Steffon Moore

P Chattanooga Lookouts

Age 30 LHP 6'3" / 185 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2021	24	ATB	20	29	6.59	3.00	32.4%	20.9%	—	K 24.0% · BB 24.7% · FIP 4.20
2026	29	AACIN	20	25	6.48	5.14	33.9%	22.3%	—	K 27.4% · BB 24.5% · FIP 6.07
2027PROJ	30	MLBCIN	13	14	5.52	5.52	26.2%	20.0%	-0.2
2028PROJ31% MLB	31	MLBCIN	6	6	5.52	5.60	25.5%	19.3%	-0.1

Next 2 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0 WAR median (P10 0 / P90 0, comp-based) · star 0% · didn't stick 100%

CompsAnthony Gose (age 30) · Braulio Lara (age 28) · Chris Nunn (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 122130vR 138

ERA5.52

FIP5.52

K%26.2%

BB%20.0%

K-BB%6.2%

Proj IP14

Value2027 · WAR

Runs saved vs league avg · 14 IP

Grades · Contract

Scouting Grades

K†6060

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 + 2027 so far)
2018	21	ROK MLE	Princeton Rays	17	0	29	114	33	11	2	0%	1.7	19.7%	12.1%	7.6%	2.5%	1.88	4.31	—
2018	21	ROK RAW	Princeton Rays	17	0	29	114	33	11	2	0%	1.7	28.9%	9.6%	19.3%	1.8%	1.88	2.86	—
2019	22	A MLE	Bowling Green Hot Rods	5	1	7	51	12	9	2	20%	1.5	17.4%	20.8%	-3.4%	4.0%	11.05	6.47	—
2019	22	A RAW	Bowling Green Hot Rods	5	1	7	51	12	9	2	20%	1.5	23.5%	17.6%	5.9%	3.9%	11.05	7.05	—
2021	24	A MLE	Charleston RiverDogs	20	0	29	148	48	31	0	0%	1.4	24.0%	24.7%	-0.7%	0.0%	6.59	4.20	—
2021	24	A RAW	Charleston RiverDogs	20	0	29	148	48	31	0	0%	1.4	32.4%	20.9%	11.5%	0.0%	6.59	3.00	—
2026	29	AA MLE	Chattanooga Lookouts	20	0	25	121	41	27	4	0%	1.2	27.4%	24.5%	2.9%	4.0%	6.48	6.07	—
2026	29	AA MLE	Chattanooga Lookouts	20	0	25	121	41	27	4	0%	1.2	27.4%	24.5%	2.9%	4.0%	6.48	6.07	—
2026	29	AA RAW	Chattanooga Lookouts	20	0	25	121	41	27	4	0%	1.2	33.9%	22.3%	11.6%	3.3%	6.48	5.14	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	CIN	13	0	14	59	15	12	2	0%	1.1	26.2%	20.0%	6.2%	3.1%	5.52	5.52	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	CIN	19	0	20	84	22	16	3	0%	1.1	25.5%	19.3%	6.2%	3.3%	5.52	5.60	-0.2
2028	31	MLB CTX	CIN	6	0	6	25	6	5	1	0%	1.0	25.5%	19.3%	6.2%	3.3%	5.52	5.60	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		6	0	6	26	7	5	1	0%	1.0	25.5%	19.3%	6.2%	3.3%	5.52	5.22	-0.0
/ 200 IP	—	RAW		190	0	200	844	224	160	32	0%	1.1	25.5%	19.3%	6.2%	3.3%	5.52	5.22	-1.6
Career	—	MLE		62	1	90	434	100	91	10	2%	1.4	23.1%	20.9%	2.2%	2.2%	5.42	5.02	-0.2
/ 200 IP	—	MLE		138	2	200	968	223	202	22	2%	1.4	23.1%	20.9%	2.2%	2.2%	5.42	5.02	-2.4

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
Steffon Moore (OGILVIE)	—	—	5.52	26.2%	20.0%	3.1%	—	5.60	25.5%	6.2%	20	+0.08	—	—	—
Anthony Gose L 2021 · 4.69 FIP	30	SU	4.69	29.9%	19.7%	2.9%	.250	4.08	27.7%	15.5%	66	-0.61	3.78	233	75
Braulio Lara L 2017 · 5.80 FIP	28	SU	5.80	19.8%	17.8%	3.9%	.361	—	—	—	—	—	3.96	118	71
Chris Nunn L 2021 · 4.72 FIP	30	SU	4.72	24.0%	19.2%	2.2%	.235	—	—	—	—	—	3.30	180	71
Juan Pablo Perez L 2007 · 5.32 FIP	28	SU	5.32	17.5%	14.0%	3.5%	.324	—	—	—	—	—	1.75	104	70
Ron Mahay L 2001 · 5.36 FIP	30	SU	5.36	27.9%	16.3%	4.7%	.227	3.89	19.5%	11.2%	127	-1.47	3.14	568	69
Fabian Williamson L 2019 · 4.78 FIP	30	SU	4.78	20.5%	21.1%	1.3%	.352	—	—	—	—	—	3.39	154	69
Keith Hessler L 2018 · 4.96 FIP	29	SU	4.96	19.8%	13.3%	3.4%	.348	—	—	—	—	—	3.31	228	68
Jack Leathersich L 2018 · 4.55 FIP	28	SU	4.55	21.7%	19.8%	1.4%	.224	—	—	—	—	—	3.16	101	66
Kevin Chapman L 2018 · 5.66 FIP	30	SU	5.66	17.1%	15.7%	3.7%	.238	—	—	—	—	—	3.01	194	65
Doug Creek L 2000 · 4.57 FIP	31	SU	4.57	27.5%	13.6%	3.8%	.267	4.75	21.9%	7.8%	132	+0.18	4.48	277	64
Clay Rapada L 2011 · 4.34 FIP	30	SU	4.34	26.1%	10.1%	3.9%	.268	3.00	24.5%	14.2%	38	-1.34	3.00	120	64
Aaron Brown L 2022 · 5.38 FIP	30	SU	5.38	21.3%	12.5%	4.5%	.253	—	—	—	—	—	4.04	269	64
Buddy Baumann L 2018 · 4.87 FIP	30	SU	4.87	20.5%	11.9%	3.6%	.258	—	—	—	—	—	2.92	155	63
Cam Booser L 2022 · 6.54 FIP	30	SU	6.54	20.8%	20.7%	4.7%	.350	4.49	24.8%	15.2%	157	-2.05	2.76	314	63
James Pazos L 2021 · 4.41 FIP	30	SU	4.41	26.0%	12.0%	3.6%	.350	—	—	—	—	—	2.55	261	62
Hung-Chih Kuo L 2011 · 4.46 FIP	30	SU	4.46	28.3%	16.5%	3.0%	.303	—	—	—	—	—	1.63	287	62
Kelly Wunsch L 2002 · 4.60 FIP	30	SU	4.60	15.9%	13.0%	2.2%	.242	3.54	20.8%	8.3%	60	-1.06	3.36	175	61
Mike Zagurski L 2012 · 4.48 FIP	29	SU	4.48	20.9%	11.7%	3.0%	.305	—	—	—	—	—	2.94	120	61
Brian Shouse L 2002 · 5.54 FIP	33	SU	5.54	15.5%	11.3%	4.2%	.245	3.31	16.3%	10.7%	159	-2.23	2.32	339	60
Andrew Barbosa L 2017 · 4.67 FIP	29	SU	4.67	20.2%	9.6%	3.8%	.301	—	—	—	—	—	2.70	175	60