Marco Jimenez

P Erie SeaWolves

Age 27 RHP 5'11" / 239 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	A+DET	38	57	2.05	2.98	23.3%	12.6%	—	K 18.0% · BB 14.4% · FIP 3.76
2025	25	A+DET	39	60	1.50	3.07	26.0%	7.5%	—	K 20.0% · BB 8.6% · FIP 4.28
2026	26	MIX3 levels	15	16	5.51	3.16	23.0%	4.1%	—	K 23.0% · BB 4.1% · FIP 3.16
2027PROJ	27	MLBDET	1	1	4.70	4.70	19.6%	9.9%	-0.0
2028PROJ38% MLB	28	MLBDET	19	20	4.71	4.74	19.8%	10.0%	-0.0
2029PROJ56% MLB	29	MLBDET	25	26	4.78	4.84	19.9%	10.1%	-0.1

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

Contract

No contract data on file.

Scouting grades · 20-80

Stuff45Control50Command50

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

CompsLuis Mateo (age 27) · Ricky Stone (age 27) · Tyler Walker (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 122114vR 106

ERA4.70

FIP4.70

K%19.6%

BB%9.9%

K-BB%9.7%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL5050

CMD5050

K†4545

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)
2017	17	ROK MLE	DSL Tigers	3	0	8	38	9	3	0	0%	2.8	23.7%	7.9%	15.8%	0.0%	8.64	2.10	—
2017	17	ROK RAW	DSL Tigers	3	0	8	38	9	3	0	0%	2.8	23.7%	7.9%	15.8%	0.0%	8.64	2.02	—
2018	18	ROK MLE	DSL Tigers 2	4	0	6	23	4	2	0	0%	1.4	17.4%	8.7%	8.7%	0.0%	3.18	2.73	—
2018	18	ROK RAW	DSL Tigers 2	4	0	6	23	4	2	0	0%	1.4	17.4%	8.7%	8.7%	0.0%	3.18	2.75	—
2022	22	MIX MLE	2 levels	13	10	35	169	46	25	4	77%	2.7	19.6%	17.7%	1.9%	2.9%	6.37	5.27	—
2022	22	MIX RAW	2 levels	13	10	35	169	46	25	4	77%	2.7	27.2%	14.8%	12.4%	2.4%	6.37	4.09	—
2023	23	A MLE	Lakeland Flying Tigers	12	7	31	152	32	16	0	58%	2.6	15.6%	12.4%	3.2%	0.0%	7.63	3.36	—
2023	23	A RAW	Lakeland Flying Tigers	12	7	31	152	32	16	0	58%	2.6	21.1%	10.5%	10.5%	0.0%	7.63	2.58	—
2024	24	A+ MLE	West Michigan Whitecaps	38	0	57	223	52	28	1	0%	1.5	18.0%	14.4%	3.5%	0.6%	2.05	3.76	—
2024	24	A+ MLE	West Michigan Whitecaps	38	0	57	223	52	28	1	0%	1.5	18.0%	14.4%	3.5%	0.6%	2.05	3.76	—
2024	24	A+ RAW	West Michigan Whitecaps	38	0	57	223	52	28	1	0%	1.5	23.3%	12.6%	10.8%	0.4%	2.05	2.98	—
2025	25	A+ MLE	West Michigan Whitecaps	39	0	60	227	59	17	5	0%	1.5	20.0%	8.6%	11.4%	3.2%	1.50	4.28	—
2025	25	A+ MLE	West Michigan Whitecaps	39	0	60	227	59	17	5	0%	1.5	20.0%	8.6%	11.4%	3.2%	1.50	4.28	—
2025	25	A+ RAW	West Michigan Whitecaps	39	0	60	227	59	17	5	0%	1.5	26.0%	7.5%	18.5%	2.2%	1.50	3.07	—
2026	26	MIX MLE	3 levels	15	0	16	74	17	3	2	0%	1.1	23.0%	4.1%	18.9%	2.7%	5.51	3.16	—
2026	26	MIX MLE	3 levels	15	0	16	74	17	3	2	0%	1.1	23.0%	4.1%	18.9%	2.7%	5.51	3.16	—
2026	26	MIX RAW	3 levels	15	0	16	74	17	3	2	0%	1.1	23.0%	4.1%	18.9%	2.7%	5.51	3.16	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	DET	1	0	1	4	1	0	0	0%	1.0	19.6%	9.9%	9.7%	3.0%	4.70	4.70	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	DET	52	0	54	229	45	23	7	0%	1.0	19.8%	10.0%	9.9%	3.1%	4.71	4.74	-0.1
2029	29	MLB MLE	DET	44	0	46	195	39	20	6	0%	1.0	19.9%	10.1%	9.7%	3.2%	4.78	4.84	-0.2
2028	28	MLB CTX	DET	19	0	20	84	17	8	3	0%	1.1	19.8%	10.0%	9.9%	3.1%	4.71	4.74	-0.0
2029	29	MLB CTX	DET	25	0	26	110	22	11	4	0%	1.0	19.9%	10.1%	9.7%	3.2%	4.78	4.84	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		44	0	46	194	39	20	6	0%	1.0	19.9%	10.0%	9.8%	3.1%	4.75	4.42	+0.1
/ 200 IP	—	RAW		190	0	200	844	169	87	26	0%	1.1	19.9%	10.0%	9.8%	3.1%	4.75	4.42	+0.3
Career	—	MLE		124	17	213	906	172	109	16	14%	1.7	19.0%	12.0%	7.0%	1.7%	3.97	3.96	-0.3
/ 200 IP	—	MLE		116	16	200	849	162	102	15	14%	1.7	19.0%	12.0%	7.0%	1.7%	3.97	3.96	-0.6

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 AAErie SeaWolves · 8 IPFIP 4.57 → 5.54 (+0.97)K% 23.3% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.26%	—	×0.810	18.84%
BB% (unintentional) /BF	6.98%	—	×1.100	7.67%
HR / BF /BF	4.65%	÷1.000	×1.200	5.58%

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 4.57 → 5.54, 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).

2026 ALakeland Flying Tigers · 8 IPFIP 1.59 → 1.98 (+0.39)K% 17.9% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.86%	—	×0.740	13.21%
BB% (unintentional) /BF	0.00%	—	×1.180	0.00%
HR / BF /BF	0.00%	÷1.000	×1.300	0.00%

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 100).

Result: FIP 1.59 → 1.98, 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 A+West Michigan Whitecaps · 60 IPFIP 3.06 → 4.28 (+1.22)K% 26.0% → 20.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.99%	—	×0.770	20.01%
BB% (unintentional) /BF	7.49%	—	×1.150	8.61%
HR / BF /BF	2.20%	÷0.850	×1.250	3.24%

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 70).

Result: FIP 3.06 → 4.28, 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).

2024 A+West Michigan Whitecaps · 57 IPFIP 2.97 → 3.76 (+0.79)K% 23.3% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.32%	—	×0.770	17.96%
BB% (unintentional) /BF	12.56%	—	×1.150	14.44%
HR / BF /BF	0.45%	÷0.889	×1.250	0.63%

Result: FIP 2.97 → 3.76, 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 ALakeland Flying Tigers · 31 IPFIP 2.66 → 3.36 (+0.70)K% 21.1% → 15.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.05%	—	×0.740	15.58%
BB% (unintentional) /BF	10.53%	—	×1.180	12.42%
HR / BF /BF	0.00%	÷1.216	×1.300	0.00%

Result: FIP 2.66 → 3.36, 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 ALakeland Flying Tigers · 24 IPFIP 3.74 → 4.67 (+0.93)K% 26.1% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.05%	—	×0.740	19.28%
BB% (unintentional) /BF	15.13%	—	×1.180	17.85%
HR / BF /BF	1.68%	÷1.279	×1.300	1.71%

Result: FIP 3.74 → 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).

2022 ROKFCL Tigers · 12 IPFIP 4.54 → 6.70 (+2.16)K% 30.0% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.00%	—	×0.680	20.40%
BB% (unintentional) /BF	14.00%	—	×1.250	17.50%
HR / BF /BF	4.00%	÷0.990	×1.400	5.66%

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 98).

Result: FIP 4.54 → 6.70, 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 ROKDSL Tigers 2 · 6 IPFIP 2.73 → 3.48 (+0.75)K% 17.4% → 11.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.39%	—	×0.680	11.83%
BB% (unintentional) /BF	8.70%	—	×1.250	10.87%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Result: FIP 2.73 → 3.48, 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).

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
Marco Jimenez (OGILVIE)	—	—	4.70	19.6%	9.9%	3.0%	—	4.79	19.9%	9.8%	100	+0.09	—	—	—
Luis Mateo R 2017 · 4.60 FIP	27	SU	4.60	17.6%	11.2%	2.9%	.309	5.55	8.6%	-4.8%	43	+0.95	3.48	160	87
Ricky Stone R 2002 · 4.16 FIP	27	SU	4.16	18.8%	9.3%	2.7%	.297	4.96	13.7%	7.4%	165	+0.80	4.16	243	87
Tyler Walker R 2004 · 4.28 FIP	28	SU	4.28	17.5%	8.4%	2.9%	.311	3.77	18.5%	10.4%	101	-0.51	2.38	289	86
Cody Satterwhite R 2015 · 3.71 FIP	28	SU	3.71	20.2%	9.8%	1.9%	.333	4.04	17.7%	10.2%	75	+0.33	3.69	147	86
Emmanuel Chapman R 2024 · 4.08 FIP	25	SW	4.08	19.7%	10.6%	2.4%	.256	4.52	17.8%	1.3%	117	+0.44	3.81	198	85
Brett McKinney R 2017 · 4.66 FIP	26	SU	4.66	18.5%	9.9%	3.4%	.287	—	—	—	—	—	3.43	183	85
J.J. Putz R 2004 · 4.57 FIP	27	SU	4.57	17.1%	7.3%	3.6%	.283	2.58	28.5%	23.0%	210	-1.99	1.43	563	84
Austin Ross R 2016 · 3.81 FIP	27	SU	3.81	22.9%	8.0%	3.0%	.295	3.67	12.4%	5.2%	127	-0.14	3.16	269	83
Jarret Whorff R 2024 · 4.04 FIP	25	SU	4.04	18.9%	10.2%	2.3%	.271	4.52	19.6%	12.0%	123	+0.48	3.88	257	83
Francisco Rodriguez R 2010 · 4.33 FIP	27	SU	4.33	17.2%	11.0%	2.4%	.283	5.00	11.9%	3.4%	14	+0.67	3.16	334	83
Derek Gordon R 2016 · 4.62 FIP	25	SW	4.62	19.9%	9.3%	3.7%	.315	—	—	—	—	—	4.62	146	83
Jorge Reyes R 2015 · 4.58 FIP	27	SW	4.58	15.9%	8.5%	3.2%	.307	3.49	14.2%	6.2%	129	-1.09	3.39	227	83
Troy Neiman R 2017 · 4.03 FIP	26	SU	4.03	18.1%	8.3%	2.5%	.282	—	—	—	—	—	4.03	199	82
Cody Tucker R 2024 · 4.97 FIP	25	SU	4.97	22.0%	12.0%	4.0%	.272	5.36	15.8%	-1.9%	40	+0.39	4.97	105	82
Jason Frasor R 2005 · 3.90 FIP	27	SU	3.90	20.3%	8.5%	2.6%	.282	3.66	22.9%	13.0%	154	-0.24	2.71	647	82
Mike Adams R 2022 · 5.36 FIP	27	SU	5.36	17.1%	11.2%	4.2%	.326	—	—	—	—	—	3.65	109	82
Coleman Huntley III R 2021 · 3.85 FIP	28	SW	3.85	20.2%	7.4%	2.8%	.348	3.56	23.4%	13.2%	86	-0.29	2.38	160	82
Cole Sulser R 2017 · 3.52 FIP	27	SU	3.52	22.6%	10.2%	1.9%	.321	2.85	28.2%	18.4%	140	-0.67	2.38	554	82
Cody Hall R 2015 · 3.51 FIP	27	SU	3.51	16.5%	9.3%	1.1%	.306	4.08	23.1%	11.7%	66	+0.57	3.51	134	82
Ryan Doolittle R 2015 · 4.03 FIP	27	SU	4.03	15.1%	6.7%	2.5%	.315	4.38	13.9%	6.8%	44	+0.35	4.03	101	81

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	0.9	57	19.7%	10.0%	1.18	4.72
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Josias Manzanillo ('04)	1.7	57	20.0%	10.2%	1.21	4.71
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Kevin Quackenbush ('21)	1.0	52	21.0%	9.2%	1.04	4.41
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bill Scherrer ('82-'88, 1 WAR*)	1.6	62	20.7%*	10.2%*	1.19*	4.44*