Danny Young

P Atlanta Braves

Age 33 LHP 6'3" / 200 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	30	MIX2 levels	57	0	52	3.63	2.77	30.3%	12.1%	1.1	K 29.0% · BB 11.6% · FIP 2.84
2025	31	MLBNYM	10	0	8	4.32	1.06	35.1%	8.1%	0.3
2026	32	MIX4 levels	29	2	25	3.91	4.72	24.6%	16.9%	-0.1	K 23.1% · BB 16.9% · FIP 5.83
2027PROJ	33	MLBATL	45	0	47	4.75	4.88	25.1%	13.7%	-0.2
2028PROJ78% MLB	34	MLBATL	30	0	32	4.96	5.13	24.0%	13.7%	-0.2
2029PROJ74% MLB	35	MLBATL	22	0	23	5.20	5.40	23.0%	13.9%	-0.2

Last 3 seasons WAR 1.4 · 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

K%55

FB Velo38

xwOBA vs10

CompsKelly Wunsch (age 33) · Doug Creek (age 33) · Ryan O'Rourke (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 110118vR 126

ERA4.75

FIP4.88

K%25.1%

BB%13.7%

K-BB%11.4%

Proj IP57

Value2027 · WAR

Runs saved vs league avg · 57 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL4040

CMD5555

K†6060

Statcast Percentiles

FB Velo

p3893.7

Whiff%

p4624.7%

p5523.1%

xwOBA vs

p100.391

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)
2016	22	A MLE	Lansing Lugnuts	21	0	23	104	18	9	2	0%	1.1	12.8%	10.2%	2.6%	2.6%	2.70	4.73	—
2016	22	A RAW	Lansing Lugnuts	21	0	23	104	18	9	2	0%	1.1	17.3%	8.7%	8.7%	1.9%	2.70	3.83	—
2017	23	MIX MLE	2 levels	47	0	63	268	50	19	3	0%	1.3	14.7%	7.9%	6.8%	1.1%	3.00	3.49	—
2017	23	MIX RAW	2 levels	47	0	63	268	50	19	3	0%	1.3	18.7%	7.1%	11.6%	1.1%	3.00	3.04	—
2018	24	AA MLE	New Hampshire Fisher Cats	40	0	57	248	48	19	3	0%	1.4	15.7%	8.4%	7.2%	1.5%	4.13	3.69	—
2018	24	AA RAW	New Hampshire Fisher Cats	40	0	57	248	48	19	3	0%	1.4	19.4%	7.7%	11.7%	1.2%	4.13	3.10	—
2019	25	MIX MLE	2 levels	38	0	49	213	42	26	3	0%	1.3	15.3%	13.0%	2.3%	1.7%	2.76	4.36	—
2019	25	MIX RAW	2 levels	38	0	49	213	42	26	3	0%	1.3	19.7%	12.2%	7.5%	1.4%	2.76	3.77	—
2021	27	AAA MLE	Columbus Clippers	40	0	52	234	58	25	9	0%	1.3	21.8%	11.2%	10.6%	4.1%	4.47	4.92	—
2021	27	AAA RAW	Columbus Clippers	40	0	52	234	58	25	9	0%	1.3	24.8%	10.7%	14.1%	3.8%	4.47	4.55	—
2022	28	MIX MLE	2 levels	43	0	43	185	63	15	1	0%	1.0	32.8%	8.9%	23.9%	0.0%	3.80	1.46	+1.6
2022	28	MIX RAW	2 levels	43	0	43	185	63	15	1	0%	1.0	34.1%	8.1%	25.9%	0.5%	3.80	1.51	+1.6
2023	29	MIX MLE	2 levels	24	0	24	115	29	13	4	0%	1.0	19.4%	12.4%	7.0%	5.6%	4.50	6.10	-0.4
2023	29	MIX RAW	2 levels	24	0	24	115	29	13	4	0%	1.0	25.2%	11.3%	13.9%	3.5%	4.50	4.47	+0.0
2024	30	MIX MLE	2 levels	57	0	52	231	70	28	3	0%	0.9	29.0%	11.6%	17.3%	1.3%	3.63	2.84	+1.1
2024	30	MIX MLE	2 levels	57	0	52	231	70	28	3	0%	0.9	29.0%	11.6%	17.3%	1.3%	3.63	2.84	+1.1
2024	30	MIX RAW	2 levels	57	0	52	231	70	28	3	0%	0.9	30.3%	12.1%	18.2%	1.3%	3.63	2.77	+1.1
2025	31	MLB MLE	New York Mets	10	0	8	37	13	3	0	0%	0.8	35.1%	8.1%	27.0%	0.0%	4.32	1.16	+0.3
2025	31	MLB MLE	New York Mets	10	0	8	37	13	3	0	0%	0.8	35.1%	8.1%	27.0%	0.0%	4.32	1.16	+0.3
2025	31	MLB RAW	New York Mets	10	0	8	37	13	3	0	0%	0.8	35.1%	8.1%	27.0%	0.0%	4.32	1.06	+0.3
2026	32	MIX MLE	4 levels	29	2	25	118	29	20	3	7%	0.9	23.1%	16.9%	6.2%	4.6%	3.91	5.83	-0.4
2026	32	MIX MLE	4 levels	29	2	25	118	29	20	3	7%	0.9	23.1%	16.9%	6.2%	4.6%	3.91	5.83	-0.4
2026	32	MIX RAW	4 levels	29	2	25	118	29	20	3	7%	0.9	24.6%	16.9%	7.6%	2.5%	3.91	4.72	-0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			79	1	73	334	93	35	7	1%	0.9	27.8%	10.5%	17.4%	2.1%	4.68	3.24	+1.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	ATL	45	0	47	198	50	27	6	0%	1.0	25.1%	13.7%	11.4%	3.3%	4.75	4.88	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	ATL	40	0	42	175	42	24	6	0%	1.0	24.0%	13.7%	10.3%	3.5%	4.96	5.13	-0.3
2029	35	MLB MLE	ATL	30	0	32	134	31	19	5	0%	1.1	23.0%	13.9%	9.0%	3.8%	5.20	5.40	-0.3
2030	36	MLB MLE	ATL	24	0	25	106	23	15	4	0%	1.0	22.0%	14.3%	7.7%	4.2%	5.49	5.72	-0.3
2028	34	MLB CTX	ATL	30	0	32	135	32	19	5	0%	1.1	24.0%	13.7%	10.3%	3.5%	4.96	5.13	-0.2
2029	35	MLB CTX	ATL	22	0	23	97	22	14	4	0%	1.0	23.0%	13.9%	9.0%	3.8%	5.20	5.40	-0.2
2030	36	MLB CTX	ATL	15	0	16	68	15	10	3	0%	1.1	22.0%	14.3%	7.7%	4.2%	5.49	5.72	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		147	1	145	638	163	77	18	1%	1.0	25.6%	12.1%	13.5%	2.9%	4.92	4.06	+0.8
/ 200 IP	—	RAW		204	1	200	880	225	106	25	1%	1.0	25.6%	12.1%	13.5%	2.9%	4.92	4.06	+1.2
Career	—	MLE		349	2	397	1753	365	187	38	1%	1.1	20.8%	10.7%	10.2%	2.1%	3.65	3.87	+0.2
/ 200 IP	—	MLE		176	1	200	884	184	94	19	1%	1.1	20.8%	10.7%	10.2%	2.1%	3.65	3.87	+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 AAAGwinnett Stripers · 9 IPFIP 3.58 → 3.60 (+0.02)K% 20.0% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.860	17.20%
BB% (unintentional) /BF	17.14%	—	×0.900	15.43%
HR / BF /BF	0.00%	÷1.000	×1.100	0.00%

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 3.58 → 3.60, 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 AAASyracuse Mets · 14 IPFIP 2.40 → 2.58 (+0.18)K% 33.3% → 28.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.860	28.67%
BB% (unintentional) /BF	16.67%	—	×0.900	15.00%
HR / BF /BF	0.00%	÷1.059	×1.100	0.00%

Result: FIP 2.40 → 2.58, 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 AAAGwinnett Stripers · 16 IPFIP 5.69 → 6.10 (+0.41)K% 22.5% → 19.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.50%	—	×0.860	19.35%
BB% (unintentional) /BF	13.75%	—	×0.900	12.38%
HR / BF /BF	5.00%	÷0.984	×1.100	5.59%

Result: FIP 5.69 → 6.10, 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 AAAGwinnett Stripers · 36 IPFIP 1.03 → 1.46 (+0.43)K% 37.3% → 32.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.25%	—	×0.880	32.78%
BB% (unintentional) /BF	8.50%	—	×1.050	8.92%
HR / BF /BF	0.00%	÷0.981	×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 96).

Result: FIP 1.03 → 1.46, 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).

2021 AAAColumbus Clippers · 52 IPFIP 4.47 → 4.92 (+0.45)K% 24.8% → 21.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.79%	—	×0.880	21.81%
BB% (unintentional) /BF	10.68%	—	×1.050	11.22%
HR / BF /BF	3.85%	÷1.034	×1.100	4.09%

Result: FIP 4.47 → 4.92, 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 AANew Hampshire Fisher Cats · 40 IPFIP 3.65 → 4.36 (+0.71)K% 18.9% → 15.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.93%	—	×0.810	15.34%
BB% (unintentional) /BF	11.83%	—	×1.100	13.02%
HR / BF /BF	1.18%	÷0.860	×1.200	1.65%

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 72).

Result: FIP 3.65 → 4.36, 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 AAABuffalo Bisons · 9 IPFIP 4.16 → 4.60 (+0.44)K% 22.7% → 20.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.73%	—	×0.880	20.00%
BB% (unintentional) /BF	13.64%	—	×1.050	14.32%
HR / BF /BF	2.27%	÷1.000	×1.100	2.50%

Result: FIP 4.16 → 4.60, 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 AANew Hampshire Fisher Cats · 57 IPFIP 3.10 → 3.69 (+0.59)K% 19.4% → 15.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.35%	—	×0.810	15.68%
BB% (unintentional) /BF	7.66%	—	×1.100	8.43%
HR / BF /BF	1.21%	÷0.945	×1.200	1.54%

Result: FIP 3.10 → 3.69, 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).

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
Danny Young (OGILVIE)	—	—	4.88	25.1%	13.7%	3.3%	—	5.37	23.2%	9.2%	98	+0.49	—	—	—
Kelly Wunsch L 2005 · 3.82 FIP	33	SU	3.82	21.0%	11.4%	1.9%	.261	—	—	—	—	—	3.36	175	76
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	75
Ryan O'Rourke L 2019 · 4.08 FIP	31	SU	4.08	22.1%	14.3%	1.9%	.290	—	—	—	—	—	3.05	145	75
Juan Pablo Perez L 2013 · 3.68 FIP	34	SU	3.68	25.2%	11.5%	2.3%	.250	3.68	26.5%	11.2%	51	-0.00	1.75	104	74
Ryan Sherriff L 2023 · 3.78 FIP	33	SU	3.78	21.9%	11.0%	2.1%	.297	—	—	—	—	—	2.96	245	72
Adam Liberatore L 2018 · 4.28 FIP	31	SU	4.28	18.6%	9.1%	2.9%	.354	—	—	—	—	—	2.38	124	71
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	69
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	68
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	67
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	67
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	67
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	67
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	66
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	65
Edward Paredes L 2019 · 5.10 FIP	32	SU	5.10	21.5%	7.3%	5.3%	.364	—	—	—	—	—	2.36	130	65
Stephen Randolph L 2007 · 5.97 FIP	33	SU	5.97	28.2%	19.2%	5.1%	.450	—	—	—	—	—	4.83	155	64
Adam Loewen L 2017 · 4.22 FIP	33	SU	4.22	23.4%	17.4%	1.6%	.293	—	—	—	—	—	2.96	340	59
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	58
Clay Rapada L 2015 · 3.84 FIP	34	SU	3.84	14.3%	8.0%	1.7%	.299	—	—	—	—	—	3.00	120	58
Edwin Escobar L 2024 · 5.12 FIP	32	SU	5.12	19.6%	14.0%	3.5%	.275	—	—	—	—	—	4.28	218	58

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	46	25.2%	13.0%	1.20	4.91
John Hudek ('99)	1.0	40	23.0%	13.7%	1.30	4.43
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*
Armando Almanza ('05)	1.1	54	24.4%	14.3%	1.43	4.82
David Aardsma ('15)	1.7	48	23.1%	12.4%	1.09	4.27
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*