Luke Weaver

P Pittsburgh Pirates

Age 33 RHP 6'2" / 180 lbs MLB peak 0.6 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR
2024	30	MLBNYY	62	84	2.89	3.12	31.1%	7.9%	1.4
2025	31	MLBNYY	64	65	3.62	3.76	27.5%	7.3%	0.6
2026	32	MLBPIT	60	60	2.69	2.77	27.3%	6.3%	1.3
2027PROJ	33	MLBPIT	55	58	3.52	3.60	28.2%	7.3%	0.7
2028PROJ	34	MLBPIT	45	47	3.62	3.77	27.3%	7.8%	0.4
2029PROJ	35	MLBPIT	34	36	3.90	4.10	26.3%	8.4%	0.1

Last 3 seasons WAR 3.3 · 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 vs90

K%78

FB Velo61

Form4.67 ERA (proj 3.52) · K 29.2% (proj 28.2%) · BB 6.9% (proj 7.3%) · last 90d · 17 IP through Oct 27

CompsTim Dillard (age 33) · Tony Barnette (age 33) · Joe Nelson (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9385vR 77

ERA3.52

FIP3.60

K%28.2%

BB%7.3%

K-BB%20.9%

Proj IP58

Value2027 · WAR

Runs saved vs league avg · 58 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p6195.3

Whiff%

p8230.3%

p7827.3%

xwOBA vs

p900.272

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	Palm Beach Cardinals	19	19	105	426	88	19	2	100%	5.5	15.9%	5.1%	10.8%	0.6%	1.62	2.73	—
2015	21	A+ RAW	Palm Beach Cardinals	19	19	105	426	88	19	2	100%	5.5	20.7%	4.5%	16.2%	0.5%	1.62	2.22	—
2016	22	MIX MLE	3 levels	22	21	119	497	137	24	11	95%	5.4	24.5%	4.8%	19.6%	2.5%	2.64	3.00	+3.6
2016	22	MIX RAW	3 levels	22	21	119	497	137	24	11	95%	5.4	27.6%	4.8%	22.7%	2.2%	2.64	2.61	+4.3
2017	23	MIX MLE	2 levels	28	25	138	557	148	34	10	89%	4.9	24.9%	6.3%	18.7%	2.0%	3.13	2.86	+4.4
2017	23	MIX RAW	2 levels	28	25	138	557	148	34	10	89%	4.9	26.6%	6.1%	20.5%	1.8%	3.13	2.64	+4.8
2018	24	MIX MLE	2 levels	31	26	140	624	128	52	20	84%	4.5	19.9%	8.5%	11.3%	3.4%	4.94	4.35	+1.7
2018	24	MIX RAW	2 levels	31	26	140	624	128	52	20	84%	4.5	20.5%	8.3%	12.2%	3.2%	4.94	4.24	+1.9
2019	25	MLB MLE	Arizona Diamondbacks	12	12	64	260	69	13	6	100%	5.4	26.5%	5.0%	21.5%	2.4%	2.94	2.83	+2.1
2019	25	MLB RAW	Arizona Diamondbacks	12	12	64	260	69	13	6	100%	5.4	26.5%	5.0%	21.5%	2.3%	2.94	2.77	+2.1
2020	26	MLB MLE	Arizona Diamondbacks	12	12	52	236	55	18	10	100%	4.3	23.3%	7.6%	15.7%	4.5%	6.58	4.56	+0.5
2020	26	MLB RAW	Arizona Diamondbacks	12	12	52	236	55	18	10	100%	4.3	23.3%	7.6%	15.7%	4.2%	6.58	4.52	+0.5
2021	27	MIX MLE	3 levels	16	16	76	320	80	21	11	100%	4.7	22.5%	6.2%	16.4%	4.2%	4.16	4.30	+1.0
2021	27	MIX RAW	3 levels	16	16	76	320	80	21	11	100%	4.7	25.0%	6.6%	18.4%	3.4%	4.16	3.71	+1.5
2022	28	MIX MLE	2 levels	28	2	42	199	43	15	2	7%	1.5	21.8%	7.5%	14.4%	0.6%	6.05	2.54	+1.0
2022	28	MIX RAW	2 levels	28	2	42	199	43	15	2	7%	1.5	21.6%	7.5%	14.1%	1.0%	6.05	2.74	+0.9
2023	29	MIX MLE	2 levels	31	27	133	596	118	44	30	87%	4.3	19.4%	7.1%	12.3%	4.8%	6.17	5.01	+0.6
2023	29	MIX RAW	2 levels	31	27	133	596	118	44	30	87%	4.3	19.8%	7.4%	12.4%	5.0%	6.17	5.26	+0.2
2024	30	MLB MLE	New York Yankees	62	0	84	331	103	26	10	0%	1.4	31.1%	7.9%	23.3%	2.8%	2.89	3.02	+1.5
2024	30	MLB MLE	New York Yankees	62	0	84	331	103	26	10	0%	1.4	31.1%	7.9%	23.3%	2.8%	2.89	3.02	+1.5
2024	30	MLB RAW	New York Yankees	62	0	84	331	103	26	10	0%	1.4	31.1%	7.9%	23.3%	3.0%	2.89	3.12	+1.4
2025	31	MLB MLE	New York Yankees	64	0	65	262	72	19	10	0%	1.0	27.5%	7.3%	20.2%	3.6%	3.62	3.66	+0.7
2025	31	MLB MLE	New York Yankees	64	0	65	262	72	19	10	0%	1.0	27.5%	7.3%	20.2%	3.6%	3.62	3.66	+0.7
2025	31	MLB RAW	New York Yankees	64	0	65	262	72	19	10	0%	1.0	27.5%	7.3%	20.2%	3.8%	3.62	3.76	+0.6
2026	32	MLB MLE	Pittsburgh Pirates	60	0	60	238	65	15	5	0%	1.0	27.3%	6.3%	21.0%	2.3%	2.69	2.84	+1.2
2026	32	MLB MLE	Pittsburgh Pirates	60	0	60	238	65	15	5	0%	1.0	27.3%	6.3%	21.0%	2.3%	2.69	2.84	+1.2
2026	32	MLB RAW	Pittsburgh Pirates	60	0	60	238	65	15	5	0%	1.0	27.3%	6.3%	21.0%	2.1%	2.69	2.77	+1.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			330	106	783	3367	811	241	115	32%	2.4	24.1%	7.2%	16.9%	3.4%	4.58	3.86	+6.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	PIT	55	0	58	245	69	18	7	0%	1.1	28.2%	7.3%	20.9%	2.9%	3.52	3.60	+0.7
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	PIT	45	0	47	199	54	16	6	0%	1.0	27.3%	7.8%	19.5%	3.2%	3.75	3.90	+0.4
2029	35	MLB MLE	PIT	34	0	36	151	40	13	5	0%	1.1	26.3%	8.4%	18.0%	3.5%	4.04	4.24	+0.1
2030	36	MLB MLE	PIT	23	0	24	102	26	9	4	0%	1.1	25.3%	9.0%	16.3%	3.9%	4.38	4.61	-0.0
2028	34	MLB CTX	PIT	45	0	47	198	54	16	6	0%	1.0	27.3%	7.8%	19.5%	2.9%	3.62	3.77	+0.4
2029	35	MLB CTX	PIT	34	0	36	152	40	13	5	0%	1.1	26.3%	8.4%	18.0%	3.2%	3.90	4.10	+0.1
2030	36	MLB CTX	PIT	23	0	24	101	26	9	4	0%	1.0	25.3%	9.0%	16.3%	3.6%	4.22	4.45	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		432	106	890	3819	931	278	129	25%	2.1	24.4%	7.3%	17.1%	3.4%	4.50	3.82	+7.7
/ 200 IP	—	RAW		97	24	200	858	209	62	29	25%	2.1	24.4%	7.3%	17.1%	3.4%	4.50	3.82	+1.7
Career	—	MLE		385	160	1078	4546	1047	302	131	42%	2.8	23.0%	6.6%	16.4%	2.9%	3.86	3.58	+6.9
/ 200 IP	—	MLE		71	30	200	843	194	56	24	42%	2.8	23.0%	6.6%	16.4%	2.9%	3.86	3.58	+1.5

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.

2023 AAALouisville Bats · 9 IPFIP 4.00 → 4.24 (+0.24)K% 27.3% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.27%	—	×0.860	23.45%
BB% (unintentional) /BF	12.12%	—	×0.900	10.91%
HR / BF /BF	3.03%	÷1.054	×1.100	3.16%

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 111).

Result: FIP 4.00 → 4.24, 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).

2022 AAAReno Aces · 6 IPFIP 4.62 → 5.18 (+0.56)K% 20.0% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.880	17.60%
BB% (unintentional) /BF	8.00%	—	×1.050	8.40%
HR / BF /BF	4.00%	÷0.965	×1.100	4.56%

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 93).

Result: FIP 4.62 → 5.18, 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 AAAReno Aces · 7 IPFIP 1.52 → 1.98 (+0.46)K% 37.5% → 33.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.50%	—	×0.880	33.00%
BB% (unintentional) /BF	12.50%	—	×1.050	13.12%
HR / BF /BF	0.00%	÷0.958	×1.100	0.00%

Result: FIP 1.52 → 1.98, 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 AAAMemphis Redbirds · 78 IPFIP 2.28 → 2.64 (+0.36)K% 24.9% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.92%	—	×0.880	21.93%
BB% (unintentional) /BF	5.90%	—	×1.050	6.20%
HR / BF /BF	0.98%	÷0.980	×1.100	1.10%

Result: FIP 2.28 → 2.64, 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 AASpringfield Cardinals · 77 IPFIP 1.81 → 2.34 (+0.53)K% 28.6% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.57%	—	×0.810	23.14%
BB% (unintentional) /BF	3.25%	—	×1.100	3.57%
HR / BF /BF	1.30%	÷1.155	×1.200	1.35%

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 131).

Result: FIP 1.81 → 2.34, 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 AAAMemphis Redbirds · 6 IPFIP 2.72 → 2.96 (+0.24)K% 18.2% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.18%	—	×0.880	16.00%
BB% (unintentional) /BF	9.09%	—	×1.050	9.55%
HR / BF /BF	0.00%	÷0.931	×1.100	0.00%

Result: FIP 2.72 → 2.96, 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).

2015 A+Palm Beach Cardinals · 105 IPFIP 2.18 → 2.73 (+0.55)K% 20.7% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.66%	—	×0.770	15.91%
BB% (unintentional) /BF	4.46%	—	×1.150	5.13%
HR / BF /BF	0.47%	÷0.989	×1.250	0.59%

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 98).

Result: FIP 2.18 → 2.73, 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
Luke Weaver (OGILVIE)	—	—	—	—	—	2.9%	—	4.17	26.5%	18.3%	107	+0.57	—	—	—
Tim Dillard R 2016 · 3.13 FIP	33	SU	3.13	22.6%	8.2%	1.7%	.358	4.14	13.7%	6.9%	250	+1.01	2.92	432	56
Tony Barnette R 2017 · 3.56 FIP	33	SU	3.56	22.6%	7.1%	2.7%	.335	2.61	25.0%	20.2%	26	-0.95	2.61	144	56
Joe Nelson R 2008 · 3.08 FIP	33	SU	3.08	26.1%	7.8%	2.2%	.252	5.35	19.8%	5.5%	40	+2.27	3.08	139	56
Dale Thayer R 2014 · 3.56 FIP	33	SU	3.56	23.4%	4.9%	3.3%	.243	4.34	15.8%	8.8%	38	+0.78	2.75	239	55
Bob Wells R 2000 · 3.93 FIP	33	SU	3.93	21.7%	3.7%	4.0%	.266	4.57	14.2%	8.6%	127	+0.64	3.93	627	55
Brendan Donnelly R 2004 · 3.05 FIP	33	SU	3.05	32.6%	8.7%	2.9%	.302	3.88	19.0%	11.8%	150	+0.83	2.23	385	54
Samuel Deduno R 2016 · 2.99 FIP	33	SU	2.99	22.3%	5.4%	2.0%	.163	—	—	—	—	—	2.99	327	54
Jim Henderson R 2016 · 4.55 FIP	33	SU	4.55	25.8%	9.0%	4.5%	.287	—	—	—	—	—	1.86	167	53
Kazuhiro Sasaki R 2001 · 2.79 FIP	33	SU	2.79	23.8%	3.4%	2.3%	.228	2.95	25.8%	18.5%	94	+0.16	2.76	223	53
Mike Adams R 2011 · 2.35 FIP	33	SU	2.35	26.7%	4.3%	1.7%	.210	3.58	21.5%	13.3%	96	+1.23	1.36	405	53
Rafael Betancourt R 2008 · 4.12 FIP	33	SU	4.12	20.7%	6.5%	3.6%	.304	2.37	31.4%	27.3%	181	-1.75	1.79	686	52
Blake Parker R 2018 · 4.12 FIP	33	SU	4.12	25.4%	6.5%	4.3%	.290	4.12	24.9%	16.5%	121	+0.00	2.52	406	52
Spencer Patton R 2021 · 3.04 FIP	33	SU	3.04	27.9%	8.7%	2.2%	.305	4.97	21.2%	10.4%	88	+1.93	2.79	239	51
Matt Herges R 2003 · 2.90 FIP	33	SU	2.90	20.5%	8.1%	0.9%	.278	4.39	11.1%	4.4%	165	+1.49	2.90	691	51
Jason Urquidez R 2016 · 2.39 FIP	33	SU	2.39	22.6%	5.3%	1.0%	.328	1.25	28.2%	24.0%	46	-1.14	1.25	123	51
Giovanni Carrara R 2001 · 4.06 FIP	33	SU	4.06	20.1%	6.0%	3.5%	.249	4.28	15.7%	7.9%	173	+0.22	2.50	462	51
Jim Miller R 2015 · 3.95 FIP	33	SU	3.95	18.8%	4.1%	3.5%	.275	5.43	20.4%	6.3%	17	+1.48	3.95	140	50
Neil Wagner R 2017 · 3.11 FIP	33	SU	3.11	20.7%	8.6%	1.2%	.257	—	—	—	—	—	3.11	135	50
Chris Jakubauskas R 2011 · 4.42 FIP	32	SW	4.42	15.7%	7.9%	3.0%	.339	—	—	—	—	—	4.42	165	50
Tommy Nance R 2024 · 3.51 FIP	33	SU	3.51	20.2%	5.8%	2.5%	.327	2.84	26.3%	19.5%	123	-0.67	2.08	360	50

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	4.7	63	24.6%	7.5%	1.31	4.45
Jesse Chavez ('25)	5.7	82	21.4%	7.4%	1.32	4.27
Ed Nunez ('82-'94, 2 WAR*)	3.3	54	24.5%*	9.5%*	1.24*	4.37*
Dennis Cook ('88-'02, 7 WAR*)	5.1	72	21.4%*	8.6%*	1.39*	4.02*
Brett Cecil ('18)	3.8	76	20.7%	8.3%	1.14	4.29
Yusmeiro Petit ('21)	4.5	70	20.7%	5.5%	1.36	3.93
Joe Price ('80-'90, 7 WAR*)	4.5	82	23.3%*	8.8%*	1.49*	4.15*