Hayden Wynja

P ACL Giants

Age 28 LHP 6'8" / 232 lbs ROK

Overview

ROKPROSPECT

MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	24	MIX2 levels	29	16	97	4.16	3.51	27.3%	9.0%	—	K 20.5% · BB 10.5% · FIP 4.74
2024	25	A+SF	15	11	56	4.95	3.85	23.3%	9.1%	—	K 18.0% · BB 10.5% · FIP 4.79
2026	27	MIX3 levels	15	2	23	3.52	3.14	30.5%	11.6%	—	K 30.5% · BB 11.6% · FIP 3.14
2027PROJ	28	MLBSF	—	—	0	4.55	4.55	21.6%	9.8%	—
2028PROJ30% MLB	29	MLBSF	9	0	9	4.61	4.66	21.5%	10.0%	-0.0

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

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 0.0 / P90 3.3, comp-based) · star 0% · didn't stick 82%

CompsHector Hernandez (age 28) · Matt Whitehouse (age 28) · Chad Bell (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 103112vR 120

ERA4.55

FIP4.55

K%21.6%

BB%9.8%

K-BB%11.8%

Proj IP39

Value2027 · WAR

Runs saved vs league avg · 39 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)
2022	23	ROK MLE	ACL Giants Orange	3	0	3	16	3	0	1	0%	1.1	18.8%	0.0%	18.8%	6.2%	8.10	4.95	—
2022	23	ROK RAW	ACL Giants Orange	3	0	3	16	3	0	1	0%	1.1	18.8%	0.0%	18.8%	6.2%	8.10	5.20	—
2023	24	MIX MLE	2 levels	29	16	97	422	115	38	12	55%	3.4	20.5%	10.5%	10.0%	3.7%	4.16	4.74	—
2023	24	MIX RAW	2 levels	29	16	97	422	115	38	12	55%	3.4	27.3%	9.0%	18.2%	2.8%	4.16	3.51	—
2024	25	A+ MLE	Eugene Emeralds	15	11	56	253	59	23	7	73%	3.8	18.0%	10.5%	7.5%	3.4%	4.95	4.79	—
2024	25	A+ MLE	Eugene Emeralds	15	11	56	253	59	23	7	73%	3.8	18.0%	10.5%	7.5%	3.4%	4.95	4.79	—
2024	25	A+ RAW	Eugene Emeralds	15	11	56	253	59	23	7	73%	3.8	23.3%	9.1%	14.2%	2.8%	4.95	3.85	—
2026	27	MIX MLE	3 levels	15	2	23	95	29	11	2	13%	1.5	30.5%	11.6%	18.9%	2.1%	3.52	3.14	—
2026	27	MIX MLE	3 levels	15	2	23	95	29	11	2	13%	1.5	30.5%	11.6%	18.9%	2.1%	3.52	3.14	—
2026	27	MIX RAW	3 levels	15	2	23	95	29	11	2	13%	1.5	30.5%	11.6%	18.9%	2.1%	3.52	3.14	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	SF	—	—	0	—	—	—	—	—	—	21.6%	9.8%	11.8%	3.0%	4.55	4.55	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	SF	30	0	31	133	29	13	4	0%	1.0	21.5%	10.0%	11.6%	3.2%	4.61	4.66	-0.0
2028	29	MLB CTX	SF	9	0	9	38	8	4	1	0%	1.0	21.5%	10.0%	11.6%	3.2%	4.61	4.66	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	9	40	9	4	1	0%	1.0	21.5%	10.0%	11.6%	3.2%	4.61	4.28	+0.0
/ 200 IP	—	RAW		190	0	200	844	192	85	21	0%	1.1	21.5%	10.0%	11.6%	3.2%	4.61	4.28	+0.6
Career	—	MLE		62	29	180	786	164	82	27	47%	2.9	20.9%	10.4%	10.5%	3.5%	4.40	4.57	-0.0
/ 200 IP	—	MLE		69	32	200	873	182	91	30	47%	2.9	20.9%	10.4%	10.5%	3.5%	4.40	4.57	-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 ROKACL Giants · 11 IPFIP 4.07 → 6.16 (+2.09)K% 31.2% → 21.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.25%	—	×0.680	21.25%
BB% (unintentional) /BF	10.42%	—	×1.250	13.02%
HR / BF /BF	4.17%	÷1.000	×1.400	5.83%

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 4.07 → 6.16, 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).

2026 ASan Jose Giants · 9 IPFIP 1.61 → 2.65 (+1.04)K% 35.3% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.29%	—	×0.740	26.12%
BB% (unintentional) /BF	11.76%	—	×1.180	13.88%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 1.61 → 2.65, 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+Eugene Emeralds · 56 IPFIP 3.80 → 4.79 (+0.99)K% 23.3% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.32%	—	×0.770	17.96%
BB% (unintentional) /BF	9.09%	—	×1.150	10.45%
HR / BF /BF	2.77%	÷1.010	×1.250	3.43%

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 102).

Result: FIP 3.80 → 4.79, 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 ASan Jose Giants · 54 IPFIP 3.03 → 4.52 (+1.49)K% 29.7% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.69%	—	×0.740	21.97%
BB% (unintentional) /BF	7.86%	—	×1.180	9.28%
HR / BF /BF	2.62%	÷0.890	×1.300	3.83%

Result: FIP 3.03 → 4.52, 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 A+Eugene Emeralds · 43 IPFIP 4.06 → 5.01 (+0.95)K% 24.4% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.35%	—	×0.770	18.75%
BB% (unintentional) /BF	10.36%	—	×1.150	11.92%
HR / BF /BF	3.11%	÷1.076	×1.250	3.61%

Result: FIP 4.06 → 5.01, 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
Hayden Wynja (OGILVIE)	—	—	4.55	21.6%	9.8%	3.0%	—	4.66	21.5%	11.6%	31	+0.11	—	—	—
Hector Hernandez L 2019 · 3.39 FIP	28	SW	3.39	20.2%	9.0%	1.5%	.290	—	—	—	—	—	2.17	121	77
Matt Whitehouse L 2019 · 4.07 FIP	28	SW	4.07	20.1%	10.9%	2.3%	.339	—	—	—	—	—	3.37	353	76
Chad Bell L 2017 · 4.57 FIP	28	SW	4.57	19.4%	8.9%	3.6%	.341	4.38	18.8%	11.4%	57	-0.19	3.39	393	76
John Rheinecker L 2007 · 5.13 FIP	28	SW	5.13	16.7%	10.9%	3.8%	.317	—	—	—	—	—	4.14	121	74
Tommy Phelps L 2003 · 3.39 FIP	29	SW	3.39	15.6%	8.0%	1.1%	.322	4.47	16.9%	8.9%	57	+1.08	3.39	120	73
Randy Keisler L 2005 · 5.07 FIP	29	SW	5.07	16.4%	9.9%	3.8%	.295	5.51	6.5%	0.0%	17	+0.44	5.07	135	70
Austin Warner L 2022 · 4.78 FIP	28	SW	4.78	16.9%	9.0%	3.6%	.319	—	—	—	—	—	3.81	491	69
Edgar Olmos L 2017 · 3.64 FIP	27	SW	3.64	18.9%	9.7%	1.7%	.252	—	—	—	—	—	3.19	203	69
Tommy Vail L 2024 · 3.65 FIP	25	SW	3.65	27.5%	15.3%	1.7%	.237	5.19	19.5%	2.9%	99	+1.54	3.65	168	68
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	68
Kyle Hunter L 2017 · 4.50 FIP	28	SU	4.50	14.0%	6.1%	3.3%	.335	—	—	—	—	—	4.32	188	67
Chris Reed L 2016 · 4.67 FIP	26	SW	4.67	16.4%	9.8%	3.1%	.238	—	—	—	—	—	4.67	137	67
Everett Teaford L 2012 · 5.47 FIP	28	SW	5.47	13.3%	8.0%	4.5%	.291	4.42	13.9%	6.3%	103	-1.05	4.42	208	66
Andy Otero L 2021 · 3.89 FIP	29	SP-	3.89	24.7%	6.2%	3.8%	.298	4.36	14.5%	5.6%	68	+0.47	2.86	200	66
Tyler Alexander L 2019 · 5.56 FIP	27	SP-	5.56	21.7%	9.8%	5.6%	.289	5.27	15.7%	5.0%	26	-0.29	5.27	128	66
Yohan Flande L 2014 · 3.65 FIP	28	SP-	3.65	14.1%	5.8%	1.8%	.266	3.90	14.1%	7.9%	312	+0.25	3.18	394	65
T.J. Sikkema L 2024 · 3.57 FIP	26	SP-	3.57	18.5%	6.0%	2.3%	.282	4.10	16.1%	7.2%	87	+0.53	3.57	300	65
Miguel Pena L 2019 · 5.08 FIP	28	SW	5.08	16.0%	7.0%	4.4%	.369	—	—	—	—	—	2.98	282	65
Brendan Nail L 2023 · 4.36 FIP	27	SU	4.36	19.3%	10.5%	2.8%	.262	—	—	—	—	—	3.45	165	65
Colton Turner L 2019 · 4.23 FIP	28	SW	4.23	22.4%	9.2%	3.4%	.345	—	—	—	—	—	2.79	325	65

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	0.4	35	21.5%	9.9%	1.19	4.58
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
Jacob Barnes ('25)	1.7	48	22.0%	9.2%	1.15	4.79
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*