Luis Contreras

P Sugar Land Space Cowboys

Age 31 RHP 6'1" / 175 lbs AAA

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	27	MIX2 levels	39	0	63	4.55	2.97	31.8%	9.5%	—	K 26.8% · BB 9.1% · FIP 3.60
2024	28	MIX2 levels	52	0	53	2.56	2.91	27.2%	10.2%	1.0	K 23.9% · BB 9.5% · FIP 3.40
2025	29	MIX2 levels	54	0	58	4.47	4.18	21.6%	14.1%	0.3	K 19.3% · BB 13.0% · FIP 4.30
2026	30	No MLB games played
2027PROJ	31	MLBHOU	6	0	6	4.75	5.00	20.5%	13.5%	-0.0
2028PROJ37% MLB	32	MLBHOU	15	0	16	4.99	5.19	20.0%	13.5%	-0.1
2029PROJ55% MLB	33	MLBHOU	18	0	19	5.21	5.41	19.4%	13.6%	-0.2

Last 3 seasons WAR 1.3 · Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

xwOBA vs71

K%60

FB Velo10

CompsJim Miller (age 30) · Dustin Molleken (age 31) · Neil Wagner (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 128120vR 112

ERA4.75

FIP5.00

K%20.5%

BB%13.5%

K-BB%7.0%

Proj IP63

Value2027 · WAR

Runs saved vs league avg · 63 IP

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL3535

CMD4040

K†5050

Statcast Percentiles

FB Velo

p1091.1

Whiff%

p9032.3%

p6024.1%

xwOBA vs

p710.292

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)
2019	23	MIX MLE	3 levels	16	4	50	203	73	22	3	25%	3.1	26.4%	12.8%	13.7%	2.0%	2.86	3.59	—
2019	23	MIX RAW	3 levels	16	4	50	203	73	22	3	25%	3.1	36.0%	10.8%	25.1%	1.5%	2.86	2.29	—
2021	25	AA MLE	Biloxi Shuckers	3	3	9	40	19	3	2	100%	2.9	47.5%	7.5%	40.0%	5.0%	5.19	2.78	—
2021	25	AA RAW	Biloxi Shuckers	3	3	9	40	19	3	2	100%	2.9	47.5%	7.5%	40.0%	5.0%	5.19	2.75	—
2022	26	MIX MLE	2 levels	35	0	51	223	73	29	4	0%	1.5	26.8%	12.4%	14.5%	1.3%	3.88	3.13	—
2022	26	MIX RAW	2 levels	35	0	51	223	73	29	4	0%	1.5	32.7%	13.0%	19.7%	1.8%	3.88	2.96	—
2023	27	MIX MLE	2 levels	39	0	63	283	90	27	7	0%	1.6	26.8%	9.1%	17.8%	3.0%	4.55	3.60	—
2023	27	MIX RAW	2 levels	39	0	63	283	90	27	7	0%	1.6	31.8%	9.5%	22.3%	2.5%	4.55	2.97	—
2024	28	MIX MLE	2 levels	52	0	53	206	56	21	3	0%	1.0	23.9%	9.5%	14.4%	2.0%	2.56	3.40	+0.7
2024	28	MIX MLE	2 levels	52	0	53	206	56	21	3	0%	1.0	23.9%	9.5%	14.4%	2.0%	2.56	3.40	+0.7
2024	28	MIX RAW	2 levels	52	0	53	206	56	21	3	0%	1.0	27.2%	10.2%	17.0%	1.5%	2.56	2.91	+1.0
2025	29	MIX MLE	2 levels	54	0	58	255	55	36	5	0%	1.1	19.3%	13.0%	6.2%	2.2%	4.47	4.30	+0.2
2025	29	MIX MLE	2 levels	54	0	58	255	55	36	5	0%	1.1	19.3%	13.0%	6.2%	2.2%	4.47	4.30	+0.2
2025	29	MIX RAW	2 levels	54	0	58	255	55	36	5	0%	1.1	21.6%	14.1%	7.5%	2.0%	4.47	4.18	+0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			14	0	18	80	19	10	2	0%	1.3	23.8%	12.5%	11.2%	2.5%	7.50	4.10	+0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	HOU	6	0	6	25	5	3	1	0%	1.0	20.5%	13.5%	7.0%	2.8%	4.75	5.00	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	HOU	42	0	44	188	37	25	6	0%	1.1	20.0%	13.5%	6.5%	3.1%	4.99	5.19	-0.3
2029	33	MLB MLE	HOU	33	0	35	147	29	20	5	0%	1.1	19.4%	13.6%	5.8%	3.3%	5.21	5.41	-0.3
2028	32	MLB CTX	HOU	15	0	16	68	13	9	2	0%	1.1	20.0%	13.5%	6.5%	3.1%	4.99	5.19	-0.1
2029	33	MLB CTX	HOU	18	0	19	80	16	11	3	0%	1.1	19.4%	13.6%	5.8%	3.3%	5.21	5.41	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		48	0	54	230	49	30	7	0%	1.1	21.1%	13.2%	7.9%	3.0%	5.91	4.62	-0.0
/ 200 IP	—	RAW		179	0	200	859	183	112	26	0%	1.1	21.1%	13.2%	7.9%	3.0%	5.91	4.62	-0.2
Career	—	MLE		199	7	284	1210	307	135	27	4%	1.4	25.4%	11.2%	14.2%	2.2%	3.77	3.60	-0.6
/ 200 IP	—	MLE		140	5	200	851	216	95	19	4%	1.4	25.4%	11.2%	14.2%	2.2%	3.77	3.60	-1.2

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 AAASugar Land Space Cowboys · 46 IPFIP 3.92 → 4.11 (+0.19)K% 20.9% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.90%	—	×0.860	17.97%
BB% (unintentional) /BF	13.93%	—	×0.900	12.54%
HR / BF /BF	1.49%	÷0.961	×1.100	1.71%

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 92).

Result: FIP 3.92 → 4.11, 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 · 47 IPFIP 3.01 → 3.40 (+0.39)K% 27.8% → 23.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.78%	—	×0.860	23.89%
BB% (unintentional) /BF	10.56%	—	×0.900	9.50%
HR / BF /BF	1.67%	÷0.903	×1.100	2.03%

Result: FIP 3.01 → 3.40, 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 · 45 IPFIP 3.16 → 3.69 (+0.53)K% 30.3% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.35%	—	×0.860	26.10%
BB% (unintentional) /BF	9.95%	—	×0.900	8.96%
HR / BF /BF	2.49%	÷0.905	×1.100	3.02%

Result: FIP 3.16 → 3.69, 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 AABiloxi Shuckers · 18 IPFIP 2.53 → 3.39 (+0.86)K% 35.4% → 28.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.37%	—	×0.810	28.65%
BB% (unintentional) /BF	8.54%	—	×1.100	9.39%
HR / BF /BF	2.44%	÷1.055	×1.200	2.77%

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 111).

Result: FIP 2.53 → 3.39, 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 AABiloxi Shuckers · 42 IPFIP 2.34 → 3.13 (+0.79)K% 33.1% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.15%	—	×0.810	26.85%
BB% (unintentional) /BF	11.24%	—	×1.100	12.36%
HR / BF /BF	1.12%	÷1.012	×1.200	1.33%

Result: FIP 2.34 → 3.13, 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 AAANashville Sounds · 9 IPFIP 5.45 → 6.28 (+0.84)K% 31.1% → 27.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.11%	—	×0.880	27.38%
BB% (unintentional) /BF	20.00%	—	×1.050	21.00%
HR / BF /BF	4.44%	÷0.946	×1.100	5.17%

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 89).

Result: FIP 5.45 → 6.28, 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 AABiloxi Shuckers · 9 IPFIP 2.78 → 4.44 (+1.66)K% 47.5% → 38.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	47.50%	—	×0.810	38.48%
BB% (unintentional) /BF	7.50%	—	×1.100	8.25%
HR / BF /BF	5.00%	÷0.929	×1.200	6.46%

Result: FIP 2.78 → 4.44, 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).

2019 AWisconsin Timber Rattlers · 25 IPFIP 3.42 → 4.77 (+1.35)K% 30.8% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.77%	—	×0.740	22.77%
BB% (unintentional) /BF	10.58%	—	×1.180	12.48%
HR / BF /BF	2.88%	÷1.022	×1.300	3.67%

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 104).

Result: FIP 3.42 → 4.77, 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
Luis Contreras (OGILVIE)	—	—	5.00	20.5%	13.5%	2.8%	—	5.29	19.7%	6.2%	79	+0.29	—	—	—
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	79
Dustin Molleken R 2016 · 4.04 FIP	31	SU	4.04	19.6%	12.1%	1.9%	.276	3.38	24.3%	11.9%	16	-0.66	3.38	129	79
Neil Wagner R 2016 · 4.05 FIP	32	SU	4.05	19.8%	12.3%	1.9%	.360	3.11	20.7%	12.1%	54	-0.94	3.11	135	77
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	75
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	72
Peter Moylan R 2010 · 4.02 FIP	31	SU	4.02	19.2%	11.4%	2.0%	.262	5.72	8.6%	0.0%	15	+1.70	2.54	431	72
Brian Sanches R 2010 · 4.24 FIP	31	SU	4.24	21.3%	10.6%	2.9%	.217	4.35	19.6%	8.5%	62	+0.11	3.39	229	71
Miguel Mejia R 2019 · 4.41 FIP	31	SU	4.41	15.7%	10.7%	2.3%	.341	—	—	—	—	—	3.37	108	71
Jeff Fulchino R 2011 · 4.44 FIP	31	SU	4.44	20.4%	11.1%	3.0%	.302	—	—	—	—	—	3.36	178	71
Manny Acosta R 2012 · 4.49 FIP	31	SU	4.49	21.3%	11.1%	3.2%	.295	—	—	—	—	—	3.08	350	71
Scott Atchison R 2007 · 4.55 FIP	31	SU	4.55	19.1%	7.6%	3.8%	.297	4.59	16.2%	9.5%	60	+0.04	2.52	340	71
Fredy Quintero R 2019 · 4.62 FIP	31	SU	4.62	17.2%	13.7%	2.2%	.310	—	—	—	—	—	4.29	241	70
Kerry Ligtenberg R 2002 · 4.09 FIP	31	SU	4.09	18.1%	10.7%	2.1%	.237	3.86	18.8%	13.2%	114	-0.23	2.94	381	70
Grant Black R 2023 · 5.49 FIP	29	SU	5.49	15.9%	11.3%	4.2%	.352	—	—	—	—	—	4.46	215	70
Luis Angel Daniel R 2016 · 4.56 FIP	31	SU	4.56	13.4%	8.9%	2.7%	.286	4.16	9.8%	0.3%	53	-0.40	4.16	156	70
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	70
Antonio Guzman R 2019 · 4.96 FIP	31	SU	4.96	19.3%	14.7%	3.0%	.326	—	—	—	—	—	3.15	254	68
Dalier Hinojosa R 2016 · 4.30 FIP	30	SU	4.30	18.7%	12.6%	2.2%	.329	—	—	—	—	—	3.41	104	68
Tyler Sturdevant R 2017 · 4.48 FIP	31	SU	4.48	13.5%	6.7%	3.0%	.300	—	—	—	—	—	3.44	149	68
Rudy Gonzalez R 2015 · 4.52 FIP	34	SW	4.52	13.5%	9.6%	2.4%	.347	3.84	14.0%	6.5%	79	-0.68	3.31	119	67

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	0.8	54	20.5%	13.4%	1.15	5.22
Matt Anderson ('05)	1.3	51	19.3%	13.5%	1.05	5.19
Tyler Yates ('09)	1.2	62	19.7%	12.0%	0.94	5.12
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
John Hudek ('99)	1.0	40	23.0%	13.7%	1.30	4.43
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*