Justus Sheffield

P Louisville Bats

Age 31 LHP 5'10" / 224 lbs AAA peak 0.5 · 2027

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	26	MIX2 levels	30	25	115	6.67	5.13	17.2%	9.8%	0.4	K 15.3% · BB 10.2% · FIP 5.06
2023	27	MIX2 levels	24	12	64	7.63	5.22	19.9%	15.2%	—	K 17.4% · BB 13.6% · FIP 5.22
2024	28	MIX2 levels	19	8	47	6.75	4.54	20.1%	11.8%	—	K 15.9% · BB 10.8% · FIP 4.64
2025	29	No MLB games played
2026	30	No MLB games played
2027PROJ	31	MLBCIN	4	4	23	4.54	4.55	21.6%	9.6%	0.2
2028PROJ40% MLB	32	MLBCIN	8	8	51	4.70	4.80	20.8%	10.0%	0.4
2029PROJ57% MLB	33	MLBCIN	10	10	60	4.93	5.08	19.9%	10.4%	0.2

Last 3 seasons WAR 0.4 · Next 3 projected WAR 0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2022

xwOBA vs15

FB Velo10

K%10

CompsJorge Castillo (age 33) · Tomas Solis (age 32) · Arturo Lopez (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 103112vR 120

ERA4.54

FIP4.55

K%21.6%

BB%9.6%

K-BB%12.0%

Proj IP165

Value2027 · WAR

Runs saved vs league avg · 165 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1091.6

Whiff%

p1014.9%

p1013.7%

xwOBA vs

p150.353

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	A MLE	Lake County Captains	26	26	128	555	138	38	8	100%	4.9	18.4%	8.1%	10.3%	1.6%	3.31	3.45	—
2015	19	A RAW	Lake County Captains	26	26	128	555	138	38	8	100%	4.9	24.9%	6.8%	18.0%	1.4%	3.31	2.65	—
2016	20	MIX MLE	2 levels	25	25	125	526	129	53	6	100%	5.0	18.2%	11.3%	6.9%	1.7%	3.09	3.94	—
2016	20	MIX RAW	2 levels	25	25	125	526	129	53	6	100%	5.0	24.5%	10.1%	14.4%	1.1%	3.09	2.93	—
2017	21	MIX MLE	2 levels	19	19	98	423	88	33	14	100%	5.2	16.4%	8.7%	7.7%	4.3%	3.12	5.19	—
2017	21	MIX RAW	2 levels	19	19	98	423	88	33	14	100%	5.2	20.8%	7.8%	13.0%	3.3%	3.12	4.17	—
2018	22	MIX MLE	3 levels	28	20	119	489	123	53	5	71%	4.2	22.2%	11.2%	11.0%	0.9%	2.65	3.14	+3.3
2018	22	MIX RAW	3 levels	28	20	119	489	123	53	5	71%	4.2	25.2%	10.8%	14.3%	1.0%	2.65	2.91	+3.7
2019	23	MIX MLE	3 levels	33	31	169	736	170	77	21	94%	5.1	20.1%	11.0%	9.1%	3.2%	4.42	4.57	+1.6
2019	23	MIX RAW	3 levels	33	31	169	736	170	77	21	94%	5.1	23.1%	10.5%	12.6%	2.9%	4.42	4.07	+2.7
2020	24	MLB MLE	Seattle Mariners	10	10	55	232	48	20	2	100%	5.5	20.7%	8.6%	12.1%	0.9%	3.58	2.93	+1.7
2020	24	MLB RAW	Seattle Mariners	10	10	55	232	48	20	2	100%	5.5	20.7%	8.6%	12.1%	0.9%	3.58	2.92	+1.7
2021	25	MIX MLE	2 levels	26	17	89	424	77	49	15	65%	3.4	16.4%	10.9%	5.5%	3.7%	7.00	5.15	+0.3
2021	25	MIX RAW	2 levels	26	17	89	424	77	49	15	65%	3.4	18.2%	11.6%	6.6%	3.5%	7.00	5.22	+0.2
2022	26	MIX MLE	2 levels	30	25	115	541	93	53	20	83%	3.8	15.3%	10.2%	5.1%	3.6%	6.67	5.06	+0.4
2022	26	MIX RAW	2 levels	30	25	115	541	93	53	20	83%	3.8	17.2%	9.8%	7.4%	3.7%	6.67	5.13	+0.4
2023	27	MIX MLE	2 levels	24	12	64	302	60	46	9	50%	2.7	17.4%	13.6%	3.7%	3.4%	7.63	5.22	—
2023	27	MIX RAW	2 levels	24	12	64	302	60	46	9	50%	2.7	19.9%	15.2%	4.6%	3.0%	7.63	5.22	—
2024	28	MIX MLE	2 levels	19	8	47	229	46	27	6	42%	2.5	15.9%	10.8%	5.1%	2.8%	6.75	4.64	—
2024	28	MIX MLE	2 levels	19	8	47	229	46	27	6	42%	2.5	15.9%	10.8%	5.1%	2.8%	6.75	4.64	—
2024	28	MIX RAW	2 levels	19	8	47	229	46	27	6	42%	2.5	20.1%	11.8%	8.3%	2.6%	6.75	4.54	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			48	33	186	850	155	89	23	69%	3.9	18.2%	10.5%	7.8%	2.7%	5.47	4.48	+2.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	CIN	4	4	23	97	21	9	3	100%	5.8	21.6%	9.6%	12.0%	3.1%	4.54	4.55	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	CIN	21	21	128	541	112	54	18	100%	6.1	20.8%	10.0%	10.8%	3.3%	4.70	4.80	+0.9
2029	33	MLB MLE	CIN	17	17	105	442	88	46	16	100%	6.2	19.9%	10.4%	9.5%	3.6%	4.93	5.08	+0.4
2030	34	MLB MLE	CIN	14	14	86	365	70	40	14	100%	6.2	19.0%	10.9%	8.1%	3.9%	5.20	5.39	+0.0
2028	32	MLB CTX	CIN	8	8	51	215	45	21	7	100%	6.4	20.8%	10.0%	10.8%	3.3%	4.70	4.80	+0.4
2029	33	MLB CTX	CIN	10	10	60	253	50	26	9	100%	6.0	19.9%	10.4%	9.5%	3.6%	4.93	5.08	+0.2
2030	34	MLB CTX	CIN	8	8	45	190	36	21	7	100%	5.6	19.0%	10.9%	8.1%	3.9%	5.20	5.39	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		74	59	342	1508	286	158	47	80%	4.6	19.0%	10.5%	8.5%	3.1%	5.22	4.52	+3.5
/ 200 IP	—	RAW		43	35	200	882	167	92	28	80%	4.6	19.0%	10.5%	8.5%	3.1%	5.22	4.52	+2.1
Career	—	MLE		240	193	1008	4457	813	464	118	80%	4.2	18.2%	10.4%	7.8%	2.7%	4.53	4.33	+3.3
/ 200 IP	—	MLE		48	38	200	885	161	92	23	80%	4.2	18.2%	10.4%	7.8%	2.7%	4.53	4.33	+1.3

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 AAALouisville Bats · 43 IPFIP 4.59 → 4.64 (+0.05)K% 18.5% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.52%	—	×0.860	15.93%
BB% (unintentional) /BF	12.04%	—	×0.900	10.83%
HR / BF /BF	2.78%	÷1.111	×1.100	2.75%

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 122).

Result: FIP 4.59 → 4.64, 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 AAAGwinnett Stripers · 63 IPFIP 4.98 → 5.22 (+0.24)K% 20.2% → 17.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.20%	—	×0.860	17.37%
BB% (unintentional) /BF	15.15%	—	×0.900	13.64%
HR / BF /BF	3.03%	÷0.984	×1.100	3.39%

Result: FIP 4.98 → 5.22, 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 AAATacoma Rainiers · 103 IPFIP 4.96 → 5.12 (+0.16)K% 17.6% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.55%	—	×0.880	15.44%
BB% (unintentional) /BF	9.59%	—	×1.050	10.07%
HR / BF /BF	3.88%	÷1.144	×1.100	3.73%

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 129).

Result: FIP 4.96 → 5.12, 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 AAATacoma Rainiers · 8 IPFIP 3.75 → 4.42 (+0.67)K% 35.9% → 31.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.90%	—	×0.880	31.59%
BB% (unintentional) /BF	17.95%	—	×1.050	18.85%
HR / BF /BF	2.56%	÷0.970	×1.100	2.91%

Result: FIP 3.75 → 4.42, 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 AAArkansas Travelers · 78 IPFIP 2.21 → 3.12 (+0.90)K% 27.9% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.87%	—	×0.810	22.57%
BB% (unintentional) /BF	5.90%	—	×1.100	6.49%
HR / BF /BF	1.31%	÷0.784	×1.200	2.01%

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 57).

Result: FIP 2.21 → 3.12, 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 AAATacoma Rainiers · 55 IPFIP 6.04 → 6.44 (+0.40)K% 18.3% → 16.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.25%	—	×0.880	16.06%
BB% (unintentional) /BF	15.59%	—	×1.050	16.37%
HR / BF /BF	4.56%	÷1.049	×1.100	4.78%

Result: FIP 6.04 → 6.44, 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 AAAScranton/Wilkes-Barre RailRiders · 88 IPFIP 2.86 → 3.18 (+0.32)K% 23.1% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.14%	—	×0.880	20.36%
BB% (unintentional) /BF	9.92%	—	×1.050	10.41%
HR / BF /BF	0.83%	÷1.046	×1.100	0.87%

Result: FIP 2.86 → 3.18, 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 AATrenton Thunder · 28 IPFIP 2.23 → 3.03 (+0.80)K% 34.8% → 28.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.82%	—	×0.810	28.21%
BB% (unintentional) /BF	12.50%	—	×1.100	13.75%
HR / BF /BF	0.89%	÷1.034	×1.200	1.04%

Result: FIP 2.23 → 3.03, 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).

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
Justus Sheffield (OGILVIE)	—	—	—	—	—	3.1%	—	5.05	20.0%	9.6%	319	+0.50	—	—	—
Jorge Castillo L 2015 · 4.50 FIP	33	SP	4.50	16.8%	9.2%	3.0%	.292	4.95	12.4%	7.2%	186	+0.45	4.50	408	68
Tomas Solis L 2015 · 4.20 FIP	32	SP	4.20	15.0%	6.2%	2.9%	.264	5.09	12.0%	3.7%	159	+0.89	4.20	327	65
Arturo Lopez L 2015 · 4.80 FIP	32	SP	4.80	13.7%	6.2%	3.8%	.301	4.80	10.9%	4.2%	217	+0.00	4.34	445	65
Alejandro Astorga L 2017 · 4.01 FIP	30	SP	4.01	14.4%	8.2%	2.0%	.306	—	—	—	—	—	3.72	311	63
Chris Narveson L 2011 · 4.01 FIP	29	SP	4.01	18.0%	9.2%	2.3%	.291	—	—	—	—	—	4.00	625	63
Oscar Rivera L 2015 · 3.68 FIP	34	SP	3.68	14.2%	6.9%	1.7%	.298	4.66	10.4%	3.0%	129	+0.98	3.68	237	62
Daniel Rodriguez L 2016 · 4.46 FIP	31	SP	4.46	19.3%	11.1%	2.9%	.333	4.32	16.9%	8.2%	226	-0.14	2.89	391	61
Brian Tallet L 2009 · 4.45 FIP	31	SP-	4.45	16.7%	9.8%	2.8%	.294	6.14	14.7%	5.2%	91	+1.69	2.59	443	61
Roy Merritt L 2017 · 3.95 FIP	31	SP	3.95	16.2%	5.8%	2.7%	.339	—	—	—	—	—	3.93	129	60
Paul Oseguera L 2015 · 3.83 FIP	31	SP	3.83	17.6%	8.5%	2.1%	.297	5.62	5.6%	-6.9%	28	+1.79	3.83	162	60
Everett Teaford L 2015 · 4.42 FIP	31	SP-	4.42	13.9%	7.6%	2.8%	.324	—	—	—	—	—	4.42	208	59
Joey Lucchesi L 2024 · 4.73 FIP	31	SP-	4.73	14.9%	10.1%	2.9%	.293	3.65	22.6%	15.8%	102	-1.08	3.12	817	58
Orlando Lara L 2016 · 3.85 FIP	31	SP	3.85	13.8%	7.4%	1.8%	.308	4.24	18.5%	11.3%	202	+0.39	3.85	426	57
Ryan Verdugo L 2017 · 3.36 FIP	30	SP-	3.36	22.7%	5.4%	2.7%	.333	—	—	—	—	—	3.36	153	57
Frank Garces L 2019 · 4.84 FIP	29	SP	4.84	15.0%	7.9%	3.6%	.334	—	—	—	—	—	4.32	306	56
Tsuyoshi Wada L 2014 · 3.60 FIP	33	SP	3.60	19.7%	6.2%	2.5%	.290	3.66	16.8%	9.7%	119	+0.06	3.60	188	56
Irwin Delgado L 2019 · 4.73 FIP	30	SP	4.73	15.6%	9.5%	3.2%	.404	—	—	—	—	—	3.52	383	55
Brandon Mann L 2016 · 4.72 FIP	32	SP	4.72	19.4%	7.9%	4.1%	.320	3.97	19.0%	7.6%	128	-0.75	3.59	190	55
Carlos Teller L 2017 · 4.63 FIP	30	SP	4.63	12.2%	9.6%	2.5%	.322	4.90	13.1%	-1.1%	60	+0.27	3.75	333	55
Santiago Gutierrez L 2017 · 3.95 FIP	31	SP-	3.95	15.0%	8.2%	2.0%	.366	6.54	17.1%	3.7%	46	+2.59	3.90	341	54

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	3.4	96	19.9%	10.2%	1.23	4.97
James Kaprielian ('23)	1.6	106	20.5%	9.7%	1.30	4.61
Mike Bolsinger ('17)	1.2	58	20.5%	9.6%	1.33	4.92
David Clyde ('73-'79, 0 WAR*)	2.1	104	19.6%*	9.7%*	1.00*	5.24*
Wayne Simpson ('70-'77, 1 WAR*)	3.2	106	17.4%*	11.0%*	1.09*	5.03*
Jeff Robinson ('87-'92, 0 WAR*)	3.5	118	18.3%*	10.9%*	1.38*	5.14*
Felix Doubront ('15)	2.6	103	19.5%	9.7%	1.10	4.89