Holden Laws

P Everett AquaSox

Age 27 LHP 6'2" / 205 lbs A+

Overview

A+PROSPECT

MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	22	MIX2 levels	24	0	34	4.24	4.22	26.6%	12.0%	—	K 19.0% · BB 14.6% · FIP 5.98
2023	23	AModesto Nuts	36	0	52	5.19	2.56	27.6%	5.4%	—	K 20.4% · BB 6.4% · FIP 3.88
2024	24	A+SEA	42	0	47	3.66	4.09	17.3%	10.5%	—	K 13.3% · BB 12.0% · FIP 4.72
2025	25	No MLB games played
2026	26	No MLB games played
2027PROJ	27	MLBSEA	—	—	0	4.68	4.68	20.6%	10.3%	—
2028PROJ37% MLB	28	MLBSEA	8	0	8	4.70	4.73	20.8%	10.4%	-0.0

Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsColton Johnson (age 26) · Mitchell Tyranski (age 26) · Doug Slaten (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 106114vR 122

ERA4.68

FIP4.68

K%20.6%

BB%10.3%

K-BB%10.3%

Proj IP28

Value2027 · WAR

Runs saved vs league avg · 28 IP

Grades · Contract

Scouting Grades

K†5050

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	18	ROK MLE	AZL Mariners	9	5	11	51	9	1	2	56%	1.3	12.0%	2.5%	9.5%	5.5%	4.76	5.41	—
2018	18	ROK RAW	AZL Mariners	9	5	11	51	9	1	2	56%	1.3	17.6%	2.0%	15.7%	3.9%	4.76	4.07	—
2019	19	ROK MLE	AZL Mariners	11	6	26	115	30	5	1	55%	2.4	17.7%	5.4%	12.3%	1.2%	5.54	2.96	—
2019	19	ROK RAW	AZL Mariners	11	6	26	115	30	5	1	55%	2.4	26.1%	4.3%	21.7%	0.9%	5.54	1.87	—
2021	21	MIX MLE	3 levels	11	5	28	127	30	13	5	45%	2.6	19.3%	15.6%	3.7%	5.3%	5.08	6.35	—
2021	21	MIX RAW	3 levels	11	5	28	127	30	13	5	45%	2.6	23.6%	10.2%	13.4%	3.9%	5.08	4.65	—
2022	22	MIX MLE	2 levels	24	0	34	158	42	19	5	0%	1.4	19.0%	14.6%	4.4%	4.8%	4.24	5.98	—
2022	22	MIX RAW	2 levels	24	0	34	158	42	19	5	0%	1.4	26.6%	12.0%	14.6%	3.2%	4.24	4.22	—
2023	23	A MLE	Modesto Nuts	36	0	52	239	66	13	5	0%	1.4	20.4%	6.4%	14.0%	3.1%	5.19	3.88	—
2023	23	A RAW	Modesto Nuts	36	0	52	239	66	13	5	0%	1.4	27.6%	5.4%	22.2%	2.1%	5.19	2.56	—
2024	24	A+ MLE	Everett AquaSox	42	0	47	191	33	20	4	0%	1.1	13.3%	12.0%	1.3%	2.2%	3.66	4.72	—
2024	24	A+ MLE	Everett AquaSox	42	0	47	191	33	20	4	0%	1.1	13.3%	12.0%	1.3%	2.2%	3.66	4.72	—
2024	24	A+ RAW	Everett AquaSox	42	0	47	191	33	20	4	0%	1.1	17.3%	10.5%	6.8%	2.1%	3.66	4.09	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	SEA	—	—	0	—	—	—	—	—	—	20.6%	10.3%	10.3%	3.0%	4.68	4.68	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	SEA	21	0	22	95	20	10	3	0%	1.1	20.8%	10.4%	10.4%	3.1%	4.70	4.73	-0.0
2028	28	MLB CTX	SEA	8	0	8	34	7	4	1	0%	1.0	20.8%	10.4%	10.4%	3.1%	4.70	4.73	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		8	0	8	35	7	4	1	0%	1.0	20.8%	10.4%	10.4%	3.1%	4.70	4.35	+0.0
/ 200 IP	—	RAW		190	0	200	844	171	97	24	0%	1.1	20.8%	10.4%	10.4%	3.1%	4.70	4.35	+0.5
Career	—	MLE		133	16	198	881	155	89	30	12%	1.5	17.6%	10.1%	7.6%	3.4%	4.67	4.76	-0.0
/ 200 IP	—	MLE		134	16	200	888	157	89	30	12%	1.5	17.6%	10.1%	7.6%	3.4%	4.67	4.76	-0.4

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.

2024 A+Everett AquaSox · 47 IPFIP 4.12 → 4.72 (+0.61)K% 17.3% → 13.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.28%	—	×0.770	13.30%
BB% (unintentional) /BF	10.47%	—	×1.150	12.04%
HR / BF /BF	2.09%	÷1.175	×1.250	2.23%

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 135).

Result: FIP 4.12 → 4.72, 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 AModesto Nuts · 52 IPFIP 2.61 → 3.88 (+1.27)K% 27.6% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.62%	—	×0.740	20.44%
BB% (unintentional) /BF	5.44%	—	×1.180	6.42%
HR / BF /BF	2.09%	÷0.883	×1.300	3.08%

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 77).

Result: FIP 2.61 → 3.88, 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 AModesto Nuts · 20 IPFIP 5.17 → 7.56 (+2.40)K% 27.2% → 20.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.17%	—	×0.740	20.11%
BB% (unintentional) /BF	10.87%	—	×1.180	12.83%
HR / BF /BF	5.43%	÷0.855	×1.300	8.27%

Result: FIP 5.17 → 7.56, 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 ROKACL Mariners · 14 IPFIP 2.65 → 3.78 (+1.13)K% 25.8% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.76%	—	×0.680	17.52%
BB% (unintentional) /BF	13.64%	—	×1.250	17.05%
HR / BF /BF	0.00%	÷1.033	×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 107).

Result: FIP 2.65 → 3.78, 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 ROKACL Mariners · 20 IPFIP 4.16 → 6.35 (+2.19)K% 28.4% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.41%	—	×0.680	19.32%
BB% (unintentional) /BF	12.50%	—	×1.250	15.62%
HR / BF /BF	3.41%	÷0.904	×1.400	5.28%

Result: FIP 4.16 → 6.35, 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 AAArkansas Travelers · 6 IPFIP 4.99 → 5.90 (+0.91)K% 10.3% → 8.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	10.34%	—	×0.810	8.38%
BB% (unintentional) /BF	6.90%	—	×1.100	7.59%
HR / BF /BF	3.45%	÷0.892	×1.200	4.64%

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 78).

Result: FIP 4.99 → 5.90, 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 ROKAZL Mariners · 26 IPFIP 1.93 → 2.96 (+1.03)K% 26.1% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.09%	—	×0.680	17.74%
BB% (unintentional) /BF	4.35%	—	×1.250	5.43%
HR / BF /BF	0.87%	÷1.000	×1.400	1.22%

Result: FIP 1.93 → 2.96, 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 Mariners · 11 IPFIP 4.01 → 5.41 (+1.40)K% 17.6% → 12.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.65%	—	×0.680	12.00%
BB% (unintentional) /BF	1.96%	—	×1.250	2.45%
HR / BF /BF	3.92%	÷1.000	×1.400	5.49%

Result: FIP 4.01 → 5.41, 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
Holden Laws (OGILVIE)	—	—	4.68	20.6%	10.3%	3.0%	—	4.73	20.8%	10.4%	22	+0.05	—	—	—
Colton Johnson L 2024 · 3.92 FIP	26	SU	3.92	20.8%	11.0%	2.1%	.309	4.53	12.2%	-0.4%	48	+0.61	3.92	106	85
Mitchell Tyranski L 2024 · 4.90 FIP	26	SU	4.90	21.0%	12.3%	3.7%	.234	3.46	20.5%	4.0%	57	-1.44	3.46	145	82
Doug Slaten L 2007 · 4.08 FIP	27	SU	4.08	17.2%	8.6%	2.5%	.316	3.81	17.6%	8.2%	73	-0.27	3.22	139	82
Juan Grullon L 2016 · 4.64 FIP	26	SU	4.64	19.8%	10.9%	3.3%	.305	—	—	—	—	—	4.64	134	82
Jeff Ibarra L 2016 · 3.75 FIP	28	SU	3.75	17.8%	9.7%	1.7%	.321	3.29	19.2%	13.8%	66	-0.46	2.85	101	81
Ryan Verdugo L 2015 · 3.61 FIP	28	SU	3.61	19.8%	10.8%	1.5%	.281	3.36	22.7%	17.3%	82	-0.25	3.36	153	81
George Sherrill L 2004 · 4.36 FIP	27	SU	4.36	15.4%	7.7%	2.9%	.273	2.90	28.3%	18.2%	105	-1.46	2.74	323	81
Haylen Green L 2023 · 4.09 FIP	25	SU	4.09	18.6%	10.8%	2.2%	.317	—	—	—	—	—	4.02	104	80
Bryan Harper L 2016 · 4.13 FIP	26	SU	4.13	19.3%	9.6%	2.6%	.197	4.63	14.9%	1.0%	46	+0.50	4.13	133	80
Jeremy Horst L 2013 · 4.46 FIP	27	SU	4.46	17.1%	8.9%	3.0%	.356	3.92	17.2%	5.4%	108	-0.54	2.12	181	80
David Rollins L 2017 · 5.58 FIP	27	SU	5.58	18.0%	12.1%	4.5%	.260	5.68	15.9%	12.5%	20	+0.10	3.59	132	80
Adam Liberatore L 2015 · 3.64 FIP	28	SU	3.64	21.1%	7.3%	2.5%	.267	3.17	23.3%	15.2%	73	-0.47	2.38	124	79
Will Gilbert L 2019 · 4.42 FIP	25	SU	4.42	19.9%	10.3%	3.1%	.306	—	—	—	—	—	2.92	141	79
Brendan Nail L 2023 · 4.36 FIP	27	SU	4.36	19.3%	10.5%	2.8%	.262	—	—	—	—	—	3.45	165	79
Kelly Wunsch L 2000 · 3.65 FIP	28	SU	3.65	19.7%	10.8%	1.5%	.261	4.17	17.6%	5.9%	90	+0.52	3.36	175	79
Jackson Lancaster L 2024 · 4.48 FIP	25	SU	4.48	24.0%	11.1%	3.6%	.355	5.36	18.3%	4.9%	93	+0.88	4.15	142	78
Aaron Brown L 2019 · 4.04 FIP	27	SU	4.04	22.9%	13.5%	2.1%	.317	4.77	19.4%	6.7%	129	+0.73	4.04	269	78
Adrian Gusman L 2019 · 4.31 FIP	27	SU	4.31	17.9%	9.7%	2.7%	.273	—	—	—	—	—	2.94	141	78
Brad Kuntz L 2018 · 4.10 FIP	26	SU	4.10	20.9%	11.7%	2.4%	.352	—	—	—	—	—	2.35	197	78
Braulio Lara L 2016 · 4.35 FIP	27	SU	4.35	17.7%	11.0%	2.5%	.289	5.80	19.8%	2.0%	40	+1.45	3.96	118	78

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	0.3	25	20.7%	10.4%	1.17	4.69
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Manny Acosta ('12)	1.2	41	20.5%	10.9%	1.09	3.99
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*