Jarlin Susana

P Harrisburg Senators

Age 23 RHP 6'6" / 235 lbs AA Svc 0.0 · Ctrl thru 2032 peak 1.0 · 2030

Overview

AAPROSPECTPre-ArbFA 2033

OGV OFP50OGV rank#34ETA2028MLB%6%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	20	MIX2 levels	24	24	104	4.34	1.71	35.4%	10.8%	—	K 26.7% · BB 12.6% · FIP 2.75
2025	21	MIX2 levels	14	14	56	3.51	2.23	38.9%	13.9%	—	K 30.8% · BB 16.9% · FIP 3.63
2026	22	MIX3 levels	8	8	20	6.20	1.72	39.4%	11.7%	—	K 32.1% · BB 8.3% · FIP 2.68
2027PROJ	23	MLBWSH	1	1	5	3.93	3.93	33.0%	13.9%	0.1
2028PROJ46% MLB	24	MLBWSH	9	9	49	3.85	3.78	32.5%	12.4%	1.0
2029PROJ68% MLB	25	MLBWSH	14	14	80	3.77	3.70	32.1%	11.5%	1.6

Next 3 projected WAR 2.7Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2032Service0.0First FA2033

2027Pre-Arb$0.8M2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Arb-1$5M2031Arb-2$8M2032Ext$11M

Career WAR2.0 WAR median (P10 -0.5 / P90 28, comp-based) · star 6% · didn't stick 51%

CompsSean Mooney (age 23) · George Klassen (age 22) · Jackson Baumeister (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 108100vR 92

ERA3.93

FIP3.93

K%33.0%

BB%13.9%

K-BB%19.1%

Proj IP90

Value2027 · WAR

Runs saved vs league avg · 90 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit+$38M ctrl surplus

Contract

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

Status Pre-Arb

MLB Debut 2027

Service 0 yrs (est)

Team Control Through 2032

First FA Year 2033

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+0.1	$0.4M	+$0.0M (cut)
2028	Pre-Arb	$0.8M	+1.0	$7M	+$7M
2029	Pre-Arb	$0.8M	+1.6	$11M	+$10M
2030	Arb-1	$5M	+2.0	$13M	+$9M
2031	Arb-2	$8M	+2.1	$12M	+$7M
2032	Ext	beyond projection horizon · no WAR estimate
Totals		$15M		$44M	+$33M

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)
2022	18	MIX MLE	2 levels	13	12	45	179	66	20	2	92%	3.5	26.7%	13.9%	12.8%	1.1%	2.40	3.23	—
2022	18	MIX RAW	2 levels	13	12	45	179	66	20	2	92%	3.5	36.9%	11.2%	25.7%	1.1%	2.40	2.08	—
2023	19	A MLE	Fredericksburg Nationals	17	17	63	284	62	40	3	100%	3.7	16.2%	16.6%	-0.5%	1.5%	5.14	4.66	—
2023	19	A RAW	Fredericksburg Nationals	17	17	63	284	62	40	3	100%	3.7	21.8%	14.1%	7.7%	1.1%	5.14	3.66	—
2024	20	MIX MLE	2 levels	24	24	104	444	157	48	2	100%	4.3	26.7%	12.6%	14.0%	0.6%	4.34	2.75	—
2024	20	MIX MLE	2 levels	24	24	104	444	157	48	2	100%	4.3	26.7%	12.6%	14.0%	0.6%	4.34	2.75	—
2024	20	MIX RAW	2 levels	24	24	104	444	157	48	2	100%	4.3	35.4%	10.8%	24.5%	0.5%	4.34	1.71	—
2025	21	MIX MLE	2 levels	14	14	56	244	95	34	3	100%	4.0	30.8%	16.9%	13.8%	1.8%	3.51	3.63	—
2025	21	MIX MLE	2 levels	14	14	56	244	95	34	3	100%	4.0	30.8%	16.9%	13.8%	1.8%	3.51	3.63	—
2025	21	MIX RAW	2 levels	14	14	56	244	95	34	3	100%	4.0	38.9%	13.9%	25.0%	1.2%	3.51	2.23	—
2026	22	MIX MLE	3 levels	8	8	20	94	37	11	1	100%	2.5	32.1%	8.3%	23.8%	2.3%	6.20	2.68	—
2026	22	MIX MLE	3 levels	8	8	20	94	37	11	1	100%	2.5	32.1%	8.3%	23.8%	2.3%	6.20	2.68	—
2026	22	MIX RAW	3 levels	8	8	20	94	37	11	1	100%	2.5	39.4%	11.7%	27.7%	1.1%	6.20	1.72	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	23	MLB	WSH	1	1	5	21	7	3	1	100%	5.0	33.0%	13.9%	19.1%	2.7%	3.93	3.93	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	24	MLB MLE	WSH	19	19	107	452	147	56	12	100%	5.6	32.5%	12.4%	20.1%	2.7%	3.85	3.78	+2.1
2029	25	MLB MLE	WSH	20	20	117	495	159	57	13	100%	5.9	32.1%	11.5%	20.6%	2.7%	3.77	3.70	+2.4
2030	26	MLB MLE	WSH	21	21	125	527	168	59	14	100%	5.9	31.8%	11.2%	20.6%	2.7%	3.74	3.70	+2.5
2031	27	MLB MLE	WSH	20	20	122	516	163	58	14	100%	6.1	31.5%	11.2%	20.3%	2.8%	3.75	3.75	+2.4
2032	28	MLB MLE	WSH	20	20	118	498	156	57	14	100%	5.9	31.4%	11.4%	20.1%	2.9%	3.80	3.84	+2.2
2033	29	MLB MLE	WSH	19	19	111	469	146	54	14	100%	5.8	31.2%	11.6%	19.6%	3.0%	3.90	3.97	+1.9
2034	30	MLB MLE	WSH	17	17	102	431	133	51	14	100%	6.0	30.8%	11.9%	18.9%	3.2%	4.05	4.15	+1.5
2035	31	MLB MLE	WSH	15	15	92	388	118	47	13	100%	6.1	30.4%	12.2%	18.2%	3.4%	4.23	4.35	+1.1
2036	32	MLB MLE	WSH	13	13	81	342	102	43	13	100%	6.2	30.0%	12.6%	17.3%	3.7%	4.44	4.57	+0.8
2037	33	MLB MLE	WSH	12	12	70	294	87	38	12	100%	5.8	29.5%	13.1%	16.4%	4.0%	4.67	4.82	+0.5
2038	34	MLB MLE	WSH	10	10	59	249	72	34	11	100%	5.9	28.9%	13.6%	15.3%	4.3%	4.93	5.10	+0.2
2028	24	MLB CTX	WSH	9	9	49	207	67	26	6	100%	5.4	32.5%	12.4%	20.1%	2.7%	3.85	3.78	+1.0
2029	25	MLB CTX	WSH	14	14	80	338	108	39	9	100%	5.7	32.1%	11.5%	20.6%	2.7%	3.77	3.70	+1.6
2030	26	MLB CTX	WSH	17	17	100	422	134	47	11	100%	5.9	31.8%	11.2%	20.6%	2.7%	3.74	3.70	+2.0
2031	27	MLB CTX	WSH	18	18	105	443	140	50	12	100%	5.8	31.5%	11.2%	20.3%	2.8%	3.75	3.75	+2.1
2032	28	MLB CTX	WSH	18	18	105	443	139	50	13	100%	5.8	31.4%	11.4%	20.1%	2.9%	3.80	3.84	+2.0
2033	29	MLB CTX	WSH	17	17	101	426	133	49	13	100%	5.9	31.2%	11.6%	19.6%	3.0%	3.90	3.97	+1.7
2034	30	MLB CTX	WSH	16	16	94	397	122	47	13	100%	5.9	30.8%	11.9%	18.9%	3.2%	4.05	4.15	+1.4
2035	31	MLB CTX	WSH	14	14	86	363	110	44	12	100%	6.1	30.4%	12.2%	18.2%	3.4%	4.23	4.35	+1.1
2036	32	MLB CTX	WSH	13	13	76	321	96	41	12	100%	5.8	30.0%	12.6%	17.3%	3.7%	4.44	4.57	+0.7
2037	33	MLB CTX	WSH	11	11	66	279	82	36	11	100%	6.0	29.5%	13.1%	16.4%	4.0%	4.67	4.82	+0.4
2038	34	MLB CTX	WSH	9	9	53	224	65	30	10	100%	5.9	28.9%	13.6%	15.3%	4.3%	4.93	5.10	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		154	154	916	3868	1199	461	122	100%	5.9	31.0%	11.9%	19.1%	3.1%	4.05	3.72	+18.7
/ 200 IP	—	RAW		34	34	200	844	262	101	27	100%	6.0	31.0%	11.9%	19.1%	3.1%	4.05	3.72	+4.1
Career	—	MLE		76	75	288	1245	317	177	15	99%	3.8	25.5%	14.2%	11.2%	1.2%	4.18	3.42	+17.5
/ 200 IP	—	MLE		53	52	200	864	220	123	11	99%	3.8	25.5%	14.2%	11.2%	1.2%	4.18	3.42	+3.2

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 AAHarrisburg Senators · 11 IPFIP 1.75 → 2.68 (+0.94)K% 39.6% → 32.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.62%	—	×0.810	32.09%
BB% (unintentional) /BF	7.55%	—	×1.100	8.30%
HR / BF /BF	1.89%	÷1.000	×1.200	2.26%

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 100).

Result: FIP 1.75 → 2.68, 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).

2026 A+Wilmington Blue Rocks · 6 IPFIP 0.23 → 1.47 (+1.24)K% 52.0% → 40.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	52.00%	—	×0.770	40.04%
BB% (unintentional) /BF	12.00%	—	×1.150	13.80%
HR / BF /BF	0.00%	÷1.000	×1.250	0.00%

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 0.23 → 1.47, 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 AAHarrisburg Senators · 47 IPFIP 2.63 → 3.63 (+1.00)K% 38.0% → 30.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.98%	—	×0.810	30.76%
BB% (unintentional) /BF	15.38%	—	×1.100	16.92%
HR / BF /BF	1.44%	÷0.963	×1.200	1.80%

Result: FIP 2.63 → 3.63, 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 A+Wilmington Blue Rocks · 9 IPFIP 0.05 → 1.02 (+0.97)K% 44.4% → 34.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	44.44%	—	×0.770	34.22%
BB% (unintentional) /BF	5.56%	—	×1.150	6.39%
HR / BF /BF	0.00%	÷0.967	×1.250	0.00%

Result: FIP 0.05 → 1.02, 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 · 56 IPFIP 1.78 → 2.81 (+1.03)K% 34.2% → 25.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.16%	—	×0.740	25.28%
BB% (unintentional) /BF	12.35%	—	×1.180	14.57%
HR / BF /BF	0.00%	÷1.078	×1.300	0.00%

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 116).

Result: FIP 1.78 → 2.81, 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 A+Wilmington Blue Rocks · 47 IPFIP 1.67 → 2.68 (+1.01)K% 36.8% → 28.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.82%	—	×0.770	28.35%
BB% (unintentional) /BF	8.96%	—	×1.150	10.30%
HR / BF /BF	1.00%	÷1.016	×1.250	1.22%

Result: FIP 1.67 → 2.68, 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).

2023 AFredericksburg Nationals · 63 IPFIP 3.62 → 4.66 (+1.04)K% 21.8% → 16.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.83%	—	×0.740	16.15%
BB% (unintentional) /BF	14.08%	—	×1.180	16.62%
HR / BF /BF	1.06%	÷0.917	×1.300	1.50%

Result: FIP 3.62 → 4.66, 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 ROKFCL Nationals · 35 IPFIP 1.60 → 3.23 (+1.63)K% 39.3% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.26%	—	×0.680	26.70%
BB% (unintentional) /BF	11.11%	—	×1.250	13.89%
HR / BF /BF	0.74%	÷0.911	×1.400	1.14%

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 82).

Result: FIP 1.60 → 3.23, 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
Jarlin Susana (OGILVIE)	—	—	—	—	—	2.7%	—	3.72	32.1%	20.5%	349	-0.21	—	—	—
Sean Mooney R 2021 · 3.36 FIP	23	SP	3.36	30.2%	15.3%	1.6%	.250	4.70	24.7%	11.2%	60	+1.34	3.36	102	77
George Klassen R 2024 · 3.50 FIP	22	SP	3.50	27.0%	13.6%	1.7%	.299	4.01	20.6%	9.1%	221	+0.51	3.50	314	77
Jackson Baumeister R 2024 · 3.32 FIP	22	SP	3.32	25.2%	13.4%	1.2%	.270	5.44	18.9%	6.2%	166	+2.12	3.32	265	73
Griff McGarry R 2022 · 4.20 FIP	23	SP	4.20	29.0%	15.2%	2.9%	.252	4.12	26.1%	8.5%	157	-0.08	2.46	282	73
David Festa R 2023 · 3.68 FIP	23	SP	3.68	24.5%	11.2%	2.2%	.341	3.71	27.2%	19.1%	209	+0.03	3.67	405	71
River Ryan R 2022 · 3.69 FIP	23	SP	3.69	26.1%	12.2%	2.3%	.321	3.88	20.3%	9.2%	134	+0.19	2.44	223	71
Luis Gil R 2021 · 3.92 FIP	23	SP	3.92	29.2%	14.2%	2.7%	.276	4.13	26.8%	14.3%	173	+0.21	3.11	567	71
Gavin Williams R 2022 · 3.44 FIP	23	SP	3.44	26.2%	9.9%	2.4%	.238	3.87	25.1%	14.3%	398	+0.43	3.39	697	70
Matt Brash R 2021 · 3.46 FIP	23	SP	3.46	27.8%	13.3%	1.9%	.273	2.76	32.2%	20.3%	147	-0.70	1.91	309	69
Clayton Beeter R 2022 · 4.42 FIP	23	SP	4.42	30.0%	14.5%	3.7%	.327	3.97	26.7%	12.9%	217	-0.45	2.60	395	69
Mason Black R 2023 · 4.23 FIP	23	SP	4.23	25.2%	10.0%	3.6%	.284	5.09	18.0%	8.3%	333	+0.86	3.95	569	69
Brody McCullough R 2023 · 3.58 FIP	23	SP	3.58	23.1%	10.3%	2.1%	.267	4.45	21.3%	11.7%	42	+0.87	3.58	129	69
Carson Ragsdale R 2021 · 4.21 FIP	23	SP	4.21	25.0%	10.7%	3.4%	.349	4.27	25.0%	14.6%	148	+0.06	2.00	352	68
Sam Benschoter R 2022 · 3.71 FIP	24	SP-	3.71	26.3%	9.2%	3.0%	.344	4.96	18.7%	8.6%	306	+1.25	3.61	441	68
Shohei Ohtani R 2018 · 3.43 FIP	24	SP	3.43	29.9%	10.4%	2.8%	.267	3.14	29.3%	21.4%	130	-0.29	1.76	613	68
Ty Madden R 2023 · 4.52 FIP	23	SP	4.52	24.0%	11.2%	3.7%	.304	4.75	21.2%	12.0%	217	+0.23	4.39	458	68
Jaden Hamm R 2024 · 3.79 FIP	21	SP	3.79	23.5%	8.9%	2.8%	.273	4.79	17.1%	7.3%	83	+1.00	3.79	182	67
Alec Marsh R 2021 · 4.70 FIP	23	SP	4.70	32.1%	13.5%	4.7%	.340	4.87	23.2%	13.4%	399	+0.17	3.93	424	67
Luis Garcia R 2019 · 3.80 FIP	22	SP-	3.80	28.9%	13.1%	2.7%	.266	3.77	25.4%	17.9%	313	-0.03	3.40	535	67
Cade Smith R 2024 · 3.86 FIP	22	SP	3.86	23.2%	13.3%	1.9%	.273	5.35	18.2%	6.6%	157	+1.49	3.86	243	67

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	6.0	100	31.3%	12.1%	1.19	4.01
Juan Berenguer ('78-'92, 9 WAR*)	6.0	100	26.4%*	11.6%*	1.13*	4.14*
Dinelson Lamet ('24)	1.8	61	29.9%	10.7%	1.30	4.63
Kerry Wood ('12)	6.9	115	27.0%	11.4%	0.97	3.67
John Hiller ('65-'80, 25 WAR*)	6.2	96	28.7%*	10.1%*	1.16*	3.19*
Wayne Twitchell ('70-'79, 4 WAR*)	5.3	133	24.2%*	11.3%*	1.16*	4.56*
Brad Peacock ('21)	2.8	93	24.7%	10.1%	1.27	4.11