Liam Sullivan

P Fredericksburg Nationals

Age 25 LHP 6'6" / 255 lbs A peak 0.2 · 2030

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	22	AWSH	2	2	9	1.93	1.06	40.5%	11.9%	—	K 40.5% · BB 11.9% · FIP 1.19
2025	23	MIX2 levels	15	14	51	2.49	3.04	32.2%	10.1%	—	K 23.0% · BB 12.3% · FIP 4.45
2026	24	MIX2 levels	27	19	90	5.88	5.15	26.2%	12.4%	—	K 19.7% · BB 14.5% · FIP 6.54
2027PROJ	25	MLBWSH	—	—	0	5.53	5.53	20.6%	13.6%	—
2028PROJ43% MLB	26	MLBWSH	5	5	28	5.39	5.38	21.0%	13.0%	0.0
2029PROJ63% MLB	27	MLBWSH	6	6	37	5.32	5.33	21.1%	12.7%	0.0

Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.2 / P90 0.6, comp-based) · star 0% · didn't stick 96%

CompsErik Rivera (age 23) · Hayden Mullins (age 23) · Jimmy Robbins (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 122130vR 138

ERA5.53

FIP5.53

K%20.6%

BB%13.6%

K-BB%7.0%

Proj IP54

Value2027 · WAR

Runs saved vs league avg · 54 IP

Grades · Contract

Scouting Grades

K†5055

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)
2023	21	MIX MLE	2 levels	7	6	16	72	25	12	2	86%	2.3	25.7%	20.5%	5.2%	4.1%	4.96	5.78	—
2023	21	MIX RAW	2 levels	7	6	16	72	25	12	2	86%	2.3	34.7%	16.7%	18.1%	2.8%	4.96	3.83	—
2024	22	A MLE	Fredericksburg Nationals	2	2	9	42	17	5	0	100%	4.7	40.5%	11.9%	28.6%	0.0%	1.93	1.19	—
2024	22	A MLE	Fredericksburg Nationals	2	2	9	42	17	5	0	100%	4.7	40.5%	11.9%	28.6%	0.0%	1.93	1.19	—
2024	22	A RAW	Fredericksburg Nationals	2	2	9	42	17	5	0	100%	4.7	40.5%	11.9%	28.6%	0.0%	1.93	1.06	—
2025	23	MIX MLE	2 levels	15	14	51	199	64	20	5	93%	3.4	23.0%	12.3%	10.6%	3.1%	2.49	4.45	—
2025	23	MIX MLE	2 levels	15	14	51	199	64	20	5	93%	3.4	23.0%	12.3%	10.6%	3.1%	2.49	4.45	—
2025	23	MIX RAW	2 levels	15	14	51	199	64	20	5	93%	3.4	32.2%	10.1%	22.1%	2.5%	2.49	3.04	—
2026	24	MIX MLE	2 levels	27	19	90	404	106	50	19	70%	3.3	19.7%	14.5%	5.3%	6.0%	5.88	6.54	—
2026	24	MIX MLE	2 levels	27	19	90	404	106	50	19	70%	3.3	19.7%	14.5%	5.3%	6.0%	5.88	6.54	—
2026	24	MIX RAW	2 levels	27	19	90	404	106	50	19	70%	3.3	26.2%	12.4%	13.9%	4.7%	5.88	5.15	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	WSH	—	—	0	—	—	—	—	—	—	20.6%	13.6%	7.0%	3.8%	5.53	5.53	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	WSH	11	11	65	276	58	36	10	100%	5.9	21.0%	13.0%	8.0%	3.7%	5.39	5.38	+0.0
2029	27	MLB MLE	WSH	10	10	59	250	53	32	9	100%	5.9	21.1%	12.7%	8.4%	3.7%	5.32	5.33	+0.0
2030	28	MLB MLE	WSH	10	10	61	256	59	30	10	100%	6.1	23.0%	11.8%	11.2%	3.8%	5.16	5.09	+0.2
2031	29	MLB MLE	WSH	9	9	56	236	54	28	9	100%	6.2	22.8%	11.9%	10.8%	3.9%	5.18	5.20	+0.1
2032	30	MLB MLE	WSH	8	8	50	212	47	26	9	100%	6.3	22.4%	12.2%	10.2%	4.1%	5.30	5.38	+0.0
2028	26	MLB CTX	WSH	5	5	28	118	25	15	4	100%	5.6	21.0%	13.0%	8.0%	3.7%	5.39	5.38	+0.0
2029	27	MLB CTX	WSH	6	6	37	156	33	20	6	100%	6.2	21.1%	12.7%	8.4%	3.7%	5.32	5.33	+0.0
2030	28	MLB CTX	WSH	8	8	46	194	45	23	7	100%	5.8	23.0%	11.8%	11.2%	3.8%	5.16	5.09	+0.2
2031	29	MLB CTX	WSH	8	8	45	190	43	23	7	100%	5.6	22.8%	11.9%	10.8%	3.9%	5.18	5.20	+0.1
2032	30	MLB CTX	WSH	7	7	43	182	41	22	7	100%	6.1	22.4%	12.2%	10.2%	4.1%	5.30	5.38	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		33	33	199	840	186	103	32	100%	6.0	22.2%	12.3%	9.9%	3.8%	5.26	4.88	+1.2
/ 200 IP	—	RAW		33	33	200	844	187	103	32	100%	6.0	22.2%	12.3%	9.9%	3.8%	5.26	4.88	+1.2
Career	—	MLE		51	41	167	717	161	103	33	80%	3.3	22.4%	14.3%	8.1%	4.6%	4.54	5.57	+0.4
/ 200 IP	—	MLE		61	49	200	860	193	123	40	80%	3.3	22.4%	14.3%	8.1%	4.6%	4.54	5.57	+0.3

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.

2026 AFredericksburg Nationals · 55 IPFIP 4.11 → 5.49 (+1.38)K% 27.2% → 20.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.20%	—	×0.740	20.13%
BB% (unintentional) /BF	13.39%	—	×1.180	15.80%
HR / BF /BF	2.93%	÷1.000	×1.300	3.81%

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 100).

Result: FIP 4.11 → 5.49, 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).

2026 A+Wilmington Blue Rocks · 35 IPFIP 6.38 → 8.06 (+1.69)K% 24.8% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.85%	—	×0.770	19.13%
BB% (unintentional) /BF	10.91%	—	×1.150	12.55%
HR / BF /BF	7.27%	÷1.000	×1.250	9.09%

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 100).

Result: FIP 6.38 → 8.06, 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).

2025 AFredericksburg Nationals · 31 IPFIP 3.59 → 4.94 (+1.35)K% 29.8% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.75%	—	×0.740	22.02%
BB% (unintentional) /BF	5.79%	—	×1.180	6.83%
HR / BF /BF	4.13%	÷1.040	×1.300	5.16%

Result: FIP 3.59 → 4.94, 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).

2025 ROKFCL Nationals · 20 IPFIP 2.18 → 3.68 (+1.50)K% 35.9% → 24.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.90%	—	×0.680	24.41%
BB% (unintentional) /BF	16.67%	—	×1.250	20.83%
HR / BF /BF	0.00%	÷1.328	×1.400	0.00%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 166).

Result: FIP 2.18 → 3.68, 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).

2024 AFredericksburg Nationals · 9 IPFIP 1.19 → 2.35 (+1.16)K% 40.5% → 30.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.48%	—	×0.740	29.95%
BB% (unintentional) /BF	11.90%	—	×1.180	14.05%
HR / BF /BF	0.00%	÷1.078	×1.300	0.00%

Result: FIP 1.19 → 2.35, 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 AFredericksburg Nationals · 15 IPFIP 3.96 → 5.78 (+1.82)K% 34.8% → 25.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.78%	—	×0.740	25.74%
BB% (unintentional) /BF	17.39%	—	×1.180	20.52%
HR / BF /BF	2.90%	÷0.917	×1.300	4.11%

Result: FIP 3.96 → 5.78, 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
Liam Sullivan (OGILVIE)	—	—	5.53	20.6%	13.6%	3.8%	—	5.27	21.7%	9.2%	185	-0.26	—	—	—
Erik Rivera L 2024 · 5.71 FIP	23	SP-	5.71	19.0%	14.6%	4.3%	.255	4.74	23.9%	6.3%	106	-0.97	4.42	141	85
Hayden Mullins L 2024 · 4.39 FIP	23	SP-	4.39	23.4%	12.4%	3.1%	.288	3.69	25.5%	11.8%	194	-0.70	3.54	283	79
Jimmy Robbins L 2023 · 4.69 FIP	25	SP-	4.69	17.8%	15.2%	2.1%	.290	5.73	19.6%	3.8%	13	+1.04	3.85	176	76
Hayden Wynja L 2024 · 4.79 FIP	25	SP-	4.79	18.0%	10.5%	3.4%	.274	—	—	—	—	—	4.74	154	73
Nate Peterson L 2024 · 5.51 FIP	24	SP-	5.51	19.2%	11.4%	4.7%	.296	4.75	16.0%	3.7%	148	-0.76	4.27	315	73
Garrett Schoenle L 2023 · 5.38 FIP	25	SP-	5.38	20.5%	15.0%	3.9%	.307	3.58	20.9%	12.1%	174	-1.80	2.32	362	73
Brett Adcock L 2019 · 5.34 FIP	23	SP	5.34	17.4%	13.6%	3.6%	.295	—	—	—	—	—	4.02	301	72
Avery Weems L 2022 · 4.87 FIP	25	SP-	4.87	21.3%	8.6%	4.5%	.323	5.13	20.5%	12.3%	38	+0.26	2.46	227	71
Mark Manfredi Sr. L 2024 · 4.60 FIP	24	SW	4.60	22.0%	14.9%	2.7%	.289	3.22	25.4%	11.6%	128	-1.38	2.91	204	71
Christian MacLeod L 2024 · 4.77 FIP	24	SP	4.77	21.5%	13.6%	3.2%	.269	4.50	18.0%	3.0%	128	-0.27	3.88	280	71
Tyler Alexander L 2019 · 5.56 FIP	27	SP-	5.56	21.7%	9.8%	5.6%	.289	5.27	15.7%	5.0%	26	-0.29	5.27	128	71
Justin Marks L 2015 · 4.60 FIP	27	SP-	4.60	15.4%	10.5%	2.7%	.323	3.88	19.0%	9.1%	216	-0.72	3.83	324	70
Nick Zwack L 2023 · 5.41 FIP	24	SP-	5.41	20.2%	9.6%	5.1%	.346	5.30	19.0%	8.6%	105	-0.11	3.16	292	70
Miguel Cienfuegos L 2023 · 5.12 FIP	26	SP	5.12	13.6%	10.5%	3.4%	.257	4.54	14.3%	5.8%	242	-0.58	2.95	313	70
Luis Leroy Cruz L 2015 · 5.03 FIP	24	SP-	5.03	16.0%	10.1%	3.7%	.289	—	—	—	—	—	5.03	116	70
John Koronka L 2005 · 4.77 FIP	25	SP-	4.77	13.2%	10.5%	2.6%	.304	4.81	10.5%	2.2%	135	+0.04	3.99	151	70
Luke Fox L 2024 · 5.24 FIP	22	SP	5.24	21.8%	19.2%	2.8%	.284	4.16	21.4%	8.1%	125	-1.08	3.60	156	70
Jaylen Nowlin L 2024 · 5.15 FIP	23	SP-	5.15	18.7%	12.6%	3.7%	.299	4.77	21.7%	3.2%	100	-0.38	3.45	372	69
Logan Darnell L 2014 · 4.78 FIP	25	SP-	4.78	19.6%	7.1%	4.4%	.338	4.10	13.4%	6.1%	262	-0.68	3.16	454	69
Marcelo Martinez L 2022 · 5.73 FIP	25	SP-	5.73	20.2%	11.3%	5.3%	.287	6.79	11.9%	7.1%	21	+1.06	3.29	427	69

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 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	1.7	58	21.8%	12.5%	1.47	5.31
Paul Spoljaric ('00)	1.4	69	22.1%	12.9%	1.33	5.52
Scott Proctor ('11)	1.7	57	19.0%	10.9%	1.52	4.78
Amir Garrett ('24)	1.7	55	26.7%	13.3%	1.52	4.95
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*