A.J. Puk

P ACL D-backs

Age 32 LHP 6'7" / 248 lbs ROK peak 0.3 · 2027 ILInjured 60-Day (D60)

Overview

ROKRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MIX4 levels	66	4	75	3.24	2.47	30.7%	8.4%	1.9	K 29.9% · BB 8.8% · FIP 2.68
2025	30	MLBARI	8	0	8	3.38	4.10	34.3%	5.7%	0.0
2026	31	MIX2 levels	5	3	5	3.86	2.67	23.5%	11.8%	—	K 23.5% · BB 11.8% · FIP 2.60
2027PROJ	32	MLBARI	1	0	1	3.75	3.90	26.7%	8.9%	0.0
2028PROJ32% MLB	33	MLBARI	16	0	17	4.01	4.18	25.8%	9.3%	0.1
2029PROJ27% MLB	34	MLBARI	11	0	12	4.30	4.49	24.9%	9.8%	0.0

Last 3 seasons WAR 1.9 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff60Control45Command60FB velo55

CompsHideki Okajima (age 32) · Raul Valdes (age 32) · Ryan Buchter (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9199vR 107

ERA3.75

FIP3.90

K%26.7%

BB%8.9%

K-BB%17.8%

Proj IP39

Value2027 · WAR

Runs saved vs league avg · 39 IP

Grades · Contract

Scouting Grades

STUF6060

CTRL4545

CMD6060

K†6060

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)
2017	22	MIX MLE	2 levels	27	24	125	533	184	48	3	89%	4.6	27.2%	10.1%	17.1%	0.7%	4.03	2.46	—
2017	22	MIX RAW	2 levels	27	24	125	533	184	48	3	89%	4.6	34.5%	9.0%	25.5%	0.6%	4.03	1.62	—
2019	24	MIX MLE	4 levels	28	4	37	151	51	15	8	14%	1.3	33.8%	9.9%	23.8%	5.3%	4.42	4.41	+0.1
2019	24	MIX RAW	4 levels	28	4	37	151	51	15	8	14%	1.3	33.8%	9.9%	23.8%	5.3%	4.42	4.38	+0.1
2021	26	MIX MLE	2 levels	41	4	62	291	74	25	13	10%	1.5	23.0%	8.9%	14.1%	5.2%	6.10	5.14	-0.4
2021	26	MIX RAW	2 levels	41	4	62	291	74	25	13	10%	1.5	25.4%	8.6%	16.8%	4.5%	6.10	4.65	-0.1
2022	27	MLB MLE	Oakland Athletics	62	0	66	281	76	20	7	0%	1.1	27.0%	7.1%	19.9%	2.7%	3.12	3.22	+1.1
2022	27	MLB RAW	Oakland Athletics	62	0	66	281	76	20	7	0%	1.1	27.0%	7.1%	19.9%	2.5%	3.12	3.08	+1.2
2023	28	MIX MLE	2 levels	61	0	59	253	82	12	11	0%	1.0	32.2%	4.5%	27.7%	4.3%	3.94	3.34	+0.9
2023	28	MIX RAW	2 levels	61	0	59	253	82	12	11	0%	1.0	32.4%	4.7%	27.7%	4.3%	3.94	3.35	+0.8
2024	29	MIX MLE	4 levels	66	4	75	309	95	26	5	6%	1.1	29.9%	8.8%	21.1%	1.8%	3.24	2.68	+1.7
2024	29	MIX MLE	4 levels	66	4	75	309	95	26	5	6%	1.1	29.9%	8.8%	21.1%	1.8%	3.24	2.68	+1.7
2024	29	MIX RAW	4 levels	66	4	75	309	95	26	5	6%	1.1	30.7%	8.4%	22.3%	1.6%	3.24	2.47	+1.9
2025	30	MLB MLE	Arizona Diamondbacks	8	0	8	35	12	2	2	0%	1.0	34.3%	5.7%	28.6%	5.7%	3.38	4.07	+0.0
2025	30	MLB MLE	Arizona Diamondbacks	8	0	8	35	12	2	2	0%	1.0	34.3%	5.7%	28.6%	5.7%	3.38	4.07	+0.0
2025	30	MLB RAW	Arizona Diamondbacks	8	0	8	35	12	2	2	0%	1.0	34.3%	5.7%	28.6%	5.7%	3.38	4.10	+0.0
2026	31	MIX MLE	2 levels	5	3	5	17	4	2	0	60%	0.9	23.5%	11.8%	11.8%	0.0%	3.86	2.60	—
2026	31	MIX MLE	2 levels	5	3	5	17	4	2	0	60%	0.9	23.5%	11.8%	11.8%	0.0%	3.86	2.60	—
2026	31	MIX RAW	2 levels	5	3	5	17	4	2	0	60%	0.9	23.5%	11.8%	11.8%	0.0%	3.86	2.67	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			212	4	227	964	283	70	26	2%	1.1	29.4%	7.3%	22.1%	2.7%	3.53	3.02	+4.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	ARI	1	0	1	4	1	0	0	0%	1.0	26.7%	8.9%	17.8%	2.8%	3.75	3.90	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	ARI	50	0	53	224	58	21	7	0%	1.1	25.8%	9.3%	16.5%	3.1%	4.01	4.18	+0.2
2029	34	MLB MLE	ARI	42	0	44	184	46	18	6	0%	1.0	24.9%	9.8%	15.1%	3.4%	4.30	4.49	+0.0
2028	33	MLB CTX	ARI	16	0	17	72	19	7	2	0%	1.1	25.8%	9.3%	16.5%	3.1%	4.01	4.18	+0.1
2029	34	MLB CTX	ARI	11	0	12	51	13	5	2	0%	1.1	24.9%	9.8%	15.1%	3.4%	4.30	4.49	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		240	4	256	1086	314	82	30	2%	1.1	28.9%	7.5%	21.4%	2.8%	3.60	3.12	+4.4
/ 200 IP	—	RAW		187	3	200	849	245	64	23	2%	1.1	28.9%	7.5%	21.4%	2.8%	3.60	3.12	+3.4
Career	—	MLE		298	39	437	1870	529	158	53	13%	1.5	28.3%	8.4%	19.9%	2.8%	4.06	3.34	+4.4
/ 200 IP	—	MLE		136	18	200	856	242	72	24	13%	1.5	28.3%	8.4%	19.9%	2.8%	4.06	3.34	+2.7

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.

2021 AAALas Vegas Aviators · 49 IPFIP 4.91 → 5.72 (+0.81)K% 25.7% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.66%	—	×0.880	22.58%
BB% (unintentional) /BF	8.41%	—	×1.050	8.83%
HR / BF /BF	5.31%	÷0.941	×1.100	6.21%

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 88).

Result: FIP 4.91 → 5.72, 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 AAALas Vegas Aviators · 11 IPFIP 4.64 → 4.98 (+0.35)K% 36.4% → 32.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.36%	—	×0.880	32.00%
BB% (unintentional) /BF	6.82%	—	×1.050	7.16%
HR / BF /BF	6.82%	÷1.119	×1.100	6.70%

Result: FIP 4.64 → 4.98, 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 AAMidland RockHounds · 8 IPFIP 4.19 → 5.70 (+1.51)K% 37.1% → 30.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.14%	—	×0.810	30.09%
BB% (unintentional) /BF	8.57%	—	×1.100	9.43%
HR / BF /BF	5.71%	÷0.954	×1.200	7.19%

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 91).

Result: FIP 4.19 → 5.70, 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+Stockton Ports · 6 IPFIP 6.48 → 8.02 (+1.54)K% 36.0% → 27.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.00%	—	×0.770	27.72%
BB% (unintentional) /BF	16.00%	—	×1.150	18.40%
HR / BF /BF	8.00%	÷1.114	×1.250	8.98%

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 123).

Result: FIP 6.48 → 8.02, 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 AAMidland RockHounds · 64 IPFIP 2.03 → 2.79 (+0.76)K% 30.8% → 25.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.82%	—	×0.810	24.97%
BB% (unintentional) /BF	8.96%	—	×1.100	9.86%
HR / BF /BF	0.72%	÷0.862	×1.200	1.00%

Result: FIP 2.03 → 2.79, 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).

2017 A+Stockton Ports · 61 IPFIP 1.20 → 2.10 (+0.90)K% 38.6% → 29.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.58%	—	×0.770	29.71%
BB% (unintentional) /BF	9.06%	—	×1.150	10.41%
HR / BF /BF	0.39%	÷1.397	×1.250	0.35%

Result: FIP 1.20 → 2.10, 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).

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
A.J. Puk (OGILVIE)	—	—	3.90	26.7%	8.9%	2.8%	—	4.32	25.4%	15.9%	97	+0.42	—	—	—
Hideki Okajima L 2008 · 3.49 FIP	32	SU	3.49	23.3%	8.5%	2.3%	.253	4.09	18.4%	11.4%	107	+0.60	3.05	238	74
Raul Valdes L 2010 · 4.02 FIP	32	SU	4.02	21.4%	9.9%	2.7%	.301	3.14	27.4%	22.5%	78	-0.88	2.29	160	72
Ryan Buchter L 2019 · 4.75 FIP	32	SU	4.75	25.3%	10.6%	4.4%	.286	5.24	22.9%	9.7%	32	+0.49	2.37	296	71
Grant Dayton L 2020 · 3.75 FIP	32	SU	3.75	27.4%	8.5%	3.4%	.254	3.84	23.2%	13.8%	62	+0.09	1.63	277	70
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	69
Cory Luebke L 2016 · 3.88 FIP	31	SU	3.88	26.4%	9.1%	3.4%	.354	—	—	—	—	—	2.80	216	68
Pedro Feliciano L 2009 · 3.36 FIP	32	SU	3.36	24.4%	5.8%	2.9%	.272	2.69	20.0%	11.4%	63	-0.67	2.69	378	66
Jeremy Bleich L 2019 · 4.41 FIP	32	SW	4.41	20.1%	7.0%	3.9%	.360	—	—	—	—	—	3.20	241	66
George Sherrill L 2009 · 2.95 FIP	32	SU	2.95	21.6%	7.1%	1.4%	.249	3.79	19.7%	10.4%	72	+0.84	2.74	323	65
Clay Rapada L 2012 · 3.00 FIP	31	SU	3.00	24.5%	10.3%	1.2%	.273	3.84	14.3%	6.3%	44	+0.84	3.00	120	65
Mike Myers L 2001 · 3.22 FIP	32	SU	3.22	21.3%	10.1%	1.2%	.263	4.20	15.7%	5.5%	116	+0.98	3.22	533	65
Ricardo Rincon L 2002 · 2.80 FIP	32	SU	2.80	22.1%	4.5%	1.8%	.270	4.19	17.7%	7.4%	137	+1.39	2.72	436	64
Anthony Gose L 2022 · 4.71 FIP	31	SU	4.71	30.4%	14.1%	4.4%	.234	4.63	23.9%	12.2%	82	-0.08	3.78	233	64
Caleb Thielbar L 2019 · 3.05 FIP	32	SU	3.05	25.9%	5.3%	2.7%	.337	2.71	30.2%	22.6%	143	-0.34	2.22	603	63
Zach Phillips L 2019 · 3.67 FIP	32	SU	3.67	19.1%	8.5%	2.0%	.355	—	—	—	—	—	2.33	202	63
Heriberto Ruelas L 2015 · 2.95 FIP	33	SU	2.95	19.1%	7.3%	1.0%	.352	3.57	16.2%	8.5%	89	+0.62	2.95	117	63
Adam Liberatore L 2018 · 4.28 FIP	31	SU	4.28	18.6%	9.1%	2.9%	.354	—	—	—	—	—	2.38	124	62
Edward Paredes L 2019 · 5.10 FIP	32	SU	5.10	21.5%	7.3%	5.3%	.364	—	—	—	—	—	2.36	130	62
Hisanori Takahashi L 2010 · 3.50 FIP	35	SW	3.50	22.1%	7.0%	2.5%	.292	3.81	21.1%	15.0%	118	+0.31	3.50	240	61
Brady Feigl L 2024 · 4.12 FIP	33	SU	4.12	23.7%	4.7%	4.4%	.312	3.70	22.2%	14.9%	14	-0.42	2.69	212	61

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	1.8	61	28.0%	8.5%	1.10	3.72
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*
Josh Fields ('18)	1.4	46	27.5%	8.0%	0.98	3.71
Diego Castillo ('24)	1.4	56	27.2%	9.6%	1.07	3.20
Danny Farquhar ('18)	1.4	54	26.9%	9.2%	0.99	3.93
Buddy Schultz ('75-'79, 2 WAR*)	1.2	60	27.4%*	8.5%*	1.21*	4.14*
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*