Anthony Nunez

P Baltimore Orioles

Age 26 RHP 6'2" / 220 lbs MLB peak 0.6 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	MIX2 levels	9	1	10	2.70	2.20	28.6%	11.9%	—	K 28.6% · BB 11.9% · FIP 2.20
2025	24	MIX3 levels	49	0	57	2.06	1.79	37.7%	10.0%	—	K 30.6% · BB 10.5% · FIP 2.43
2026	25	MIX2 levels	63	0	73	4.21	3.20	27.9%	9.6%	1.2	K 26.9% · BB 9.4% · FIP 3.25
2027PROJ	26	MLBBAL	43	0	45	3.88	3.73	28.0%	9.5%	0.4
2028PROJ85% MLB	27	MLBBAL	41	0	43	3.95	3.90	27.5%	9.5%	0.4
2029PROJ89% MLB	28	MLBBAL	36	0	38	4.01	4.02	27.1%	9.6%	0.3

Last 3 seasons WAR 1.2 · Next 3 projected WAR 1.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo72

K%70

xwOBA vs57

Form3.31 ERA (proj 3.88) · K 30.4% (proj 28.0%) · BB 10.1% (proj 9.5%) · last 90d · 16 IP through Oct 27

CompsMychal Givens (age 26) · Tyler Kinley (age 26) · Spencer Patton (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10395vR 87

ERA3.88

FIP3.73

K%28.0%

BB%9.5%

K-BB%18.6%

Proj IP56

Value2027 · WAR

Runs saved vs league avg · 56 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p7296.1

Whiff%

p9032.8%

p7025.9%

xwOBA vs

p570.305

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)
2024	23	MIX MLE	2 levels	9	1	10	42	12	5	0	11%	1.1	28.6%	11.9%	16.7%	0.0%	2.70	2.20	—
2024	23	MIX MLE	2 levels	9	1	10	42	12	5	0	11%	1.1	28.6%	11.9%	16.7%	0.0%	2.70	2.20	—
2024	23	MIX RAW	2 levels	9	1	10	42	12	5	0	11%	1.1	28.6%	11.9%	16.7%	0.0%	2.70	2.20	—
2025	24	MIX MLE	3 levels	49	0	57	220	83	22	2	0%	1.2	30.6%	10.5%	20.1%	1.1%	2.06	2.43	—
2025	24	MIX MLE	3 levels	49	0	57	220	83	22	2	0%	1.2	30.6%	10.5%	20.1%	1.1%	2.06	2.43	—
2025	24	MIX RAW	3 levels	49	0	57	220	83	22	2	0%	1.2	37.7%	10.0%	27.7%	0.9%	2.06	1.79	—
2026	25	MIX MLE	2 levels	63	0	73	312	87	30	7	0%	1.2	26.9%	9.4%	17.5%	2.2%	4.21	3.25	+1.1
2026	25	MIX MLE	2 levels	63	0	73	312	87	30	7	0%	1.2	26.9%	9.4%	17.5%	2.2%	4.21	3.25	+1.1
2026	25	MIX RAW	2 levels	63	0	73	312	87	30	7	0%	1.2	27.9%	9.6%	18.3%	2.2%	4.21	3.20	+1.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			52	0	60	255	66	24	5	0%	1.1	25.9%	9.4%	16.5%	2.0%	4.07	3.18	+1.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	BAL	43	0	45	190	53	18	5	0%	1.0	28.0%	9.5%	18.6%	2.6%	3.88	3.73	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	BAL	48	0	50	212	58	20	6	0%	1.0	27.5%	9.5%	18.0%	2.7%	3.88	3.83	+0.4
2029	28	MLB MLE	BAL	41	0	43	180	49	17	5	0%	1.0	27.1%	9.6%	17.5%	2.8%	3.94	3.95	+0.3
2028	27	MLB CTX	BAL	41	0	43	182	50	17	5	0%	1.0	27.5%	9.5%	18.0%	2.8%	3.95	3.90	+0.4
2029	28	MLB CTX	BAL	36	0	38	160	43	15	5	0%	1.1	27.1%	9.6%	17.5%	2.9%	4.01	4.02	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		129	0	141	597	159	57	15	0%	1.1	26.7%	9.5%	17.2%	2.5%	4.02	3.41	+1.9
/ 200 IP	—	RAW		184	0	200	849	226	81	21	0%	1.1	26.7%	9.5%	17.2%	2.5%	4.02	3.41	+2.7
Career	—	MLE		121	1	139	574	163	58	9	1%	1.2	28.5%	10.0%	18.4%	1.6%	3.23	2.86	+1.7
/ 200 IP	—	MLE		174	1	200	824	235	83	13	1%	1.2	28.5%	10.0%	18.4%	1.6%	3.23	2.86	+2.2

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 AAANorfolk Tides · 13 IPFIP 3.25 → 3.74 (+0.49)K% 36.8% → 31.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.84%	—	×0.860	31.68%
BB% (unintentional) /BF	10.53%	—	×0.900	9.47%
HR / BF /BF	3.51%	÷1.000	×1.100	3.86%

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 3.25 → 3.74, 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).

2025 AAChesapeake Baysox · 27 IPFIP 1.46 → 2.20 (+0.74)K% 36.9% → 29.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.89%	—	×0.810	29.88%
BB% (unintentional) /BF	11.65%	—	×1.100	12.82%
HR / BF /BF	0.00%	÷1.248	×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 150).

Result: FIP 1.46 → 2.20, 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).

2025 AAANorfolk Tides · 16 IPFIP 3.23 → 3.77 (+0.54)K% 32.3% → 27.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.31%	—	×0.860	27.78%
BB% (unintentional) /BF	9.23%	—	×0.900	8.31%
HR / BF /BF	3.08%	÷0.945	×1.100	3.58%

Result: FIP 3.23 → 3.77, 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).

2025 A+Brooklyn Cyclones · 14 IPFIP 0.18 → 1.22 (+1.04)K% 46.2% → 35.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	46.15%	—	×0.770	35.54%
BB% (unintentional) /BF	7.69%	—	×1.150	8.85%
HR / BF /BF	0.00%	÷1.073	×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 115).

Result: FIP 0.18 → 1.22, 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).

2024 ASt. Lucie Mets · 8 IPFIP 2.51 → 3.44 (+0.93)K% 27.8% → 20.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.78%	—	×0.740	20.56%
BB% (unintentional) /BF	13.89%	—	×1.180	16.39%
HR / BF /BF	0.00%	÷0.826	×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 65).

Result: FIP 2.51 → 3.44, 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
Anthony Nunez (OGILVIE)	—	—	—	—	—	2.6%	—	3.89	27.3%	17.8%	93	+0.16	—	—	—
Mychal Givens R 2016 · 2.84 FIP	26	SU	2.84	30.7%	10.9%	1.7%	.299	3.27	28.3%	20.0%	218	+0.43	1.77	526	82
Tyler Kinley R 2017 · 3.74 FIP	26	SU	3.74	25.0%	10.3%	2.6%	.295	3.82	25.0%	11.7%	140	+0.08	1.58	602	81
Spencer Patton R 2015 · 3.47 FIP	27	SU	3.47	26.8%	9.6%	2.6%	.295	2.79	30.3%	18.1%	57	-0.68	2.79	239	81
Raynel Espinal R 2018 · 2.60 FIP	26	SU	2.60	29.1%	9.1%	1.5%	.313	3.75	21.4%	13.0%	193	+1.15	2.48	507	80
Luke Bard R 2017 · 2.87 FIP	26	SU	2.87	28.7%	8.0%	2.1%	.362	4.57	21.8%	13.9%	128	+1.70	2.87	388	79
Juan Minaya R 2017 · 3.69 FIP	26	SU	3.69	24.4%	9.6%	2.6%	.291	3.63	25.1%	14.5%	132	-0.06	3.20	446	79
Gerardo Reyes R 2019 · 4.03 FIP	26	SU	4.03	29.8%	10.1%	4.0%	.310	4.50	24.7%	9.0%	46	+0.47	3.15	371	79
Trevor Gott R 2019 · 2.97 FIP	26	SU	2.97	26.6%	7.9%	2.0%	.272	4.64	24.1%	15.6%	99	+1.67	2.71	455	78
Daniel Bard R 2011 · 2.83 FIP	26	SU	2.83	25.7%	7.3%	1.8%	.218	5.69	13.7%	-1.5%	59	+2.86	2.56	456	78
Tucker Healy R 2016 · 2.82 FIP	26	SU	2.82	30.4%	10.5%	1.8%	.294	4.64	16.9%	5.8%	67	+1.82	2.82	174	77
Luke Jackson R 2018 · 2.67 FIP	26	SU	2.67	28.5%	10.7%	1.1%	.316	3.26	28.0%	19.3%	163	+0.59	2.67	580	76
Jaden Hill R 2024 · 3.02 FIP	24	SU	3.02	26.7%	7.1%	2.3%	.360	2.95	25.4%	16.0%	87	-0.07	2.48	169	76
Brad Lidge R 2003 · 2.97 FIP	26	SU	2.97	27.8%	10.0%	1.7%	.256	2.24	36.7%	28.9%	240	-0.73	1.56	595	75
Chad Sobotka R 2019 · 4.29 FIP	26	SU	4.29	29.5%	10.4%	4.3%	.344	4.42	15.2%	0.8%	39	+0.13	2.87	278	75
Sam Wolff R 2017 · 3.40 FIP	26	SU	3.40	26.6%	8.0%	2.8%	.291	2.98	24.1%	13.3%	63	-0.42	2.66	178	75
Jon Edwards R 2015 · 3.40 FIP	27	SU	3.40	31.7%	13.1%	2.4%	.264	2.40	30.3%	22.6%	30	-1.00	2.40	132	75
Alex Lange R 2022 · 3.00 FIP	26	SU	3.00	30.3%	11.1%	1.9%	.273	3.86	26.3%	10.9%	108	+0.86	3.00	511	75
Rowan Wick R 2019 · 2.50 FIP	26	SU	2.50	26.5%	8.0%	1.1%	.253	3.54	25.3%	15.4%	104	+1.04	2.44	361	75
Brad Brach R 2012 · 4.12 FIP	26	SU	4.12	26.8%	9.3%	3.8%	.232	3.54	24.3%	13.5%	173	-0.58	2.69	570	75
Jose Veras R 2008 · 3.67 FIP	27	SU	3.67	24.9%	9.1%	2.8%	.281	4.10	23.8%	11.7%	169	+0.43	3.37	422	74

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	1.0	52	27.1%	9.7%	0.96	3.95
Danny Farquhar ('18)	1.4	54	26.9%	9.2%	0.99	3.93
Cam Bedrosian ('21)	1.5	50	24.0%	10.2%	0.92	3.81
Oliver Drake ('20)	1.0	68	26.2%	9.5%	1.06	4.27
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*