Justin Steele — OGILVIE

Justin Steele P Iowa Cubs

Age 31 LHP 6'2" / 205 lbs AAA Svc 4.0 · Ctrl thru 2027 peak 1.5 · 2026 ILInjured 60-Day (D60)

2026 FULL-SEASON PROJECTIONpark-neutral Marcel · 96 proj IP

wRC+ AGAINSTvL 9199vR 107

ERA3.64

FIP3.90

K%22.9%

BB%6.2%

K-BB%16.8%

ROS IP97

Value2026 · WAR

Runs saved vs league avg · 96 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control-$4M ctrl surplus

Grades · Statcast · Arsenal · Contract

Scouting Grades

OFP—60

STUF5555

CTRL6565

CMD6565

K†5555

Statcast Percentiles

FB Velo

p1090.8

Whiff%

p1018.5%

p5322.8%

xwOBA vs

p240.343

FB+3.7 (63%)

SI (6%)

CU (4%)

CH-2.2 (3%)

SL-2.4 (29%)

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status Arb-2

MLB Debut 2021

Service 4.831 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Ext	$0.5M	+0.0	$0.1M	-$0.4M
2027	Arb-3	$9M	+0.7	$3M	+$0.0M (cut)
Totals		$0.5M		$3M	-$0.4M

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 industry-standard fWAR.

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 + 2026 so far)
2016	21	A MLE	South Bend Cubs	19	19	77	361	76	39	3	100%	4.1	15.6%	12.7%	2.8%	1.1%	5.00	3.99	—
2016	21	A RAW	South Bend Cubs	19	19	77	361	76	39	3	100%	4.1	21.1%	10.8%	10.2%	0.8%	5.00	3.15	—
2017	22	A+ MLE	Myrtle Beach Pelicans	20	20	99	432	82	36	6	100%	4.9	14.6%	9.6%	5.0%	1.9%	2.92	4.10	—
2017	22	A+ RAW	Myrtle Beach Pelicans	20	20	99	432	82	36	6	100%	4.9	19.0%	8.3%	10.6%	1.4%	2.92	3.32	—
2018	23	MIX MLE	3 levels	11	11	47	185	53	13	2	100%	4.2	23.1%	8.3%	14.7%	1.0%	2.31	2.74	—
2018	23	MIX RAW	3 levels	11	11	47	185	53	13	2	100%	4.2	28.6%	7.0%	21.6%	1.1%	2.31	2.22	—
2019	24	AA MLE	Tennessee Smokies	11	11	39	170	42	20	3	100%	3.5	20.0%	12.9%	7.1%	1.9%	5.59	4.07	—
2019	24	AA RAW	Tennessee Smokies	11	11	39	170	42	20	3	100%	3.5	24.7%	11.8%	12.9%	1.8%	5.59	3.49	—
2021	26	MIX MLE	2 levels	29	14	84	358	88	37	13	48%	2.9	23.6%	10.5%	13.1%	3.8%	3.31	4.50	+0.0
2021	26	MIX RAW	2 levels	29	14	84	358	88	37	13	48%	2.9	24.6%	10.3%	14.2%	3.6%	3.31	4.33	+0.2
2022	27	MLB MLE	Chicago Cubs	24	24	119	512	126	50	8	100%	5.0	24.6%	9.8%	14.8%	1.6%	3.18	3.15	+2.6
2022	27	MLB RAW	Chicago Cubs	24	24	119	512	126	50	8	100%	5.0	24.6%	9.8%	14.8%	1.6%	3.18	3.12	+2.6
2023	28	MLB MLE	Chicago Cubs	30	30	173	716	176	36	14	100%	5.8	24.6%	5.0%	19.6%	2.0%	3.06	2.78	+4.7
2023	28	MLB MLE	Chicago Cubs	30	30	173	716	176	36	14	100%	5.8	24.6%	5.0%	19.6%	2.0%	3.06	2.78	+4.7
2023	28	MLB RAW	Chicago Cubs	30	30	173	716	176	36	14	100%	5.8	24.6%	5.0%	19.6%	2.0%	3.06	2.74	+4.8
2024	29	MIX MLE	2 levels	25	25	138	572	139	38	12	100%	5.5	24.3%	6.7%	17.7%	2.2%	3.20	3.12	+3.1
2024	29	MIX MLE	2 levels	25	25	138	572	139	38	12	100%	5.5	24.3%	6.7%	17.7%	2.2%	3.20	3.12	+3.1
2024	29	MIX RAW	2 levels	25	25	138	572	139	38	12	100%	5.5	24.3%	6.6%	17.7%	2.1%	3.20	3.04	+3.2
2025	30	MLB MLE	Chicago Cubs	4	4	23	92	21	5	5	100%	5.7	22.8%	5.4%	17.4%	5.6%	4.76	4.96	-0.0
2025	30	MLB MLE	Chicago Cubs	4	4	23	92	21	5	5	100%	5.7	22.8%	5.4%	17.4%	5.6%	4.76	4.96	-0.0
2025	30	MLB RAW	Chicago Cubs	4	4	23	92	21	5	5	100%	5.7	22.8%	5.4%	17.4%	5.4%	4.76	4.78	+0.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			102	91	507	2123	517	153	51	89%	5.0	24.4%	7.2%	17.1%	2.4%	3.30	3.27	+10.1
▸ 2026 season
YTD	31	AAA MLE	Iowa Cubs	3	2	6	27	6	0	0	67%	1.9	—	—	—	—	6.35	—	—
YTD	31	AAA MLE	Iowa Cubs	3	2	6	27	6	0	0	67%	1.9	—	—	—	—	6.35	—	—
▸ 2026 season — so far · projected rest · full
2026	31	AAA RAW	CHC	3	2	6	27	6	0	0	67%	1.9	22.2%	0.0%	22.2%	0.0%	6.35	1.22	—
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	32	MLB MLE	CHC	14	14	83	351	78	23	11	100%	5.9	22.1%	6.6%	15.6%	3.1%	3.95	4.15	+0.7
2028	33	MLB MLE	CHC	13	13	76	322	75	20	11	100%	5.9	23.3%	6.2%	17.1%	3.4%	4.08	4.16	+0.7
2029	34	MLB MLE	CHC	12	12	69	293	66	20	11	100%	5.8	22.4%	6.7%	15.7%	3.7%	4.31	4.46	+0.4
2027	32	MLB CTX	CHC	14	14	83	350	78	23	11	100%	5.9	22.1%	6.6%	15.6%	3.0%	3.89	4.09	+0.7
2028	33	MLB CTX	CHC	13	13	76	321	75	20	10	100%	5.8	23.3%	6.2%	17.1%	3.3%	4.01	4.09	+0.7
2029	34	MLB CTX	CHC	12	12	69	291	65	20	10	100%	5.8	22.4%	6.7%	15.7%	3.6%	4.23	4.38	+0.4
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		140	129	736	3089	735	216	82	92%	5.3	23.8%	7.0%	16.8%	2.7%	3.53	3.44	+13.1
/ 200 IP	—	RAW		38	35	200	840	200	59	22	92%	5.2	23.8%	7.0%	16.8%	2.7%	3.53	3.44	+3.6
Career	—	MLE		176	160	804	3425	749	292	71	91%	4.6	21.9%	8.5%	13.3%	2.1%	3.45	3.47	+11.8
/ 200 IP	—	MLE		44	40	200	852	186	72	18	91%	4.6	21.9%	8.5%	13.3%	2.1%	3.45	3.47	+3.2

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
Justin Steele (OGILVIE)	—	—	3.90	22.9%	6.2%	2.9%	—	4.25	22.6%	16.1%	229	+0.35	—	—	—
David Price L 2017 · 3.46 FIP	31	SP-	3.46	24.0%	7.6%	2.6%	.273	3.71	25.8%	18.9%	283	+0.25	2.65	922	64
Jeff Locke L 2017 · 4.18 FIP	29	SP	4.18	17.1%	7.9%	2.8%	.345	—	—	—	—	—	3.79	328	63
James Paxton L 2020 · 3.93 FIP	31	SP	3.93	28.9%	7.8%	4.2%	.358	4.47	24.0%	14.7%	118	+0.54	2.46	924	61
Danny Duffy L 2020 · 4.71 FIP	31	SP	4.71	23.6%	9.1%	4.5%	.281	3.36	24.8%	13.7%	92	-1.35	3.29	915	60
Kwang Hyun Kim L 2020 · 3.76 FIP	32	SP	3.76	15.6%	6.5%	2.1%	.214	4.21	17.7%	9.5%	107	+0.45	3.76	146	54
Hyun Jin Ryu L 2018 · 2.79 FIP	31	SP	2.79	27.5%	4.3%	2.7%	.278	3.28	22.2%	17.8%	419	+0.49	2.79	725	54
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	53
Franklin Morales L 2017 · 4.02 FIP	31	SP-	4.02	15.0%	8.0%	2.2%	.267	—	—	—	—	—	3.37	101	53
Wade Miley L 2018 · 3.36 FIP	31	SP	3.36	16.7%	7.0%	1.4%	.286	4.04	18.7%	10.6%	345	+0.68	3.36	1,167	51
Francisley Bueno L 2015 · 3.77 FIP	34	SP	3.77	14.8%	7.1%	1.9%	.315	3.99	13.3%	6.6%	110	+0.22	3.48	138	50
Wei-Yin Chen L 2016 · 4.51 FIP	31	SP	4.51	19.2%	4.6%	4.5%	.299	4.37	19.6%	13.1%	235	-0.14	3.68	549	50
Patrick Corbin L 2020 · 3.97 FIP	31	SP	3.97	20.3%	5.8%	3.4%	.361	4.91	17.5%	10.3%	504	+0.94	2.30	1,829	48
Nick Additon L 2017 · 3.13 FIP	29	SP	3.13	19.3%	9.1%	0.9%	.301	—	—	—	—	—	3.13	217	48
Ryan Verdugo L 2017 · 3.36 FIP	30	SP-	3.36	22.7%	5.4%	2.7%	.333	—	—	—	—	—	3.36	153	47
Jason Vargas L 2015 · 4.31 FIP	32	SP	4.31	14.8%	6.6%	2.9%	.295	4.65	19.2%	12.1%	285	+0.34	4.02	478	47
Marlon Arias L 2015 · 4.32 FIP	30	SP	4.32	16.8%	12.2%	2.0%	.330	3.73	17.2%	9.5%	22	-0.59	3.73	154	46
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	46
Dallas Keuchel L 2019 · 4.31 FIP	31	SP	4.31	18.7%	7.8%	3.3%	.289	4.33	15.0%	6.7%	321	+0.02	2.86	1,402	45
Tsuyoshi Wada L 2015 · 3.66 FIP	34	SP	3.66	16.8%	7.1%	2.0%	.307	—	—	—	—	—	3.66	119	45
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	44

Career Comps

Retired MLB careers whose totals most resemble what we're projecting for this player. Pool: 133 completed pitcher careers (2015-2024).

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	1.6	78	22.7%	6.4%	1.26	3.98
Eli Morgan ('24)	1.3	66	23.8%	6.4%	1.46	3.97
Adbert Alzolay ('23)	1.1	70	26.1%	7.0%	1.32	3.84
Jarlín García ('22)	1.5	61	19.6%	7.8%	1.33	3.79
Chris Devenski ('24)	1.9	62	26.0%	6.9%	1.25	3.61
Craig Stammen ('22)	2.0	66	23.0%	5.4%	1.19	3.36
Félix Peña ('20)	1.2	62	23.6%	8.3%	1.37	4.46