Grant Wolfram

P Baltimore Orioles

Age 30 LHP 6'7" / 250 lbs MLB peak 0.6 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	46	60	3.13	3.13	27.6%	10.0%	—	K 22.0% · BB 9.1% · FIP 3.76
2025	28	MIX2 levels	49	59	4.42	2.64	24.7%	10.0%	1.4	K 22.9% · BB 9.5% · FIP 2.76
2026	29	MLBBAL	60	52	4.30	2.37	27.0%	6.6%	1.4
2027PROJ	30	MLBBAL	40	42	3.82	3.64	25.4%	8.8%	0.5
2028PROJ87% MLB	31	MLBBAL	35	37	3.92	3.94	24.4%	9.2%	0.3
2029PROJ90% MLB	32	MLBBAL	29	30	4.11	4.22	23.5%	9.6%	0.1

Last 3 seasons WAR 2.7 · Next 3 projected WAR 0.9Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%76

xwOBA vs74

FB Velo64

Form4.66 ERA (proj 3.82) · K 30.5% (proj 25.4%) · BB 8.5% (proj 8.8%) ▲ last 90d · 19 IP through Oct 27

CompsJared Koenig (age 30) · Raul Valdes (age 32) · Brian Moran (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 8290vR 98

ERA3.82

FIP3.64

K%25.4%

BB%8.8%

K-BB%16.5%

Proj IP50

Value2027 · WAR

Runs saved vs league avg · 50 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL3535

CMD4545

K†6060

Statcast Percentiles

FB Velo

p6495.5

Whiff%

p5025.2%

p7627.0%

xwOBA vs

p740.289

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	AZL Rangers	8	1	11	45	10	6	0	12%	1.3	22.2%	13.3%	8.9%	0.0%	3.38	2.91	—
2018	21	ROK RAW	AZL Rangers	8	1	11	45	10	6	0	12%	1.3	22.2%	13.3%	8.9%	0.0%	3.38	2.91	—
2019	22	A MLE	Hickory Crawdads	25	9	69	308	73	30	3	36%	2.8	17.5%	11.5%	6.0%	1.1%	4.28	3.66	—
2019	22	A RAW	Hickory Crawdads	25	9	69	308	73	30	3	36%	2.8	23.7%	9.7%	14.0%	1.0%	4.28	2.85	—
2021	24	A+ MLE	Hickory Crawdads	17	14	66	303	99	34	11	82%	3.9	25.2%	12.9%	12.3%	5.2%	4.21	5.44	—
2021	24	A+ RAW	Hickory Crawdads	17	14	66	303	99	34	11	82%	3.9	32.7%	11.2%	21.5%	3.6%	4.21	3.81	—
2022	25	AA MLE	Frisco RoughRiders	39	0	57	260	71	42	3	0%	1.5	22.1%	17.8%	4.3%	1.5%	4.42	4.31	—
2022	25	AA RAW	Frisco RoughRiders	39	0	57	260	71	42	3	0%	1.5	27.3%	16.2%	11.2%	1.2%	4.42	3.50	—
2023	26	MIX MLE	2 levels	40	1	62	255	78	24	6	2%	1.6	25.0%	9.6%	15.4%	2.8%	3.90	3.72	—
2023	26	MIX RAW	2 levels	40	1	62	255	78	24	6	2%	1.6	30.6%	9.4%	21.2%	2.4%	3.90	3.00	—
2024	27	MIX MLE	2 levels	46	0	60	250	69	25	5	0%	1.3	22.0%	9.1%	13.0%	2.5%	3.13	3.76	—
2024	27	MIX MLE	2 levels	46	0	60	250	69	25	5	0%	1.3	22.0%	9.1%	13.0%	2.5%	3.13	3.76	—
2024	27	MIX RAW	2 levels	46	0	60	250	69	25	5	0%	1.3	27.6%	10.0%	17.6%	2.0%	3.13	3.13	—
2025	28	MIX MLE	2 levels	49	0	59	271	67	27	2	0%	1.2	22.9%	9.5%	13.4%	0.7%	4.42	2.76	+1.3
2025	28	MIX MLE	2 levels	49	0	59	271	67	27	2	0%	1.2	22.9%	9.5%	13.4%	0.7%	4.42	2.76	+1.3
2025	28	MIX RAW	2 levels	49	0	59	271	67	27	2	0%	1.2	24.7%	10.0%	14.8%	0.7%	4.42	2.64	+1.4
2026	29	MLB MLE	Baltimore Orioles	60	0	52	226	61	15	3	0%	0.9	27.0%	6.6%	20.4%	1.3%	4.30	2.36	+1.4
2026	29	MLB MLE	Baltimore Orioles	60	0	52	226	61	15	3	0%	0.9	27.0%	6.6%	20.4%	1.3%	4.30	2.36	+1.4
2026	29	MLB RAW	Baltimore Orioles	60	0	52	226	61	15	3	0%	0.9	27.0%	6.6%	20.4%	1.3%	4.30	2.37	+1.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			81	0	79	359	92	29	5	0%	1.0	25.6%	8.1%	17.5%	1.4%	4.67	2.69	+1.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	BAL	40	0	42	177	45	16	4	0%	1.1	25.4%	8.8%	16.5%	2.2%	3.82	3.64	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	BAL	40	0	42	179	44	17	4	0%	1.1	24.4%	9.2%	15.2%	2.5%	3.92	3.94	+0.3
2029	32	MLB MLE	BAL	31	0	33	139	33	13	4	0%	1.1	23.5%	9.6%	13.9%	2.8%	4.11	4.22	+0.1
2028	31	MLB CTX	BAL	35	0	37	156	38	14	4	0%	1.1	24.4%	9.2%	15.2%	2.5%	3.92	3.94	+0.3
2029	32	MLB CTX	BAL	29	0	30	127	30	12	3	0%	1.0	23.5%	9.6%	13.9%	2.8%	4.11	4.22	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		145	0	146	641	160	55	12	0%	1.0	24.9%	8.7%	16.3%	1.9%	4.37	3.15	+2.4
/ 200 IP	—	RAW		198	0	200	879	220	76	16	0%	1.0	24.9%	8.7%	16.3%	1.9%	4.37	3.15	+3.3
Career	—	MLE		284	25	437	1918	440	214	41	9%	1.5	22.9%	11.2%	11.7%	2.1%	4.07	3.75	+2.2
/ 200 IP	—	MLE		130	11	200	877	201	98	19	9%	1.5	22.9%	11.2%	11.7%	2.1%	4.07	3.75	+2.8

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.

2025 AAANorfolk Tides · 32 IPFIP 2.09 → 2.28 (+0.19)K% 26.1% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.09%	—	×0.860	22.43%
BB% (unintentional) /BF	9.42%	—	×0.900	8.48%
HR / BF /BF	0.00%	÷0.945	×1.100	0.00%

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 89).

Result: FIP 2.09 → 2.28, 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 AAARound Rock Express · 57 IPFIP 3.37 → 3.76 (+0.39)K% 25.6% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.63%	—	×0.860	22.04%
BB% (unintentional) /BF	10.08%	—	×0.900	9.08%
HR / BF /BF	2.10%	÷0.928	×1.100	2.49%

Result: FIP 3.37 → 3.76, 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 AAFrisco RoughRiders · 49 IPFIP 2.20 → 3.14 (+0.94)K% 35.8% → 29.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.83%	—	×0.810	29.02%
BB% (unintentional) /BF	7.49%	—	×1.100	8.24%
HR / BF /BF	2.14%	÷0.974	×1.200	2.63%

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 95).

Result: FIP 2.20 → 3.14, 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 AAARound Rock Express · 13 IPFIP 5.21 → 5.32 (+0.11)K% 16.2% → 13.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.18%	—	×0.860	13.91%
BB% (unintentional) /BF	14.71%	—	×0.900	13.24%
HR / BF /BF	2.94%	÷1.035	×1.100	3.13%

Result: FIP 5.21 → 5.32, 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).

2022 AAFrisco RoughRiders · 57 IPFIP 3.47 → 4.31 (+0.84)K% 27.3% → 22.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.31%	—	×0.810	22.12%
BB% (unintentional) /BF	16.15%	—	×1.100	17.77%
HR / BF /BF	1.15%	÷0.915	×1.200	1.51%

Result: FIP 3.47 → 4.31, 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 A+Hickory Crawdads · 66 IPFIP 3.75 → 5.44 (+1.68)K% 32.7% → 25.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.67%	—	×0.770	25.16%
BB% (unintentional) /BF	11.22%	—	×1.150	12.90%
HR / BF /BF	3.63%	÷0.881	×1.250	5.15%

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 76).

Result: FIP 3.75 → 5.44, 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 AHickory Crawdads · 69 IPFIP 2.87 → 3.66 (+0.80)K% 23.7% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.70%	—	×0.740	17.54%
BB% (unintentional) /BF	9.74%	—	×1.180	11.49%
HR / BF /BF	0.97%	÷1.183	×1.300	1.07%

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 137).

Result: FIP 2.87 → 3.66, 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).

2018 ROKAZL Rangers · 11 IPFIP 2.91 → 3.94 (+1.02)K% 22.2% → 15.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.22%	—	×0.680	15.11%
BB% (unintentional) /BF	13.33%	—	×1.250	16.67%
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 2.91 → 3.94, 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).

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
Grant Wolfram (OGILVIE)	—	—	3.64	25.4%	8.8%	2.2%	—	4.06	24.0%	14.6%	75	+0.42	—	—	—
Jared Koenig L 2024 · 2.79 FIP	30	SU	2.79	23.8%	7.2%	1.4%	.279	2.99	23.6%	15.9%	86	+0.20	2.79	475	82
Raul Valdes L 2010 · 4.02 FIP	32	SU	4.02	21.4%	9.9%	2.7%	.301	3.14	27.4%	22.5%	78	-0.88	2.29	160	79
Brian Moran L 2019 · 3.40 FIP	30	SU	3.40	26.9%	10.0%	2.4%	.269	2.99	25.5%	18.5%	99	-0.41	1.80	421	78
Matt Thornton L 2007 · 3.13 FIP	30	SU	3.13	22.1%	8.0%	1.6%	.324	2.19	30.7%	24.4%	200	-0.94	1.71	663	76
Hideki Okajima L 2007 · 3.05 FIP	31	SU	3.05	23.2%	5.5%	2.2%	.234	3.87	20.2%	12.6%	169	+0.82	3.05	238	75
Scott Sauerbeck L 2002 · 2.79 FIP	30	SU	2.79	27.5%	9.0%	1.6%	.291	4.27	20.4%	8.0%	92	+1.48	2.79	386	75
Nick Hagadone L 2015 · 3.65 FIP	29	SU	3.65	22.6%	8.9%	2.4%	.329	3.74	22.6%	13.3%	33	+0.09	2.97	141	74
Daniel Rodriguez L 2015 · 2.89 FIP	30	SU	2.89	20.2%	9.4%	0.6%	.256	4.17	16.3%	5.9%	234	+1.28	2.89	391	74
Kyle Regnault L 2018 · 3.82 FIP	29	SU	3.82	27.6%	9.7%	3.3%	.367	—	—	—	—	—	2.88	204	73
Doug Slaten L 2010 · 3.22 FIP	30	SU	3.22	20.7%	9.8%	1.1%	.269	4.85	13.5%	3.1%	29	+1.63	3.22	139	73
Pedro Feliciano L 2007 · 3.07 FIP	30	SU	3.07	22.2%	9.8%	1.1%	.239	3.28	21.8%	14.5%	175	+0.21	2.69	378	72
Ryan Buchter L 2017 · 4.45 FIP	30	SU	4.45	24.3%	9.3%	4.0%	.202	4.19	25.3%	15.6%	85	-0.26	2.37	296	72
Brian Fuentes L 2006 · 3.47 FIP	30	SU	3.47	26.6%	8.0%	2.9%	.246	3.22	24.6%	15.8%	179	-0.25	2.08	602	72
George Sherrill L 2007 · 2.82 FIP	30	SU	2.82	30.8%	8.8%	2.2%	.226	3.61	20.7%	11.3%	159	+0.79	2.74	323	72
Clay Rapada L 2011 · 4.34 FIP	30	SU	4.34	26.1%	10.1%	3.9%	.268	3.00	24.5%	14.2%	38	-1.34	3.00	120	72
Jason Christiansen L 2000 · 3.08 FIP	30	SU	3.08	25.2%	10.5%	1.4%	.288	4.28	20.1%	10.6%	62	+1.20	2.22	429	71
Andrew Barbosa L 2017 · 4.67 FIP	29	SU	4.67	20.2%	9.6%	3.8%	.301	—	—	—	—	—	2.70	175	71
Cory Luebke L 2016 · 3.88 FIP	31	SU	3.88	26.4%	9.1%	3.4%	.354	—	—	—	—	—	2.80	216	71
Jorge Ibarra L 2017 · 3.09 FIP	29	SU	3.09	19.3%	6.5%	1.4%	.351	—	—	—	—	—	2.55	146	70
Sammy Solís L 2019 · 4.05 FIP	30	SU	4.05	26.2%	8.9%	3.7%	.291	—	—	—	—	—	2.51	190	70

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	1.0	41	25.0%	8.9%	0.78	4.22
David Carpenter ('19)	1.1	43	23.5%	8.4%	0.92	3.69
Ed Vosberg ('86-'02, 1 WAR*)	1.2	47	21.0%*	9.6%*	0.86*	4.06*
Danny Farquhar ('18)	1.4	54	26.9%	9.2%	0.99	3.93
Josh Fields ('18)	1.4	46	27.5%	8.0%	0.98	3.71
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*
Dave Geisel ('78-'85, 2 WAR*)	1.0	42	23.5%*	10.6%*	0.84*	4.12*