Brad Keller

P Philadelphia Phillies

Age 32 RHP 6'5" / 255 lbs MLB peak 0.2 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MIX2 levels	32	15	110	4.09	3.88	19.3%	8.0%	0.9	K 17.6% · BB 7.5% · FIP 4.01
2025	30	MLBCHC	68	1	70	2.07	2.64	27.2%	8.0%	1.6
2026	31	MIX2 levels	34	0	33	4.32	4.24	23.1%	9.1%	0.1	K 23.7% · BB 9.6% · FIP 3.83
2027PROJ	32	MLBPHI	3	3	21	3.85	3.94	24.5%	8.6%	0.4
2028PROJ	33	MLBPHI	5	5	30	4.07	4.22	23.6%	9.0%	0.4

Last 3 seasons WAR 2.6 · Next 2 projected WAR 0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo85

xwOBA vs79

K%58

CompsElian Leyva (age 30) · Mitch Lively (age 31) · Mike Burns (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 108100vR 92

ERA3.85

FIP3.94

K%24.5%

BB%8.6%

K-BB%15.9%

Proj IP21

Value2027 · WAR

Runs saved vs league avg · 21 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p8597.0

Whiff%

p3022.5%

p5823.7%

xwOBA vs

p790.284

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)
2015	20	A MLE	Kane County Cougars	26	25	142	586	109	37	3	96%	5.5	13.8%	7.5%	6.3%	0.8%	2.60	3.30	—
2015	20	A RAW	Kane County Cougars	26	25	142	586	109	37	3	96%	5.5	18.6%	6.3%	12.3%	0.5%	2.60	2.62	—
2016	21	A+ MLE	Visalia Rawhide	24	24	135	558	99	26	13	100%	5.6	13.7%	5.4%	8.3%	2.6%	4.47	4.03	—
2016	21	A+ RAW	Visalia Rawhide	24	24	135	558	99	26	13	100%	5.6	17.7%	4.7%	13.1%	2.3%	4.47	3.46	—
2017	22	AA MLE	Jackson Generals	26	26	131	580	111	56	7	100%	5.0	15.5%	10.6%	4.9%	1.5%	4.68	3.94	—
2017	22	AA RAW	Jackson Generals	26	26	131	580	111	56	7	100%	5.0	19.1%	9.7%	9.5%	1.2%	4.68	3.38	—
2018	23	MLB MLE	Kansas City Royals	41	20	140	583	96	49	7	49%	3.4	16.5%	8.4%	8.1%	1.3%	3.08	3.49	+1.8
2018	23	MLB RAW	Kansas City Royals	41	20	140	583	96	49	7	49%	3.4	16.5%	8.4%	8.1%	1.2%	3.08	3.43	+1.9
2019	24	MLB MLE	Kansas City Royals	28	28	165	709	122	68	15	100%	5.9	17.2%	9.6%	7.6%	2.3%	4.19	4.12	+2.5
2019	24	MLB RAW	Kansas City Royals	28	28	165	709	122	68	15	100%	5.9	17.2%	9.6%	7.6%	2.1%	4.19	4.04	+2.7
2020	25	MLB MLE	Kansas City Royals	9	9	55	215	35	17	2	100%	6.1	16.3%	7.9%	8.4%	1.0%	2.47	3.28	+1.4
2020	25	MLB RAW	Kansas City Royals	9	9	55	215	35	17	2	100%	6.1	16.3%	7.9%	8.4%	0.9%	2.47	3.23	+1.5
2021	26	MLB MLE	Kansas City Royals	26	26	134	613	120	63	18	100%	5.1	19.6%	10.3%	9.3%	3.2%	5.39	4.49	+1.4
2021	26	MLB RAW	Kansas City Royals	26	26	134	613	120	63	18	100%	5.1	19.6%	10.3%	9.3%	2.9%	5.39	4.47	+1.5
2022	27	MLB MLE	Kansas City Royals	35	22	140	617	102	56	17	63%	4.0	16.5%	9.1%	7.5%	3.0%	5.09	4.49	+1.5
2022	27	MLB RAW	Kansas City Royals	35	22	140	617	102	56	17	63%	4.0	16.5%	9.1%	7.5%	2.8%	5.09	4.42	+1.6
2023	28	MIX MLE	4 levels	28	12	65	318	46	73	5	43%	2.3	13.1%	23.7%	-10.6%	1.6%	6.26	5.89	-1.0
2023	28	MIX RAW	4 levels	28	12	65	318	46	73	5	43%	2.3	14.5%	23.0%	-8.5%	1.6%	6.26	6.07	-1.1
2024	29	MIX MLE	2 levels	32	15	110	476	92	38	12	47%	3.4	17.6%	7.5%	10.1%	2.6%	4.09	4.01	+0.7
2024	29	MIX MLE	2 levels	32	15	110	476	92	38	12	47%	3.4	17.6%	7.5%	10.1%	2.6%	4.09	4.01	+0.7
2024	29	MIX RAW	2 levels	32	15	110	476	92	38	12	47%	3.4	19.3%	8.0%	11.3%	2.5%	4.09	3.88	+0.9
2025	30	MLB MLE	Chicago Cubs	68	1	70	276	75	22	4	1%	1.0	27.2%	8.0%	19.2%	1.5%	2.07	2.64	+1.6
2025	30	MLB MLE	Chicago Cubs	68	1	70	276	75	22	4	1%	1.0	27.2%	8.0%	19.2%	1.5%	2.07	2.64	+1.6
2025	30	MLB RAW	Chicago Cubs	68	1	70	276	75	22	4	1%	1.0	27.2%	8.0%	19.2%	1.4%	2.07	2.64	+1.6
2026	31	MIX MLE	2 levels	34	0	33	143	33	13	5	0%	1.0	23.7%	9.6%	14.1%	2.8%	4.32	3.83	+0.3
2026	31	MIX MLE	2 levels	34	0	33	143	33	13	5	0%	1.0	23.7%	9.6%	14.1%	2.8%	4.32	3.83	+0.3
2026	31	MIX RAW	2 levels	34	0	33	143	33	13	5	0%	1.0	23.1%	9.1%	14.0%	3.5%	4.32	4.24	+0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			266	117	821	3551	645	348	79	44%	3.1	18.2%	9.8%	8.4%	2.2%	4.13	4.05	+4.9
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	PHI	3	3	21	89	22	8	2	100%	7.0	24.5%	8.6%	15.9%	2.6%	3.85	3.94	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	PHI	5	5	30	125	30	11	4	100%	5.9	23.6%	9.0%	14.6%	2.9%	4.07	4.22	+0.4
2028	33	MLB CTX	PHI	5	5	30	127	30	11	4	100%	6.0	23.6%	9.0%	14.6%	2.9%	4.07	4.22	+0.4
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		271	122	851	3676	675	359	83	45%	3.1	18.4%	9.8%	8.6%	2.2%	4.13	4.02	+5.3
/ 200 IP	—	RAW		64	29	200	864	159	84	20	45%	3.1	18.4%	9.8%	8.6%	2.2%	4.13	4.02	+1.3
Career	—	MLE		377	208	1319	5674	956	535	117	55%	3.5	16.8%	9.4%	7.4%	2.1%	4.11	4.00	+13.6
/ 200 IP	—	MLE		57	32	200	860	145	81	18	55%	3.5	16.8%	9.4%	7.4%	2.1%	4.11	4.00	+3.2

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.

2024 AAAWorcester Red Sox · 69 IPFIP 2.92 → 3.13 (+0.21)K% 21.1% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.13%	—	×0.860	18.17%
BB% (unintentional) /BF	8.10%	—	×0.900	7.29%
HR / BF /BF	1.06%	÷0.996	×1.100	1.17%

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 99).

Result: FIP 2.92 → 3.13, 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 AAAOmaha Storm Chasers · 9 IPFIP 7.82 → 7.63 (−0.19)K% 8.5% → 7.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	8.47%	—	×0.860	7.29%
BB% (unintentional) /BF	35.59%	—	×0.900	32.03%
HR / BF /BF	1.69%	÷0.942	×1.100	1.98%

Result: FIP 7.82 → 7.63, 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 AANorthwest Arkansas Naturals · 9 IPFIP 4.13 → 5.17 (+1.04)K% 21.6% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.62%	—	×0.810	17.51%
BB% (unintentional) /BF	10.81%	—	×1.100	11.89%
HR / BF /BF	2.70%	÷0.872	×1.200	3.72%

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 74).

Result: FIP 4.13 → 5.17, 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 AAJackson Generals · 131 IPFIP 3.37 → 3.94 (+0.57)K% 19.1% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.14%	—	×0.810	15.50%
BB% (unintentional) /BF	9.66%	—	×1.100	10.62%
HR / BF /BF	1.21%	÷0.985	×1.200	1.47%

Result: FIP 3.37 → 3.94, 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 A+Visalia Rawhide · 135 IPFIP 3.47 → 4.03 (+0.56)K% 17.7% → 13.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.74%	—	×0.770	13.66%
BB% (unintentional) /BF	4.66%	—	×1.150	5.36%
HR / BF /BF	2.33%	÷1.134	×1.250	2.57%

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 127).

Result: FIP 3.47 → 4.03, 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).

2015 AKane County Cougars · 142 IPFIP 2.61 → 3.30 (+0.69)K% 18.6% → 13.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.60%	—	×0.740	13.76%
BB% (unintentional) /BF	6.31%	—	×1.180	7.45%
HR / BF /BF	0.51%	÷0.881	×1.300	0.76%

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 76).

Result: FIP 2.61 → 3.30, 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).

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
Brad Keller (OGILVIE)	—	—	—	—	—	2.6%	—	4.22	23.7%	14.6%	30	+0.28	—	—	—
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	64
Mitch Lively R 2017 · 3.47 FIP	31	SP-	3.47	17.0%	6.4%	1.8%	.304	—	—	—	—	—	2.39	158	62
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	60
Radhames Liz R 2015 · 2.81 FIP	31	SW	2.81	24.8%	9.2%	1.2%	.283	4.45	21.8%	7.9%	23	+1.64	2.81	219	58
Angel Sánchez R 2023 · 4.90 FIP	33	SW	4.90	19.0%	10.5%	3.8%	.333	3.77	11.8%	6.8%	27	-1.13	3.77	284	57
Jared Fernandez R 2003 · 3.57 FIP	31	SP-	3.57	11.8%	6.2%	1.2%	.269	—	—	—	—	—	3.57	101	55
Chris Jakubauskas R 2011 · 4.42 FIP	32	SW	4.42	15.7%	7.9%	3.0%	.339	—	—	—	—	—	4.42	165	54
Mike Fyhrie R 2002 · 3.86 FIP	32	SW	3.86	13.7%	9.0%	1.4%	.267	—	—	—	—	—	3.08	173	52
Todd Redmond R 2015 · 3.86 FIP	30	SW	3.86	15.4%	7.1%	2.1%	.311	—	—	—	—	—	3.21	247	52
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	51
Tim Dillard R 2015 · 3.58 FIP	32	SW	3.58	15.9%	7.7%	1.5%	.330	3.85	16.7%	8.1%	144	+0.27	2.92	432	51
Yohan Pino R 2015 · 4.13 FIP	31	SP-	4.13	17.8%	5.8%	3.3%	.312	5.33	15.2%	11.6%	35	+1.20	3.84	193	51
Bruce Billings R 2015 · 3.09 FIP	29	SP-	3.09	15.6%	5.6%	1.1%	.309	—	—	—	—	—	3.09	121	50
Reinier Roibal R 2019 · 4.91 FIP	30	SP	4.91	17.5%	11.8%	3.3%	.426	—	—	—	—	—	3.11	133	49
Cody Satterwhite R 2017 · 4.22 FIP	30	SU	4.22	17.0%	7.1%	3.0%	.310	—	—	—	—	—	3.69	147	49
Brian Sanches R 2011 · 4.35 FIP	32	SU	4.35	19.6%	11.1%	2.7%	.250	—	—	—	—	—	3.39	229	48
Miguel Socolovich R 2018 · 3.55 FIP	32	SU	3.55	20.8%	5.6%	2.7%	.338	3.55	18.4%	13.7%	42	+0.00	2.65	299	48
Austin Bibens-Dirkx R 2017 · 5.03 FIP	32	SW	5.03	14.0%	6.6%	4.2%	.268	5.28	17.5%	9.7%	166	+0.25	3.97	567	48
Hector Velázquez R 2021 · 3.81 FIP	32	SU	3.81	19.2%	8.3%	2.3%	.304	—	—	—	—	—	2.75	536	48
Danny Gutierrez R 2017 · 4.11 FIP	30	SP	4.11	15.1%	6.1%	2.8%	.362	—	—	—	—	—	3.34	239	47

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	4.4	79	18.5%	9.9%	0.87	4.12
Tom Gorzelanny ('16)	4.4	88	18.4%	10.0%	1.00	4.40
Don Aase ('77-'90, 12 WAR*)	5.5	92	20.7%*	9.6%*	0.94*	4.14*
Don Hood ('73-'83, 4 WAR*)	4.2	85	16.0%*	9.9%*	0.85*	4.22*
Neil Allen ('79-'89, 6 WAR*)	4.9	99	19.8%*	9.8%*	0.93*	4.33*
Darren Dreifort ('04)	4.4	97	21.2%	10.3%	0.93	4.36
Chad Gaudin ('13)	4.2	93	18.2%	10.3%	0.99	4.44