Yovanny Cruz

P Rochester Red Wings

Age 27 RHP 6'0" / 180 lbs AAA

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	AASD	23	30	4.55	3.23	24.8%	11.3%	—	K 20.1% · BB 12.5% · FIP 3.96
2025	25	AABOS	34	59	3.03	3.94	28.2%	16.9%	—	K 22.9% · BB 18.5% · FIP 4.67
2026	26	MIX2 levels	55	59	3.84	3.29	28.5%	10.4%	0.9	K 25.3% · BB 9.7% · FIP 3.54
2027PROJ	27	MLBWSH	45	47	4.50	4.58	25.4%	13.8%	-0.0
2028PROJ79% MLB	28	MLBWSH	40	42	4.58	4.64	25.1%	13.5%	-0.0
2029PROJ84% MLB	29	MLBWSH	36	38	4.69	4.78	24.4%	13.4%	-0.1

Last 3 seasons WAR 0.9 · Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo90

K%45

xwOBA vs16

Career WAR0.0 WAR median (P10 -0.3 / P90 1.0, comp-based) · star 0% · didn't stick 91%

CompsBrian Ellington (age 26) · Joe Colón J (age 27) · Lucas Erceg (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 120112vR 104

ERA4.50

FIP4.58

K%25.4%

BB%13.8%

K-BB%11.6%

Proj IP67

Value2027 · WAR

Runs saved vs league avg · 67 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p9099.8

Whiff%

p5425.9%

p4521.4%

xwOBA vs

p160.352

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 Cubs 1	13	12	56	238	54	14	3	92%	4.3	15.4%	7.4%	8.1%	1.8%	3.51	3.70	—
2017	17	ROK RAW	DSL Cubs 1	13	12	56	238	54	14	3	92%	4.3	22.7%	5.9%	16.8%	1.3%	3.51	2.62	—
2018	18	ROK MLE	AZL Cubs 2	10	10	44	184	50	13	1	100%	4.4	18.5%	8.8%	9.6%	0.8%	2.86	3.08	—
2018	18	ROK RAW	AZL Cubs 2	10	10	44	184	50	13	1	100%	4.4	27.2%	7.1%	20.1%	0.5%	2.86	2.01	—
2019	19	ROK MLE	AZL Cubs 2	4	4	9	41	7	7	0	100%	2.2	17.1%	17.1%	0.0%	0.0%	4.00	3.82	—
2019	19	ROK RAW	AZL Cubs 2	4	4	9	41	7	7	0	100%	2.2	17.1%	17.1%	0.0%	0.0%	4.00	3.88	—
2022	22	MIX MLE	2 levels	10	0	14	57	20	2	2	0%	1.4	35.1%	3.5%	31.6%	3.5%	3.95	2.51	—
2022	22	MIX RAW	2 levels	10	0	14	57	20	2	2	0%	1.4	35.1%	3.5%	31.6%	3.5%	3.95	2.51	—
2023	23	MIX MLE	2 levels	16	0	21	93	24	10	0	0%	1.3	20.4%	12.5%	7.9%	0.0%	1.71	2.96	—
2023	23	MIX RAW	2 levels	16	0	21	93	24	10	0	0%	1.3	25.8%	10.8%	15.1%	0.0%	1.71	2.24	—
2024	24	AA MLE	San Antonio Missions	23	0	30	141	35	16	2	0%	1.3	20.1%	12.5%	7.6%	1.8%	4.55	3.96	—
2024	24	AA MLE	San Antonio Missions	23	0	30	141	35	16	2	0%	1.3	20.1%	12.5%	7.6%	1.8%	4.55	3.96	—
2024	24	AA RAW	San Antonio Missions	23	0	30	141	35	16	2	0%	1.3	24.8%	11.3%	13.5%	1.4%	4.55	3.23	—
2025	25	AA MLE	Portland Sea Dogs	34	0	59	255	72	43	5	0%	1.7	22.9%	18.5%	4.3%	2.1%	3.03	4.67	—
2025	25	AA MLE	Portland Sea Dogs	34	0	59	255	72	43	5	0%	1.7	22.9%	18.5%	4.3%	2.1%	3.03	4.67	—
2025	25	AA RAW	Portland Sea Dogs	34	0	59	255	72	43	5	0%	1.7	28.2%	16.9%	11.4%	2.0%	3.03	3.94	—
2026	26	MIX MLE	2 levels	55	0	59	260	74	27	6	0%	1.1	25.3%	9.7%	15.6%	2.5%	3.84	3.54	+0.7
2026	26	MIX MLE	2 levels	55	0	59	260	74	27	6	0%	1.1	25.3%	9.7%	15.6%	2.5%	3.84	3.54	+0.7
2026	26	MIX RAW	2 levels	55	0	59	260	74	27	6	0%	1.1	28.5%	10.4%	18.1%	2.3%	3.84	3.29	+0.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			17	0	16	70	15	9	2	0%	0.9	21.4%	12.9%	8.6%	2.9%	5.06	4.54	+0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	WSH	45	0	47	198	50	27	5	0%	1.0	25.4%	13.8%	11.6%	2.7%	4.50	4.58	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	WSH	51	0	54	226	57	31	6	0%	1.0	25.1%	13.5%	11.6%	2.9%	4.58	4.64	-0.1
2029	29	MLB MLE	WSH	43	0	46	192	47	26	6	0%	1.1	24.4%	13.4%	11.0%	3.0%	4.69	4.78	-0.1
2028	28	MLB CTX	WSH	40	0	42	177	44	24	5	0%	1.1	25.1%	13.5%	11.6%	2.9%	4.58	4.64	-0.0
2029	29	MLB CTX	WSH	36	0	38	160	39	22	5	0%	1.1	24.4%	13.4%	11.0%	3.0%	4.69	4.78	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		94	0	97	411	99	55	12	0%	1.0	24.2%	13.4%	10.8%	2.9%	4.70	4.35	+0.2
/ 200 IP	—	RAW		194	0	200	849	205	114	25	0%	1.0	24.2%	13.4%	10.8%	2.9%	4.70	4.35	+0.5
Career	—	MLE		165	26	292	1269	269	144	22	16%	1.8	21.2%	11.4%	9.8%	1.7%	3.39	3.70	-0.2
/ 200 IP	—	MLE		113	18	200	870	185	99	15	16%	1.8	21.2%	11.4%	9.8%	1.7%	3.39	3.70	-0.3

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 AAARochester Red Wings · 43 IPFIP 2.83 → 3.20 (+0.36)K% 31.1% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.05%	—	×0.860	26.71%
BB% (unintentional) /BF	9.47%	—	×0.900	8.53%
HR / BF /BF	2.11%	÷1.000	×1.100	2.32%

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 2.83 → 3.20, 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 AAPortland Sea Dogs · 59 IPFIP 3.93 → 4.67 (+0.74)K% 28.2% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.24%	—	×0.810	22.87%
BB% (unintentional) /BF	16.86%	—	×1.100	18.55%
HR / BF /BF	1.96%	÷1.119	×1.200	2.10%

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 124).

Result: FIP 3.93 → 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).

2024 AASan Antonio Missions · 30 IPFIP 3.22 → 3.96 (+0.74)K% 24.8% → 20.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.82%	—	×0.810	20.11%
BB% (unintentional) /BF	11.35%	—	×1.100	12.48%
HR / BF /BF	1.42%	÷0.953	×1.200	1.79%

Result: FIP 3.22 → 3.96, 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 A+South Bend Cubs · 19 IPFIP 2.24 → 2.96 (+0.72)K% 26.5% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.51%	—	×0.770	20.41%
BB% (unintentional) /BF	10.84%	—	×1.150	12.47%
HR / BF /BF	0.00%	÷1.197	×1.250	0.00%

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 139).

Result: FIP 2.24 → 2.96, 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 A+South Bend Cubs · 8 IPFIP 3.69 → 4.68 (+0.99)K% 19.4% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.44%	—	×0.770	14.97%
BB% (unintentional) /BF	5.56%	—	×1.150	6.39%
HR / BF /BF	2.78%	÷0.938	×1.250	3.70%

Result: FIP 3.69 → 4.68, 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 ROKACL Cubs · 5 IPFIP 0.49 → 3.35 (+2.86)K% 61.9% → 42.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	61.90%	—	×0.680	42.10%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
HR / BF /BF	4.76%	÷0.963	×1.400	6.93%

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 93).

Result: FIP 0.49 → 3.35, 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 ROKAZL Cubs 2 · 9 IPFIP 3.82 → 4.82 (+1.00)K% 17.1% → 11.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.07%	—	×0.680	11.61%
BB% (unintentional) /BF	17.07%	—	×1.250	21.34%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Result: FIP 3.82 → 4.82, 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 ROKAZL Cubs 2 · 44 IPFIP 2.00 → 3.08 (+1.08)K% 27.2% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.17%	—	×0.680	18.48%
BB% (unintentional) /BF	7.07%	—	×1.250	8.83%
HR / BF /BF	0.54%	÷1.000	×1.400	0.76%

Result: FIP 2.00 → 3.08, 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
Yovanny Cruz (OGILVIE)	—	—	—	—	—	2.7%	—	4.70	24.8%	11.3%	99	+0.12	—	—	—
Brian Ellington R 2017 · 4.75 FIP	26	SU	4.75	25.5%	14.9%	3.5%	.283	5.61	22.4%	5.3%	29	+0.86	2.75	233	74
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	72
Lucas Erceg R 2022 · 4.48 FIP	27	SU	4.48	20.8%	14.0%	2.5%	.339	2.96	24.6%	15.9%	193	-1.52	2.10	351	71
Spencer Bivens R 2022 · 4.86 FIP	28	SU	4.86	19.8%	13.5%	3.1%	.265	3.85	18.1%	10.3%	272	-1.01	3.52	391	70
Jacob Bosiokovic R 2021 · 3.93 FIP	27	SU	3.93	26.4%	14.3%	2.3%	.274	4.80	21.7%	10.2%	69	+0.87	3.84	181	70
Marcos Mateo R 2011 · 3.40 FIP	27	SU	3.40	25.5%	10.2%	2.1%	.361	—	—	—	—	—	3.12	104	70
Seth Halvorsen R 2024 · 3.82 FIP	24	SU	3.82	21.0%	12.5%	1.7%	.330	4.30	21.3%	11.0%	96	+0.48	3.82	131	69
Daniel Robert R 2022 · 4.20 FIP	27	SU	4.20	24.3%	16.3%	2.0%	.312	3.16	24.5%	15.4%	130	-1.04	2.32	186	69
Beck Wheeler R 2016 · 4.42 FIP	27	SU	4.42	24.9%	14.5%	2.9%	.360	5.40	15.3%	3.1%	58	+0.98	3.46	173	69
Jason Bulger R 2008 · 4.60 FIP	29	SU	4.60	27.4%	12.3%	4.1%	.293	3.94	25.1%	13.3%	90	-0.66	3.78	106	69
Fernando Rodriguez Jr. R 2011 · 3.85 FIP	27	SU	3.85	24.7%	10.8%	2.7%	.315	3.90	25.2%	16.5%	70	+0.05	3.34	335	69
Jose De La Torre R 2013 · 5.22 FIP	27	SU	5.22	28.3%	18.9%	3.9%	.308	3.87	17.6%	6.6%	110	-1.35	2.64	141	68
Austin Adams R 2015 · 3.51 FIP	28	SU	3.51	18.6%	9.5%	1.4%	.331	3.40	21.1%	15.0%	56	-0.11	3.40	162	68
Sean Reynolds R 2024 · 3.55 FIP	26	SU	3.55	23.0%	11.8%	1.6%	.367	4.93	18.5%	3.0%	55	+1.38	3.55	258	68
Grant Balfour R 2004 · 3.79 FIP	26	SU	3.79	24.4%	11.6%	2.3%	.292	4.01	24.8%	8.3%	25	+0.22	2.04	533	68
Shintaro Fujinami R 2023 · 4.09 FIP	29	SU	4.09	23.2%	12.3%	2.5%	.290	4.49	22.0%	0.2%	51	+0.40	4.09	130	68
José Ramírez R 2017 · 4.56 FIP	27	SU	4.56	21.7%	10.9%	3.5%	.218	—	—	—	—	—	3.36	206	68
Ty Adcock R 2024 · 3.76 FIP	27	SU	3.76	20.8%	8.9%	2.4%	.405	4.85	20.4%	11.6%	66	+1.09	3.76	122	68
Tayron Guerrero R 2018 · 4.05 FIP	27	SU	4.05	25.4%	10.8%	3.1%	.344	4.95	20.6%	5.0%	65	+0.90	2.12	376	68
Connor Sadzeck R 2019 · 4.20 FIP	27	SU	4.20	25.2%	13.1%	2.9%	.238	4.61	22.7%	10.8%	94	+0.41	3.20	549	68

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	61	24.7%	13.5%	1.10	4.62
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Derrick Turnbow ('08)	1.3	64	23.4%	14.8%	0.87	4.30
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*
Armando Almanza ('05)	1.1	54	24.4%	14.3%	1.43	4.82
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*