Jake Woodford

P Durham Bulls

Age 30 RHP 6'4" / 215 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	29	26	129	5.02	3.94	20.7%	6.4%	2.2	K 18.5% · BB 5.9% · FIP 4.33
2025	28	MIX2 levels	36	10	98	5.25	4.00	18.6%	7.3%	0.6	K 16.7% · BB 6.8% · FIP 4.04
2026	29	MIX2 levels	33	7	67	6.04	4.04	19.6%	5.6%	0.4	K 18.0% · BB 5.3% · FIP 4.20
2027PROJ	30	MLBTB	10	10	62	5.00	4.65	16.5%	6.4%	0.5
2028PROJ95% MLB	31	MLBTB	5	5	32	4.93	4.88	15.7%	6.8%	0.2
2029PROJ95% MLB	32	MLBTB	3	3	19	5.05	5.13	14.9%	7.1%	0.1

Last 3 seasons WAR 3.3 · Next 3 projected WAR 0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo26

K%26

xwOBA vs10

CompsElian Leyva (age 30) · Jorge Martinez (age 31) · Juan Omar Espinoza (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 122113vR 105

ERA5.00

FIP4.65

K%16.5%

BB%6.4%

K-BB%10.1%

Proj IP62

Value2027 · WAR

Runs saved vs league avg · 62 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p2692.8

Whiff%

p1720.6%

p2618.7%

xwOBA vs

p100.374

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)
2015	18	ROK MLE	GCL Cardinals	8	5	26	112	21	7	1	62%	3.3	12.8%	7.8%	4.9%	1.2%	2.39	3.70	—
2015	18	ROK RAW	GCL Cardinals	8	5	26	112	21	7	1	62%	3.3	18.8%	6.2%	12.5%	0.9%	2.39	2.80	—
2016	19	A MLE	Peoria Chiefs	21	21	109	459	82	37	7	100%	5.2	13.2%	9.5%	3.7%	1.9%	3.31	4.21	—
2016	19	A RAW	Peoria Chiefs	21	21	109	459	82	37	7	100%	5.2	17.9%	8.1%	9.8%	1.5%	3.31	3.45	—
2017	20	A+ MLE	Palm Beach Cardinals	23	21	119	513	72	39	7	91%	5.2	10.8%	8.7%	2.1%	2.1%	3.10	4.43	—
2017	20	A+ RAW	Palm Beach Cardinals	23	21	119	513	72	39	7	91%	5.2	14.0%	7.6%	6.4%	1.4%	3.10	3.64	—
2018	21	MIX MLE	2 levels	28	28	145	657	101	62	18	100%	5.2	12.9%	10.2%	2.8%	2.9%	4.90	4.87	—
2018	21	MIX RAW	2 levels	28	28	145	657	101	62	18	100%	5.2	15.4%	9.4%	5.9%	2.7%	4.90	4.60	—
2019	22	AAA MLE	Memphis Redbirds	26	26	152	643	131	75	22	100%	5.8	17.9%	12.2%	5.7%	3.8%	4.15	5.24	—
2019	22	AAA RAW	Memphis Redbirds	26	26	152	643	131	75	22	100%	5.8	20.4%	11.7%	8.7%	3.4%	4.15	4.74	—
2020	23	MLB MLE	St. Louis Cardinals	12	1	21	85	16	5	7	8%	1.8	18.8%	5.9%	12.9%	8.9%	5.57	7.12	-0.6
2020	23	MLB RAW	St. Louis Cardinals	12	1	21	85	16	5	7	8%	1.8	18.8%	5.9%	12.9%	8.2%	5.57	6.62	-0.5
2021	24	MIX MLE	2 levels	33	15	102	445	75	37	11	45%	3.1	16.2%	8.4%	7.7%	2.7%	4.16	4.30	+0.3
2021	24	MIX RAW	2 levels	33	15	102	445	75	37	11	45%	3.1	16.9%	8.3%	8.5%	2.5%	4.16	4.12	+0.5
2022	25	MIX MLE	2 levels	38	11	91	371	63	29	3	29%	2.4	15.7%	8.1%	7.6%	0.9%	2.66	3.26	+1.4
2022	25	MIX RAW	2 levels	38	11	91	371	63	29	3	29%	2.4	17.0%	7.8%	9.2%	0.8%	2.66	3.10	+1.6
2023	26	MIX MLE	3 levels	25	17	76	342	63	33	16	68%	3.1	15.6%	9.9%	5.7%	4.9%	4.95	5.73	-0.3
2023	26	MIX RAW	3 levels	25	17	76	342	63	33	16	68%	3.1	18.4%	9.6%	8.8%	4.7%	4.95	5.47	-0.1
2024	27	MIX MLE	2 levels	29	26	129	565	117	36	18	90%	4.4	18.5%	5.9%	12.6%	3.7%	5.02	4.33	+1.6
2024	27	MIX MLE	2 levels	29	26	129	565	117	36	18	90%	4.4	18.5%	5.9%	12.6%	3.7%	5.02	4.33	+1.6
2024	27	MIX RAW	2 levels	29	26	129	565	117	36	18	90%	4.4	20.7%	6.4%	14.3%	3.2%	5.02	3.94	+2.2
2025	28	MIX MLE	2 levels	36	10	98	441	82	32	12	28%	2.7	16.7%	6.8%	9.9%	2.7%	5.25	4.04	+0.6
2025	28	MIX MLE	2 levels	36	10	98	441	82	32	12	28%	2.7	16.7%	6.8%	9.9%	2.7%	5.25	4.04	+0.6
2025	28	MIX RAW	2 levels	36	10	98	441	82	32	12	28%	2.7	18.6%	7.3%	11.3%	2.7%	5.25	4.00	+0.6
2026	29	MIX MLE	2 levels	33	7	67	301	59	17	10	21%	2.0	18.0%	5.3%	12.7%	3.5%	6.04	4.20	+0.3
2026	29	MIX MLE	2 levels	33	7	67	301	59	17	10	21%	2.0	18.0%	5.3%	12.7%	3.5%	6.04	4.20	+0.3
2026	29	MIX RAW	2 levels	33	7	67	301	59	17	10	21%	2.0	19.6%	5.6%	14.0%	3.3%	6.04	4.04	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			130	25	284	1259	193	91	40	19%	2.2	15.3%	7.2%	8.1%	3.2%	5.36	4.53	+0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	TB	10	10	62	262	43	17	8	100%	6.2	16.5%	6.4%	10.1%	3.2%	5.00	4.65	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	TB	6	6	34	143	22	10	5	100%	5.6	15.7%	6.8%	9.0%	3.4%	4.93	4.88	+0.2
2029	32	MLB MLE	TB	3	3	20	83	12	6	3	100%	6.5	14.9%	7.1%	7.8%	3.7%	5.05	5.13	+0.1
2028	31	MLB CTX	TB	5	5	32	135	21	9	5	100%	6.4	15.7%	6.8%	9.0%	3.4%	4.93	4.88	+0.2
2029	32	MLB CTX	TB	3	3	19	80	12	6	3	100%	6.3	14.9%	7.1%	7.8%	3.7%	5.05	5.13	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		138	33	334	1474	226	106	48	24%	2.4	15.3%	7.2%	8.2%	3.2%	5.30	4.48	+0.3
/ 200 IP	—	RAW		83	20	200	881	135	63	29	24%	2.4	15.3%	7.2%	8.2%	3.2%	5.30	4.48	+0.2
Career	—	MLE		312	188	1135	4934	763	429	147	60%	3.6	15.5%	8.7%	6.8%	3.0%	4.28	4.53	+3.1
/ 200 IP	—	MLE		55	33	200	870	134	76	26	60%	3.6	15.5%	8.7%	6.8%	3.0%	4.28	4.53	+1.9

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 AAADurham Bulls · 39 IPFIP 3.71 → 4.04 (+0.34)K% 20.4% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.36%	—	×0.860	17.51%
BB% (unintentional) /BF	5.39%	—	×0.900	4.85%
HR / BF /BF	2.99%	÷1.000	×1.100	3.29%

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 100).

Result: FIP 3.71 → 4.04, 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 AAAIowa Cubs · 61 IPFIP 4.02 → 4.14 (+0.12)K% 21.8% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.77%	—	×0.860	18.72%
BB% (unintentional) /BF	7.38%	—	×0.900	6.64%
HR / BF /BF	3.32%	÷1.125	×1.100	3.25%

Result: FIP 4.02 → 4.14, 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).

2024 AAAIndianapolis Indians · 94 IPFIP 3.68 → 4.22 (+0.53)K% 22.9% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.86%	—	×0.860	19.66%
BB% (unintentional) /BF	6.78%	—	×0.900	6.11%
HR / BF /BF	3.02%	÷0.909	×1.100	3.65%

Result: FIP 3.68 → 4.22, 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 AAAMemphis Redbirds · 21 IPFIP 4.18 → 4.62 (+0.44)K% 25.6% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.56%	—	×0.860	21.98%
BB% (unintentional) /BF	11.11%	—	×0.900	10.00%
HR / BF /BF	3.33%	÷0.955	×1.100	3.84%

Result: FIP 4.18 → 4.62, 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 AASpringfield Cardinals · 8 IPFIP 4.09 → 5.12 (+1.04)K% 36.7% → 29.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.67%	—	×0.810	29.70%
BB% (unintentional) /BF	3.33%	—	×1.100	3.67%
HR / BF /BF	6.67%	÷1.080	×1.200	7.41%

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 116).

Result: FIP 4.09 → 5.12, 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 AAAMemphis Redbirds · 43 IPFIP 3.22 → 3.53 (+0.31)K% 21.3% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.31%	—	×0.880	18.75%
BB% (unintentional) /BF	10.38%	—	×1.050	10.90%
HR / BF /BF	1.09%	÷1.048	×1.100	1.15%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, 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 110).

Result: FIP 3.22 → 3.53, 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).

2021 AAAMemphis Redbirds · 34 IPFIP 4.16 → 4.60 (+0.45)K% 16.4% → 14.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.45%	—	×0.880	14.47%
BB% (unintentional) /BF	7.89%	—	×1.050	8.29%
HR / BF /BF	2.63%	÷0.949	×1.100	3.05%

Result: FIP 4.16 → 4.60, 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 AAAMemphis Redbirds · 152 IPFIP 4.74 → 5.24 (+0.50)K% 20.4% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.37%	—	×0.880	17.93%
BB% (unintentional) /BF	11.66%	—	×1.050	12.25%
HR / BF /BF	3.42%	÷0.982	×1.100	3.83%

Result: FIP 4.74 → 5.24, 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
Jake Woodford (OGILVIE)	—	—	—	—	—	3.2%	—	4.97	15.4%	8.5%	54	+0.32	—	—	—
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	67
Jorge Martinez R 2016 · 3.53 FIP	31	SP-	3.53	12.9%	5.3%	1.6%	.266	3.71	16.5%	11.5%	154	+0.18	3.53	214	67
Juan Omar Espinoza R 2015 · 4.81 FIP	31	SP-	4.81	8.9%	6.6%	3.0%	.346	4.84	8.4%	-0.8%	52	+0.03	4.81	104	65
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	63
Ross Ohlendorf R 2013 · 4.01 FIP	30	SW	4.01	18.2%	5.3%	3.2%	.265	4.18	23.5%	14.4%	122	+0.17	3.30	617	62
Jared Fernandez R 2002 · 4.23 FIP	30	SP-	4.23	15.6%	10.0%	2.2%	.323	3.57	11.8%	5.6%	38	-0.66	3.57	101	62
David Hale R 2018 · 4.22 FIP	30	SP-	4.22	15.4%	7.5%	2.7%	.299	3.65	17.1%	11.3%	114	-0.57	3.30	581	61
Ryan Jensen R 2005 · 4.35 FIP	29	SW	4.35	15.7%	5.2%	3.5%	.310	—	—	—	—	—	4.35	253	61
Eder Llamas R 2016 · 4.12 FIP	30	SW	4.12	11.4%	6.8%	2.0%	.301	3.23	11.3%	4.6%	64	-0.89	3.23	171	61
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	61
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	61
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	60
Casey Lawrence R 2018 · 3.77 FIP	30	SP-	3.77	18.1%	4.4%	3.0%	.305	4.08	20.0%	14.8%	86	+0.31	3.57	1,374	60
Jon Leicester R 2007 · 4.44 FIP	28	SP-	4.44	11.0%	9.0%	2.1%	.292	—	—	—	—	—	3.76	113	60
Todd Redmond R 2015 · 3.86 FIP	30	SW	3.86	15.4%	7.1%	2.1%	.311	—	—	—	—	—	3.21	247	59
Edgar Alberto Garcia R 2017 · 4.01 FIP	29	SP-	4.01	17.3%	10.9%	1.8%	.305	—	—	—	—	—	4.01	272	58
Chris Mazza R 2020 · 3.94 FIP	30	SP-	3.94	21.3%	11.0%	2.3%	.348	3.95	21.4%	13.5%	111	+0.01	3.29	563	58
Alfonso Sanchez R 2017 · 4.51 FIP	29	SW	4.51	12.5%	9.8%	2.2%	.346	7.58	8.6%	1.4%	39	+3.07	4.51	224	58
Rodolfo Aguirre R 2015 · 4.29 FIP	30	SW	4.29	12.4%	6.9%	2.5%	.288	4.81	11.4%	1.3%	125	+0.52	3.39	212	58
Luke Hudson R 2006 · 3.81 FIP	29	SP-	3.81	14.5%	8.4%	1.6%	.307	—	—	—	—	—	3.81	235	58

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	2.0	40	15.5%	7.2%	1.25	5.25
Lance Painter ('03)	2.2	56	16.7%	9.0%	1.32	5.24
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*
Mike Lincoln ('10)	1.9	54	14.1%	8.9%	1.32	5.33
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*
Travis Harper ('06)	2.1	69	15.0%	7.5%	1.33	4.94
Dennis Powell ('85-'93, -2 WAR*)	1.7	49	17.6%*	10.1%*	1.18*	5.31*