Dugan Darnell

P Albuquerque Isotopes

Age 30 RHP 6'2" / 205 lbs AAA peak 0.3 · 2027

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	26	MIX2 levels	40	0	54	3.64	4.08	27.7%	9.4%	—	K 22.9% · BB 9.6% · FIP 4.62
2024	27	MIX2 levels	43	1	44	5.08	2.96	27.7%	8.9%	—	K 22.9% · BB 8.1% · FIP 3.37
2025	28	MIX2 levels	44	1	65	3.31	3.16	25.5%	9.4%	1.1	K 24.7% · BB 7.4% · FIP 3.03
2026	29	No MLB games played
2027PROJ	30	MLBCOL	7	0	7	3.84	3.84	23.9%	6.7%	0.1
2028PROJ37% MLB	31	MLBCOL	20	0	21	4.01	4.09	23.5%	7.3%	0.1
2029PROJ55% MLB	32	MLBCOL	26	0	27	4.21	4.33	23.0%	7.9%	0.1

Last 3 seasons WAR 1.1 · Next 3 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff55Control55Command60

CompsTony Barnette (age 32) · Kiko Calero (age 30) · Neil Wagner (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10698vR 90

ERA3.84

FIP3.84

K%23.9%

BB%6.7%

K-BB%17.2%

Proj IP68

Value2027 · WAR

Runs saved vs league avg · 68 IP

Grades · Contract

Scouting Grades

STUF5555

CTRL5555

CMD6060

K†5555

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)
2021	24	MIX MLE	2 levels	44	0	55	204	80	10	3	0%	1.3	30.7%	7.3%	23.4%	2.0%	1.95	2.50	—
2021	24	MIX RAW	2 levels	44	0	55	204	80	10	3	0%	1.3	39.2%	4.9%	34.3%	1.5%	1.95	1.46	—
2022	25	AA MLE	Hartford Yard Goats	38	0	48	224	68	32	9	0%	1.3	24.6%	15.7%	8.9%	4.9%	5.29	5.68	—
2022	25	AA RAW	Hartford Yard Goats	38	0	48	224	68	32	9	0%	1.3	30.4%	14.3%	16.1%	4.0%	5.29	4.72	—
2023	26	MIX MLE	2 levels	40	0	54	235	65	22	9	0%	1.4	22.9%	9.6%	13.3%	4.1%	3.64	4.62	—
2023	26	MIX RAW	2 levels	40	0	54	235	65	22	9	0%	1.4	27.7%	9.4%	18.3%	3.8%	3.64	4.08	—
2024	27	MIX MLE	2 levels	43	1	44	202	56	18	4	2%	1.0	22.9%	8.1%	14.7%	2.1%	5.08	3.37	—
2024	27	MIX MLE	2 levels	43	1	44	202	56	18	4	2%	1.0	22.9%	8.1%	14.7%	2.1%	5.08	3.37	—
2024	27	MIX RAW	2 levels	43	1	44	202	56	18	4	2%	1.0	27.7%	8.9%	18.8%	2.0%	5.08	2.96	—
2025	28	MIX MLE	2 levels	44	1	65	267	68	25	5	2%	1.5	24.7%	7.4%	17.3%	2.0%	3.31	3.03	+1.2
2025	28	MIX MLE	2 levels	44	1	65	267	68	25	5	2%	1.5	24.7%	7.4%	17.3%	2.0%	3.31	3.03	+1.2
2025	28	MIX RAW	2 levels	44	1	65	267	68	25	5	2%	1.5	25.5%	9.4%	16.1%	1.9%	3.31	3.16	+1.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			9	0	12	48	5	7	1	0%	1.3	10.4%	14.6%	-4.2%	2.1%	3.86	5.16	-0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	COL	7	0	7	30	7	2	1	0%	1.0	23.9%	6.7%	17.2%	2.8%	3.84	3.84	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	COL	54	0	57	240	56	18	7	0%	1.1	23.5%	7.3%	16.2%	3.0%	4.01	4.09	+0.3
2029	32	MLB MLE	COL	46	0	48	205	47	16	7	0%	1.1	23.0%	7.9%	15.1%	3.3%	4.21	4.33	+0.1
2028	31	MLB CTX	COL	20	0	21	89	21	6	3	0%	1.1	23.5%	7.3%	16.2%	3.0%	4.01	4.09	+0.1
2029	32	MLB CTX	COL	26	0	27	114	26	9	4	0%	1.0	23.0%	7.9%	15.1%	3.3%	4.21	4.33	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		54	0	59	249	52	22	7	0%	1.1	20.8%	9.0%	11.8%	3.0%	4.07	4.11	+0.3
/ 200 IP	—	RAW		183	0	200	840	175	74	24	0%	1.1	20.8%	9.0%	11.8%	3.0%	4.07	4.11	+1.0
Career	—	MLE		209	2	267	1132	284	109	34	1%	1.3	25.1%	9.6%	15.5%	3.0%	3.74	3.85	+0.4
/ 200 IP	—	MLE		157	1	200	848	213	82	25	1%	1.3	25.1%	9.6%	15.5%	3.0%	3.74	3.85	+0.6

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 AAAAlbuquerque Isotopes · 54 IPFIP 2.71 → 3.03 (+0.32)K% 28.8% → 24.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.77%	—	×0.860	24.74%
BB% (unintentional) /BF	8.22%	—	×0.900	7.40%
HR / BF /BF	1.83%	÷1.017	×1.100	1.98%

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 103).

Result: FIP 2.71 → 3.03, 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 AAAAlbuquerque Isotopes · 40 IPFIP 3.17 → 3.37 (+0.20)K% 26.6% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.60%	—	×0.860	22.87%
BB% (unintentional) /BF	9.04%	—	×0.900	8.14%
HR / BF /BF	2.13%	÷1.096	×1.100	2.14%

Result: FIP 3.17 → 3.37, 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 AAAAlbuquerque Isotopes · 25 IPFIP 5.48 → 5.75 (+0.27)K% 20.2% → 17.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.17%	—	×0.860	17.34%
BB% (unintentional) /BF	6.72%	—	×0.900	6.05%
HR / BF /BF	5.88%	÷1.062	×1.100	6.09%

Result: FIP 5.48 → 5.75, 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).

2023 AAHartford Yard Goats · 29 IPFIP 2.59 → 3.46 (+0.87)K% 35.3% → 28.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.34%	—	×0.810	28.63%
BB% (unintentional) /BF	12.07%	—	×1.100	13.28%
HR / BF /BF	1.72%	÷1.040	×1.200	1.99%

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 108).

Result: FIP 2.59 → 3.46, 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 AAHartford Yard Goats · 48 IPFIP 4.55 → 5.68 (+1.13)K% 30.4% → 24.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.36%	—	×0.810	24.59%
BB% (unintentional) /BF	14.29%	—	×1.100	15.71%
HR / BF /BF	4.02%	÷0.992	×1.200	4.86%

Result: FIP 4.55 → 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).

2021 A+Spokane Indians · 42 IPFIP 1.58 → 2.50 (+0.93)K% 39.9% → 30.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.87%	—	×0.770	30.70%
BB% (unintentional) /BF	6.33%	—	×1.150	7.28%
HR / BF /BF	1.90%	÷1.211	×1.250	1.96%

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 142).

Result: FIP 1.58 → 2.50, 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).

2021 AFresno Grizzlies · 14 IPFIP -0.02 → 0.79 (+0.81)K% 37.0% → 27.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.96%	—	×0.740	27.35%
BB% (unintentional) /BF	0.00%	—	×1.180	0.00%
HR / BF /BF	0.00%	÷1.218	×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 144).

Result: FIP -0.02 → 0.79, 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
Dugan Darnell (OGILVIE)	—	—	3.84	23.9%	6.7%	2.8%	—	4.20	23.3%	15.7%	105	+0.36	—	—	—
Tony Barnette R 2016 · 3.05 FIP	32	SU	3.05	19.9%	6.1%	1.6%	.281	3.26	23.4%	17.0%	84	+0.21	2.61	144	82
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	81
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	81
Mike Fyhrie R 2000 · 3.08 FIP	30	SU	3.08	19.5%	5.0%	1.8%	.309	3.87	13.7%	4.4%	69	+0.79	3.08	173	80
Gregory Infante R 2017 · 2.97 FIP	30	SU	2.97	22.8%	8.2%	1.4%	.251	4.07	22.0%	17.4%	50	+1.10	2.97	230	78
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	78
Jumbo Diaz R 2014 · 2.87 FIP	30	SU	2.87	26.1%	7.0%	2.0%	.283	3.64	23.0%	15.0%	186	+0.77	2.80	319	77
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	77
Matt Bush R 2016 · 2.87 FIP	30	SU	2.87	24.7%	6.0%	2.0%	.232	3.94	22.2%	12.7%	75	+1.07	2.87	249	77
Tyler Sturdevant R 2016 · 3.44 FIP	30	SU	3.44	23.8%	6.5%	2.8%	.323	4.48	13.5%	6.8%	60	+1.04	3.44	149	76
Gerardo Sanchez R 2019 · 3.58 FIP	30	SU	3.58	20.5%	5.4%	2.8%	.300	—	—	—	—	—	2.65	137	76
Cristhian Martinez R 2012 · 3.09 FIP	30	SU	3.09	20.8%	4.8%	2.1%	.326	—	—	—	—	—	3.09	204	76
Hirokazu Sawamura R 2021 · 4.48 FIP	33	SU	4.48	26.2%	11.2%	4.0%	.263	4.02	18.1%	6.8%	51	-0.46	4.02	104	76
James Hoyt R 2017 · 3.19 FIP	30	SU	3.19	30.4%	7.5%	3.1%	.338	3.30	24.7%	15.1%	87	+0.11	1.61	312	75
Jared Burton R 2012 · 3.09 FIP	31	SU	3.09	22.4%	6.1%	2.0%	.212	3.59	19.9%	12.6%	144	+0.50	3.09	367	75
Adrian Ramirez R 2019 · 4.29 FIP	31	SU	4.29	21.7%	6.3%	4.0%	.327	—	—	—	—	—	3.04	137	75
Ryan Tepera R 2018 · 3.90 FIP	30	SU	3.90	25.9%	8.7%	3.4%	.282	3.20	28.4%	19.9%	104	-0.70	2.35	445	75
Blake Smith R 2016 · 3.59 FIP	28	SU	3.59	22.4%	8.6%	2.4%	.307	—	—	—	—	—	3.17	124	75
Kazuhiro Sasaki R 2000 · 3.93 FIP	32	SU	3.93	29.4%	9.8%	3.8%	.212	2.88	24.9%	19.3%	161	-1.05	2.76	223	75
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	75

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	0.9	62	22.7%	7.7%	1.14	3.99
Shawn Tolleson ('16)	1.1	54	23.1%	8.3%	1.28	3.92
Michael Tonkin ('25)	1.6	55	23.2%	8.1%	1.28	4.23
Hisanori Takahashi ('13)	1.2	81	21.6%	8.2%	1.07	3.99
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Gary Wayne ('89-'94, 2 WAR*)	1.2	62	19.9%*	9.4%*	1.05*	3.88*
Jay Ritchie ('64-'68, 2 WAR*)	1.5	58	21.1%*	8.0%*	1.01*	4.21*