Ryan Hawks

P Arkansas Travelers

Age 26 RHP 6'2" / 235 lbs AA peak 0.1 · 2028

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	24	A+SEA	22	21	116	3.79	3.95	18.1%	7.2%	—	K 13.9% · BB 8.2% · FIP 4.78
2026	25	AASEA	24	22	105	6.36	4.90	16.4%	9.5%	—	K 13.2% · BB 10.5% · FIP 5.49
2027PROJ	26	MLBSEA	1	1	2	5.65	5.65	11.9%	10.3%	-0.0
2028PROJ38% MLB	27	MLBSEA	5	5	29	5.53	5.54	12.9%	10.1%	-0.0
2029PROJ60% MLB	28	MLBSEA	6	6	39	5.49	5.53	13.5%	10.1%	-0.1

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

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control50Command40

Career WAR0.0 WAR median (P10 -0.1 / P90 0.0, comp-based) · star 0% · didn't stick 98%

CompsJordan Cooper (age 26) · Josh Banks (age 26) · Wes Obermueller (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 140132vR 124

ERA5.65

FIP5.65

K%11.9%

BB%10.3%

K-BB%1.6%

Proj IP77

Value2027 · WAR

Runs saved vs league avg · 77 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL5050

CMD4040

K†3030

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)
2023	22	MIX MLE	2 levels	6	6	13	54	14	5	0	100%	2.2	25.9%	9.3%	16.7%	0.0%	2.77	2.08	—
2023	22	MIX RAW	2 levels	6	6	13	54	14	5	0	100%	2.2	25.9%	9.3%	16.7%	0.0%	2.77	2.10	—
2024	23	A+ MLE	Everett AquaSox	25	25	121	537	95	34	22	100%	4.8	13.6%	7.3%	6.3%	4.4%	5.59	5.26	—
2024	23	A+ MLE	Everett AquaSox	25	25	121	537	95	34	22	100%	4.8	13.6%	7.3%	6.3%	4.4%	5.59	5.26	—
2024	23	A+ RAW	Everett AquaSox	25	25	121	537	95	34	22	100%	4.8	17.7%	6.3%	11.4%	4.1%	5.59	4.74	—
2025	24	A+ MLE	Everett AquaSox	22	21	116	475	86	34	13	95%	5.3	13.9%	8.2%	5.7%	3.3%	3.79	4.78	—
2025	24	A+ MLE	Everett AquaSox	22	21	116	475	86	34	13	95%	5.3	13.9%	8.2%	5.7%	3.3%	3.79	4.78	—
2025	24	A+ RAW	Everett AquaSox	22	21	116	475	86	34	13	95%	5.3	18.1%	7.2%	10.9%	2.7%	3.79	3.95	—
2026	25	AA MLE	Arkansas Travelers	24	22	105	483	79	46	16	92%	4.4	13.2%	10.5%	2.8%	4.0%	6.36	5.49	—
2026	25	AA MLE	Arkansas Travelers	24	22	105	483	79	46	16	92%	4.4	13.2%	10.5%	2.8%	4.0%	6.36	5.49	—
2026	25	AA RAW	Arkansas Travelers	24	22	105	483	79	46	16	92%	4.4	16.4%	9.5%	6.8%	3.3%	6.36	4.90	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	SEA	1	1	2	8	1	1	0	100%	2.0	11.9%	10.3%	1.6%	3.4%	5.65	5.65	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	SEA	13	13	76	323	42	33	11	100%	5.9	12.9%	10.1%	2.8%	3.4%	5.53	5.54	-0.1
2029	28	MLB MLE	SEA	11	11	66	277	37	28	10	100%	6.0	13.5%	10.1%	3.4%	3.5%	5.49	5.53	-0.1
2030	29	MLB MLE	SEA	10	10	59	250	34	26	9	100%	5.9	13.7%	10.2%	3.5%	3.6%	5.53	5.60	-0.1
2031	30	MLB MLE	SEA	9	9	54	226	31	24	9	100%	6.0	13.5%	10.4%	3.1%	3.8%	5.64	5.74	-0.2
2028	27	MLB CTX	SEA	5	5	29	122	16	12	4	100%	5.8	12.9%	10.1%	2.8%	3.4%	5.53	5.54	-0.0
2029	28	MLB CTX	SEA	6	6	39	165	22	17	6	100%	6.5	13.5%	10.1%	3.4%	3.5%	5.49	5.53	-0.1
2030	29	MLB CTX	SEA	7	7	42	177	24	18	6	100%	6.0	13.7%	10.2%	3.5%	3.6%	5.53	5.60	-0.1
2031	30	MLB CTX	SEA	7	7	42	177	24	18	7	100%	6.0	13.5%	10.4%	3.1%	3.8%	5.64	5.74	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		25	25	152	641	86	65	23	100%	6.1	13.4%	10.2%	3.2%	3.6%	5.55	5.23	+0.3
/ 200 IP	—	RAW		33	33	200	844	113	86	30	100%	6.0	13.4%	10.2%	3.2%	3.6%	5.55	5.23	+0.4
Career	—	MLE		77	74	355	1549	217	134	58	96%	4.6	14.0%	8.6%	5.4%	3.8%	5.13	5.07	-0.6
/ 200 IP	—	MLE		43	42	200	873	123	75	33	96%	4.6	14.0%	8.6%	5.4%	3.8%	5.13	5.07	-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.

2026 AAArkansas Travelers · 105 IPFIP 4.74 → 5.49 (+0.75)K% 16.4% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.36%	—	×0.810	13.25%
BB% (unintentional) /BF	9.52%	—	×1.100	10.48%
HR / BF /BF	3.31%	÷1.000	×1.200	3.98%

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 4.74 → 5.49, 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).

2025 A+Everett AquaSox · 116 IPFIP 3.98 → 4.78 (+0.80)K% 18.1% → 13.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.11%	—	×0.770	13.94%
BB% (unintentional) /BF	7.16%	—	×1.150	8.23%
HR / BF /BF	2.74%	÷1.036	×1.250	3.30%

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 107).

Result: FIP 3.98 → 4.78, 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).

2024 A+Everett AquaSox · 121 IPFIP 4.66 → 5.26 (+0.61)K% 17.7% → 13.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.69%	—	×0.770	13.62%
BB% (unintentional) /BF	6.33%	—	×1.150	7.28%
HR / BF /BF	4.10%	÷1.175	×1.250	4.36%

Result: FIP 4.66 → 5.26, 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 · 10 IPFIP 2.24 → 3.09 (+0.86)K% 27.3% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.27%	—	×0.740	20.18%
BB% (unintentional) /BF	11.36%	—	×1.180	13.41%
HR / BF /BF	0.00%	÷0.883	×1.300	0.00%

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 2.24 → 3.09, 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
Ryan Hawks (OGILVIE)	—	—	5.65	11.9%	10.3%	3.4%	—	5.55	13.3%	3.2%	201	-0.10	—	—	—
Jordan Cooper R 2015 · 5.01 FIP	26	SP	5.01	9.2%	10.2%	2.5%	.305	—	—	—	—	—	5.01	106	86
Josh Banks R 2008 · 4.81 FIP	26	SP-	4.81	11.6%	7.3%	3.2%	.283	6.01	9.0%	6.0%	23	+1.20	4.81	108	84
Wes Obermueller R 2003 · 4.93 FIP	26	SP	4.93	11.2%	7.6%	3.3%	.301	4.77	11.1%	2.0%	183	-0.16	4.72	308	81
Paul Rigdon R 2001 · 5.34 FIP	25	SP	5.34	13.6%	11.1%	3.6%	.283	—	—	—	—	—	5.29	167	81
Nestor Molina R 2016 · 4.83 FIP	27	SP	4.83	15.0%	8.0%	3.6%	.304	3.61	17.0%	10.2%	289	-1.22	3.01	401	80
J.D. Martin R 2009 · 5.18 FIP	26	SP	5.18	10.9%	5.9%	4.1%	.263	4.79	14.6%	9.9%	48	-0.39	4.79	414	80
Caleb Clay R 2015 · 4.67 FIP	27	SP	4.67	9.9%	6.9%	2.8%	.324	—	—	—	—	—	4.67	111	80
Andrew Quezada R 2023 · 5.33 FIP	26	SP-	5.33	14.4%	9.5%	4.1%	.344	4.90	12.7%	5.3%	173	-0.43	4.40	412	80
Travis Smith R 2002 · 5.28 FIP	29	SP	5.28	13.1%	8.2%	4.1%	.324	5.71	15.0%	9.0%	51	+0.43	3.67	105	79
Hiram Burgos R 2013 · 4.89 FIP	25	SP	4.89	12.9%	7.9%	3.4%	.314	3.73	18.0%	8.7%	293	-1.16	3.40	384	79
Nick Belzer R 2021 · 4.51 FIP	25	SP	4.51	12.8%	8.6%	2.6%	.276	—	—	—	—	—	4.23	112	78
M.D. Johnson R 2023 · 5.64 FIP	26	SP	5.64	16.4%	12.7%	4.2%	.254	3.52	14.6%	4.7%	67	-2.12	3.52	395	78
Scarlyn Reyes R 2016 · 4.52 FIP	26	SP	4.52	13.9%	11.9%	2.0%	.321	4.87	13.7%	5.3%	70	+0.35	4.16	317	78
Enrique Gonzalez R 2006 · 4.49 FIP	24	SP-	4.49	14.3%	7.4%	3.0%	.287	—	—	—	—	—	4.49	132	78
Darrell Rasner R 2007 · 5.15 FIP	26	SP	5.15	9.9%	7.2%	3.6%	.284	4.43	13.1%	5.7%	113	-0.72	4.07	158	78
Jake Bockenstedt R 2024 · 6.05 FIP	24	SP	6.05	17.0%	13.1%	5.0%	.322	4.35	16.8%	5.4%	126	-1.70	3.74	218	77
Thomas Farr R 2024 · 5.38 FIP	25	SP	5.38	12.6%	9.3%	4.0%	.295	5.61	10.6%	1.2%	83	+0.23	5.05	423	77
Tyler Carpenter R 2017 · 4.88 FIP	25	SP	4.88	11.0%	6.7%	3.4%	.287	4.10	13.8%	6.3%	49	-0.78	3.68	296	77
Justin Miller R 2004 · 5.41 FIP	26	SP-	5.41	12.5%	10.4%	3.7%	.316	2.63	28.6%	21.7%	62	-2.78	2.63	373	76
Drew Rucinski R 2015 · 5.52 FIP	26	SP	5.52	15.0%	9.1%	4.6%	.336	3.58	16.8%	10.9%	278	-1.94	2.69	409	76

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	1.7	66	13.0%	10.2%	1.36	5.57
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Mike Lincoln ('10)	1.9	54	14.1%	8.9%	1.32	5.33
Luther Hackman ('03)	1.1	71	13.3%	10.9%	1.10	5.09
Russ Swan ('89-'94, -2 WAR*)	1.3	89	12.3%*	9.9%*	1.13*	5.09*
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*