Paul Blackburn

P New York Yankees

Age 33 RHP 6'1" / 196 lbs MLB peak 0.6 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	30	MIX3 levels	18	16	86	5.02	4.47	17.9%	7.3%	0.9	K 18.7% · BB 6.6% · FIP 4.45
2025	31	MIX5 levels	27	16	94	4.39	3.69	22.7%	7.8%	1.9	K 18.5% · BB 6.7% · FIP 3.59
2026	32	MLBNYY	62	2	85	1.59	3.68	20.5%	9.5%	0.9
2027PROJ	33	MLBNYY	8	8	48	4.10	4.28	19.7%	8.5%	0.6
2028PROJ	34	MLBNYY	7	7	43	4.39	4.58	18.8%	9.0%	0.4
2029PROJ	35	MLBNYY	5	5	30	4.71	4.92	17.8%	9.6%	0.2

Last 3 seasons WAR 3.7 · Next 3 projected WAR 1.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs66

FB Velo52

K%38

Form0.34 ERA (proj 4.10) · K 23.1% (proj 19.7%) · BB 12.0% (proj 8.5%) · last 90d · 26 IP through Oct 27

CompsMitch Lively (age 31) · Jared Fernandez (age 31) · Austin Bibens-Dirkx (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10899vR 91

ERA4.10

FIP4.28

K%19.7%

BB%8.5%

K-BB%11.2%

Proj IP48

Value2027 · WAR

Runs saved vs league avg · 48 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p5294.7

Whiff%

p3222.8%

p3820.5%

xwOBA vs

p660.296

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	21	A+ MLE	Myrtle Beach Pelicans	18	18	90	371	63	22	3	100%	5.0	13.1%	6.8%	6.3%	1.1%	3.11	3.48	—
2015	21	A+ RAW	Myrtle Beach Pelicans	18	18	90	371	63	22	3	100%	5.0	17.0%	5.9%	11.1%	0.8%	3.11	2.87	—
2016	22	AA MLE	Jackson Generals	26	25	143	587	99	35	8	96%	5.5	13.7%	6.6%	7.1%	1.6%	3.27	3.68	—
2016	22	AA RAW	Jackson Generals	26	25	143	587	99	35	8	96%	5.5	16.9%	6.0%	10.9%	1.4%	3.27	3.18	—
2017	23	MIX MLE	2 levels	25	24	138	566	78	42	11	96%	5.5	12.6%	7.7%	4.9%	2.3%	3.12	4.28	+1.8
2017	23	MIX RAW	2 levels	25	24	138	566	78	42	11	96%	5.5	13.8%	7.4%	6.4%	1.9%	3.12	3.92	+2.5
2018	24	MIX MLE	2 levels	7	7	31	138	20	7	2	100%	4.5	16.0%	5.0%	10.9%	1.8%	7.18	3.40	+0.8
2018	24	MIX RAW	2 levels	7	7	31	138	20	7	2	100%	4.5	14.5%	5.1%	9.4%	1.4%	7.18	3.32	+0.8
2019	25	MIX MLE	2 levels	28	23	144	596	100	38	21	82%	5.1	14.9%	6.7%	8.3%	3.5%	4.82	4.62	+1.3
2019	25	MIX RAW	2 levels	28	23	144	596	100	38	21	82%	5.1	16.8%	6.4%	10.4%	3.5%	4.82	4.40	+1.7
2020	26	MLB MLE	Oakland Athletics	1	1	2	14	2	2	0	100%	2.3	14.3%	14.3%	0.0%	0.0%	27.00	3.70	+0.0
2020	26	MLB RAW	Oakland Athletics	1	1	2	14	2	2	0	100%	2.3	14.3%	14.3%	0.0%	0.0%	27.00	3.96	+0.0
2021	27	MIX MLE	2 levels	26	25	127	575	106	37	16	96%	4.9	16.8%	6.7%	10.1%	3.2%	5.24	4.26	+1.7
2021	27	MIX RAW	2 levels	26	25	127	575	106	37	16	96%	4.9	18.4%	6.4%	12.0%	2.8%	5.24	3.94	+2.2
2022	28	MLB MLE	Oakland Athletics	21	21	111	467	89	28	15	100%	5.3	19.1%	6.0%	13.1%	3.5%	4.28	4.19	+1.6
2022	28	MLB RAW	Oakland Athletics	21	21	111	467	89	28	15	100%	5.3	19.1%	6.0%	13.1%	3.2%	4.28	4.01	+1.8
2023	29	MIX MLE	3 levels	27	26	122	554	114	48	14	96%	4.5	20.8%	8.6%	12.2%	2.8%	4.88	3.99	+2.0
2023	29	MIX RAW	3 levels	27	26	122	554	114	48	14	96%	4.5	20.6%	8.7%	11.9%	2.5%	4.88	3.91	+2.2
2024	30	MIX MLE	3 levels	18	16	86	369	66	27	13	89%	4.8	18.7%	6.6%	12.0%	3.8%	5.02	4.45	+0.9
2024	30	MIX MLE	3 levels	18	16	86	369	66	27	13	89%	4.8	18.7%	6.6%	12.0%	3.8%	5.02	4.45	+0.9
2024	30	MIX RAW	3 levels	18	16	86	369	66	27	13	89%	4.8	17.9%	7.3%	10.6%	3.5%	5.02	4.47	+0.9
2025	31	MIX MLE	5 levels	27	16	94	396	90	31	11	59%	3.5	18.5%	6.7%	11.8%	2.2%	4.39	3.59	+2.1
2025	31	MIX MLE	5 levels	27	16	94	396	90	31	11	59%	3.5	18.5%	6.7%	11.8%	2.2%	4.39	3.59	+2.1
2025	31	MIX RAW	5 levels	27	16	94	396	90	31	11	59%	3.5	22.7%	7.8%	14.9%	2.8%	4.39	3.69	+1.9
2026	32	MLB MLE	New York Yankees	62	2	85	336	69	32	7	3%	1.4	20.5%	9.5%	11.0%	2.0%	1.59	3.64	+0.9
2026	32	MLB MLE	New York Yankees	62	2	85	336	69	32	7	3%	1.4	20.5%	9.5%	11.0%	2.0%	1.59	3.64	+0.9
2026	32	MLB RAW	New York Yankees	62	2	85	336	69	32	7	3%	1.4	20.5%	9.5%	11.0%	2.1%	1.59	3.68	+0.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			163	88	552	2361	432	173	69	54%	3.4	18.3%	7.3%	11.0%	2.9%	4.45	4.10	+8.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	NYY	8	8	48	203	40	17	5	100%	6.0	19.7%	8.5%	11.2%	2.5%	4.10	4.28	+0.6
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	NYY	7	7	43	182	34	16	5	100%	6.2	18.8%	9.0%	9.7%	2.8%	4.39	4.58	+0.4
2029	35	MLB MLE	NYY	5	5	30	125	22	12	4	100%	5.9	17.8%	9.6%	8.2%	3.2%	4.71	4.92	+0.2
2028	34	MLB CTX	NYY	7	7	43	182	34	16	5	100%	6.1	18.8%	9.0%	9.7%	2.8%	4.39	4.58	+0.4
2029	35	MLB CTX	NYY	5	5	30	127	23	12	4	100%	6.0	17.8%	9.6%	8.2%	3.2%	4.71	4.92	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		175	100	625	2668	488	201	78	57%	3.6	18.3%	7.5%	10.8%	2.9%	4.46	4.12	+9.5
/ 200 IP	—	RAW		56	32	200	854	156	64	25	57%	3.6	18.3%	7.5%	10.8%	2.9%	4.46	4.12	+3.0
Career	—	MLE		286	204	1174	4969	825	353	130	71%	4.1	16.6%	7.1%	9.5%	2.6%	4.16	4.04	+9.1
/ 200 IP	—	MLE		49	35	200	847	141	60	22	71%	4.1	16.6%	7.1%	9.5%	2.6%	4.16	4.04	+2.9

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.

2025 AAASyracuse Mets · 42 IPFIP 2.95 → 3.06 (+0.11)K% 20.4% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.36%	—	×0.860	17.51%
BB% (unintentional) /BF	7.19%	—	×0.900	6.47%
HR / BF /BF	1.20%	÷1.167	×1.100	1.13%

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 133).

Result: FIP 2.95 → 3.06, 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+Brooklyn Cyclones · 5 IPFIP 6.72 → 8.41 (+1.69)K% 33.3% → 25.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.770	25.67%
BB% (unintentional) /BF	9.52%	—	×1.150	10.95%
HR / BF /BF	9.52%	÷1.073	×1.250	11.10%

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 115).

Result: FIP 6.72 → 8.41, 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).

2024 AAASyracuse Mets · 10 IPFIP 4.27 → 4.36 (+0.09)K% 12.8% → 11.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.77%	—	×0.860	10.98%
BB% (unintentional) /BF	8.51%	—	×0.900	7.66%
HR / BF /BF	2.13%	÷1.059	×1.100	2.21%

Result: FIP 4.27 → 4.36, 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 AAALas Vegas Aviators · 16 IPFIP 4.96 → 5.26 (+0.30)K% 13.0% → 11.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.99%	—	×0.860	11.17%
BB% (unintentional) /BF	6.49%	—	×0.900	5.84%
HR / BF /BF	3.90%	÷0.996	×1.100	4.30%

Result: FIP 4.96 → 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).

2021 AAALas Vegas Aviators · 89 IPFIP 3.36 → 3.79 (+0.43)K% 20.0% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.880	17.60%
BB% (unintentional) /BF	6.75%	—	×1.050	7.09%
HR / BF /BF	2.00%	÷0.941	×1.100	2.34%

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 88).

Result: FIP 3.36 → 3.79, 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).

2019 AAALas Vegas Aviators · 133 IPFIP 4.29 → 4.47 (+0.18)K% 17.1% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.07%	—	×0.880	15.02%
BB% (unintentional) /BF	6.31%	—	×1.050	6.62%
HR / BF /BF	3.34%	÷1.119	×1.100	3.28%

Result: FIP 4.29 → 4.47, 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).

2017 AAANashville Sounds · 80 IPFIP 3.67 → 4.16 (+0.49)K% 17.1% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.07%	—	×0.880	15.02%
BB% (unintentional) /BF	7.93%	—	×1.050	8.32%
HR / BF /BF	1.83%	÷0.868	×1.100	2.32%

Result: FIP 3.67 → 4.16, 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).

2016 AAJackson Generals · 143 IPFIP 3.18 → 3.68 (+0.50)K% 16.9% → 13.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.87%	—	×0.810	13.66%
BB% (unintentional) /BF	5.96%	—	×1.100	6.56%
HR / BF /BF	1.36%	÷0.992	×1.200	1.65%

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 98).

Result: FIP 3.18 → 3.68, 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
Paul Blackburn (OGILVIE)	—	—	—	—	—	2.5%	—	4.72	18.4%	9.1%	73	+0.44	—	—	—
Mitch Lively R 2017 · 3.47 FIP	31	SP-	3.47	17.0%	6.4%	1.8%	.304	—	—	—	—	—	2.39	158	67
Jared Fernandez R 2003 · 3.57 FIP	31	SP-	3.57	11.8%	6.2%	1.2%	.269	—	—	—	—	—	3.57	101	63
Austin Bibens-Dirkx R 2018 · 4.89 FIP	33	SP-	4.89	17.9%	7.6%	4.3%	.322	4.82	15.9%	9.5%	147	-0.07	3.97	567	62
Osvaldo Fernandez R 2001 · 4.53 FIP	32	SP-	4.53	9.6%	8.2%	2.2%	.324	—	—	—	—	—	4.25	387	62
Marco Quevedo R 2019 · 5.17 FIP	32	SP-	5.17	13.6%	11.4%	3.2%	.344	—	—	—	—	—	4.13	300	62
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	61
Deck McGuire R 2022 · 5.12 FIP	33	SP-	5.12	15.7%	13.1%	3.1%	.279	—	—	—	—	—	3.41	622	59
Casey Lawrence R 2021 · 4.08 FIP	33	SP-	4.08	20.0%	5.2%	3.7%	.284	4.99	15.9%	10.6%	440	+0.91	3.57	1,374	59
Kenshin Kawakami R 2009 · 3.97 FIP	34	SP-	3.97	15.7%	7.6%	2.2%	.277	4.06	15.1%	9.5%	87	+0.09	3.97	244	59
Juan Omar Espinoza R 2016 · 4.84 FIP	32	SP-	4.84	8.4%	9.2%	2.4%	.348	—	—	—	—	—	4.81	104	56
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	56
Pete Walker R 2002 · 4.59 FIP	33	SP-	4.59	13.4%	7.7%	3.0%	.279	5.16	12.0%	2.8%	139	+0.57	4.45	327	55
Eder Llamas R 2017 · 3.23 FIP	31	SP	3.23	11.3%	6.7%	0.4%	.368	—	—	—	—	—	3.23	171	54
Josh Lindblom R 2020 · 3.50 FIP	33	SP	3.50	27.2%	8.4%	3.0%	.308	4.46	21.7%	13.8%	255	+0.96	1.83	480	54
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	54
Junior Guerra R 2018 · 3.99 FIP	33	SP	3.99	22.3%	9.0%	3.0%	.309	4.12	21.2%	9.1%	173	+0.13	3.18	646	53
Thad Weber R 2017 · 5.25 FIP	32	SP-	5.25	13.2%	4.4%	4.9%	.398	—	—	—	—	—	4.40	378	52
Rolando Valdez R 2019 · 5.36 FIP	33	SP-	5.36	11.7%	7.6%	4.2%	.360	—	—	—	—	—	3.06	258	52
Shawn Haviland R 2017 · 5.00 FIP	31	SP-	5.00	16.3%	8.1%	4.1%	.261	—	—	—	—	—	3.69	283	52
Jarrett Grube R 2015 · 3.75 FIP	33	SP	3.75	18.7%	4.2%	3.1%	.285	4.57	17.3%	9.6%	253	+0.82	3.75	393	52

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	3.4	61	18.4%	7.8%	1.12	4.43
Steve Crawford ('80-'91, 3 WAR*)	2.8	63	18.2%*	7.4%*	1.04*	4.28*
Anthony Swarzak ('21)	3.3	73	17.8%	7.3%	1.20	4.42
Ross Detwiler ('22)	3.8	68	15.3%	8.2%	1.11	4.56
Donne Wall ('02)	2.4	59	16.1%	7.7%	1.18	4.20
Ted Power ('81-'93, 8 WAR*)	5.8	97	18.4%*	8.9%*	1.05*	4.38*
Randy Moffitt ('72-'83, 4 WAR*)	3.9	78	19.4%*	8.3%*	1.08*	4.19*