFIP 4.15 → 4.75 (+0.60)K% 18.9% → 15.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.90%	—	×0.810	15.31%
BB% (unintentional) /BF	10.53%	—	×1.100	11.58%
HR / BF /BF	2.39%	÷1.065	×1.200	2.70%

Result: FIP 4.15 → 4.75, 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+High Desert Mavericks · 11 IPFIP 6.65 → 7.22 (+0.58)K% 12.0% → 9.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.00%	—	×0.770	9.24%
BB% (unintentional) /BF	10.00%	—	×1.150	11.50%
HR / BF /BF	6.00%	÷1.194	×1.250	6.28%

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 139).

Result: FIP 6.65 → 7.22, 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
Reed Garrett (OGILVIE)	—	—	3.64	30.9%	10.2%	2.7%	—	4.26	29.1%	18.0%	106	+0.62	—	—	—
Kazuhiro Sasaki R 2002 · 2.76 FIP	34	SU	2.76	29.3%	6.4%	2.4%	.247	3.30	19.3%	10.6%	33	+0.54	2.76	223	72
Jumbo Diaz R 2018 · 2.80 FIP	34	SU	2.80	23.2%	10.4%	0.6%	.296	2.98	25.0%	17.3%	56	+0.18	2.80	319	69
Fernando Cruz R 2024 · 2.94 FIP	34	SU	2.94	37.8%	11.5%	2.9%	.328	3.39	32.1%	19.6%	103	+0.45	2.50	371	67
Huascar Brazobán R 2024 · 3.08 FIP	34	SU	3.08	23.5%	11.5%	0.9%	.259	3.71	21.3%	11.7%	144	+0.63	3.08	370	67
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
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	61
Dustin Molleken R 2017 · 3.38 FIP	32	SU	3.38	24.3%	12.4%	1.4%	.311	—	—	—	—	—	3.38	129	60
Neil Wagner R 2017 · 3.11 FIP	33	SU	3.11	20.7%	8.6%	1.2%	.257	—	—	—	—	—	3.11	135	60
Jay Jackson R 2022 · 2.98 FIP	34	SU	2.98	27.5%	5.3%	2.8%	.327	4.83	26.2%	20.2%	85	+1.85	2.36	261	59
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	59
Nate Jones R 2020 · 4.53 FIP	34	SU	4.53	26.7%	5.8%	5.4%	.377	7.14	16.1%	6.9%	19	+2.61	2.57	307	58
Tony Barnette R 2018 · 2.61 FIP	34	SU	2.61	25.0%	4.8%	1.8%	.239	—	—	—	—	—	2.61	144	57
Akinori Otsuka R 2006 · 2.70 FIP	34	SU	2.70	20.3%	4.7%	1.3%	.292	2.39	17.6%	11.5%	32	-0.31	2.39	232	57
Ryan Brasier R 2022 · 3.55 FIP	34	SU	3.55	24.3%	4.6%	3.5%	.331	2.95	22.3%	16.1%	114	-0.60	2.31	426	57
Josh Lueke R 2019 · 4.11 FIP	34	SU	4.11	20.4%	6.4%	3.5%	.311	—	—	—	—	—	2.29	191	56
Greg Burke R 2015 · 3.61 FIP	32	SU	3.61	22.1%	7.3%	2.7%	.241	—	—	—	—	—	3.61	139	56
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	55
Diego Moreno R 2021 · 4.75 FIP	34	SU	4.75	18.6%	9.4%	3.7%	.232	—	—	—	—	—	2.29	187	55
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	55
Preston Guilmet R 2021 · 4.17 FIP	34	SU	4.17	28.6%	6.6%	4.8%	.246	—	—	—	—	—	2.31	288	54

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	1.5	51	27.5%	11.5%	1.10	4.38
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*
Fernando Rodriguez Jr. ('16)	1.2	58	24.6%	11.1%	0.93	4.35
Antonio Bastardo ('17)	2.0	56	28.0%	11.4%	1.01	4.01
Tony Cingrani ('18)	1.7	56	25.8%	11.3%	1.26	4.01
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*