Julian Tonghini

P Wilmington Blue Rocks

Age 25 RHP 6'2" / 196 lbs A+

Overview

A+PROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	24	MIX2 levels	14	22	4.50	2.92	31.6%	10.5%	—	K 21.4% · BB 12.8% · FIP 5.45
2027PROJ	25	MLBWSH	6	6	4.66	4.66	22.6%	11.1%	-0.0
2028PROJ43% MLB	26	MLBWSH	9	9	4.62	4.61	22.9%	10.9%	-0.0

Next 2 projected WAR -0.0Projected 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 99%

CompsJosh Zeid (age 26) · Grant Balfour (age 25) · Chris Jefferson (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 122114vR 105

ERA4.66

FIP4.66

K%22.6%

BB%11.1%

K-BB%11.5%

Proj IP6

Value2027 · WAR

Runs saved vs league avg · 6 IP

Grades · Contract

Scouting Grades

K†5555

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)
2026	24	MIX MLE	2 levels	14	0	22	95	30	10	2	0%	1.6	21.4%	12.8%	8.6%	4.6%	4.50	5.45	—
2026	24	MIX MLE	2 levels	14	0	22	95	30	10	2	0%	1.6	21.4%	12.8%	8.6%	4.6%	4.50	5.45	—
2026	24	MIX RAW	2 levels	14	0	22	95	30	10	2	0%	1.6	31.6%	10.5%	21.1%	2.1%	4.50	2.92	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	WSH	6	0	6	25	6	3	1	0%	1.0	22.6%	11.1%	11.5%	3.1%	4.66	4.66	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	WSH	19	0	20	84	19	9	3	0%	1.1	22.9%	10.9%	12.0%	3.1%	4.62	4.61	-0.0
2028	26	MLB CTX	WSH	9	0	9	38	9	4	1	0%	1.0	22.9%	10.9%	12.0%	3.1%	4.62	4.61	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		8	0	9	36	8	4	1	0%	1.1	22.9%	10.9%	12.0%	3.1%	4.62	4.23	+0.0
/ 200 IP	—	RAW		190	0	200	844	187	94	23	0%	1.1	22.9%	10.9%	12.0%	3.1%	4.62	4.23	+0.8
Career	—	MLE		14	0	22	95	20	12	4	0%	1.6	21.4%	12.8%	8.6%	4.6%	4.50	5.45	-0.0
/ 200 IP	—	MLE		127	0	200	864	185	110	40	0%	1.6	21.4%	12.8%	8.6%	4.6%	4.50	5.45	-0.1

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
Julian Tonghini (OGILVIE)	—	—	4.66	22.6%	11.1%	3.1%	—	4.61	22.9%	12.0%	20	-0.05	—	—	—
Josh Zeid R 2013 · 4.00 FIP	26	SU	4.00	20.3%	9.3%	2.6%	.287	4.75	16.2%	4.8%	183	+0.75	4.00	313	86
Grant Balfour R 2003 · 4.13 FIP	25	SU	4.13	26.1%	10.4%	3.5%	.275	3.79	24.4%	12.8%	39	-0.34	2.04	533	86
Chris Jefferson R 2022 · 3.53 FIP	25	SU	3.53	22.4%	10.2%	1.9%	.330	4.99	16.5%	3.9%	101	+1.46	3.53	140	85
Michael Wuertz R 2004 · 4.46 FIP	25	SU	4.46	24.2%	12.9%	3.2%	.243	3.39	26.1%	16.6%	189	-1.07	2.27	414	85
Francisco Del Rosario R 2006 · 5.13 FIP	25	SU	5.13	19.4%	13.0%	3.7%	.290	3.93	19.7%	10.3%	26	-1.20	3.93	194	85
Brad Boxberger R 2013 · 4.40 FIP	25	SU	4.40	25.5%	13.8%	3.1%	.296	3.54	32.3%	22.2%	152	-0.86	2.63	478	84
Jason Stoffel R 2015 · 3.61 FIP	26	SU	3.61	23.4%	10.1%	2.2%	.267	3.49	27.2%	19.2%	59	-0.12	3.49	103	84
Fernando Salas R 2010 · 4.27 FIP	25	SU	4.27	21.8%	9.8%	3.2%	.276	3.29	23.5%	16.8%	162	-0.98	2.60	539	84
Guillermo Moscoso R 2009 · 3.56 FIP	25	SU	3.56	18.8%	9.4%	1.6%	.311	4.33	15.8%	8.5%	178	+0.77	3.56	486	84
Shawn Tolleson R 2012 · 3.86 FIP	24	SU	3.86	24.4%	11.9%	2.4%	.265	3.47	24.4%	18.5%	144	-0.39	3.05	218	84
Jesus Pirela R 2015 · 3.84 FIP	26	SU	3.84	23.7%	11.6%	2.3%	.305	3.92	17.1%	13.9%	45	+0.08	3.24	161	84
Luis Vizcaino R 2000 · 4.11 FIP	25	SU	4.11	18.8%	11.5%	2.1%	.354	4.31	22.7%	14.9%	180	+0.20	3.07	564	83
Garrett Mock R 2008 · 3.57 FIP	25	SU	3.57	25.6%	11.1%	2.2%	.300	4.06	17.1%	7.4%	91	+0.49	3.57	132	83
Chaz Roe R 2013 · 4.02 FIP	26	SU	4.02	25.3%	10.5%	3.1%	.259	2.81	24.6%	16.2%	133	-1.21	1.72	279	83
Jon Leicester R 2004 · 4.69 FIP	25	SU	4.69	20.0%	8.6%	4.0%	.280	4.44	11.0%	2.0%	32	-0.25	3.76	113	83
Brandon Cunniff R 2015 · 4.28 FIP	26	SU	4.28	24.5%	13.2%	2.9%	.256	4.32	20.3%	9.0%	115	+0.04	3.89	180	83
Nolan Clenney R 2021 · 3.73 FIP	25	SU	3.73	25.5%	8.4%	3.1%	.340	4.35	22.4%	13.7%	185	+0.62	3.73	223	82
Jackson Hicks R 2023 · 3.90 FIP	25	SU	3.90	22.6%	10.5%	2.5%	.336	—	—	—	—	—	2.17	116	82
Dan Kolb R 2001 · 4.49 FIP	26	SU	4.49	21.4%	12.9%	2.9%	.295	3.61	14.3%	5.5%	131	-0.88	3.00	283	82
Hueston Morrill R 2024 · 4.54 FIP	24	SU	4.54	19.8%	8.7%	3.7%	.302	3.24	19.0%	8.2%	54	-1.30	3.09	102	82