Jake Irvin

P Washington Nationals

Age 30 RHP 6'6" / 234 lbs MLB peak 0.2 · 2027

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MLBWSH	33	33	188	4.41	4.26	20.3%	6.6%	2.5
2025	28	MLBWSH	33	33	180	5.70	5.50	15.8%	7.9%	-0.2
2026	29	MIX3 levels	25	23	118	4.96	4.48	23.9%	9.6%	1.3	K 23.4% · BB 10.2% · FIP 4.75
2027PROJ	30	MLBWSH	14	14	81	5.12	5.22	19.6%	8.8%	0.2
2028PROJ	31	MLBWSH	12	12	74	5.32	5.45	18.9%	9.2%	-0.0
2029PROJ	32	MLBWSH	10	10	58	5.55	5.71	18.1%	9.6%	-0.2

Last 3 seasons WAR 3.6 · Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%57

FB Velo32

xwOBA vs17

Form5.04 ERA (proj 5.12) · K 25.9% (proj 19.6%) · BB 8.3% (proj 8.8%) ▲▲ last 60d · 25 IP through Oct 27

CompsChase Anderson (age 30) · Tom Koehler (age 30) · Matt Shoemaker (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 132124vR 116

ERA5.12

FIP5.22

K%19.6%

BB%8.8%

K-BB%10.8%

Proj IP81

Value2027 · WAR

Runs saved vs league avg · 81 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p3293.2

Whiff%

p4124.0%

p5723.4%

xwOBA vs

p170.351

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)
2018	21	ROK MLE	GCL Nationals	7	3	13	53	9	3	0	43%	1.8	11.5%	7.1%	4.5%	0.0%	1.42	3.02	—
2018	21	ROK RAW	GCL Nationals	7	3	13	53	9	3	0	43%	1.8	17.0%	5.7%	11.3%	0.0%	1.42	2.39	—
2019	22	A MLE	Hagerstown Suns	25	25	128	536	113	38	14	100%	5.1	15.6%	8.4%	7.2%	3.5%	3.79	4.75	—
2019	22	A RAW	Hagerstown Suns	25	25	128	536	113	38	14	100%	5.1	21.1%	7.1%	14.0%	2.6%	3.79	3.65	—
2022	25	MIX MLE	2 levels	24	24	103	424	107	28	9	100%	4.3	20.2%	7.4%	12.8%	2.6%	3.83	3.76	—
2022	25	MIX RAW	2 levels	24	24	103	424	107	28	9	100%	4.3	25.2%	6.6%	18.6%	2.1%	3.83	2.97	—
2023	26	MIX MLE	2 levels	29	29	143	628	119	65	23	100%	4.9	18.5%	10.2%	8.3%	3.7%	4.77	4.85	+0.9
2023	26	MIX RAW	2 levels	29	29	143	628	119	65	23	100%	4.9	18.9%	10.4%	8.6%	3.7%	4.77	4.89	+0.8
2024	27	MLB MLE	Washington Nationals	33	33	188	769	156	51	29	100%	5.7	20.3%	6.6%	13.7%	3.8%	4.41	4.30	+2.4
2024	27	MLB MLE	Washington Nationals	33	33	188	769	156	51	29	100%	5.7	20.3%	6.6%	13.7%	3.8%	4.41	4.30	+2.4
2024	27	MLB RAW	Washington Nationals	33	33	188	769	156	51	29	100%	5.7	20.3%	6.6%	13.7%	3.8%	4.41	4.26	+2.5
2025	28	MLB MLE	Washington Nationals	33	33	180	787	124	62	38	100%	5.5	15.8%	7.9%	7.9%	4.8%	5.70	5.42	-0.0
2025	28	MLB MLE	Washington Nationals	33	33	180	787	124	62	38	100%	5.5	15.8%	7.9%	7.9%	4.8%	5.70	5.42	-0.0
2025	28	MLB RAW	Washington Nationals	33	33	180	787	124	62	38	100%	5.5	15.8%	7.9%	7.9%	4.8%	5.70	5.50	-0.2
2026	29	MIX MLE	3 levels	25	23	118	510	122	49	20	92%	4.7	23.4%	10.2%	13.2%	4.3%	4.96	4.75	+0.9
2026	29	MIX MLE	3 levels	25	23	118	510	122	49	20	92%	4.7	23.4%	10.2%	13.2%	4.3%	4.96	4.75	+0.9
2026	29	MIX RAW	3 levels	25	23	118	510	122	49	20	92%	4.7	23.9%	9.6%	14.3%	3.9%	4.96	4.48	+1.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			112	110	595	2556	489	215	107	98%	5.3	19.1%	8.4%	10.7%	4.2%	5.03	4.88	+3.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	WSH	14	14	81	342	67	30	14	100%	5.8	19.6%	8.8%	10.8%	4.2%	5.12	5.22	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	WSH	12	12	74	314	59	29	14	100%	6.2	18.9%	9.2%	9.7%	4.4%	5.32	5.45	-0.0
2029	32	MLB MLE	WSH	10	10	58	246	44	24	11	100%	5.8	18.1%	9.6%	8.5%	4.6%	5.55	5.71	-0.2
2028	31	MLB CTX	WSH	12	12	74	312	59	29	14	100%	6.2	18.9%	9.2%	9.7%	4.4%	5.32	5.45	-0.0
2029	32	MLB CTX	WSH	10	10	58	245	44	23	11	100%	5.8	18.1%	9.6%	8.5%	4.6%	5.55	5.71	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		134	132	728	3116	593	267	132	99%	5.4	19.0%	8.6%	10.4%	4.2%	5.10	4.91	+4.1
/ 200 IP	—	RAW		37	36	200	856	163	73	36	99%	5.4	19.0%	8.6%	10.4%	4.2%	5.10	4.91	+1.1
Career	—	MLE		176	170	873	3707	691	309	141	97%	5.0	18.6%	8.3%	10.3%	3.8%	4.61	4.68	+3.3
/ 200 IP	—	MLE		40	39	200	849	158	71	32	97%	5.0	18.6%	8.3%	10.3%	3.8%	4.61	4.68	+0.9

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 · 8 IPFIP 0.92 → 1.46 (+0.54)K% 31.0% → 25.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.03%	—	×0.810	25.14%
BB% (unintentional) /BF	3.45%	—	×1.100	3.79%
HR / BF /BF	0.00%	÷1.000	×1.200	0.00%

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 0.92 → 1.46, 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 AAARochester Red Wings · 22 IPFIP 4.48 → 4.65 (+0.17)K% 20.4% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.41%	—	×0.860	17.55%
BB% (unintentional) /BF	11.22%	—	×0.900	10.10%
HR / BF /BF	3.06%	÷1.058	×1.100	3.18%

Factors used: pitcher AAA level factors (Triple-A 2023+ robo-zone set: walks improve on promotion) — K ×0.86, BB ×0.90, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 112).

Result: FIP 4.48 → 4.65, 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 AAHarrisburg Senators · 73 IPFIP 3.39 → 4.25 (+0.86)K% 25.5% → 20.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.49%	—	×0.810	20.65%
BB% (unintentional) /BF	6.54%	—	×1.100	7.19%
HR / BF /BF	2.94%	÷0.979	×1.200	3.60%

Result: FIP 3.39 → 4.25, 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 A+Wilmington Blue Rocks · 30 IPFIP 1.88 → 2.49 (+0.61)K% 24.6% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.58%	—	×0.770	18.92%
BB% (unintentional) /BF	6.78%	—	×1.150	7.80%
HR / BF /BF	0.00%	÷1.114	×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 123).

Result: FIP 1.88 → 2.49, 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).

2019 AHagerstown Suns · 128 IPFIP 3.65 → 4.75 (+1.10)K% 21.1% → 15.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.08%	—	×0.740	15.60%
BB% (unintentional) /BF	7.09%	—	×1.180	8.37%
HR / BF /BF	2.61%	÷0.976	×1.300	3.48%

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 95).

Result: FIP 3.65 → 4.75, 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).

2018 ROKGCL Nationals · 13 IPFIP 2.38 → 3.02 (+0.64)K% 17.0% → 11.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.98%	—	×0.680	11.55%
BB% (unintentional) /BF	5.66%	—	×1.250	7.08%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 2.38 → 3.02, 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).

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
Jake Irvin (OGILVIE)	—	—	—	—	—	4.2%	—	5.56	18.5%	9.2%	133	+0.34	—	—	—
Chase Anderson R 2018 · 4.98 FIP	30	SP	4.98	19.9%	8.9%	4.4%	.235	4.93	20.1%	11.9%	253	-0.05	3.30	1,260	71
Tom Koehler R 2016 · 4.38 FIP	30	SP	4.38	19.0%	9.8%	3.0%	.291	4.66	22.4%	13.4%	110	+0.28	3.76	822	68
Matt Shoemaker R 2017 · 4.88 FIP	30	SP	4.88	21.2%	8.6%	4.5%	.271	4.29	23.5%	15.5%	88	-0.59	3.12	728	67
Hideki Irabu R 2000 · 4.38 FIP	31	SP	4.38	17.0%	5.7%	3.6%	.374	5.19	17.2%	11.0%	64	+0.81	3.78	514	65
Miguel González R 2014 · 4.49 FIP	30	SP	4.49	16.5%	7.5%	3.4%	.268	4.26	16.6%	9.5%	457	-0.23	3.72	905	65
Rolando Arrojo R 2000 · 4.47 FIP	32	SP	4.47	16.1%	8.0%	3.1%	.291	3.68	16.4%	9.2%	185	-0.79	3.50	700	62
Todd Ritchie R 2002 · 4.66 FIP	30	SP	4.66	12.4%	8.0%	2.9%	.331	4.78	11.5%	3.9%	28	+0.12	3.03	828	58
Lance Lynn R 2017 · 4.68 FIP	30	SP	4.68	19.7%	9.4%	3.7%	.237	3.25	25.9%	17.8%	449	-1.43	2.85	2,006	57
Chris Young R 2009 · 5.20 FIP	30	SP	5.20	14.9%	11.0%	3.6%	.245	4.27	17.5%	9.5%	159	-0.93	3.17	1,298	56
Rodrigo Lopez R 2006 · 4.67 FIP	30	SP-	4.67	16.1%	6.7%	3.8%	.325	4.30	13.2%	7.9%	109	-0.37	4.06	1,344	56
Nick Blackburn R 2012 · 5.80 FIP	30	SP	5.80	9.2%	5.7%	5.0%	.329	—	—	—	—	—	4.19	819	56
Jae Weong Seo R 2007 · 5.35 FIP	30	SP	5.35	11.3%	6.0%	4.4%	.376	—	—	—	—	—	3.65	605	55
Jeremy Guthrie R 2009 · 5.09 FIP	30	SP	5.09	12.6%	6.8%	4.0%	.282	4.41	13.7%	7.5%	599	-0.68	4.08	1,834	54
Brian Moehler R 2002 · 4.92 FIP	30	SP	4.92	11.2%	4.7%	4.0%	.300	4.06	13.1%	8.1%	172	-0.86	3.81	1,559	54
Victor Zambrano R 2006 · 6.06 FIP	30	SP	6.06	15.5%	11.3%	5.1%	.303	6.68	12.8%	-3.2%	23	+0.62	3.42	706	53
Chi Chi González R 2022 · 4.30 FIP	30	SP-	4.30	17.6%	8.0%	3.0%	.315	5.33	11.2%	5.6%	122	+1.03	4.01	800	53
Brian Tollberg R 2002 · 4.98 FIP	29	SP	4.98	11.5%	5.9%	3.8%	.339	—	—	—	—	—	4.02	297	53
Ramon Ortiz R 2003 · 4.99 FIP	30	SP	4.99	11.5%	7.7%	3.4%	.288	4.88	13.0%	6.8%	490	-0.11	4.32	1,525	53
Daisuke Matsuzaka R 2011 · 4.88 FIP	30	SP	4.88	15.6%	13.8%	2.5%	.246	4.30	20.6%	9.6%	168	-0.58	3.77	790	53
Chris Holt R 2001 · 4.50 FIP	29	SP-	4.50	11.5%	7.5%	2.6%	.328	—	—	—	—	—	3.65	732	52

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	4.0	116	19.1%	8.6%	1.64	5.11
Claudio Vargas ('10)	3.8	109	16.2%	8.7%	1.49	4.83
Jason Bergmann ('10)	1.9	97	17.5%	9.0%	1.50	5.04
Bob Sykes ('77-'81, 0 WAR*)	2.3	91	16.3%*	9.6%*	1.54*	5.05*
Paul Moskau ('77-'83, 3 WAR*)	3.2	91	19.8%*	8.9%*	1.50*	4.84*
Mark Grant ('84-'93, 0 WAR*)	3.2	91	18.0%*	8.5%*	1.41*	4.84*
Hideki Irabu ('02)	2.6	103	18.1%	7.8%	1.59	5.15