Jesus Cruz

P Rocket City Trash Pandas

Age 32 RHP 6'1" / 230 lbs AA

Overview

AARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	27	MIX2 levels	35	0	36	4.71	4.78	28.1%	12.5%	-0.1	K 28.4% · BB 13.9% · FIP 4.50
2023	28	AAAPHI	28	2	35	5.40	3.73	24.7%	10.1%	—	K 21.2% · BB 9.1% · FIP 3.95
2025	30	AALAA	11	5	26	4.15	3.45	18.5%	11.3%	—	K 15.0% · BB 12.4% · FIP 3.92
2026	31	No MLB games played
2027PROJ	32	MLBLAA	—	—	0	4.84	4.84	19.0%	11.0%	—
2028PROJ31% MLB	33	MLBLAA	5	0	5	4.93	5.03	18.9%	11.3%	-0.0

Last 3 seasons WAR -0.1 · Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsMiguel Mejia (age 31) · Neil Wagner (age 32) · Joe Nelson (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 125117vR 109

ERA4.84

FIP4.84

K%19.0%

BB%11.0%

K-BB%8.0%

Proj IP14

Value2027 · WAR

Runs saved vs league avg · 14 IP

Grades · Contract

Scouting Grades

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	22	MIX MLE	2 levels	23	0	26	116	33	11	1	0%	1.1	21.2%	10.6%	10.6%	0.9%	4.50	3.15	—
2017	22	MIX RAW	2 levels	23	0	26	116	33	11	1	0%	1.1	28.4%	9.5%	19.0%	0.9%	4.50	2.33	—
2018	23	MIX MLE	2 levels	30	16	85	360	104	41	5	53%	2.8	22.1%	13.2%	8.9%	2.0%	3.27	4.02	—
2018	23	MIX RAW	2 levels	30	16	85	360	104	41	5	53%	2.8	28.9%	11.4%	17.5%	1.4%	3.27	2.87	—
2019	24	MIX MLE	2 levels	52	0	61	280	89	44	8	0%	1.2	26.4%	15.6%	10.9%	3.4%	6.02	4.71	—
2019	24	MIX RAW	2 levels	52	0	61	280	89	44	8	0%	1.2	31.8%	15.7%	16.1%	2.9%	6.02	4.05	—
2020	25	MLB MLE	St. Louis Cardinals	1	0	1	7	2	1	0	0%	1.0	28.6%	14.3%	14.3%	0.0%	18.00	2.50	+0.0
2020	25	MLB RAW	St. Louis Cardinals	1	0	1	7	2	1	0	0%	1.0	28.6%	14.3%	14.3%	0.0%	18.00	2.10	+0.0
2021	26	AAA MLE	Memphis Redbirds	37	0	35	161	38	25	1	0%	1.0	20.8%	16.3%	4.5%	0.7%	3.06	3.81	—
2021	26	AAA RAW	Memphis Redbirds	37	0	35	161	38	25	1	0%	1.0	23.6%	15.5%	8.1%	0.6%	3.06	3.44	—
2022	27	MIX MLE	2 levels	35	0	36	160	45	20	7	0%	1.0	28.4%	13.9%	14.5%	3.7%	4.71	4.50	+0.0
2022	27	MIX RAW	2 levels	35	0	36	160	45	20	7	0%	1.0	28.1%	12.5%	15.6%	4.4%	4.71	4.78	-0.1
2023	28	AAA MLE	Lehigh Valley IronPigs	28	2	35	158	39	16	4	7%	1.2	21.2%	9.1%	12.1%	2.7%	5.40	3.95	—
2023	28	AAA RAW	Lehigh Valley IronPigs	28	2	35	158	39	16	4	7%	1.2	24.7%	10.1%	14.6%	2.5%	5.40	3.73	—
2025	30	AA MLE	Rocket City Trash Pandas	11	5	26	124	23	14	1	45%	2.4	15.0%	12.4%	2.6%	0.9%	4.15	3.92	—
2025	30	AA MLE	Rocket City Trash Pandas	11	5	26	124	23	14	1	45%	2.4	15.0%	12.4%	2.6%	0.9%	4.15	3.92	—
2025	30	AA RAW	Rocket City Trash Pandas	11	5	26	124	23	14	1	45%	2.4	18.5%	11.3%	7.3%	0.8%	4.15	3.45	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			8	0	10	46	8	5	3	0%	1.2	17.4%	10.9%	6.5%	6.5%	7.45	7.03	-0.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	LAA	—	—	0	—	—	—	—	—	—	19.0%	11.0%	8.0%	2.8%	4.84	4.84	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	LAA	15	0	16	68	13	8	2	0%	1.1	18.9%	11.3%	7.6%	3.1%	4.93	5.03	-0.1
2028	33	MLB CTX	LAA	5	0	5	21	4	2	1	0%	1.0	18.9%	11.3%	7.6%	3.1%	4.93	5.03	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		13	0	15	67	12	7	4	0%	1.1	17.9%	11.0%	6.9%	5.5%	6.59	5.98	-0.2
/ 200 IP	—	RAW		174	0	200	915	164	95	55	0%	1.1	17.9%	11.0%	6.9%	5.5%	6.59	5.98	-3.3
Career	—	MLE		217	23	306	1366	311	183	30	11%	1.4	22.8%	13.4%	9.4%	2.2%	4.44	4.09	-0.4
/ 200 IP	—	MLE		142	15	200	892	203	119	20	11%	1.4	22.8%	13.4%	9.4%	2.2%	4.44	4.09	-2.9

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 AARocket City Trash Pandas · 26 IPFIP 3.41 → 3.92 (+0.51)K% 18.5% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.55%	—	×0.810	15.02%
BB% (unintentional) /BF	11.29%	—	×1.100	12.42%
HR / BF /BF	0.81%	÷1.028	×1.200	0.94%

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 106).

Result: FIP 3.41 → 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).

2023 AAALehigh Valley IronPigs · 35 IPFIP 3.69 → 3.95 (+0.26)K% 24.7% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.68%	—	×0.860	21.23%
BB% (unintentional) /BF	10.13%	—	×0.900	9.11%
HR / BF /BF	2.53%	÷1.028	×1.100	2.71%

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 106).

Result: FIP 3.69 → 3.95, 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 AAAGwinnett Stripers · 28 IPFIP 3.87 → 4.50 (+0.63)K% 32.2% → 28.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.23%	—	×0.880	28.36%
BB% (unintentional) /BF	13.22%	—	×1.050	13.88%
HR / BF /BF	3.31%	÷0.981	×1.100	3.71%

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 96).

Result: FIP 3.87 → 4.50, 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 AAAMemphis Redbirds · 35 IPFIP 3.41 → 3.81 (+0.39)K% 23.6% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.60%	—	×0.880	20.77%
BB% (unintentional) /BF	15.53%	—	×1.050	16.30%
HR / BF /BF	0.62%	÷0.949	×1.100	0.72%

Result: FIP 3.41 → 3.81, 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).

2019 AAAMemphis Redbirds · 58 IPFIP 4.11 → 4.71 (+0.60)K% 30.0% → 26.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.04%	—	×0.880	26.43%
BB% (unintentional) /BF	14.83%	—	×1.050	15.57%
HR / BF /BF	3.04%	÷0.982	×1.100	3.41%

Result: FIP 4.11 → 4.71, 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 A+Palm Beach Cardinals · 69 IPFIP 3.01 → 4.26 (+1.25)K% 29.8% → 23.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.82%	—	×0.770	22.96%
BB% (unintentional) /BF	11.58%	—	×1.150	13.32%
HR / BF /BF	1.75%	÷0.852	×1.250	2.57%

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 3.01 → 4.26, 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).

2018 APeoria Chiefs · 17 IPFIP 2.31 → 3.11 (+0.80)K% 25.3% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.33%	—	×0.740	18.75%
BB% (unintentional) /BF	10.67%	—	×1.180	12.59%
HR / BF /BF	0.00%	÷0.981	×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 96).

Result: FIP 2.31 → 3.11, 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).

2017 AAASultanes de Monterrey · 12 IPFIP 3.94 → 4.25 (+0.31)K% 18.3% → 16.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.33%	—	×0.880	16.13%
BB% (unintentional) /BF	11.67%	—	×1.050	12.25%
HR / BF /BF	1.67%	÷1.043	×1.100	1.76%

Result: FIP 3.94 → 4.25, 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
Jesus Cruz (OGILVIE)	—	—	4.84	19.0%	11.0%	2.8%	—	5.03	18.9%	7.6%	16	+0.19	—	—	—
Miguel Mejia R 2019 · 4.41 FIP	31	SU	4.41	15.7%	10.7%	2.3%	.341	—	—	—	—	—	3.37	108	80
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	79
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	79
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	78
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	77
Jim Henderson R 2015 · 5.27 FIP	32	SU	5.27	16.7%	11.9%	3.8%	.307	4.55	25.8%	16.8%	35	-0.72	1.86	167	76
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	75
Mike Buddie R 2002 · 4.26 FIP	31	SU	4.26	15.1%	7.6%	2.7%	.297	—	—	—	—	—	3.76	123	75
Jeff Fulchino R 2011 · 4.44 FIP	31	SU	4.44	20.4%	11.1%	3.0%	.302	—	—	—	—	—	3.36	178	75
Ryan Kelly R 2019 · 4.33 FIP	31	SU	4.33	14.7%	7.2%	2.8%	.307	—	—	—	—	—	2.49	131	75
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	74
A.J. Schugel R 2021 · 4.82 FIP	32	SU	4.82	16.6%	12.3%	2.9%	.351	—	—	—	—	—	2.80	299	74
Brian Sanches R 2011 · 4.35 FIP	32	SU	4.35	19.6%	11.1%	2.7%	.250	—	—	—	—	—	3.39	229	73
Juan Sandoval R 2015 · 3.82 FIP	34	SU	3.82	15.4%	6.0%	2.3%	.294	3.33	17.4%	8.8%	116	-0.49	3.24	225	73
Kane Davis R 2007 · 4.82 FIP	32	SU	4.82	16.9%	10.2%	3.4%	.366	—	—	—	—	—	3.40	125	73
Felipe Arredondo R 2019 · 4.65 FIP	32	SU	4.65	16.2%	7.1%	3.7%	.272	—	—	—	—	—	3.92	337	72
Dalier Hinojosa R 2016 · 4.30 FIP	30	SU	4.30	18.7%	12.6%	2.2%	.329	—	—	—	—	—	3.41	104	72
Dan Winkler R 2022 · 3.87 FIP	32	SU	3.87	24.4%	14.0%	1.9%	.281	—	—	—	—	—	2.40	231	72
Fredy Quintero R 2019 · 4.62 FIP	31	SU	4.62	17.2%	13.7%	2.2%	.310	—	—	—	—	—	4.29	241	72
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	71