Gus Varland

P Washington Nationals

Age 30 RHP 6'1" / 225 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	58	1	64	5.80	3.54	23.9%	7.0%	0.8	K 21.8% · BB 6.6% · FIP 3.72
2025	28	MIX2 levels	8	1	6	5.68	4.52	35.5%	19.4%	—	K 35.5% · BB 19.4% · FIP 4.33
2026	29	MIX2 levels	64	0	62	4.76	4.37	25.5%	9.4%	0.1	K 23.6% · BB 8.9% · FIP 4.49
2027PROJ	30	MLBWSH	32	0	34	4.75	4.75	23.0%	9.5%	-0.1
2028PROJ88% MLB	31	MLBWSH	30	0	31	4.85	4.94	22.3%	9.8%	-0.1
2029PROJ90% MLB	32	MLBWSH	24	0	25	5.01	5.15	21.6%	10.2%	-0.2

Last 3 seasons WAR 0.9 · Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo58

K%39

xwOBA vs10

CompsJoe Nelson (age 31) · Neil Wagner (age 29) · Jim Miller (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 136128vR 120

ERA4.75

FIP4.75

K%23.0%

BB%9.5%

K-BB%13.5%

Proj IP41

Value2027 · WAR

Runs saved vs league avg · 41 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL4040

CMD4545

K†5555

Statcast Percentiles

FB Velo

p5895.1

Whiff%

p2521.8%

p3920.6%

xwOBA vs

p100.392

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	MIX MLE	2 levels	6	6	20	75	28	4	1	100%	3.4	29.2%	5.0%	24.2%	2.0%	0.89	2.39	—
2018	21	MIX RAW	2 levels	6	6	20	75	28	4	1	100%	3.4	37.3%	5.3%	32.0%	1.3%	0.89	1.58	—
2019	22	A+ MLE	Stockton Ports	5	4	26	106	27	8	3	80%	5.3	19.6%	8.7%	10.9%	3.2%	2.39	4.29	—
2019	22	A+ RAW	Stockton Ports	5	4	26	106	27	8	3	80%	5.3	25.5%	7.5%	17.9%	2.8%	2.39	3.44	—
2021	24	AA MLE	Tulsa Drillers	16	14	35	153	22	18	7	88%	2.2	11.6%	12.9%	-1.3%	5.9%	5.71	6.98	—
2021	24	AA RAW	Tulsa Drillers	16	14	35	153	22	18	7	88%	2.2	14.4%	11.8%	2.6%	4.6%	5.71	6.01	—
2022	25	AA MLE	Tulsa Drillers	41	7	71	324	85	36	11	17%	1.7	21.3%	12.2%	9.0%	4.1%	6.11	5.11	—
2022	25	AA RAW	Tulsa Drillers	41	7	71	324	85	36	11	17%	1.7	26.2%	11.1%	15.1%	3.4%	6.11	4.25	—
2023	26	MIX MLE	3 levels	51	1	59	264	62	28	7	2%	1.2	22.2%	10.2%	12.0%	2.9%	4.55	4.09	+0.3
2023	26	MIX RAW	3 levels	51	1	59	264	62	28	7	2%	1.2	23.5%	10.6%	12.9%	2.7%	4.55	3.96	+0.4
2024	27	MIX MLE	2 levels	58	1	64	285	68	20	8	2%	1.1	21.8%	6.6%	15.3%	3.0%	5.80	3.72	+0.6
2024	27	MIX MLE	2 levels	58	1	64	285	68	20	8	2%	1.1	21.8%	6.6%	15.3%	3.0%	5.80	3.72	+0.6
2024	27	MIX RAW	2 levels	58	1	64	285	68	20	8	2%	1.1	23.9%	7.0%	16.8%	2.8%	5.80	3.54	+0.8
2025	28	MIX MLE	2 levels	8	1	6	31	11	6	1	12%	0.8	35.5%	19.4%	16.1%	3.2%	5.68	4.33	—
2025	28	MIX MLE	2 levels	8	1	6	31	11	6	1	12%	0.8	35.5%	19.4%	16.1%	3.2%	5.68	4.33	—
2025	28	MIX RAW	2 levels	8	1	6	31	11	6	1	12%	0.8	35.5%	19.4%	16.1%	3.2%	5.68	4.52	—
2026	29	MIX MLE	2 levels	64	0	62	278	71	26	11	0%	1.0	23.6%	8.9%	14.7%	4.1%	4.76	4.49	+0.0
2026	29	MIX MLE	2 levels	64	0	62	278	71	26	11	0%	1.0	23.6%	8.9%	14.7%	4.1%	4.76	4.49	+0.0
2026	29	MIX RAW	2 levels	64	0	62	278	71	26	11	0%	1.0	25.5%	9.4%	16.2%	4.0%	4.76	4.37	+0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			76	0	80	373	79	36	12	0%	1.0	21.2%	9.7%	11.5%	3.2%	5.54	4.43	+0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	WSH	32	0	34	144	33	14	5	0%	1.1	23.0%	9.5%	13.5%	3.7%	4.75	4.75	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	WSH	34	0	36	152	34	15	6	0%	1.1	22.3%	9.8%	12.5%	3.8%	4.85	4.94	-0.2
2029	32	MLB MLE	WSH	26	0	27	115	25	12	5	0%	1.1	21.6%	10.2%	11.4%	4.0%	5.01	5.15	-0.2
2028	31	MLB CTX	WSH	30	0	31	131	29	13	5	0%	1.0	22.3%	9.8%	12.5%	3.8%	4.85	4.94	-0.1
2029	32	MLB CTX	WSH	24	0	25	106	23	11	4	0%	1.0	21.6%	10.2%	11.4%	4.0%	5.01	5.15	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		129	0	136	609	131	60	21	0%	1.1	21.5%	9.8%	11.7%	3.5%	5.28	4.44	+0.2
/ 200 IP	—	RAW		191	0	200	898	193	88	31	0%	1.0	21.5%	9.8%	11.7%	3.5%	5.28	4.44	+0.3
Career	—	MLE		249	34	344	1516	327	149	56	14%	1.4	21.6%	9.8%	11.7%	3.7%	4.90	4.54	-0.2
/ 200 IP	—	MLE		145	20	200	882	190	87	32	14%	1.4	21.6%	9.8%	11.7%	3.7%	4.90	4.54	-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 AAARochester Red Wings · 29 IPFIP 3.44 → 3.87 (+0.43)K% 31.7% → 27.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.71%	—	×0.860	27.27%
BB% (unintentional) /BF	9.76%	—	×0.900	8.78%
HR / BF /BF	3.25%	÷1.000	×1.100	3.58%

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 100).

Result: FIP 3.44 → 3.87, 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 AAACharlotte Knights · 5 IPFIP 4.72 → 4.54 (−0.19)K% 34.6% → 29.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.62%	—	×0.860	29.77%
BB% (unintentional) /BF	19.23%	—	×0.900	17.31%
HR / BF /BF	3.85%	÷1.320	×1.100	3.21%

Result: FIP 4.72 → 4.54, 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 AAACharlotte Knights · 37 IPFIP 3.97 → 4.32 (+0.35)K% 24.1% → 20.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.12%	—	×0.860	20.74%
BB% (unintentional) /BF	7.65%	—	×0.900	6.88%
HR / BF /BF	3.53%	÷1.016	×1.100	3.82%

Result: FIP 3.97 → 4.32, 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 AAAOklahoma City Dodgers · 37 IPFIP 3.21 → 3.58 (+0.37)K% 28.0% → 24.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.00%	—	×0.860	24.08%
BB% (unintentional) /BF	8.00%	—	×0.900	7.20%
HR / BF /BF	2.67%	÷1.006	×1.100	2.92%

Result: FIP 3.21 → 3.58, 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 AATulsa Drillers · 71 IPFIP 4.16 → 5.11 (+0.95)K% 26.2% → 21.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.23%	—	×0.810	21.25%
BB% (unintentional) /BF	11.11%	—	×1.100	12.22%
HR / BF /BF	3.40%	÷0.993	×1.200	4.10%

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 99).

Result: FIP 4.16 → 5.11, 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).

2021 AATulsa Drillers · 35 IPFIP 5.89 → 6.98 (+1.09)K% 14.4% → 11.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.38%	—	×0.810	11.65%
BB% (unintentional) /BF	11.76%	—	×1.100	12.94%
HR / BF /BF	4.58%	÷0.935	×1.200	5.87%

Result: FIP 5.89 → 6.98, 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 A+Stockton Ports · 26 IPFIP 3.46 → 4.29 (+0.83)K% 25.5% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.47%	—	×0.770	19.61%
BB% (unintentional) /BF	7.55%	—	×1.150	8.68%
HR / BF /BF	2.83%	÷1.114	×1.250	3.18%

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 3.46 → 4.29, 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 ABeloit Snappers · 19 IPFIP 1.08 → 2.39 (+1.31)K% 39.4% → 29.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.44%	—	×0.740	29.18%
BB% (unintentional) /BF	4.23%	—	×1.180	4.99%
HR / BF /BF	1.41%	÷0.895	×1.300	2.04%

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 79).

Result: FIP 1.08 → 2.39, 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
Gus Varland (OGILVIE)	—	—	4.75	23.0%	9.5%	3.7%	—	5.03	22.0%	12.0%	63	+0.28	—	—	—
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	83
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	83
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	80
Erik Davis R 2017 · 4.25 FIP	30	SU	4.25	22.2%	11.1%	3.0%	.349	3.52	17.4%	8.5%	65	-0.73	3.05	227	78
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	77
Jhan Mariñez R 2018 · 4.09 FIP	29	SU	4.09	21.2%	7.9%	3.2%	.331	—	—	—	—	—	3.16	253	77
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	77
Jose Manuel Lopez R 2015 · 5.21 FIP	30	SU	5.21	18.6%	7.6%	4.9%	.373	3.56	18.5%	9.3%	93	-1.65	3.50	170	76
Andrew Robinson R 2017 · 4.32 FIP	29	SU	4.32	23.4%	8.8%	3.8%	.245	—	—	—	—	—	3.19	160	76
Jeremy Fikac R 2004 · 4.91 FIP	29	SU	4.91	19.6%	8.0%	4.5%	.276	—	—	—	—	—	3.10	136	76
Manny Acosta R 2011 · 3.75 FIP	30	SU	3.75	22.5%	7.4%	2.9%	.321	4.49	21.3%	10.2%	47	+0.74	3.08	350	76
Hirokazu Sawamura R 2021 · 4.48 FIP	33	SU	4.48	26.2%	11.2%	4.0%	.263	4.02	18.1%	6.8%	51	-0.46	4.02	104	75
Adrian Ramirez R 2019 · 4.29 FIP	31	SU	4.29	21.7%	6.3%	4.0%	.327	—	—	—	—	—	3.04	137	75
Mike Broadway R 2017 · 4.73 FIP	30	SU	4.73	18.3%	10.2%	3.4%	.245	4.65	23.0%	12.4%	49	-0.08	1.74	195	75
Esteban Haro R 2016 · 4.55 FIP	30	SU	4.55	17.1%	10.2%	2.9%	.338	3.83	11.6%	6.3%	75	-0.72	3.76	164	74
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	74
Scott Atchison R 2007 · 4.55 FIP	31	SU	4.55	19.1%	7.6%	3.8%	.297	4.59	16.2%	9.5%	60	+0.04	2.52	340	74
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	74
Ryan Tepera R 2018 · 3.90 FIP	30	SU	3.90	25.9%	8.7%	3.4%	.282	3.20	28.4%	19.9%	104	-0.70	2.35	445	73
Jeff Fulchino R 2010 · 4.30 FIP	30	SU	4.30	21.2%	9.2%	3.3%	.319	4.44	20.4%	9.3%	35	+0.14	3.36	178	73

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	0.9	31	21.8%	10.1%	1.37	5.15
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Scott Service ('04)	2.1	46	22.2%	9.9%	1.23	5.04
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Tom Dukes ('67-'72, -2 WAR*)	1.1	43	22.7%*	8.7%*	1.16*	5.37*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Dennis Powell ('85-'93, -2 WAR*)	1.7	49	17.6%*	10.1%*	1.18*	5.31*