Lake Bachar

P Pittsburgh Pirates

Age 32 RHP 6'2" / 219 lbs MLB peak 0.1 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MIX2 levels	57	1	82	3.95	4.10	27.0%	9.9%	0.4	K 23.2% · BB 8.9% · FIP 4.54
2025	30	MIX2 levels	56	1	74	3.89	3.80	26.4%	9.1%	0.7	K 25.3% · BB 9.1% · FIP 4.07
2026	31	MLBPIT	53	12	87	3.43	4.12	26.0%	9.8%	0.4
2027PROJ	32	MLBPIT	64	0	67	4.19	4.46	26.4%	9.8%	0.1
2028PROJ95% MLB	33	MLBPIT	45	0	47	4.52	4.74	25.6%	10.3%	-0.1
2029PROJ90% MLB	34	MLBPIT	30	0	32	4.83	5.04	24.7%	10.8%	-0.2

Last 3 seasons WAR 1.5 · Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs78

K%71

FB Velo48

Form2.25 ERA (proj 4.19) · K 26.4% (proj 26.4%) · BB 11.6% (proj 9.8%) · last 90d · 32 IP through Oct 27

CompsChris Hatcher (age 32) · Nick Martinez (age 32) · Mike Broadway (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10799vR 91

ERA4.19

FIP4.46

K%26.4%

BB%9.8%

K-BB%16.6%

Proj IP67

Value2027 · WAR

Runs saved vs league avg · 67 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL4040

CMD5050

K†6060

Statcast Percentiles

FB Velo

p4894.4

Whiff%

p8130.2%

p7126.0%

xwOBA vs

p780.285

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)
2016	21	MIX MLE	3 levels	15	5	37	143	41	7	1	33%	2.4	20.7%	6.5%	14.2%	1.2%	3.19	2.85	—
2016	21	MIX RAW	3 levels	15	5	37	143	41	7	1	33%	2.4	28.7%	4.9%	23.8%	0.7%	3.19	1.79	—
2017	22	MIX MLE	2 levels	13	7	51	201	47	14	7	54%	3.9	16.7%	8.5%	8.2%	4.4%	3.38	5.18	—
2017	22	MIX RAW	2 levels	13	7	51	201	47	14	7	54%	3.9	23.4%	7.0%	16.4%	3.5%	3.38	3.87	—
2018	23	MIX MLE	2 levels	27	18	115	497	80	46	18	67%	4.3	12.9%	10.3%	2.6%	5.3%	4.68	6.22	—
2018	23	MIX RAW	2 levels	27	18	115	497	80	46	18	67%	4.3	16.1%	9.3%	6.8%	3.6%	4.68	4.94	—
2019	24	MIX MLE	2 levels	25	20	133	561	133	60	18	80%	5.3	19.0%	11.9%	7.1%	3.0%	3.93	4.65	—
2019	24	MIX RAW	2 levels	25	20	133	561	133	60	18	80%	5.3	23.7%	10.7%	13.0%	3.2%	3.93	4.22	—
2022	27	AA MLE	San Antonio Missions	27	7	45	202	44	17	10	26%	1.7	17.6%	9.3%	8.4%	6.8%	6.15	6.53	—
2022	27	AA RAW	San Antonio Missions	27	7	45	202	44	17	10	26%	1.7	21.8%	8.4%	13.4%	5.0%	6.15	5.15	—
2023	28	AA MLE	San Antonio Missions	42	0	60	251	69	25	4	0%	1.4	22.3%	11.0%	11.3%	2.3%	2.69	3.89	—
2023	28	AA RAW	San Antonio Missions	42	0	60	251	69	25	4	0%	1.4	27.5%	10.0%	17.5%	1.6%	2.69	2.92	—
2024	29	MIX MLE	2 levels	57	1	82	355	96	35	13	2%	1.4	23.2%	8.9%	14.3%	4.2%	3.95	4.54	+0.0
2024	29	MIX MLE	2 levels	57	1	82	355	96	35	13	2%	1.4	23.2%	8.9%	14.3%	4.2%	3.95	4.54	+0.0
2024	29	MIX RAW	2 levels	57	1	82	355	96	35	13	2%	1.4	27.0%	9.9%	17.2%	3.7%	3.95	4.10	+0.4
2025	30	MIX MLE	2 levels	56	1	74	307	81	28	10	2%	1.3	25.3%	9.1%	16.2%	3.6%	3.89	4.07	+0.4
2025	30	MIX MLE	2 levels	56	1	74	307	81	28	10	2%	1.3	25.3%	9.1%	16.2%	3.6%	3.89	4.07	+0.4
2025	30	MIX RAW	2 levels	56	1	74	307	81	28	10	2%	1.3	26.4%	9.1%	17.3%	3.3%	3.89	3.80	+0.7
2026	31	MLB MLE	Pittsburgh Pirates	53	12	87	358	93	35	13	23%	1.6	26.0%	9.8%	16.2%	3.9%	3.43	4.30	+0.3
2026	31	MLB MLE	Pittsburgh Pirates	53	12	87	358	93	35	13	23%	1.6	26.0%	9.8%	16.2%	3.9%	3.43	4.30	+0.3
2026	31	MLB RAW	Pittsburgh Pirates	53	12	87	358	93	35	13	23%	1.6	26.0%	9.8%	16.2%	3.6%	3.43	4.12	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			116	13	167	694	179	66	25	11%	1.4	25.8%	9.5%	16.3%	3.6%	3.66	4.09	+0.9
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	PIT	64	0	67	283	75	28	10	0%	1.0	26.4%	9.8%	16.6%	3.6%	4.19	4.46	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	PIT	47	0	50	209	54	21	8	0%	1.1	25.6%	10.3%	15.3%	3.9%	4.52	4.74	-0.1
2029	34	MLB MLE	PIT	33	0	35	147	36	16	6	0%	1.1	24.7%	10.8%	13.9%	4.2%	4.83	5.04	-0.2
2028	33	MLB CTX	PIT	45	0	47	198	51	20	8	0%	1.0	25.6%	10.3%	15.3%	3.9%	4.52	4.74	-0.1
2029	34	MLB CTX	PIT	30	0	32	135	33	15	6	0%	1.1	24.7%	10.8%	13.9%	4.2%	4.83	5.04	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		191	13	246	1026	263	101	38	7%	1.3	25.6%	9.8%	15.8%	3.7%	3.98	4.23	+0.9
/ 200 IP	—	RAW		155	11	200	835	214	82	31	7%	1.3	25.6%	9.8%	15.8%	3.7%	3.98	4.23	+0.8
Career	—	MLE		315	71	684	2875	579	285	113	23%	2.2	20.1%	9.9%	10.2%	3.9%	3.95	4.82	+0.6
/ 200 IP	—	MLE		92	21	200	841	169	83	33	23%	2.2	20.1%	9.9%	10.2%	3.9%	3.95	4.82	+0.5

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.

2024 AAAJacksonville Jumbo Shrimp · 73 IPFIP 3.98 → 4.54 (+0.56)K% 27.0% → 23.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.98%	—	×0.860	23.21%
BB% (unintentional) /BF	9.84%	—	×0.900	8.86%
HR / BF /BF	3.49%	÷0.925	×1.100	4.15%

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 85).

Result: FIP 3.98 → 4.54, 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).

2023 AASan Antonio Missions · 60 IPFIP 2.91 → 3.89 (+0.97)K% 27.5% → 22.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.49%	—	×0.810	22.27%
BB% (unintentional) /BF	9.96%	—	×1.100	10.96%
HR / BF /BF	1.59%	÷0.820	×1.200	2.33%

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 64).

Result: FIP 2.91 → 3.89, 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 AASan Antonio Missions · 45 IPFIP 5.04 → 6.53 (+1.49)K% 21.8% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.78%	—	×0.810	17.64%
BB% (unintentional) /BF	8.42%	—	×1.100	9.26%
HR / BF /BF	4.95%	÷0.870	×1.200	6.83%

Result: FIP 5.04 → 6.53, 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).

2019 AAAmarillo Sod Poodles · 127 IPFIP 4.33 → 4.65 (+0.33)K% 23.5% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.51%	—	×0.810	19.04%
BB% (unintentional) /BF	10.82%	—	×1.100	11.90%
HR / BF /BF	3.36%	÷1.337	×1.200	3.01%

Result: FIP 4.33 → 4.65, 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).

2019 A+Lake Elsinore Storm · 6 IPFIP 1.75 → 2.44 (+0.70)K% 28.0% → 21.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.00%	—	×0.770	21.56%
BB% (unintentional) /BF	8.00%	—	×1.150	9.20%
HR / BF /BF	0.00%	÷0.900	×1.250	0.00%

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 80).

Result: FIP 1.75 → 2.44, 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).

2018 AASan Antonio Missions · 87 IPFIP 5.09 → 6.43 (+1.35)K% 16.0% → 13.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.02%	—	×0.810	12.98%
BB% (unintentional) /BF	9.56%	—	×1.100	10.52%
HR / BF /BF	3.88%	÷0.824	×1.200	5.64%

Result: FIP 5.09 → 6.43, 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).

2018 A+Lake Elsinore Storm · 28 IPFIP 4.25 → 5.46 (+1.21)K% 16.4% → 12.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.36%	—	×0.770	12.60%
BB% (unintentional) /BF	8.18%	—	×1.150	9.41%
HR / BF /BF	2.73%	÷0.839	×1.250	4.06%

Result: FIP 4.25 → 5.46, 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 AFort Wayne TinCaps · 38 IPFIP 4.25 → 5.30 (+1.05)K% 19.0% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.05%	—	×0.740	14.10%
BB% (unintentional) /BF	4.08%	—	×1.180	4.82%
HR / BF /BF	4.08%	÷1.048	×1.300	5.06%

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 110).

Result: FIP 4.25 → 5.30, 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
Lake Bachar (OGILVIE)	—	—	4.46	26.4%	9.8%	3.6%	—	4.86	25.2%	14.7%	84	+0.40	—	—	—
Chris Hatcher R 2017 · 4.31 FIP	32	SU	4.31	24.5%	7.4%	4.3%	.291	5.32	18.0%	8.4%	36	+1.01	2.51	246	63
Nick Martinez R 2023 · 3.62 FIP	32	SU	3.62	23.0%	8.5%	2.5%	.286	3.71	17.3%	13.0%	488	+0.09	2.94	1,288	63
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	63
Jose Veras R 2013 · 3.51 FIP	32	SU	3.51	23.6%	8.3%	2.5%	.234	4.28	21.9%	10.2%	65	+0.77	3.37	422	62
Jumbo Diaz R 2016 · 3.85 FIP	32	SU	3.85	22.3%	9.2%	2.7%	.247	3.28	23.0%	13.8%	141	-0.57	2.80	319	62
Brian Sanches R 2011 · 4.35 FIP	32	SU	4.35	19.6%	11.1%	2.7%	.250	—	—	—	—	—	3.39	229	62
Scot Shields R 2007 · 3.58 FIP	32	SU	3.58	24.1%	10.3%	2.2%	.271	4.26	20.3%	7.3%	127	+0.68	2.77	686	62
Dale Thayer R 2013 · 3.62 FIP	32	SU	3.62	23.7%	7.4%	2.9%	.287	3.85	20.6%	15.0%	103	+0.23	2.75	239	62
Kazuhiro Sasaki R 2000 · 3.93 FIP	32	SU	3.93	29.4%	9.8%	3.8%	.212	2.88	24.9%	19.3%	161	-1.05	2.76	223	61
Hunter Strickland R 2021 · 3.96 FIP	32	SU	3.96	24.0%	9.1%	3.1%	.247	4.38	19.6%	9.6%	147	+0.42	2.30	523	61
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	60
Steve Delabar R 2015 · 3.74 FIP	32	SU	3.74	25.0%	9.9%	2.7%	.246	4.62	20.4%	4.8%	24	+0.88	2.43	229	60
George Kontos R 2017 · 3.71 FIP	32	SU	3.71	25.2%	6.5%	3.5%	.287	4.41	14.7%	8.6%	97	+0.70	2.56	421	60
Aaron Barrett R 2019 · 3.81 FIP	31	SU	3.81	23.0%	8.1%	3.0%	.246	4.56	19.9%	6.4%	38	+0.75	1.86	160	60
Spencer Bivens R 2024 · 4.07 FIP	30	SU	4.07	18.0%	5.8%	3.2%	.265	3.88	18.2%	10.9%	157	-0.19	3.52	391	59
Jon Edwards R 2019 · 4.43 FIP	31	SU	4.43	25.1%	11.6%	3.6%	.290	—	—	—	—	—	2.40	132	59
Santiago Casilla R 2012 · 3.98 FIP	32	SU	3.98	20.2%	6.6%	3.2%	.246	3.23	21.6%	13.7%	166	-0.75	2.76	647	59
Sergio Santos R 2015 · 4.17 FIP	32	SU	4.17	24.7%	8.2%	3.9%	.283	—	—	—	—	—	1.36	178	58
Miguel Socolovich R 2018 · 3.55 FIP	32	SU	3.55	20.8%	5.6%	2.7%	.338	3.55	18.4%	13.7%	42	+0.00	2.65	299	58
Jeff Fulchino R 2011 · 4.44 FIP	31	SU	4.44	20.4%	11.1%	3.0%	.302	—	—	—	—	—	3.36	178	57

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	1.6	64	25.8%	10.1%	1.43	4.04
Noé Ramirez ('22)	1.5	59	24.8%	9.4%	1.42	4.21
Colin Poche ('25)	1.1	54	26.7%	10.2%	1.32	4.01
Robert Stephenson ('25)	1.9	62	25.9%	10.1%	1.54	4.59
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Buddy Schultz ('75-'79, 2 WAR*)	1.2	60	27.4%*	8.5%*	1.21*	4.14*
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*