Domingo Robles

P Las Vegas Aviators

Age 29 LHP 6'2" / 170 lbs AAA peak 0.3 · 2027

Overview

AAAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX2 levels	22	14	87	2.91	2.88	26.8%	7.1%	—	K 21.1% · BB 7.9% · FIP 3.79
2025	27	MIX3 levels	14	5	42	4.04	3.24	21.7%	5.7%	—	K 15.2% · BB 5.8% · FIP 3.97
2026	28	MIX2 levels	41	1	76	5.68	4.11	16.8%	9.9%	—	K 14.0% · BB 9.7% · FIP 4.39
2027PROJ	29	MLBOAK	1	1	3	4.66	4.66	16.0%	7.7%	0.0
2028PROJ31% MLB	30	MLBOAK	6	6	39	4.72	4.79	16.3%	8.0%	0.3
2029PROJ51% MLB	31	MLBOAK	8	8	54	4.85	4.95	16.3%	8.3%	0.3

Next 3 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 0.0 / P90 0.1, comp-based) · star 0% · didn't stick 99%

CompsChris Michalak (age 30) · Danny Wirchansky (age 27) · James Gillheeney (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 105114vR 122

ERA4.66

FIP4.66

K%16.0%

BB%7.7%

K-BB%8.3%

Proj IP165

Value2027 · WAR

Runs saved vs league avg · 165 IP

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	17	ROK MLE	DSL Pirates	15	15	68	295	44	20	4	100%	4.6	10.1%	8.5%	1.7%	1.9%	3.95	4.36	—
2015	17	ROK RAW	DSL Pirates	15	15	68	295	44	20	4	100%	4.6	14.9%	6.8%	8.1%	1.4%	3.95	3.45	—
2016	18	ROK MLE	GCL Pirates	9	5	36	152	18	4	3	56%	4.0	8.1%	3.3%	4.8%	2.8%	4.25	4.35	—
2016	18	ROK RAW	GCL Pirates	9	5	36	152	18	4	3	56%	4.0	11.8%	2.6%	9.2%	2.0%	4.25	3.52	—
2017	19	ROK MLE	Bristol Pirates	14	14	69	303	51	16	5	100%	4.9	11.4%	6.6%	4.8%	2.3%	4.83	4.24	—
2017	19	ROK RAW	Bristol Pirates	14	14	69	303	51	16	5	100%	4.9	16.8%	5.3%	11.6%	1.7%	4.83	3.26	—
2018	20	MIX MLE	2 levels	26	26	143	608	107	36	9	100%	5.5	13.1%	6.9%	6.2%	1.6%	3.33	3.77	—
2018	20	MIX RAW	2 levels	26	26	143	608	107	36	9	100%	5.5	17.6%	5.9%	11.7%	1.5%	3.33	3.18	—
2019	21	MIX MLE	2 levels	28	28	165	684	124	36	18	100%	5.9	14.4%	5.9%	8.5%	3.8%	3.49	4.70	—
2019	21	MIX RAW	2 levels	28	28	165	684	124	36	18	100%	5.9	18.1%	5.3%	12.9%	2.6%	3.49	3.67	—
2021	23	AA MLE	Springfield Cardinals	23	21	92	411	78	24	18	91%	4.0	15.4%	6.4%	8.9%	5.3%	6.09	5.53	—
2021	23	AA RAW	Springfield Cardinals	23	21	92	411	78	24	18	91%	4.0	19.0%	5.8%	13.1%	4.4%	6.09	4.74	—
2022	24	AA MLE	Springfield Cardinals	30	10	110	495	70	42	12	33%	3.7	11.5%	9.3%	2.1%	2.7%	6.14	4.81	—
2022	24	AA RAW	Springfield Cardinals	30	10	110	495	70	42	12	33%	3.7	14.1%	8.5%	5.7%	2.4%	6.14	4.39	—
2023	25	MIX MLE	2 levels	26	24	129	546	131	38	10	92%	5.0	19.5%	7.4%	12.1%	2.7%	3.91	3.87	—
2023	25	MIX RAW	2 levels	26	24	129	546	131	38	10	92%	5.0	24.0%	7.0%	17.0%	1.8%	3.91	2.96	—
2024	26	MIX MLE	2 levels	22	14	87	340	91	24	7	64%	3.9	21.1%	7.9%	13.2%	2.7%	2.91	3.79	—
2024	26	MIX MLE	2 levels	22	14	87	340	91	24	7	64%	3.9	21.1%	7.9%	13.2%	2.7%	2.91	3.79	—
2024	26	MIX RAW	2 levels	22	14	87	340	91	24	7	64%	3.9	26.8%	7.1%	19.7%	2.1%	2.91	2.88	—
2025	27	MIX MLE	3 levels	14	5	42	175	38	10	4	36%	3.0	15.2%	5.8%	9.4%	2.6%	4.04	3.97	—
2025	27	MIX MLE	3 levels	14	5	42	175	38	10	4	36%	3.0	15.2%	5.8%	9.4%	2.6%	4.04	3.97	—
2025	27	MIX RAW	3 levels	14	5	42	175	38	10	4	36%	3.0	21.7%	5.7%	16.0%	2.3%	4.04	3.24	—
2026	28	MIX MLE	2 levels	41	1	76	345	58	34	7	2%	1.9	14.0%	9.7%	4.2%	2.3%	5.68	4.39	—
2026	28	MIX MLE	2 levels	41	1	76	345	58	34	7	2%	1.9	14.0%	9.7%	4.2%	2.3%	5.68	4.39	—
2026	28	MIX RAW	2 levels	41	1	76	345	58	34	7	2%	1.9	16.8%	9.9%	7.0%	2.0%	5.68	4.11	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	OAK	1	1	3	13	2	1	0	100%	3.0	16.0%	7.7%	8.3%	2.8%	4.66	4.66	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	OAK	19	19	126	532	87	43	16	100%	6.6	16.3%	8.0%	8.3%	3.1%	4.72	4.79	+0.9
2029	31	MLB MLE	OAK	16	16	105	444	72	37	15	100%	6.6	16.3%	8.3%	8.0%	3.3%	4.85	4.95	+0.5
2030	32	MLB MLE	OAK	14	14	91	383	62	33	13	100%	6.5	16.1%	8.7%	7.4%	3.5%	5.01	5.14	+0.3
2028	30	MLB CTX	OAK	6	6	39	165	27	13	5	100%	6.5	16.3%	8.0%	8.3%	3.1%	4.72	4.79	+0.3
2029	31	MLB CTX	OAK	8	8	54	228	37	19	7	100%	6.8	16.3%	8.3%	8.0%	3.3%	4.85	4.95	+0.3
2030	32	MLB CTX	OAK	9	9	59	249	40	22	9	100%	6.6	16.1%	8.7%	7.4%	3.5%	5.01	5.14	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		23	23	153	644	105	54	21	100%	6.6	16.2%	8.4%	7.8%	3.3%	4.88	4.61	+1.4
/ 200 IP	—	RAW		30	30	200	844	138	71	28	100%	6.6	16.2%	8.4%	7.8%	3.3%	4.88	4.61	+1.8
Career	—	MLE		248	163	1017	4354	628	316	124	66%	4.1	14.4%	7.3%	7.2%	2.8%	4.33	4.36	+1.7
/ 200 IP	—	MLE		49	32	200	856	124	62	24	66%	4.1	14.4%	7.3%	7.2%	2.8%	4.33	4.36	+1.1

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.

2026 AAALas Vegas Aviators · 35 IPFIP 5.17 → 5.40 (+0.22)K% 14.5% → 12.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.45%	—	×0.860	12.43%
BB% (unintentional) /BF	10.98%	—	×0.900	9.88%
HR / BF /BF	3.47%	÷1.000	×1.100	3.82%

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 100).

Result: FIP 5.17 → 5.40, 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).

2026 AAMidland RockHounds · 41 IPFIP 2.90 → 3.39 (+0.48)K% 19.2% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.19%	—	×0.810	15.54%
BB% (unintentional) /BF	8.72%	—	×1.100	9.59%
HR / BF /BF	0.58%	÷1.000	×1.200	0.70%

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 100).

Result: FIP 2.90 → 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).

2025 AAMidland RockHounds · 32 IPFIP 3.42 → 3.97 (+0.56)K% 18.8% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.80%	—	×0.810	15.23%
BB% (unintentional) /BF	5.26%	—	×1.100	5.79%
HR / BF /BF	2.26%	÷1.043	×1.200	2.60%

Result: FIP 3.42 → 3.97, 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 ROKACL Athletics · 9 IPFIP 0.57 → 1.58 (+1.02)K% 34.3% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.29%	—	×0.680	23.31%
BB% (unintentional) /BF	2.86%	—	×1.250	3.57%
HR / BF /BF	0.00%	÷0.926	×1.400	0.00%

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 85).

Result: FIP 0.57 → 1.58, 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 AAMidland RockHounds · 85 IPFIP 2.96 → 3.79 (+0.83)K% 26.0% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.05%	—	×0.810	21.10%
BB% (unintentional) /BF	7.19%	—	×1.100	7.90%
HR / BF /BF	2.10%	÷0.940	×1.200	2.67%

Result: FIP 2.96 → 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).

2023 AAMississippi Braves · 119 IPFIP 2.89 → 3.87 (+0.98)K% 24.1% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.09%	—	×0.810	19.51%
BB% (unintentional) /BF	6.48%	—	×1.100	7.13%
HR / BF /BF	1.82%	÷0.793	×1.200	2.76%

Result: FIP 2.89 → 3.87, 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 AAAGwinnett Stripers · 10 IPFIP 3.67 → 3.92 (+0.25)K% 23.1% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.860	19.85%
BB% (unintentional) /BF	11.54%	—	×0.900	10.38%
HR / BF /BF	1.92%	÷0.984	×1.100	2.15%

Result: FIP 3.67 → 3.92, 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 AASpringfield Cardinals · 110 IPFIP 4.31 → 4.81 (+0.50)K% 14.1% → 11.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.14%	—	×0.810	11.45%
BB% (unintentional) /BF	8.48%	—	×1.100	9.33%
HR / BF /BF	2.42%	÷1.069	×1.200	2.72%

Result: FIP 4.31 → 4.81, 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
Domingo Robles (OGILVIE)	—	—	—	—	—	2.8%	—	4.94	16.3%	7.9%	322	+0.28	—	—	—
Chris Michalak L 2001 · 4.92 FIP	30	SP-	4.92	11.0%	8.2%	3.1%	.291	4.71	7.0%	-4.3%	14	-0.21	4.71	186	80
Danny Wirchansky L 2024 · 4.47 FIP	27	SP-	4.47	16.2%	7.4%	3.3%	.246	5.88	13.0%	0.2%	68	+1.41	4.47	179	79
James Gillheeney L 2015 · 3.79 FIP	27	SP-	3.79	14.4%	8.0%	1.6%	.300	—	—	—	—	—	3.79	129	78
John Anderson L 2016 · 4.23 FIP	27	SP-	4.23	14.3%	8.7%	2.2%	.367	—	—	—	—	—	4.12	235	75
Yohan Flande L 2015 · 4.68 FIP	29	SP-	4.68	12.9%	5.5%	3.6%	.289	3.27	15.1%	8.4%	172	-1.41	3.18	394	68
Kyle Hald L 2015 · 4.33 FIP	26	SP	4.33	12.1%	7.4%	2.4%	.313	—	—	—	—	—	4.33	124	66
Matt Crouse L 2017 · 4.64 FIP	27	SP	4.64	12.0%	7.4%	2.9%	.308	—	—	—	—	—	3.99	342	66
Aaron Rozek L 2024 · 3.68 FIP	28	SP-	3.68	16.2%	5.8%	2.2%	.304	4.68	16.9%	9.0%	234	+1.00	3.68	579	66
Miguel Cienfuegos L 2024 · 5.19 FIP	27	SP-	5.19	12.4%	7.9%	3.9%	.290	3.85	16.3%	7.3%	118	-1.34	2.95	313	66
Carlos Teller L 2016 · 4.86 FIP	29	SP-	4.86	14.3%	10.7%	2.9%	.297	4.74	12.6%	1.1%	148	-0.12	3.75	333	64
Tommy Shirley L 2016 · 4.93 FIP	27	SP-	4.93	13.0%	8.8%	3.3%	.366	—	—	—	—	—	3.35	147	64
Darrell May L 2002 · 5.40 FIP	30	SP-	5.40	16.4%	8.1%	4.8%	.284	5.02	13.5%	7.2%	462	-0.38	4.24	657	63
Edgar Osuna L 2017 · 5.05 FIP	29	SP	5.05	10.6%	8.2%	3.3%	.345	5.09	10.0%	2.8%	83	+0.04	5.05	175	62
Logan Darnell L 2018 · 4.73 FIP	29	SP-	4.73	13.3%	6.0%	3.6%	.327	3.97	12.8%	6.7%	47	-0.76	3.16	454	62
Carlos Hernandez L 2016 · 3.47 FIP	29	SP-	3.47	13.4%	3.6%	1.9%	.386	2.97	16.1%	11.4%	171	-0.50	2.83	331	61
Scott Downs L 2005 · 4.22 FIP	29	SP-	4.22	18.4%	8.4%	2.9%	.283	3.29	20.5%	12.9%	206	-0.93	2.68	748	60
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	59
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	59
Nick Greenwood L 2016 · 3.71 FIP	28	SP-	3.71	11.2%	2.9%	2.2%	.288	—	—	—	—	—	3.71	277	59
Enrique Lechuga L 2015 · 4.70 FIP	29	SP-	4.70	10.0%	10.5%	2.0%	.354	3.78	10.5%	4.4%	59	-0.92	3.78	137	59

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	2.4	122	16.2%	8.1%	1.20	4.78
Paul Wilson ('05)	4.7	135	14.9%	8.1%	1.20	4.86
Brandon Claussen ('06)	1.6	105	16.0%	8.5%	1.37	5.04
Garrett Stephenson ('03)	3.3	109	14.5%	8.4%	1.26	4.55
Albert Williams ('80-'84, 6 WAR*)	3.2	129	14.9%*	8.4%*	1.26*	4.30*
Greg Mathews ('86-'92, 4 WAR*)	2.6	103	14.7%*	9.2%*	1.09*	4.52*
Tommy Boggs ('76-'85, 3 WAR*)	2.9	97	16.4%*	8.1%*	1.24*	4.77*