Hunter Gaddis

P Cleveland Guardians

Age 29 RHP 6'6" / 260 lbs MLB peak 0.4 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MLBCLE	78	75	1.57	2.55	23.7%	4.7%	1.8
2025	27	MLBCLE	73	67	3.10	3.33	26.6%	6.9%	1.0
2026	28	MIX2 levels	73	65	3.48	3.75	22.1%	8.9%	0.6	K 22.2% · BB 8.6% · FIP 3.81
2027PROJ	29	MLBCLE	55	58	3.60	3.88	24.6%	7.2%	0.5
2028PROJ95% MLB	30	MLBCLE	42	44	3.89	4.08	23.9%	7.5%	0.2
2029PROJ95% MLB	31	MLBCLE	32	34	4.15	4.32	23.1%	7.9%	0.1

Last 3 seasons WAR 3.4 · Next 3 projected WAR 0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo58

xwOBA vs51

K%50

Form3.28 ERA (proj 3.60) · K 22.8% (proj 24.6%) · BB 8.9% (proj 7.2%) ▼ last 90d · 25 IP through Oct 27

CompsPedro Báez (age 29) · John Brebbia (age 29) · Craig Stammen (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10698vR 90

ERA3.60

FIP3.88

K%24.6%

BB%7.2%

K-BB%17.4%

Proj IP58

Value2027 · WAR

Runs saved vs league avg · 58 IP

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL6060

CMD6060

K†6060

Statcast Percentiles

FB Velo

p5895.1

Whiff%

p7729.5%

p5022.2%

xwOBA vs

p510.311

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)
2019	21	ROK MLE	AZL Indians Blue	7	5	17	66	26	3	2	71%	2.5	26.8%	5.7%	21.1%	4.2%	3.12	3.89	—
2019	21	ROK RAW	AZL Indians Blue	7	5	17	66	26	3	2	71%	2.5	39.4%	4.5%	34.8%	3.0%	3.12	2.12	—
2021	23	A+ MLE	Lake County Captains	20	19	97	419	127	28	20	95%	4.9	23.3%	7.7%	15.7%	4.9%	4.16	4.78	—
2021	23	A+ RAW	Lake County Captains	20	19	97	419	127	28	20	95%	4.9	30.3%	6.7%	23.6%	4.8%	4.16	4.02	—
2022	24	MIX MLE	3 levels	26	25	129	533	163	44	24	96%	4.9	26.8%	9.0%	17.8%	4.0%	4.83	4.17	+1.9
2022	24	MIX RAW	3 levels	26	25	129	533	163	44	24	96%	4.9	30.6%	8.3%	22.3%	4.5%	4.83	4.02	+2.1
2023	25	MIX MLE	2 levels	31	22	116	520	89	47	24	71%	3.8	15.4%	8.4%	7.0%	4.8%	5.49	5.52	-0.2
2023	25	MIX RAW	2 levels	31	22	116	520	89	47	24	71%	3.8	17.1%	9.0%	8.1%	4.6%	5.49	5.46	-0.1
2024	26	MLB MLE	Cleveland Guardians	78	0	75	278	66	13	4	0%	1.0	23.7%	4.7%	19.1%	1.4%	1.57	2.48	+1.9
2024	26	MLB MLE	Cleveland Guardians	78	0	75	278	66	13	4	0%	1.0	23.7%	4.7%	19.1%	1.4%	1.57	2.48	+1.9
2024	26	MLB RAW	Cleveland Guardians	78	0	75	278	66	13	4	0%	1.0	23.7%	4.7%	19.1%	1.4%	1.57	2.55	+1.8
2025	27	MLB MLE	Cleveland Guardians	73	0	67	274	73	19	8	0%	0.9	26.6%	6.9%	19.7%	2.9%	3.10	3.34	+1.0
2025	27	MLB MLE	Cleveland Guardians	73	0	67	274	73	19	8	0%	0.9	26.6%	6.9%	19.7%	2.9%	3.10	3.34	+1.0
2025	27	MLB RAW	Cleveland Guardians	73	0	67	274	73	19	8	0%	0.9	26.6%	6.9%	19.7%	2.9%	3.10	3.33	+1.0
2026	28	MIX MLE	2 levels	73	0	65	280	62	25	7	0%	0.9	22.2%	8.6%	13.6%	2.7%	3.48	3.81	+0.6
2026	28	MIX MLE	2 levels	73	0	65	280	62	25	7	0%	0.9	22.2%	8.6%	13.6%	2.7%	3.48	3.81	+0.6
2026	28	MIX RAW	2 levels	73	0	65	280	62	25	7	0%	0.9	22.1%	8.9%	13.2%	2.5%	3.48	3.75	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			232	9	251	1031	225	71	32	4%	1.1	21.8%	6.9%	14.9%	3.1%	3.30	3.81	+2.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	CLE	55	0	58	245	60	18	7	0%	1.1	24.6%	7.2%	17.4%	2.8%	3.60	3.88	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	CLE	44	0	46	194	46	15	6	0%	1.0	23.9%	7.5%	16.4%	3.0%	3.89	4.08	+0.3
2029	31	MLB MLE	CLE	34	0	36	152	35	12	5	0%	1.1	23.1%	7.9%	15.2%	3.3%	4.15	4.32	+0.1
2028	30	MLB CTX	CLE	42	0	44	186	44	14	6	0%	1.0	23.9%	7.5%	16.4%	3.0%	3.89	4.08	+0.2
2029	31	MLB CTX	CLE	32	0	34	144	33	11	5	0%	1.1	23.1%	7.9%	15.2%	3.3%	4.15	4.32	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		306	9	329	1359	302	96	42	3%	1.1	22.2%	7.1%	15.2%	3.1%	3.47	3.83	+2.8
/ 200 IP	—	RAW		186	5	200	827	184	58	26	3%	1.1	22.2%	7.1%	15.2%	3.1%	3.47	3.83	+1.7
Career	—	MLE		308	71	566	2370	539	184	89	23%	1.8	22.7%	7.7%	15.0%	3.8%	4.01	4.23	+2.5
/ 200 IP	—	MLE		109	25	200	838	191	65	32	23%	1.8	22.7%	7.7%	15.0%	3.8%	4.01	4.23	+1.5

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 AAAColumbus Clippers · 4 IPFIP 2.92 → 3.01 (+0.09)K% 21.7% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.74%	—	×0.860	18.70%
BB% (unintentional) /BF	13.04%	—	×0.900	11.74%
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 2.92 → 3.01, 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 AAAColumbus Clippers · 74 IPFIP 5.64 → 5.92 (+0.28)K% 19.2% → 16.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.23%	—	×0.860	16.54%
BB% (unintentional) /BF	9.76%	—	×0.900	8.79%
HR / BF /BF	5.33%	÷1.037	×1.100	5.65%

Result: FIP 5.64 → 5.92, 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).

2022 AAAkron RubberDucks · 76 IPFIP 3.51 → 4.52 (+1.02)K% 32.7% → 26.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.69%	—	×0.810	26.48%
BB% (unintentional) /BF	8.33%	—	×1.100	9.17%
HR / BF /BF	3.85%	÷1.014	×1.200	4.55%

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 103).

Result: FIP 3.51 → 4.52, 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 AAAColumbus Clippers · 45 IPFIP 3.05 → 3.57 (+0.52)K% 30.9% → 27.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.94%	—	×0.880	27.23%
BB% (unintentional) /BF	8.29%	—	×1.050	8.70%
HR / BF /BF	2.76%	÷1.001	×1.100	3.04%

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 100).

Result: FIP 3.05 → 3.57, 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+Lake County Captains · 97 IPFIP 4.01 → 4.78 (+0.78)K% 30.3% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.31%	—	×0.770	23.34%
BB% (unintentional) /BF	6.68%	—	×1.150	7.68%
HR / BF /BF	4.77%	÷1.222	×1.250	4.88%

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 144).

Result: FIP 4.01 → 4.78, 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 ROKAZL Indians Blue · 17 IPFIP 2.01 → 3.89 (+1.87)K% 39.4% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.39%	—	×0.680	26.79%
BB% (unintentional) /BF	4.55%	—	×1.250	5.68%
HR / BF /BF	3.03%	÷1.000	×1.400	4.24%

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 2.01 → 3.89, 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
Hunter Gaddis (OGILVIE)	—	—	3.88	24.6%	7.2%	2.8%	—	4.19	23.5%	15.9%	82	+0.31	—	—	—
Pedro Báez R 2017 · 4.08 FIP	29	SU	4.08	22.9%	9.6%	3.1%	.261	3.18	24.7%	16.1%	143	-0.90	2.29	356	73
John Brebbia R 2019 · 2.89 FIP	29	SU	2.89	28.6%	8.2%	2.1%	.285	3.34	22.8%	17.4%	102	+0.45	2.89	576	70
Craig Stammen R 2013 · 2.68 FIP	29	SU	2.68	23.3%	7.1%	1.2%	.319	3.12	18.2%	14.3%	86	+0.44	1.82	884	69
David Carpenter R 2014 · 2.84 FIP	29	SU	2.84	25.9%	6.2%	2.1%	.327	4.98	15.8%	5.8%	50	+2.14	2.66	275	69
Blake Treinen R 2017 · 3.15 FIP	29	SU	3.15	22.8%	6.8%	2.0%	.332	2.94	26.6%	18.0%	165	-0.21	1.53	601	69
Jhan Mariñez R 2018 · 4.09 FIP	29	SU	4.09	21.2%	7.9%	3.2%	.331	—	—	—	—	—	3.16	253	69
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	68
Shane Greene R 2018 · 4.42 FIP	29	SU	4.42	23.3%	6.5%	4.5%	.304	3.93	23.0%	15.2%	114	-0.49	2.86	563	68
Matt Andriese R 2019 · 3.39 FIP	29	SU	3.39	25.5%	7.4%	2.7%	.320	3.88	24.0%	17.0%	80	+0.49	3.08	744	68
Danny Farquhar R 2016 · 4.02 FIP	29	SU	4.02	21.7%	7.6%	3.3%	.272	3.62	22.3%	11.3%	62	-0.40	1.67	351	68
Mike Wright Jr. R 2019 · 3.76 FIP	29	SW	3.76	19.9%	7.2%	2.6%	.347	4.19	17.6%	7.3%	169	+0.43	3.76	725	67
Paul Sewald R 2019 · 3.75 FIP	29	SU	3.75	22.8%	6.0%	3.3%	.330	3.20	34.6%	28.3%	129	-0.55	2.71	611	67
Jason Frasor R 2007 · 2.87 FIP	29	SU	2.87	24.4%	9.1%	1.2%	.278	3.18	22.9%	14.3%	169	+0.31	2.71	647	67
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	67
Alex Colomé R 2018 · 3.19 FIP	29	SU	3.19	25.5%	6.7%	2.5%	.283	3.68	20.5%	12.4%	148	+0.49	2.72	569	67
Deolis Guerra R 2018 · 3.59 FIP	29	SU	3.59	26.4%	7.1%	3.3%	.280	3.20	26.6%	19.8%	132	-0.39	2.53	364	67
Cory Gearrin R 2015 · 3.52 FIP	29	SU	3.52	22.1%	7.5%	2.5%	.283	3.54	22.2%	13.6%	174	+0.02	1.81	341	67
Diego Moreno R 2016 · 3.75 FIP	29	SU	3.75	21.0%	8.2%	2.5%	.347	3.13	17.8%	11.9%	54	-0.62	2.29	187	66
Tyler Yates R 2007 · 3.23 FIP	29	SU	3.23	23.5%	7.8%	2.0%	.296	4.06	18.6%	7.5%	85	+0.83	3.23	248	66
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	66

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	2.0	56	22.6%	7.3%	1.19	3.49
Jason Motte ('17)	2.0	50	23.0%	7.7%	1.11	3.30
Fernando Salas ('19)	2.4	54	23.1%	7.3%	1.05	3.91
Héctor Rondón ('20)	2.2	54	24.2%	7.4%	1.03	3.49
Joe Hoerner ('63-'77, 8 WAR*)	2.8	51	23.2%*	7.9%*	1.21*	3.52*
Tony Castillo ('88-'98, 4 WAR*)	2.6	59	18.5%*	7.3%*	0.98*	3.76*
John Habyan ('85-'96, 6 WAR*)	2.7	67	21.0%*	7.8%*	0.92*	3.83*