Mitch Keller

P Pittsburgh Pirates

Age 31 RHP 6'3" / 213 lbs MLB peak 0.6 · 2027 ILInjured 60-Day (D60)

Overview

MLBSPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR
2024	28	MLBPIT	31	31	178	4.25	3.76	21.5%	6.5%	3.5
2025	29	MLBPIT	32	32	176	4.19	3.81	20.0%	6.8%	3.4
2026	30	MLBPIT	22	22	116	5.29	4.34	17.7%	8.3%	1.4
2027PROJ	31	MLBPIT	9	9	53	4.54	4.54	19.1%	7.6%	0.5
2028PROJ	32	MLBPIT	12	12	75	4.69	4.80	18.3%	8.0%	0.5
2029PROJ	33	MLBPIT	9	9	56	4.92	5.08	17.5%	8.4%	0.2

Last 3 seasons WAR 8.3 · Next 3 projected WAR 1.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo33

K%19

xwOBA vs14

CompsMiguel González (age 31) · Chase Anderson (age 31) · Orlando Hernandez (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 125117vR 108

ERA4.54

FIP4.54

K%19.1%

BB%7.6%

K-BB%11.5%

Proj IP53

Value2027 · WAR

Runs saved vs league avg · 53 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p3393.3

Whiff%

p1620.5%

p1917.7%

xwOBA vs

p140.355

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	19	ROK MLE	Bristol Pirates	6	6	20	101	25	16	1	100%	3.3	16.8%	19.8%	-3.0%	1.4%	5.49	4.95	—
2015	19	ROK RAW	Bristol Pirates	6	6	20	101	25	16	1	100%	3.3	24.8%	15.8%	8.9%	1.0%	5.49	3.66	—
2016	20	MIX MLE	2 levels	24	24	130	511	138	19	4	100%	5.4	19.9%	4.4%	15.5%	1.0%	2.35	2.52	—
2016	20	MIX RAW	2 levels	24	24	130	511	138	19	4	100%	5.4	27.0%	3.7%	23.3%	0.8%	2.35	1.82	—
2017	21	MIX MLE	2 levels	21	21	112	448	109	31	7	100%	5.3	19.1%	7.8%	11.3%	1.9%	3.13	3.54	—
2017	21	MIX RAW	2 levels	21	21	112	448	109	31	7	100%	5.3	24.3%	6.9%	17.4%	1.6%	3.13	2.80	—
2018	22	MIX MLE	3 levels	25	25	142	597	135	55	10	100%	5.7	19.3%	10.1%	9.2%	2.2%	3.48	3.98	—
2018	22	MIX RAW	3 levels	25	25	142	597	135	55	10	100%	5.7	22.6%	9.2%	13.4%	1.7%	3.48	3.28	—
2019	23	MIX MLE	2 levels	30	30	152	663	188	51	15	100%	5.1	26.1%	8.0%	18.2%	2.5%	4.69	3.30	+3.9
2019	23	MIX RAW	2 levels	30	30	152	663	188	51	15	100%	5.1	28.4%	7.7%	20.7%	2.3%	4.69	2.92	+4.7
2020	24	MLB MLE	Pittsburgh Pirates	5	5	22	87	16	18	4	100%	4.3	18.4%	20.7%	-2.3%	5.0%	2.91	6.90	-0.4
2020	24	MLB RAW	Pittsburgh Pirates	5	5	22	87	16	18	4	100%	4.3	18.4%	20.7%	-2.3%	4.6%	2.91	6.52	-0.3
2021	25	MIX MLE	2 levels	31	29	129	598	131	60	12	94%	4.2	21.1%	10.1%	11.0%	2.1%	5.53	3.78	+2.5
2021	25	MIX RAW	2 levels	31	29	129	598	131	60	12	94%	4.2	21.9%	10.0%	11.9%	2.0%	5.53	3.68	+2.7
2022	26	MLB MLE	Pittsburgh Pirates	31	29	159	687	138	59	14	94%	5.1	20.1%	8.6%	11.5%	2.2%	3.91	3.70	+3.3
2022	26	MLB RAW	Pittsburgh Pirates	31	29	159	687	138	59	14	94%	5.1	20.1%	8.6%	11.5%	2.0%	3.91	3.62	+3.4
2023	27	MLB MLE	Pittsburgh Pirates	32	32	194	825	210	55	25	100%	6.1	25.5%	6.7%	18.8%	3.3%	4.21	3.59	+4.3
2023	27	MLB RAW	Pittsburgh Pirates	32	32	194	825	210	55	25	100%	6.1	25.5%	6.7%	18.8%	3.0%	4.21	3.46	+4.6
2024	28	MLB MLE	Pittsburgh Pirates	31	31	178	773	166	50	23	100%	5.7	21.5%	6.5%	15.0%	3.2%	4.25	3.87	+3.3
2024	28	MLB MLE	Pittsburgh Pirates	31	31	178	773	166	50	23	100%	5.7	21.5%	6.5%	15.0%	3.2%	4.25	3.87	+3.3
2024	28	MLB RAW	Pittsburgh Pirates	31	31	178	773	166	50	23	100%	5.7	21.5%	6.5%	15.0%	3.0%	4.25	3.76	+3.5
2025	29	MLB MLE	Pittsburgh Pirates	32	32	176	749	150	51	21	100%	5.5	20.0%	6.8%	13.2%	3.0%	4.19	3.94	+3.1
2025	29	MLB MLE	Pittsburgh Pirates	32	32	176	749	150	51	21	100%	5.5	20.0%	6.8%	13.2%	3.0%	4.19	3.94	+3.1
2025	29	MLB RAW	Pittsburgh Pirates	32	32	176	749	150	51	21	100%	5.5	20.0%	6.8%	13.2%	2.8%	4.19	3.81	+3.4
2026	30	MLB MLE	Pittsburgh Pirates	22	22	116	503	89	42	15	100%	5.3	17.7%	8.3%	9.3%	3.2%	5.29	4.43	+1.3
2026	30	MLB MLE	Pittsburgh Pirates	22	22	116	503	89	42	15	100%	5.3	17.7%	8.3%	9.3%	3.2%	5.29	4.43	+1.3
2026	30	MLB RAW	Pittsburgh Pirates	22	22	116	503	89	42	15	100%	5.3	17.7%	8.3%	9.3%	3.0%	5.29	4.34	+1.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			187	185	994	4321	926	339	118	99%	5.3	21.4%	7.8%	13.6%	2.7%	4.60	3.80	+19.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	PIT	9	9	53	224	43	17	7	100%	5.9	19.1%	7.6%	11.5%	3.1%	4.54	4.54	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	PIT	13	13	75	317	58	25	11	100%	5.8	18.3%	8.0%	10.3%	3.4%	4.69	4.80	+0.5
2029	33	MLB MLE	PIT	9	9	56	239	42	20	9	100%	6.3	17.5%	8.4%	9.0%	3.7%	4.92	5.08	+0.2
2028	32	MLB CTX	PIT	12	12	75	317	58	25	11	100%	6.2	18.3%	8.0%	10.3%	3.4%	4.69	4.80	+0.5
2029	33	MLB CTX	PIT	9	9	56	236	41	20	9	100%	6.2	17.5%	8.4%	9.0%	3.7%	4.92	5.08	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		209	207	1125	4877	1026	384	137	99%	5.4	21.0%	7.9%	13.2%	2.8%	4.62	3.87	+20.6
/ 200 IP	—	RAW		37	37	200	867	182	68	24	99%	5.4	21.0%	7.9%	13.2%	2.8%	4.62	3.87	+3.7
Career	—	MLE		290	286	1530	6542	1388	526	169	99%	5.3	21.2%	8.0%	13.2%	2.6%	4.11	3.74	+19.7
/ 200 IP	—	MLE		38	37	200	855	182	69	22	99%	5.3	21.2%	8.0%	13.2%	2.6%	4.11	3.74	+3.5

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.

2021 AAAIndianapolis Indians · 28 IPFIP 2.57 → 2.94 (+0.37)K% 30.5% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.47%	—	×0.880	26.81%
BB% (unintentional) /BF	9.38%	—	×1.050	9.84%
HR / BF /BF	1.56%	÷1.096	×1.100	1.57%

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 119).

Result: FIP 2.57 → 2.94, 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).

2019 AAAIndianapolis Indians · 104 IPFIP 2.87 → 3.38 (+0.51)K% 28.2% → 24.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.21%	—	×0.880	24.83%
BB% (unintentional) /BF	8.03%	—	×1.050	8.43%
HR / BF /BF	2.06%	÷0.953	×1.100	2.38%

Result: FIP 2.87 → 3.38, 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 AAAltoona Curve · 86 IPFIP 3.53 → 4.46 (+0.92)K% 22.2% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.22%	—	×0.810	18.00%
BB% (unintentional) /BF	9.36%	—	×1.100	10.29%
HR / BF /BF	2.05%	÷0.857	×1.200	2.87%

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 71).

Result: FIP 3.53 → 4.46, 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 AAAIndianapolis Indians · 52 IPFIP 2.94 → 3.28 (+0.34)K% 24.2% → 21.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.15%	—	×0.880	21.25%
BB% (unintentional) /BF	9.32%	—	×1.050	9.79%
HR / BF /BF	1.27%	÷1.041	×1.100	1.34%

Result: FIP 2.94 → 3.28, 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+Bradenton Marauders · 77 IPFIP 3.06 → 3.84 (+0.78)K% 20.9% → 16.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.92%	—	×0.770	16.10%
BB% (unintentional) /BF	6.54%	—	×1.150	7.52%
HR / BF /BF	1.63%	÷0.976	×1.250	2.09%

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 95).

Result: FIP 3.06 → 3.84, 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 AAAltoona Curve · 35 IPFIP 2.18 → 2.91 (+0.73)K% 31.7% → 25.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.69%	—	×0.810	25.67%
BB% (unintentional) /BF	7.75%	—	×1.100	8.52%
HR / BF /BF	1.41%	÷1.035	×1.200	1.63%

Result: FIP 2.18 → 2.91, 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 AWest Virginia Power · 124 IPFIP 1.75 → 2.52 (+0.77)K% 26.8% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.84%	—	×0.740	19.86%
BB% (unintentional) /BF	3.69%	—	×1.180	4.35%
HR / BF /BF	0.82%	÷1.069	×1.300	1.00%

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 114).

Result: FIP 1.75 → 2.52, 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).

2016 A+Bradenton Marauders · 6 IPFIP 1.08 → 1.75 (+0.67)K% 30.4% → 23.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.43%	—	×0.770	23.43%
BB% (unintentional) /BF	4.35%	—	×1.150	5.00%
HR / BF /BF	0.00%	÷1.098	×1.250	0.00%

Result: FIP 1.08 → 1.75, 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
Mitch Keller (OGILVIE)	—	—	—	—	—	3.1%	—	4.92	17.9%	9.8%	132	+0.38	—	—	—
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	78
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	70
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
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	67
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
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	64
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	64
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	63
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
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	60
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	57
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	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	56
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	56
Chuck Smith R 2001 · 3.99 FIP	31	SP	3.99	18.4%	8.1%	2.6%	.289	—	—	—	—	—	3.08	211	55
Jeremy Guthrie R 2010 · 4.08 FIP	31	SP	4.08	13.6%	5.6%	2.6%	.247	4.68	13.2%	6.8%	601	+0.60	4.08	1,834	55
Miguel Batista R 2002 · 3.81 FIP	31	SP-	3.81	14.2%	8.5%	1.5%	.267	4.13	14.9%	6.3%	467	+0.32	3.39	1,943	55
Brian Tollberg R 2002 · 4.98 FIP	29	SP	4.98	11.5%	5.9%	3.8%	.339	—	—	—	—	—	4.02	297	53
Jeremy Hefner R 2016 · 4.64 FIP	30	SP	4.64	16.8%	9.1%	3.3%	.305	—	—	—	—	—	3.56	322	53
Robert Person R 2001 · 4.60 FIP	31	SP	4.60	21.1%	8.9%	3.9%	.253	5.06	16.0%	2.7%	99	+0.46	3.41	885	53

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	5.9	108	20.9%	7.9%	1.10	4.62
Bud Norris ('18)	6.1	122	21.7%	9.1%	1.15	4.45
Dan Spillner ('74-'85, 5 WAR*)	7.5	124	20.6%*	9.1%*	1.11*	4.64*
Skip Lockwood ('69-'80, 11 WAR*)	6.2	103	22.5%*	9.1%*	1.06*	4.28*
Bob Shirley ('77-'87, 5 WAR*)	7.2	130	18.5%*	8.9%*	1.12*	4.43*
Travis Wood ('17)	5.0	124	18.9%	8.7%	1.09	4.26
Carlos Villanueva ('16)	5.0	91	20.4%	7.6%	1.25	4.31