Eric Lauer

P Los Angeles Dodgers

Age 32 LHP 6'3" / 209 lbs MLB peak 0.1 · 2027 ILInjured 60-Day (D60)

Overview

MLBSPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	AAAHOU	19	16	75	5.26	3.95	25.3%	9.1%	—	K 21.8% · BB 8.2% · FIP 4.47
2025	30	MIX2 levels	33	20	129	3.43	3.63	23.3%	5.9%	2.7	K 22.7% · BB 5.8% · FIP 3.74
2026	31	MLBLAD	22	18	108	5.23	5.86	15.5%	7.5%	-0.5
2027PROJ	32	MLBLAD	7	7	40	4.87	5.26	17.4%	7.3%	0.1
2028PROJ	33	MLBLAD	9	9	52	5.38	5.65	16.5%	7.7%	-0.1
2029PROJ	34	MLBLAD	8	8	47	5.56	5.68	17.6%	7.4%	-0.1

Last 3 seasons WAR 2.2 · Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs24

FB Velo10

K%10

Form8.41 ERA (proj 4.87) · K 16.0% (proj 17.4%) · BB 6.0% (proj 7.3%) · last 90d · 20 IP through Oct 27

CompsArturo Lopez (age 32) · Jorge Castillo (age 33) · Tomas Solis (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 114122vR 130

ERA4.87

FIP5.26

K%17.4%

BB%7.3%

K-BB%10.1%

Proj IP40

Value2027 · WAR

Runs saved vs league avg · 40 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1091.1

Whiff%

p1018.6%

p1015.5%

xwOBA vs

p240.342

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	2 levels	3	3	6	27	9	2	1	100%	2.0	33.3%	7.4%	25.9%	3.7%	4.50	3.26	—
2016	21	MIX RAW	2 levels	3	3	6	27	9	2	1	100%	2.0	33.3%	7.4%	25.9%	3.7%	4.50	3.27	—
2017	22	MIX MLE	2 levels	22	21	123	511	132	36	10	95%	5.6	20.3%	7.9%	12.3%	2.6%	3.30	3.80	—
2017	22	MIX RAW	2 levels	22	21	123	511	132	36	10	95%	5.6	25.8%	7.0%	18.8%	2.0%	3.30	2.89	—
2018	23	MIX MLE	3 levels	28	28	136	601	126	54	16	100%	4.9	20.2%	9.1%	11.2%	2.7%	3.96	4.00	+2.3
2018	23	MIX RAW	3 levels	28	28	136	601	126	54	16	100%	4.9	21.0%	9.0%	12.0%	2.7%	3.96	3.97	+2.3
2019	24	MLB MLE	San Diego Padres	30	29	150	651	138	47	20	97%	5.0	21.2%	7.2%	14.0%	3.0%	4.45	3.87	+2.7
2019	24	MLB RAW	San Diego Padres	30	29	150	651	138	47	20	97%	5.0	21.2%	7.2%	14.0%	3.1%	4.45	3.94	+2.6
2020	25	MLB MLE	Milwaukee Brewers	4	2	11	61	12	9	2	50%	2.8	19.7%	14.8%	4.9%	3.1%	13.09	5.02	+0.0
2020	25	MLB RAW	Milwaukee Brewers	4	2	11	61	12	9	2	50%	2.8	19.7%	14.8%	4.9%	3.3%	13.09	5.74	-0.0
2021	26	MIX MLE	2 levels	25	21	124	506	129	42	16	84%	4.9	23.9%	8.2%	15.7%	3.1%	3.06	3.83	+2.3
2021	26	MIX RAW	2 levels	25	21	124	506	129	42	16	84%	4.9	25.5%	8.3%	17.2%	3.2%	3.06	3.71	+2.5
2022	27	MLB MLE	Milwaukee Brewers	29	29	159	661	157	59	27	100%	5.5	23.8%	8.9%	14.8%	3.9%	3.69	4.36	+1.9
2022	27	MLB RAW	Milwaukee Brewers	29	29	159	661	157	59	27	100%	5.5	23.8%	8.9%	14.8%	4.1%	3.69	4.45	+1.8
2023	28	MIX MLE	3 levels	23	19	91	420	109	48	22	83%	4.0	23.5%	10.7%	12.8%	5.4%	5.81	5.44	-0.0
2023	28	MIX RAW	3 levels	23	19	91	420	109	48	22	83%	4.0	26.0%	11.4%	14.5%	5.2%	5.81	5.42	-0.0
2024	29	AAA MLE	Sugar Land Space Cowboys	19	16	75	340	86	31	11	84%	4.0	21.8%	8.2%	13.5%	3.9%	5.26	4.47	—
2024	29	AAA MLE	Sugar Land Space Cowboys	19	16	75	340	86	31	11	84%	4.0	21.8%	8.2%	13.5%	3.9%	5.26	4.47	—
2024	29	AAA RAW	Sugar Land Space Cowboys	19	16	75	340	86	31	11	84%	4.0	25.3%	9.1%	16.2%	3.2%	5.26	3.95	—
2025	30	MIX MLE	2 levels	33	20	129	528	123	31	17	61%	3.9	22.7%	5.8%	17.0%	3.3%	3.43	3.74	+2.6
2025	30	MIX MLE	2 levels	33	20	129	528	123	31	17	61%	3.9	22.7%	5.8%	17.0%	3.3%	3.43	3.74	+2.6
2025	30	MIX RAW	2 levels	33	20	129	528	123	31	17	61%	3.9	23.3%	5.9%	17.4%	3.2%	3.43	3.63	+2.7
2026	31	MLB MLE	Los Angeles Dodgers	22	18	108	466	72	35	26	82%	4.9	15.5%	7.5%	7.9%	5.4%	5.23	5.68	-0.3
2026	31	MLB MLE	Los Angeles Dodgers	22	18	108	466	72	35	26	82%	4.9	15.5%	7.5%	7.9%	5.4%	5.23	5.68	-0.3
2026	31	MLB RAW	Los Angeles Dodgers	22	18	108	466	72	35	26	82%	4.9	15.5%	7.5%	7.9%	5.6%	5.23	5.86	-0.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			170	145	810	3469	741	283	137	85%	4.8	21.4%	8.2%	13.2%	3.9%	4.28	4.52	+8.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	LAD	7	7	40	169	29	12	7	100%	5.7	17.4%	7.3%	10.1%	4.2%	4.87	5.26	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	LAD	9	9	52	218	36	17	10	100%	5.7	16.5%	7.7%	8.8%	4.5%	5.27	5.54	-0.1
2029	34	MLB MLE	LAD	8	8	47	199	35	15	10	100%	5.9	17.6%	7.4%	10.2%	4.8%	5.45	5.57	-0.1
2028	33	MLB CTX	LAD	9	9	52	220	36	17	10	100%	5.8	16.5%	7.7%	8.8%	4.7%	5.38	5.65	-0.1
2029	34	MLB CTX	LAD	8	8	47	198	35	15	10	100%	5.9	17.6%	7.4%	10.2%	5.0%	5.56	5.68	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		186	161	909	3887	812	315	157	87%	4.9	20.9%	8.1%	12.8%	4.0%	4.41	4.58	+8.6
/ 200 IP	—	RAW		41	36	200	856	179	69	35	87%	4.9	20.9%	8.1%	12.8%	4.0%	4.41	4.58	+1.9
Career	—	MLE		238	206	1112	4772	1027	392	172	87%	4.7	21.5%	8.2%	13.3%	3.6%	4.21	4.30	+8.1
/ 200 IP	—	MLE		43	37	200	859	185	70	31	87%	4.7	21.5%	8.2%	13.3%	3.6%	4.21	4.30	+1.8

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 AAABuffalo Bisons · 24 IPFIP 3.18 → 3.67 (+0.49)K% 20.6% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.59%	—	×0.860	17.71%
BB% (unintentional) /BF	5.88%	—	×0.900	5.29%
HR / BF /BF	1.96%	÷0.847	×1.100	2.55%

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 69).

Result: FIP 3.18 → 3.67, 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 AAASugar Land Space Cowboys · 75 IPFIP 3.89 → 4.47 (+0.57)K% 25.3% → 21.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.29%	—	×0.860	21.75%
BB% (unintentional) /BF	9.12%	—	×0.900	8.21%
HR / BF /BF	3.24%	÷0.903	×1.100	3.94%

Result: FIP 3.89 → 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).

2023 AAANashville Sounds · 44 IPFIP 3.49 → 4.06 (+0.57)K% 31.1% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.07%	—	×0.860	26.72%
BB% (unintentional) /BF	11.17%	—	×0.900	10.05%
HR / BF /BF	2.91%	÷0.905	×1.100	3.54%

Result: FIP 3.49 → 4.06, 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).

2018 AAAEl Paso Chihuahuas · 21 IPFIP 2.90 → 3.26 (+0.36)K% 25.6% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.58%	—	×0.880	22.51%
BB% (unintentional) /BF	10.47%	—	×1.050	10.99%
HR / BF /BF	1.16%	÷1.045	×1.100	1.22%

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 109).

Result: FIP 2.90 → 3.26, 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).

2017 A+Lake Elsinore Storm · 68 IPFIP 2.22 → 3.20 (+0.98)K% 29.6% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.58%	—	×0.770	22.77%
BB% (unintentional) /BF	6.69%	—	×1.150	7.69%
HR / BF /BF	1.41%	÷0.921	×1.250	1.91%

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 84).

Result: FIP 2.22 → 3.20, 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 AASan Antonio Missions · 55 IPFIP 3.71 → 4.55 (+0.84)K% 21.1% → 17.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.15%	—	×0.810	17.13%
BB% (unintentional) /BF	7.49%	—	×1.100	8.24%
HR / BF /BF	2.64%	÷0.940	×1.200	3.37%

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 88).

Result: FIP 3.71 → 4.55, 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 ROKAZL Padres · 4 IPFIP 3.52 → 5.72 (+2.20)K% 35.0% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.00%	—	×0.680	23.80%
BB% (unintentional) /BF	5.00%	—	×1.250	6.25%
HR / BF /BF	5.00%	÷1.000	×1.400	7.00%

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 3.52 → 5.72, 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
Eric Lauer (OGILVIE)	—	—	—	—	—	4.2%	—	5.55	17.1%	9.5%	99	+0.29	—	—	—
Arturo Lopez L 2015 · 4.80 FIP	32	SP	4.80	13.7%	6.2%	3.8%	.301	4.80	10.9%	4.2%	217	+0.00	4.34	445	70
Jorge Castillo L 2015 · 4.50 FIP	33	SP	4.50	16.8%	9.2%	3.0%	.292	4.95	12.4%	7.2%	186	+0.45	4.50	408	69
Tomas Solis L 2015 · 4.20 FIP	32	SP	4.20	15.0%	6.2%	2.9%	.264	5.09	12.0%	3.7%	159	+0.89	4.20	327	69
Brandon Mann L 2016 · 4.72 FIP	32	SP	4.72	19.4%	7.9%	4.1%	.320	3.97	19.0%	7.6%	128	-0.75	3.59	190	66
Orlando Lara L 2017 · 4.39 FIP	32	SP	4.39	14.7%	6.5%	3.1%	.346	4.09	22.0%	14.2%	104	-0.30	3.85	426	64
Everett Teaford L 2015 · 4.42 FIP	31	SP-	4.42	13.9%	7.6%	2.8%	.324	—	—	—	—	—	4.42	208	62
Kelvin Marte L 2019 · 5.25 FIP	31	SP	5.25	12.0%	10.8%	3.3%	.340	—	—	—	—	—	3.44	360	57
Matt Dermody L 2022 · 4.22 FIP	32	SP-	4.22	17.9%	5.5%	3.5%	.302	3.87	20.7%	16.1%	49	-0.35	2.38	348	55
Sean Nolin L 2021 · 4.54 FIP	31	SP-	4.54	20.4%	8.9%	3.7%	.316	5.87	19.3%	12.9%	23	+1.33	3.79	309	54
Kaz Ishii L 2005 · 5.23 FIP	31	SP	5.23	13.3%	11.5%	3.3%	.258	—	—	—	—	—	4.51	564	54
Mark Hendrickson L 2006 · 4.33 FIP	32	SP-	4.33	13.8%	8.6%	2.4%	.288	4.28	14.8%	8.8%	361	-0.05	3.04	1,169	53
Darrell May L 2004 · 5.17 FIP	32	SP	5.17	14.4%	6.1%	4.6%	.315	5.59	11.6%	4.3%	66	+0.42	4.24	657	49
Mike Montgomery L 2021 · 4.49 FIP	32	SP	4.49	18.5%	12.4%	2.5%	.347	4.44	15.5%	3.4%	147	-0.05	3.43	764	49
Anthony Vasquez L 2019 · 6.00 FIP	32	SW	6.00	14.6%	7.3%	5.9%	.383	—	—	—	—	—	4.02	671	48
Travis Blackley L 2015 · 4.91 FIP	32	SP-	4.91	15.4%	6.4%	4.2%	.324	4.45	10.5%	0.0%	137	-0.46	3.85	409	47
Luke Westphal L 2021 · 4.70 FIP	32	SP-	4.70	22.7%	13.1%	3.4%	.321	4.58	21.9%	7.6%	95	-0.12	2.97	294	43
Randy Keisler L 2007 · 5.51 FIP	31	SP-	5.51	6.5%	6.5%	3.9%	.281	—	—	—	—	—	5.07	135	43
Paul Oseguera L 2016 · 5.62 FIP	32	SP	5.62	5.6%	12.5%	2.6%	.320	—	—	—	—	—	3.83	162	42
Tim Adleman R 2019 · 4.30 FIP	31	SP	4.30	22.8%	7.8%	3.9%	.266	4.71	18.5%	11.1%	90	+0.41	3.63	605	37
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	36

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	4.8	95	20.7%	8.3%	1.56	4.42
Jerry Garvin ('77-'82, 4 WAR*)	3.0	101	19.3%*	8.4%*	1.44*	4.52*
Drew Smyly ('24)	5.7	104	23.1%	7.7%	1.49	4.20
Mark Leiter ('90-'01, 5 WAR*)	5.9	118	20.7%*	7.8%*	1.36*	4.61*
Chase Anderson ('24)	5.5	101	19.7%	8.1%	1.48	4.41
Daniel Norris ('23)	2.9	73	21.5%	8.9%	1.39	4.73
Joe Price ('80-'90, 7 WAR*)	4.5	82	23.3%*	8.8%*	1.49*	4.15*