Keegan Curtis prospect projection, MLE, ETA

Keegan Curtis P Oklahoma City Dodgers

Age 30 RHP 6'0" / 175 lbs AAA

2026 FULL-SEASON PROJECTIONpark-neutral Marcel · 19 proj IP

wRC+ AGAINSTvL 123115vR 106

ERA4.71

FIP4.71

K%19.4%

BB%9.5%

K-BB%9.8%

ROS IP19

Value2026 · WAR

Runs saved vs league avg · 19 IP

Grades · Contract

Scouting Grades

K†4545

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 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)
2018	22	ROK MLE	GCL Yankees East	11	0	15	64	15	5	2	0%	1.3	15.9%	9.8%	6.2%	4.4%	3.68	5.39	—
2018	22	ROK RAW	GCL Yankees East	11	0	15	64	15	5	2	0%	1.3	23.4%	7.8%	15.6%	3.1%	3.68	3.85	—
2019	23	A MLE	Charleston RiverDogs	8	0	17	73	17	7	0	0%	2.2	17.2%	11.3%	5.9%	0.0%	1.56	3.08	—
2019	23	A RAW	Charleston RiverDogs	8	0	17	73	17	7	0	0%	2.2	23.3%	9.6%	13.7%	0.0%	1.56	2.35	—
2021	25	MIX MLE	2 levels	25	0	27	120	35	12	1	0%	1.1	29.6%	9.4%	20.2%	0.0%	4.28	1.79	—
2021	25	MIX RAW	2 levels	25	0	27	120	35	12	1	0%	1.1	29.2%	10.0%	19.2%	0.8%	4.28	2.33	—
2022	26	MIX MLE	2 levels	33	2	40	192	42	17	6	6%	1.2	15.9%	11.5%	4.4%	4.4%	7.14	5.65	—
2022	26	MIX RAW	2 levels	33	2	40	192	42	17	6	6%	1.2	21.9%	8.9%	13.0%	3.1%	7.14	4.22	—
2023	27	AAA MLE	Oklahoma City Dodgers	20	1	33	160	26	18	5	5%	1.7	14.0%	10.1%	3.8%	3.4%	6.48	5.08	—
2023	27	AAA MLE	Oklahoma City Dodgers	20	1	33	160	26	18	5	5%	1.7	14.0%	10.1%	3.8%	3.4%	6.48	5.08	—
2023	27	AAA RAW	Oklahoma City Dodgers	20	1	33	160	26	18	5	5%	1.7	16.2%	11.2%	5.0%	3.1%	6.48	5.11	—
▸ 2026 season — projected remainder (no 2026 stats recorded)
2026	30	MLB	LAD	—	—	0	—	—	—	—	—	—	19.4%	9.5%	9.8%	3.0%	4.71	4.71	—
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	31	MLB MLE	LAD	19	0	20	84	16	8	3	0%	1.1	19.4%	9.8%	9.5%	3.2%	4.79	4.87	-0.1
2027	31	MLB CTX	LAD	7	0	7	30	6	3	1	0%	1.0	19.4%	9.8%	9.5%	3.2%	4.79	4.87	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		7	0	7	31	6	3	1	0%	1.1	19.4%	9.8%	9.5%	3.2%	4.79	4.49	+0.0
/ 200 IP	—	RAW		190	0	200	844	163	82	27	0%	1.1	19.4%	9.8%	9.5%	3.2%	4.79	4.49	+0.1
Career	—	MLE		97	3	133	609	111	64	17	3%	1.4	18.3%	10.5%	7.8%	2.8%	5.28	4.40	-0.1
/ 200 IP	—	MLE		146	5	200	916	167	96	25	3%	1.4	18.3%	10.5%	7.8%	2.8%	5.28	4.40	-0.7

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
Keegan Curtis (OGILVIE)	—	—	4.71	19.4%	9.5%	3.0%	—	4.87	19.4%	9.5%	20	+0.16	—	—	—
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	88
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	86
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	85
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	85
Esteban Haro R 2016 · 4.55 FIP	30	SU	4.55	17.1%	10.2%	2.9%	.338	3.83	11.6%	6.3%	75	-0.72	3.76	164	84
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	83
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	83
Scott Atchison R 2007 · 4.55 FIP	31	SU	4.55	19.1%	7.6%	3.8%	.297	4.59	16.2%	9.5%	60	+0.04	2.52	340	80
Erik Davis R 2017 · 4.25 FIP	30	SU	4.25	22.2%	11.1%	3.0%	.349	3.52	17.4%	8.5%	65	-0.73	3.05	227	78
Adrian Garza R 2017 · 4.47 FIP	29	SU	4.47	16.0%	7.0%	3.4%	.351	5.18	9.7%	4.1%	113	+0.71	3.94	229	78
Carlos Fisher R 2011 · 4.33 FIP	28	SU	4.33	15.5%	9.1%	2.5%	.275	—	—	—	—	—	2.48	245	78
Jose Manuel Lopez R 2015 · 5.21 FIP	30	SU	5.21	18.6%	7.6%	4.9%	.373	3.56	18.5%	9.3%	93	-1.65	3.50	170	78
Francisco Mendoza R 2016 · 3.81 FIP	28	SU	3.81	17.9%	7.7%	2.3%	.344	—	—	—	—	—	3.13	120	78
Ivan Zavala R 2017 · 5.02 FIP	30	SU	5.02	12.8%	8.0%	3.6%	.286	5.15	12.7%	5.3%	61	+0.13	4.27	209	77
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	77
Mike Broadway R 2017 · 4.73 FIP	30	SU	4.73	18.3%	10.2%	3.4%	.245	4.65	23.0%	12.4%	49	-0.08	1.74	195	76
Jason Urquidez R 2015 · 3.59 FIP	32	SU	3.59	15.6%	9.3%	1.1%	.386	1.81	25.5%	20.7%	90	-1.78	1.25	123	76
Greg Burke R 2013 · 3.70 FIP	30	SU	3.70	17.9%	8.3%	1.9%	.357	3.61	22.1%	14.8%	62	-0.09	3.61	139	76
Ryan Doolittle R 2016 · 4.38 FIP	28	SU	4.38	13.9%	7.1%	2.8%	.269	—	—	—	—	—	4.03	101	75
Jeremy Fikac R 2004 · 4.91 FIP	29	SU	4.91	19.6%	8.0%	4.5%	.276	—	—	—	—	—	3.10	136	75