Daniel Duarte

P Syracuse Mets

Age 30 RHP 6'0" / 235 lbs AAA peak 0.3 · 2027

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	26	MIX2 levels	63	0	67	3.51	3.88	21.6%	12.9%	0.5	K 19.7% · BB 12.3% · FIP 3.88
2024	27	MLBMIN	2	0	4	2.25	5.60	20.0%	6.7%	-0.0
2026	29	MIX2 levels	48	7	60	3.45	3.77	24.5%	9.4%	0.6	K 22.8% · BB 8.7% · FIP 3.94
2027PROJ	30	MLBNYM	49	0	51	4.10	4.30	23.4%	9.4%	0.1
2028PROJ86% MLB	31	MLBNYM	41	0	43	4.36	4.53	22.6%	9.8%	0.0
2029PROJ89% MLB	32	MLBNYM	35	0	37	4.60	4.77	21.9%	10.1%	-0.1

Last 3 seasons WAR 1.0 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs90

K%75

FB Velo55

Form3.44 ERA (proj 4.10) · K 25.7% (proj 23.4%) · BB 6.8% (proj 9.4%) ▲ last 90d · 18 IP through Oct 27

CompsJoe Nelson (age 31) · Neil Wagner (age 29) · Jim Miller (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 115107vR 99

ERA4.10

FIP4.30

K%23.4%

BB%9.4%

K-BB%13.9%

Proj IP63

Value2027 · WAR

Runs saved vs league avg · 63 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL4040

CMD4545

K†5555

Statcast Percentiles

FB Velo

p5594.9

Whiff%

p3022.5%

p7526.8%

xwOBA vs

p900.263

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	18	ROK MLE	AZL Rangers	4	2	6	26	3	2	0	50%	1.6	11.5%	7.7%	3.8%	0.0%	5.68	3.10	—
2015	18	ROK RAW	AZL Rangers	4	2	6	26	3	2	0	50%	1.6	11.5%	7.7%	3.8%	0.0%	5.68	3.10	—
2016	19	ROK MLE	DSL Rangers 1	12	11	59	250	44	13	2	92%	4.9	12.0%	6.5%	5.5%	1.1%	3.05	3.53	—
2016	19	ROK RAW	DSL Rangers 1	12	11	59	250	44	13	2	92%	4.9	17.6%	5.2%	12.4%	0.8%	3.05	2.71	—
2017	20	AAA MLE	Tigres de Quintana Roo	37	0	37	143	32	8	2	0%	1.0	19.7%	5.9%	13.8%	1.7%	1.96	3.12	—
2017	20	AAA RAW	Tigres de Quintana Roo	37	0	37	143	32	8	2	0%	1.0	22.4%	5.6%	16.8%	1.4%	1.96	2.72	—
2018	21	MIX MLE	2 levels	13	0	26	102	25	7	1	0%	2.0	17.3%	4.5%	12.8%	0.0%	1.05	2.21	—
2018	21	MIX RAW	2 levels	13	0	26	102	25	7	1	0%	2.0	24.5%	6.9%	17.6%	1.0%	1.05	2.48	—
2019	22	MIX MLE	3 levels	17	0	27	126	26	10	2	0%	1.6	16.0%	7.5%	8.5%	0.0%	5.60	2.69	—
2019	22	MIX RAW	3 levels	17	0	27	126	26	10	2	0%	1.6	20.6%	7.9%	12.7%	1.6%	5.60	3.25	—
2021	24	MIX MLE	4 levels	19	0	24	102	32	12	3	0%	1.2	26.0%	9.8%	16.2%	4.5%	4.56	4.62	—
2021	24	MIX RAW	4 levels	19	0	24	102	32	12	3	0%	1.2	31.4%	11.8%	19.6%	2.9%	4.56	3.56	—
2022	25	MIX MLE	2 levels	13	0	10	49	9	9	2	0%	0.8	18.4%	18.4%	0.0%	4.1%	9.58	6.12	-0.2
2022	25	MIX RAW	2 levels	13	0	10	49	9	9	2	0%	0.8	18.4%	18.4%	0.0%	4.1%	9.58	6.49	-0.2
2023	26	MIX MLE	2 levels	63	0	67	287	62	37	5	0%	1.1	19.7%	12.3%	7.4%	1.6%	3.51	3.88	+0.5
2023	26	MIX RAW	2 levels	63	0	67	287	62	37	5	0%	1.1	21.6%	12.9%	8.7%	1.7%	3.51	3.88	+0.5
2024	27	MLB MLE	Minnesota Twins	2	0	4	15	3	1	1	0%	2.0	20.0%	6.7%	13.3%	6.7%	2.25	5.91	-0.1
2024	27	MLB MLE	Minnesota Twins	2	0	4	15	3	1	1	0%	2.0	20.0%	6.7%	13.3%	6.7%	2.25	5.91	-0.1
2024	27	MLB RAW	Minnesota Twins	2	0	4	15	3	1	1	0%	2.0	20.0%	6.7%	13.3%	6.7%	2.25	5.60	-0.0
2026	29	MIX MLE	2 levels	48	7	60	245	60	23	7	15%	1.2	22.8%	8.7%	14.0%	3.0%	3.45	3.94	+0.4
2026	29	MIX MLE	2 levels	48	7	60	245	60	23	7	15%	1.2	22.8%	8.7%	14.0%	3.0%	3.45	3.94	+0.4
2026	29	MIX RAW	2 levels	48	7	60	245	60	23	7	15%	1.2	24.5%	9.4%	15.1%	2.9%	3.45	3.77	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			60	0	68	277	58	31	10	0%	1.1	20.9%	11.2%	9.7%	3.6%	3.18	4.67	-0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	NYM	49	0	51	215	50	20	6	0%	1.0	23.4%	9.4%	13.9%	2.9%	4.10	4.30	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	NYM	48	0	50	211	48	21	7	0%	1.0	22.6%	9.8%	12.9%	3.1%	4.36	4.53	+0.0
2029	32	MLB MLE	NYM	39	0	41	174	38	18	6	0%	1.1	21.9%	10.1%	11.8%	3.4%	4.60	4.77	-0.1
2028	31	MLB CTX	NYM	41	0	43	182	41	18	6	0%	1.0	22.6%	9.8%	12.9%	3.1%	4.36	4.53	+0.0
2029	32	MLB CTX	NYM	35	0	37	156	34	16	5	0%	1.1	21.9%	10.1%	11.8%	3.4%	4.60	4.77	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		136	0	147	612	133	64	21	0%	1.1	21.7%	10.5%	11.2%	3.4%	3.87	4.47	+0.1
/ 200 IP	—	RAW		184	0	200	831	181	87	29	0%	1.1	21.7%	10.5%	11.2%	3.4%	3.87	4.47	+0.2
Career	—	MLE		228	20	320	1345	250	117	25	9%	1.4	18.6%	8.7%	9.8%	1.9%	3.52	3.65	-0.2
/ 200 IP	—	MLE		143	13	200	842	156	73	16	9%	1.4	18.6%	8.7%	9.8%	1.9%	3.52	3.65	-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.

2026 AAASyracuse Mets · 30 IPFIP 4.37 → 4.65 (+0.28)K% 22.6% → 19.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.56%	—	×0.860	19.40%
BB% (unintentional) /BF	12.03%	—	×0.900	10.83%
HR / BF /BF	3.01%	÷1.000	×1.100	3.31%

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 4.37 → 4.65, 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 AAALouisville Bats · 35 IPFIP 2.35 → 2.51 (+0.16)K% 25.8% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.83%	—	×0.860	22.21%
BB% (unintentional) /BF	11.26%	—	×0.900	10.13%
HR / BF /BF	0.00%	÷1.054	×1.100	0.00%

Result: FIP 2.35 → 2.51, 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).

2022 AAALouisville Bats · 8 IPFIP 5.15 → 5.24 (+0.09)K% 20.0% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.880	17.60%
BB% (unintentional) /BF	17.14%	—	×1.050	18.00%
HR / BF /BF	2.86%	÷1.282	×1.100	2.45%

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 156).

Result: FIP 5.15 → 5.24, 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 AAChattanooga Lookouts · 12 IPFIP 3.48 → 4.62 (+1.15)K% 32.1% → 26.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.14%	—	×0.810	26.04%
BB% (unintentional) /BF	8.93%	—	×1.100	9.82%
HR / BF /BF	3.57%	÷0.950	×1.200	4.51%

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 90).

Result: FIP 3.48 → 4.62, 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+Dayton Dragons · 5 IPFIP 4.79 → 5.56 (+0.77)K% 16.0% → 12.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.00%	—	×0.770	12.32%
BB% (unintentional) /BF	24.00%	—	×1.150	27.60%
HR / BF /BF	0.00%	÷0.960	×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 92).

Result: FIP 4.79 → 5.56, 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 A+Wilmington Blue Rocks · 18 IPFIP 2.17 → 2.69 (+0.53)K% 20.8% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.78%	—	×0.770	16.00%
BB% (unintentional) /BF	6.49%	—	×1.150	7.47%
HR / BF /BF	0.00%	÷0.884	×1.250	0.00%

Result: FIP 2.17 → 2.69, 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 ALexington Legends · 4 IPFIP 7.97 → 9.45 (+1.48)K% 15.4% → 11.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.38%	—	×0.740	11.38%
BB% (unintentional) /BF	15.38%	—	×1.180	18.15%
HR / BF /BF	7.69%	÷1.095	×1.300	9.13%

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 119).

Result: FIP 7.97 → 9.45, 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).

2019 ROKAZL Royals · 5 IPFIP 1.45 → 2.29 (+0.84)K% 26.1% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.09%	—	×0.680	17.74%
BB% (unintentional) /BF	4.35%	—	×1.250	5.43%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 1.45 → 2.29, 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).

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
Daniel Duarte (OGILVIE)	—	—	4.30	23.4%	9.4%	2.9%	—	4.64	22.3%	12.4%	91	+0.34	—	—	—
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	84
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	83
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	79
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	79
Erik Davis R 2017 · 4.25 FIP	30	SU	4.25	22.2%	11.1%	3.0%	.349	3.52	17.4%	8.5%	65	-0.73	3.05	227	77
Kiko Calero R 2005 · 3.51 FIP	30	SU	3.51	22.7%	7.0%	2.6%	.252	3.23	23.3%	13.9%	99	-0.28	2.27	298	77
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
Mark Serrano R 2016 · 3.16 FIP	30	SU	3.16	17.7%	6.5%	1.3%	.290	4.36	21.1%	14.0%	88	+1.20	3.16	120	76
Brian Schlitter R 2016 · 3.28 FIP	30	SU	3.28	20.6%	10.8%	1.0%	.333	3.81	14.4%	6.6%	110	+0.53	3.27	300	75
Jhan Mariñez R 2018 · 4.09 FIP	29	SU	4.09	21.2%	7.9%	3.2%	.331	—	—	—	—	—	3.16	253	75
Andrew Robinson R 2017 · 4.32 FIP	29	SU	4.32	23.4%	8.8%	3.8%	.245	—	—	—	—	—	3.19	160	75
Tommy Nance R 2021 · 3.96 FIP	30	SU	3.96	24.9%	8.8%	3.4%	.228	3.41	24.1%	16.8%	99	-0.55	2.08	360	74
Manny Acosta R 2011 · 3.75 FIP	30	SU	3.75	22.5%	7.4%	2.9%	.321	4.49	21.3%	10.2%	47	+0.74	3.08	350	74
Fernando Rodriguez Jr. R 2015 · 3.34 FIP	31	SU	3.34	26.5%	9.6%	2.3%	.241	3.89	23.3%	13.2%	105	+0.55	3.34	335	74
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	74
Adrian Ramirez R 2019 · 4.29 FIP	31	SU	4.29	21.7%	6.3%	4.0%	.327	—	—	—	—	—	3.04	137	73
Esteban Haro R 2016 · 4.55 FIP	30	SU	4.55	17.1%	10.2%	2.9%	.338	3.83	11.6%	6.3%	75	-0.72	3.76	164	73
Austin Adams R 2016 · 3.40 FIP	29	SU	3.40	21.1%	6.1%	2.4%	.376	5.80	20.8%	10.2%	60	+2.40	3.40	162	73
Jose De La Torre R 2016 · 3.12 FIP	30	SU	3.12	22.0%	8.0%	1.6%	.248	2.64	20.5%	14.7%	19	-0.48	2.64	141	73
Blake Smith R 2016 · 3.59 FIP	28	SU	3.59	22.4%	8.6%	2.4%	.307	—	—	—	—	—	3.17	124	73

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	1.1	44	22.2%	10.1%	1.26	3.97
Manny Acosta ('12)	1.2	41	20.5%	10.9%	1.09	3.99
Louis Coleman ('18)	1.4	46	23.4%	10.8%	1.17	3.51
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Gary Wayne ('89-'94, 2 WAR*)	1.2	62	19.9%*	9.4%*	1.05*	3.88*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*