Hunter Hayes

P Springfield Cardinals

Age 26 RHP 6'1" / 185 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	MIX3 levels	29	58	2.93	2.48	23.9%	7.4%	—	K 17.8% · BB 8.7% · FIP 3.34
2025	24	MIX2 levels	36	64	4.78	3.48	23.1%	10.7%	—	K 18.0% · BB 12.2% · FIP 4.50
2026	25	AASTL	28	39	6.64	5.67	15.2%	16.2%	—	K 12.3% · BB 17.9% · FIP 5.99
2027PROJ	26	MLBSTL	1	1	5.87	5.87	14.1%	15.7%	-0.0
2028PROJ38% MLB	27	MLBSTL	15	16	5.74	5.75	15.0%	15.1%	-0.2
2029PROJ60% MLB	28	MLBSTL	20	21	5.69	5.73	15.5%	14.8%	-0.3

Next 3 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control40Command40

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsJeff Soptic (age 25) · Julian Arballo (age 27) · Trey Haley (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 145137vR 128

ERA5.87

FIP5.87

K%14.1%

BB%15.7%

K-BB%-1.6%

Proj IP60

Value2027 · WAR

Runs saved vs league avg · 60 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL4040

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)
2022	21	ROK MLE	FCL Cardinals	2	1	2	9	2	1	0	50%	1.0	22.2%	11.1%	11.1%	0.0%	9.00	2.63	—
2022	21	ROK RAW	FCL Cardinals	2	1	2	9	2	1	0	50%	1.0	22.2%	11.1%	11.1%	0.0%	9.00	2.60	—
2023	22	A MLE	Palm Beach Cardinals	20	5	61	267	48	22	5	25%	3.0	13.3%	9.7%	3.6%	2.4%	3.69	4.53	—
2023	22	A RAW	Palm Beach Cardinals	20	5	61	267	48	22	5	25%	3.0	18.0%	8.2%	9.7%	1.9%	3.69	3.67	—
2024	23	MIX MLE	3 levels	29	0	58	243	58	18	2	0%	2.0	17.8%	8.7%	9.1%	1.2%	2.93	3.34	—
2024	23	MIX MLE	3 levels	29	0	58	243	58	18	2	0%	2.0	17.8%	8.7%	9.1%	1.2%	2.93	3.34	—
2024	23	MIX RAW	3 levels	29	0	58	243	58	18	2	0%	2.0	23.9%	7.4%	16.5%	0.8%	2.93	2.48	—
2025	24	MIX MLE	2 levels	36	0	64	290	67	31	5	0%	1.8	18.0%	12.2%	5.8%	2.5%	4.78	4.50	—
2025	24	MIX MLE	2 levels	36	0	64	290	67	31	5	0%	1.8	18.0%	12.2%	5.8%	2.5%	4.78	4.50	—
2025	24	MIX RAW	2 levels	36	0	64	290	67	31	5	0%	1.8	23.1%	10.7%	12.4%	1.7%	4.78	3.48	—
2026	25	AA MLE	Springfield Cardinals	28	0	39	197	30	32	5	0%	1.4	12.3%	17.9%	-5.5%	3.0%	6.64	5.99	—
2026	25	AA MLE	Springfield Cardinals	28	0	39	197	30	32	5	0%	1.4	12.3%	17.9%	-5.5%	3.0%	6.64	5.99	—
2026	25	AA RAW	Springfield Cardinals	28	0	39	197	30	32	5	0%	1.4	15.2%	16.2%	-1.0%	2.5%	6.64	5.67	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	STL	1	0	1	4	1	1	0	0%	1.0	14.1%	15.7%	-1.6%	2.9%	5.87	5.87	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	STL	40	0	42	177	27	27	5	0%	1.1	15.0%	15.1%	-0.1%	3.0%	5.74	5.75	-0.6
2029	28	MLB MLE	STL	33	0	35	148	23	22	5	0%	1.1	15.5%	14.8%	0.7%	3.1%	5.69	5.73	-0.5
2028	27	MLB CTX	STL	15	0	16	68	10	10	2	0%	1.1	15.0%	15.1%	-0.1%	3.0%	5.74	5.75	-0.2
2029	28	MLB CTX	STL	20	0	21	89	14	13	3	0%	1.1	15.5%	14.8%	0.7%	3.1%	5.69	5.73	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		35	0	37	155	24	23	5	0%	1.0	15.3%	14.9%	0.3%	3.0%	5.71	5.36	-0.3
/ 200 IP	—	RAW		190	0	200	844	131	126	27	0%	1.1	15.3%	14.9%	0.3%	3.0%	5.71	5.36	-1.9
Career	—	MLE		115	6	225	1006	157	119	23	5%	2.0	15.7%	11.8%	3.9%	2.2%	4.37	4.50	-1.1
/ 200 IP	—	MLE		102	5	200	896	140	106	20	5%	2.0	15.7%	11.8%	3.9%	2.2%	4.37	4.50	-2.7

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 AASpringfield Cardinals · 39 IPFIP 5.26 → 5.99 (+0.73)K% 15.2% → 12.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.23%	—	×0.810	12.34%
BB% (unintentional) /BF	16.24%	—	×1.100	17.87%
HR / BF /BF	2.54%	÷1.000	×1.200	3.05%

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 5.26 → 5.99, 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+Peoria Chiefs · 48 IPFIP 3.91 → 5.13 (+1.22)K% 22.3% → 17.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.27%	—	×0.770	17.15%
BB% (unintentional) /BF	11.36%	—	×1.150	13.07%
HR / BF /BF	2.27%	÷0.857	×1.250	3.31%

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 71).

Result: FIP 3.91 → 5.13, 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 AASpringfield Cardinals · 16 IPFIP 2.01 → 2.54 (+0.52)K% 25.7% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.71%	—	×0.810	20.83%
BB% (unintentional) /BF	8.57%	—	×1.100	9.43%
HR / BF /BF	0.00%	÷1.105	×1.200	0.00%

Result: FIP 2.01 → 2.54, 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 APalm Beach Cardinals · 36 IPFIP 2.54 → 3.27 (+0.73)K% 21.5% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.53%	—	×0.740	15.93%
BB% (unintentional) /BF	6.94%	—	×1.180	8.19%
HR / BF /BF	0.69%	÷1.036	×1.300	0.87%

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 107).

Result: FIP 2.54 → 3.27, 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+Peoria Chiefs · 16 IPFIP 2.56 → 3.47 (+0.91)K% 28.2% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.17%	—	×0.770	21.69%
BB% (unintentional) /BF	8.45%	—	×1.150	9.72%
HR / BF /BF	1.41%	÷0.993	×1.250	1.77%

Result: FIP 2.56 → 3.47, 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 ROKFCL Cardinals · 7 IPFIP 1.89 → 2.80 (+0.90)K% 25.0% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.680	17.00%
BB% (unintentional) /BF	7.14%	—	×1.250	8.93%
HR / BF /BF	0.00%	÷0.975	×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 95).

Result: FIP 1.89 → 2.80, 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 APalm Beach Cardinals · 61 IPFIP 3.65 → 4.53 (+0.88)K% 18.0% → 13.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.98%	—	×0.740	13.30%
BB% (unintentional) /BF	8.24%	—	×1.180	9.72%
HR / BF /BF	1.87%	÷1.010	×1.300	2.41%

Result: FIP 3.65 → 4.53, 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
Hunter Hayes (OGILVIE)	—	—	5.87	14.1%	15.7%	2.9%	—	5.74	15.2%	0.3%	77	-0.13	—	—	—
Jeff Soptic R 2016 · 5.52 FIP	25	SU	5.52	13.6%	15.3%	3.0%	.326	—	—	—	—	—	5.30	124	86
Julian Arballo R 2015 · 5.13 FIP	27	SU	5.13	15.1%	13.8%	2.8%	.335	4.46	12.6%	0.6%	116	-0.67	4.45	214	86
Trey Haley R 2016 · 4.98 FIP	26	SU	4.98	14.0%	16.5%	1.8%	.282	—	—	—	—	—	3.14	111	86
Mike Hepple R 2016 · 5.75 FIP	26	SU	5.75	11.1%	18.5%	2.3%	.271	—	—	—	—	—	4.46	116	85
Roman Phansalkar R 2024 · 5.39 FIP	26	SU	5.39	15.8%	13.2%	3.6%	.294	4.33	18.2%	3.7%	31	-1.06	4.33	164	84
Justin Courtney R 2022 · 5.11 FIP	26	SU	5.11	16.8%	12.8%	3.3%	.331	8.63	18.4%	7.1%	21	+3.52	4.58	108	81
Mark Peterson R 2017 · 4.78 FIP	26	SU	4.78	13.7%	11.9%	2.4%	.349	—	—	—	—	—	4.65	185	81
Clate Schmidt R 2019 · 5.66 FIP	25	SU	5.66	13.5%	13.9%	3.5%	.290	—	—	—	—	—	3.51	160	81
Jeremy Guthrie R 2006 · 4.92 FIP	27	SU	4.92	15.1%	15.1%	2.1%	.349	4.57	14.8%	8.1%	566	-0.35	4.08	1,834	81
Rob Huber R 2016 · 4.73 FIP	24	SU	4.73	15.7%	14.7%	2.0%	.333	—	—	—	—	—	3.90	117	81
Tyler Burch R 2023 · 4.92 FIP	25	SU	4.92	15.0%	12.6%	2.7%	.285	—	—	—	—	—	4.56	119	81
Ricky Salinas R 2022 · 5.79 FIP	26	SU	5.79	14.3%	15.1%	3.6%	.286	—	—	—	—	—	4.77	274	81
Luis García R 2013 · 4.92 FIP	26	SU	4.92	16.7%	16.7%	2.0%	.270	3.68	20.3%	9.3%	151	-1.24	2.33	662	81
Haden Erbe R 2024 · 5.28 FIP	25	SU	5.28	18.4%	16.5%	3.0%	.320	5.19	17.8%	0.5%	40	-0.09	5.19	116	80
Stephen Johnson R 2016 · 5.15 FIP	25	SU	5.15	16.7%	12.7%	3.4%	.268	—	—	—	—	—	3.12	141	80
Kevin Gryboski R 2002 · 5.02 FIP	28	SU	5.02	13.9%	13.4%	2.5%	.263	3.83	12.0%	2.9%	126	-1.19	3.67	178	80
Kender Villegas R 2017 · 4.70 FIP	24	SU	4.70	13.3%	13.3%	1.9%	.269	—	—	—	—	—	3.26	131	80
Jesús Reyes R 2019 · 5.71 FIP	26	SU	5.71	15.9%	15.7%	3.6%	.283	5.11	17.5%	5.6%	118	-0.60	3.85	554	80
David Holman R 2017 · 5.53 FIP	27	SU	5.53	15.6%	12.7%	3.9%	.324	5.45	9.6%	0.5%	107	-0.08	5.28	129	79
Jake Gozzo R 2023 · 5.04 FIP	26	SU	5.04	16.2%	17.6%	2.0%	.227	4.32	15.6%	-1.3%	32	-0.72	4.32	162	79

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	0.7	46	14.7%	15.3%	1.15	5.78
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Matt Anderson ('05)	1.3	51	19.3%	13.5%	1.05	5.19
Doug Bochtler ('00)	1.3	65	18.6%	14.4%	1.25	4.57
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*