Zac Gallen

P Arizona Diamondbacks

Age 31 RHP 6'2" / 189 lbs MLB peak 0.3 · 2027

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	28	MLBARI	28	28	148	3.65	3.23	25.1%	8.7%	4.0
2025	29	MLBARI	33	33	192	4.83	4.39	21.5%	8.0%	2.3
2026	30	MIX2 levels	23	21	107	5.97	5.18	13.8%	7.5%	0.3	K 13.6% · BB 7.2% · FIP 5.21
2027PROJ	31	MLBARI	13	13	77	4.91	5.02	18.1%	7.8%	0.3
2028PROJ	32	MLBARI	12	12	69	5.01	5.15	17.3%	8.2%	0.1
2029PROJ	33	MLBARI	9	9	52	5.25	5.42	16.4%	8.7%	-0.1

Last 3 seasons WAR 6.5 · Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo34

K%10

xwOBA vs10

CompsMiguel González (age 31) · Orlando Hernandez (age 31) · Hideki Irabu (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 137129vR 121

ERA4.91

FIP5.02

K%18.1%

BB%7.8%

K-BB%10.2%

Proj IP77

Value2027 · WAR

Runs saved vs league avg · 77 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p3493.4

Whiff%

p1019.0%

p1013.6%

xwOBA vs

p100.384

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	20	ROK MLE	GCL Cardinals	6	3	10	36	15	0	0	50%	1.6	41.7%	0.0%	41.7%	0.0%	1.86	-0.42	—
2016	20	ROK RAW	GCL Cardinals	6	3	10	36	15	0	0	50%	1.6	41.7%	0.0%	41.7%	0.0%	1.86	-0.00	—
2017	21	MIX MLE	3 levels	26	26	148	608	121	34	11	100%	5.7	16.0%	6.2%	9.8%	1.8%	2.93	3.53	—
2017	21	MIX RAW	3 levels	26	26	148	608	121	34	11	100%	5.7	19.9%	5.6%	14.3%	1.8%	2.93	3.12	—
2018	22	AAA MLE	New Orleans Baby Cakes	25	25	133	588	136	48	14	100%	5.3	20.4%	8.6%	11.8%	2.8%	3.64	3.98	—
2018	22	AAA RAW	New Orleans Baby Cakes	25	25	133	588	136	48	14	100%	5.3	23.1%	8.2%	15.0%	2.4%	3.64	3.50	—
2019	23	MIX MLE	2 levels	29	29	171	667	208	52	18	100%	5.9	29.2%	7.9%	21.2%	2.8%	2.26	3.16	+4.8
2019	23	MIX RAW	2 levels	29	29	171	667	208	52	18	100%	5.9	31.2%	7.8%	23.4%	2.7%	2.26	2.95	+5.3
2020	24	MLB MLE	Arizona Diamondbacks	12	12	72	291	82	25	9	100%	6.0	28.2%	8.6%	19.6%	3.3%	2.75	3.61	+1.6
2020	24	MLB RAW	Arizona Diamondbacks	12	12	72	291	82	25	9	100%	6.0	28.2%	8.6%	19.6%	3.1%	2.75	3.49	+1.7
2021	25	MLB MLE	Arizona Diamondbacks	23	23	121	523	139	48	19	100%	5.3	26.6%	9.2%	17.4%	3.8%	4.30	4.13	+1.8
2021	25	MLB RAW	Arizona Diamondbacks	23	23	121	523	139	48	19	100%	5.3	26.6%	9.2%	17.4%	3.6%	4.30	4.03	+2.0
2022	26	MLB MLE	Arizona Diamondbacks	31	31	184	714	192	47	15	100%	5.9	26.9%	6.6%	20.3%	2.2%	2.54	2.88	+5.9
2022	26	MLB RAW	Arizona Diamondbacks	31	31	184	714	192	47	15	100%	5.9	26.9%	6.6%	20.3%	2.1%	2.54	2.84	+6.0
2023	27	MLB MLE	Arizona Diamondbacks	34	34	210	846	220	47	22	100%	6.2	26.0%	5.6%	20.4%	2.8%	3.47	3.12	+6.0
2023	27	MLB RAW	Arizona Diamondbacks	34	34	210	846	220	47	22	100%	6.2	26.0%	5.6%	20.4%	2.6%	3.47	3.04	+6.2
2024	28	MLB MLE	Arizona Diamondbacks	28	28	148	621	156	54	13	100%	5.3	25.1%	8.7%	16.4%	2.2%	3.65	3.30	+3.8
2024	28	MLB MLE	Arizona Diamondbacks	28	28	148	621	156	54	13	100%	5.3	25.1%	8.7%	16.4%	2.2%	3.65	3.30	+3.8
2024	28	MLB RAW	Arizona Diamondbacks	28	28	148	621	156	54	13	100%	5.3	25.1%	8.7%	16.4%	2.1%	3.65	3.23	+4.0
2025	29	MLB MLE	Arizona Diamondbacks	33	33	192	813	175	65	31	100%	5.8	21.5%	8.0%	13.5%	4.0%	4.83	4.51	+2.0
2025	29	MLB MLE	Arizona Diamondbacks	33	33	192	813	175	65	31	100%	5.8	21.5%	8.0%	13.5%	4.0%	4.83	4.51	+2.0
2025	29	MLB RAW	Arizona Diamondbacks	33	33	192	813	175	65	31	100%	5.8	21.5%	8.0%	13.5%	3.8%	4.83	4.39	+2.3
2026	30	MIX MLE	2 levels	23	21	107	480	66	36	19	91%	4.7	13.6%	7.2%	6.4%	4.3%	5.97	5.21	+0.2
2026	30	MIX MLE	2 levels	23	21	107	480	66	36	19	91%	4.7	13.6%	7.2%	6.4%	4.3%	5.97	5.21	+0.2
2026	30	MIX RAW	2 levels	23	21	107	480	66	36	19	91%	4.7	13.8%	7.5%	6.3%	4.0%	5.97	5.18	+0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			198	196	1113	4614	1124	355	136	99%	5.6	24.4%	7.7%	16.7%	2.9%	3.82	3.63	+24.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	ARI	13	13	77	325	59	26	12	100%	5.9	18.1%	7.8%	10.2%	3.8%	4.91	5.02	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	ARI	12	12	69	292	50	24	12	100%	5.8	17.3%	8.2%	9.0%	4.0%	5.13	5.27	+0.1
2029	33	MLB MLE	ARI	9	9	52	218	36	19	9	100%	5.7	16.4%	8.7%	7.7%	4.3%	5.38	5.55	-0.1
2028	32	MLB CTX	ARI	12	12	69	291	50	24	11	100%	5.8	17.3%	8.2%	9.0%	3.8%	5.01	5.15	+0.1
2029	33	MLB CTX	ARI	9	9	52	220	36	19	9	100%	5.8	16.4%	8.7%	7.7%	4.1%	5.25	5.42	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		218	216	1234	5124	1210	398	156	99%	5.7	23.6%	7.8%	15.9%	3.0%	3.94	3.76	+24.4
/ 200 IP	—	RAW		35	35	200	831	196	65	25	99%	5.7	23.6%	7.8%	15.9%	3.0%	3.94	3.76	+4.0
Career	—	MLE		270	265	1496	6187	1456	461	181	98%	5.5	23.5%	7.5%	16.1%	2.9%	3.57	3.67	+23.8
/ 200 IP	—	MLE		36	35	200	827	195	62	24	98%	5.5	23.5%	7.5%	16.1%	2.9%	3.57	3.67	+3.9

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.

2019 AAANew Orleans Baby Cakes · 91 IPFIP 2.55 → 2.93 (+0.37)K% 33.6% → 29.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.63%	—	×0.880	29.60%
BB% (unintentional) /BF	5.11%	—	×1.050	5.36%
HR / BF /BF	3.00%	÷1.100	×1.100	3.00%

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 120).

Result: FIP 2.55 → 2.93, 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 AAANew Orleans Baby Cakes · 133 IPFIP 3.49 → 3.98 (+0.49)K% 23.1% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.13%	—	×0.880	20.35%
BB% (unintentional) /BF	8.16%	—	×1.050	8.57%
HR / BF /BF	2.38%	÷0.952	×1.100	2.75%

Result: FIP 3.49 → 3.98, 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).

2017 AASpringfield Cardinals · 71 IPFIP 4.13 → 4.30 (+0.17)K% 13.8% → 11.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.82%	—	×0.810	11.19%
BB% (unintentional) /BF	5.92%	—	×1.100	6.51%
HR / BF /BF	2.63%	÷1.315	×1.200	2.40%

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 163).

Result: FIP 4.13 → 4.30, 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+Palm Beach Cardinals · 56 IPFIP 1.77 → 2.48 (+0.71)K% 25.6% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.57%	—	×0.770	19.69%
BB% (unintentional) /BF	4.57%	—	×1.150	5.25%
HR / BF /BF	0.46%	÷0.824	×1.250	0.69%

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 65).

Result: FIP 1.77 → 2.48, 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 AAAMemphis Redbirds · 21 IPFIP 3.00 → 3.48 (+0.48)K% 27.1% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.06%	—	×0.880	23.81%
BB% (unintentional) /BF	7.06%	—	×1.050	7.41%
HR / BF /BF	2.35%	÷0.980	×1.100	2.64%

Result: FIP 3.00 → 3.48, 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).

2016 ROKGCL Cardinals · 10 IPFIP -0.42 → 0.71 (+1.13)K% 41.7% → 28.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.67%	—	×0.680	28.33%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
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 -0.42 → 0.71, 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
Zac Gallen (OGILVIE)	—	—	—	—	—	3.8%	—	5.39	16.9%	8.5%	121	+0.37	—	—	—
Miguel González R 2015 · 4.53 FIP	31	SP	4.53	17.5%	7.9%	3.5%	.289	4.23	15.9%	9.0%	325	-0.30	3.72	905	76
Orlando Hernandez R 2001 · 5.30 FIP	31	SP	5.30	18.6%	9.9%	4.6%	.256	3.78	20.4%	13.1%	231	-1.52	3.35	1,315	69
Hideki Irabu R 2000 · 4.38 FIP	31	SP	4.38	17.0%	5.7%	3.6%	.374	5.19	17.2%	11.0%	64	+0.81	3.78	514	65
Chase Anderson R 2019 · 4.39 FIP	31	SP	4.39	20.9%	8.1%	3.7%	.259	5.39	19.2%	10.0%	218	+1.00	3.30	1,260	65
Rolando Arrojo R 2000 · 4.47 FIP	32	SP	4.47	16.1%	8.0%	3.1%	.291	3.68	16.4%	9.2%	185	-0.79	3.50	700	64
Tim Adleman R 2019 · 4.30 FIP	31	SP	4.30	22.8%	7.8%	3.9%	.266	4.71	18.5%	11.1%	90	+0.41	3.63	605	62
Mike Fiers R 2016 · 4.30 FIP	31	SP	4.30	18.5%	5.8%	3.7%	.308	4.96	19.2%	12.2%	510	+0.66	2.83	1,140	61
Hideo Nomo R 2000 · 4.66 FIP	31	SP	4.66	21.9%	10.6%	3.7%	.303	4.13	22.0%	11.4%	637	-0.53	2.76	1,972	59
Daisuke Matsuzaka R 2012 · 5.55 FIP	31	SP	5.55	19.1%	9.3%	5.2%	.329	3.83	21.1%	9.5%	122	-1.72	3.77	790	59
Cory Lidle R 2003 · 4.40 FIP	31	SP	4.40	13.3%	6.8%	2.9%	.297	4.23	15.4%	9.5%	567	-0.17	3.48	1,318	57
Brian Tollberg R 2002 · 4.98 FIP	29	SP	4.98	11.5%	5.9%	3.8%	.339	—	—	—	—	—	4.02	297	56
Tanner Roark R 2018 · 3.99 FIP	31	SP	3.99	19.2%	6.2%	3.2%	.289	4.57	21.1%	13.1%	259	+0.58	2.40	1,194	56
Chuck Smith R 2001 · 3.99 FIP	31	SP	3.99	18.4%	8.1%	2.6%	.289	—	—	—	—	—	3.08	211	56
Elmer Dessens R 2002 · 4.53 FIP	31	SP	4.53	12.6%	5.6%	3.3%	.257	4.20	14.6%	8.4%	346	-0.33	3.55	1,167	56
Ryan Franklin R 2004 · 5.05 FIP	31	SP	5.05	12.0%	6.9%	3.8%	.284	4.65	12.1%	6.0%	348	-0.40	3.12	1,201	55
Jeremy Hefner R 2016 · 4.64 FIP	30	SP	4.64	16.8%	9.1%	3.3%	.305	—	—	—	—	—	3.56	322	54
Paul Wilson R 2004 · 4.57 FIP	31	SP	4.57	14.7%	7.3%	3.3%	.278	5.32	13.4%	6.3%	46	+0.75	2.59	942	53
Brian Lawrence R 2007 · 4.68 FIP	31	SP	4.68	12.9%	8.6%	2.9%	.371	—	—	—	—	—	3.33	963	53
Scott Carroll R 2016 · 4.94 FIP	31	SP	4.94	10.5%	8.6%	3.0%	.289	5.71	14.4%	5.8%	22	+0.77	3.92	377	52
Dylan Axelrod R 2016 · 4.28 FIP	31	SP	4.28	13.7%	6.3%	2.8%	.302	—	—	—	—	—	2.88	468	52

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	6.6	119	23.3%	7.8%	1.20	4.01
Scott Bankhead ('86-'95, 10 WAR*)	4.5	100	21.2%*	7.3%*	1.36*	4.16*
Pete Richert ('62-'74, 13 WAR*)	5.8	90	24.4%*	8.8%*	1.26*	4.04*
Ian Kennedy ('23)	9.5	146	21.9%	8.0%	1.32	4.16
Skip Lockwood ('69-'80, 11 WAR*)	6.2	103	22.5%*	9.1%*	1.06*	4.28*
Mike Minor ('22)	7.0	128	21.6%	7.0%	1.30	4.25
Frankie Montas ('25)	3.9	98	23.6%	8.2%	1.20	4.20