Elvin Rodríguez

P Reno Aces

Age 29 RHP 6'4" / 214 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	24	MIX2 levels	30	26	129	6.28	5.39	19.9%	8.6%	0.0	K 18.0% · BB 8.9% · FIP 5.60
2023	25	MIX3 levels	12	11	51	3.20	3.99	28.3%	9.3%	0.9	K 22.6% · BB 8.9% · FIP 4.64
2025	27	MIX2 levels	36	4	65	6.51	6.39	19.3%	6.0%	-1.4	K 17.5% · BB 5.6% · FIP 6.81
2026	28	No MLB games played
2027PROJ	29	MLBBAL	2	2	15	5.14	5.34	18.1%	6.3%	0.0
2028PROJ37% MLB	30	MLBBAL	7	7	43	5.27	5.44	17.8%	6.8%	-0.0
2029PROJ55% MLB	31	MLBBAL	9	9	53	5.42	5.58	17.3%	7.2%	-0.1

Last 3 seasons WAR -0.5 · Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo48

K%35

xwOBA vs10

CompsTim Adleman (age 29) · Travis Driskill (age 30) · Walker Powell (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 135126vR 118

ERA5.14

FIP5.34

K%18.1%

BB%6.3%

K-BB%11.7%

Proj IP154

Value2027 · WAR

Runs saved vs league avg · 154 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p4894.4

Whiff%

p2922.3%

p3520.0%

xwOBA vs

p100.421

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 Angels	12	11	51	221	36	19	4	92%	4.2	11.1%	10.7%	0.3%	2.5%	4.59	4.92	—
2015	17	ROK RAW	DSL Angels	12	11	51	221	36	19	4	92%	4.2	16.3%	8.6%	7.7%	1.8%	4.59	3.83	—
2016	18	ROK MLE	AZL Angels	14	11	59	219	57	14	3	79%	4.2	17.7%	8.0%	9.7%	1.9%	1.53	3.67	—
2016	18	ROK RAW	AZL Angels	14	11	59	219	57	14	3	79%	4.2	26.0%	6.4%	19.6%	1.4%	1.53	2.54	—
2017	19	MIX MLE	2 levels	14	14	68	281	61	14	7	100%	4.9	15.0%	6.2%	8.9%	3.3%	2.91	4.44	—
2017	19	MIX RAW	2 levels	14	14	68	281	61	14	7	100%	4.9	21.7%	5.0%	16.7%	2.5%	2.91	3.26	—
2018	20	A MLE	West Michigan Whitecaps	21	21	113	465	109	32	9	100%	5.4	17.3%	8.1%	9.2%	2.7%	3.34	4.13	—
2018	20	A RAW	West Michigan Whitecaps	21	21	113	465	109	32	9	100%	5.4	23.4%	6.9%	16.6%	1.9%	3.34	3.06	—
2019	21	A+ MLE	Lakeland Flying Tigers	24	23	134	558	112	44	12	96%	5.6	15.5%	9.1%	6.4%	2.8%	3.77	4.48	—
2019	21	A+ RAW	Lakeland Flying Tigers	24	23	134	558	112	44	12	96%	5.6	20.1%	7.9%	12.2%	2.2%	3.77	3.58	—
2021	23	MIX MLE	2 levels	19	18	78	337	83	29	18	95%	4.1	19.6%	9.7%	10.0%	6.2%	5.68	6.07	—
2021	23	MIX RAW	2 levels	19	18	78	337	83	29	18	95%	4.1	24.6%	8.6%	16.0%	5.3%	5.68	5.10	—
2022	24	MIX MLE	2 levels	30	26	129	584	116	50	29	87%	4.3	18.0%	8.9%	9.1%	5.3%	6.28	5.60	-0.3
2022	24	MIX RAW	2 levels	30	26	129	584	116	50	29	87%	4.3	19.9%	8.6%	11.3%	5.0%	6.28	5.39	+0.0
2023	25	MIX MLE	3 levels	12	11	51	205	58	19	8	92%	4.2	22.6%	8.9%	13.7%	4.2%	3.20	4.64	+0.4
2023	25	MIX RAW	3 levels	12	11	51	205	58	19	8	92%	4.2	28.3%	9.3%	19.0%	3.9%	3.20	3.99	+0.9
2025	27	MIX MLE	2 levels	36	4	65	285	55	17	21	11%	1.8	17.5%	5.6%	11.9%	8.1%	6.51	6.81	-1.7
2025	27	MIX MLE	2 levels	36	4	65	285	55	17	21	11%	1.8	17.5%	5.6%	11.9%	8.1%	6.51	6.81	-1.7
2025	27	MIX RAW	2 levels	36	4	65	285	55	17	21	11%	1.8	19.3%	6.0%	13.3%	7.4%	6.51	6.39	-1.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			15	7	53	243	48	21	21	47%	3.5	19.8%	8.6%	11.1%	8.6%	9.40	7.66	-1.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	BAL	2	2	15	63	11	4	3	100%	7.5	18.1%	6.3%	11.7%	4.7%	5.14	5.34	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	BAL	20	20	117	495	88	34	23	100%	5.9	17.8%	6.8%	11.0%	4.7%	5.27	5.44	-0.1
2029	31	MLB MLE	BAL	16	16	97	409	71	29	20	100%	6.1	17.3%	7.2%	10.1%	4.8%	5.42	5.58	-0.2
2028	30	MLB CTX	BAL	7	7	43	182	32	12	9	100%	6.1	17.8%	6.8%	11.0%	4.7%	5.27	5.44	-0.0
2029	31	MLB CTX	BAL	9	9	53	224	39	16	11	100%	5.9	17.3%	7.2%	10.1%	4.8%	5.42	5.58	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		31	23	149	651	119	50	41	74%	4.8	18.4%	7.6%	10.7%	6.2%	6.78	5.93	-0.9
/ 200 IP	—	RAW		42	31	200	872	160	67	55	74%	4.8	18.4%	7.6%	10.7%	6.2%	6.78	5.93	-1.2
Career	—	MLE		182	139	747	3155	540	265	131	76%	4.1	17.1%	8.4%	8.7%	4.1%	4.34	5.00	-1.6
/ 200 IP	—	MLE		49	37	200	845	144	71	35	76%	4.1	17.1%	8.4%	8.7%	4.1%	4.34	5.00	-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 AAAReno Aces · 45 IPFIP 5.53 → 6.42 (+0.89)K% 19.0% → 16.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.97%	—	×0.860	16.32%
BB% (unintentional) /BF	5.13%	—	×0.900	4.62%
HR / BF /BF	6.15%	÷0.904	×1.100	7.49%

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 81).

Result: FIP 5.53 → 6.42, 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 AAADurham Bulls · 45 IPFIP 4.53 → 4.64 (+0.11)K% 26.2% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.23%	—	×0.860	22.56%
BB% (unintentional) /BF	9.84%	—	×0.900	8.85%
HR / BF /BF	4.37%	÷1.137	×1.100	4.23%

Result: FIP 4.53 → 4.64, 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).

2022 AAAToledo Mud Hens · 99 IPFIP 4.51 → 4.92 (+0.41)K% 20.6% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.63%	—	×0.880	18.16%
BB% (unintentional) /BF	8.16%	—	×1.050	8.57%
HR / BF /BF	3.85%	÷1.026	×1.100	4.13%

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 105).

Result: FIP 4.51 → 4.92, 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).

2021 AAErie SeaWolves · 76 IPFIP 5.16 → 6.07 (+0.91)K% 24.2% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.24%	—	×0.810	19.64%
BB% (unintentional) /BF	8.79%	—	×1.100	9.67%
HR / BF /BF	5.45%	÷1.055	×1.200	6.20%

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 5.16 → 6.07, 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+Lakeland Flying Tigers · 134 IPFIP 3.58 → 4.48 (+0.89)K% 20.1% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.07%	—	×0.770	15.46%
BB% (unintentional) /BF	7.89%	—	×1.150	9.07%
HR / BF /BF	2.15%	÷0.963	×1.250	2.79%

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 93).

Result: FIP 3.58 → 4.48, 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 AWest Michigan Whitecaps · 113 IPFIP 3.05 → 4.13 (+1.07)K% 23.4% → 17.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.44%	—	×0.740	17.35%
BB% (unintentional) /BF	6.88%	—	×1.180	8.12%
HR / BF /BF	1.94%	÷0.942	×1.300	2.67%

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 88).

Result: FIP 3.05 → 4.13, 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).

2017 ROKOrem Owlz · 54 IPFIP 3.10 → 4.37 (+1.27)K% 22.5% → 15.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.48%	—	×0.680	15.28%
BB% (unintentional) /BF	5.05%	—	×1.250	6.31%
HR / BF /BF	2.29%	÷1.000	×1.400	3.21%

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 3.10 → 4.37, 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 ABurlington Bees · 14 IPFIP 3.84 → 4.67 (+0.83)K% 19.0% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.05%	—	×0.740	14.10%
BB% (unintentional) /BF	4.76%	—	×1.180	5.62%
HR / BF /BF	3.17%	÷1.105	×1.300	3.73%

Result: FIP 3.84 → 4.67, 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).

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
Elvin Rodríguez (OGILVIE)	—	—	—	—	—	4.7%	—	5.50	17.6%	10.6%	214	+0.16	—	—	—
Tim Adleman R 2017 · 5.35 FIP	29	SP-	5.35	20.3%	9.4%	5.1%	.276	4.30	22.8%	15.0%	117	-1.05	3.63	605	76
Travis Driskill R 2002 · 4.95 FIP	30	SP-	4.95	13.2%	8.0%	3.6%	.291	4.26	15.3%	12.0%	48	-0.69	4.26	181	75
Walker Powell R 2023 · 5.21 FIP	27	SP	5.21	18.6%	5.8%	5.4%	.258	5.35	12.1%	6.3%	27	+0.14	2.87	242	72
Aaron Brooks R 2019 · 4.72 FIP	29	SP-	4.72	17.0%	7.1%	3.9%	.281	4.38	15.8%	8.8%	70	-0.34	3.71	879	71
Forrest Snow R 2018 · 5.14 FIP	29	SP-	5.14	19.6%	7.7%	5.0%	.282	5.53	18.8%	10.3%	28	+0.39	3.02	406	71
Hisashi Iwakuma R 2012 · 4.28 FIP	31	SP-	4.28	19.5%	7.7%	3.4%	.277	3.45	21.5%	17.8%	528	-0.83	3.19	884	70
Kyle Friedrichs R 2021 · 4.73 FIP	29	SP-	4.73	13.9%	6.2%	3.7%	.286	—	—	—	—	—	3.53	603	69
Cory Riordan R 2016 · 4.24 FIP	30	SP	4.24	14.3%	5.0%	3.1%	.341	—	—	—	—	—	4.24	154	68
Omar Bencomo R 2018 · 4.37 FIP	29	SP-	4.37	16.9%	3.8%	4.0%	.316	4.69	11.3%	4.7%	66	+0.32	3.70	381	68
Asher Wojciechowski R 2018 · 4.60 FIP	29	SP-	4.60	22.4%	7.8%	4.4%	.267	5.05	22.0%	13.3%	234	+0.45	3.15	678	68
Scott Richmond R 2009 · 5.11 FIP	29	SP	5.11	19.2%	9.5%	4.4%	.294	—	—	—	—	—	2.80	166	68
Caleb Boushley R 2023 · 4.79 FIP	29	SP	4.79	16.3%	7.9%	3.8%	.294	4.15	17.0%	11.5%	211	-0.64	3.05	790	67
Kohei Arihara R 2022 · 4.58 FIP	29	SP-	4.58	16.4%	7.2%	3.5%	.333	—	—	—	—	—	4.58	135	67
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	66
Andres Ivan Meza R 2015 · 4.45 FIP	28	SP	4.45	10.9%	5.6%	2.9%	.322	4.14	12.5%	4.0%	85	-0.31	4.14	275	66
Javier Solano R 2019 · 5.13 FIP	29	SP	5.13	14.7%	4.6%	4.9%	.324	—	—	—	—	—	3.67	506	66
Adrian Sampson R 2021 · 5.78 FIP	29	SP-	5.78	16.1%	8.2%	5.5%	.271	4.53	16.2%	9.4%	293	-1.25	3.23	1,012	65
Merrill Kelly R 2019 · 4.41 FIP	30	SP	4.41	20.3%	6.8%	4.0%	.289	3.83	21.1%	14.8%	390	-0.58	3.60	1,170	65
Nate Long R 2015 · 4.67 FIP	29	SP	4.67	14.8%	10.6%	2.7%	.285	—	—	—	—	—	4.67	151	65
Scott McGregor R 2015 · 4.37 FIP	28	SP-	4.37	11.8%	7.6%	2.4%	.293	—	—	—	—	—	4.37	107	64

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	2.1	105	18.0%	7.0%	2.04	5.77
Dave Johnson ('87-'93, -2 WAR*)	1.8	123	11.9%*	6.1%*	2.05*	5.61*
Dennis Springer ('02)	3.3	131	10.3%	9.0%	1.48	5.18
Dave Williams ('07)	2.0	82	13.8%	9.3%	1.41	4.83
Masato Yoshii ('02)	3.8	151	13.9%	6.9%	1.33	4.62
Dick Hughes ('66-'68, 5 WAR*)	1.5	102	24.1%*	7.1%*	1.51*	3.68*
Mike Campbell ('87-'96, -2 WAR*)	1.2	58	17.0%*	9.1%*	1.96*	5.82*