Fernando Cruz

P New York Yankees

Age 37 RHP 6'2" / 237 lbs MLB peak 0.3 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	34	MLBCIN	69	3	67	4.86	3.07	37.8%	11.5%	1.2
2025	35	MIX3 levels	53	0	52	4.18	3.10	35.6%	11.9%	0.9	K 36.0% · BB 12.0% · FIP 2.87
2026	36	MLBNYY	61	0	55	3.13	3.96	28.6%	12.8%	0.4
2027PROJ	37	MLBNYY	28	0	29	3.74	3.80	33.1%	11.9%	0.3
2028PROJ86% MLB	38	MLBNYY	28	0	29	4.03	4.23	32.0%	12.6%	0.1

Last 3 seasons WAR 2.5 · Next 2 projected WAR 0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%85

xwOBA vs82

FB Velo32

CompsMatt Bush (age 37) · Pete Walker (age 37) · Keiichi Yabu (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9890vR 82

ERA3.74

FIP3.80

K%33.1%

BB%11.9%

K-BB%21.2%

Proj IP29

Value2027 · WAR

Runs saved vs league avg · 29 IP

Grades · Statcast · Contract

Scouting Grades

STUF8080

CTRL3030

CMD7070

K†7070

Statcast Percentiles

FB Velo

p3293.2

Whiff%

p9039.1%

p8528.6%

xwOBA vs

p820.281

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	25	MIX MLE	3 levels	32	5	69	309	58	33	11	16%	2.1	15.6%	12.2%	3.4%	3.6%	5.64	5.29	—
2015	25	MIX RAW	3 levels	32	5	69	309	58	33	11	16%	2.1	18.8%	10.7%	8.1%	3.6%	5.64	4.93	—
2022	32	MIX MLE	2 levels	65	2	71	289	87	28	5	3%	1.1	27.4%	10.0%	17.3%	1.5%	2.55	2.89	+1.4
2022	32	MIX RAW	2 levels	65	2	71	289	87	28	5	3%	1.1	30.1%	9.7%	20.4%	1.7%	2.55	2.75	+1.5
2023	33	MIX MLE	2 levels	60	2	68	288	100	30	6	3%	1.1	35.1%	10.0%	25.1%	2.0%	5.19	2.50	+1.7
2023	33	MIX RAW	2 levels	60	2	68	288	100	30	6	3%	1.1	34.7%	10.4%	24.3%	2.1%	5.19	2.63	+1.6
2024	34	MLB MLE	Cincinnati Reds	69	3	67	288	109	33	9	4%	1.0	37.8%	11.5%	26.4%	2.9%	4.86	2.94	+1.3
2024	34	MLB MLE	Cincinnati Reds	69	3	67	288	109	33	9	4%	1.0	37.8%	11.5%	26.4%	2.9%	4.86	2.94	+1.3
2024	34	MLB RAW	Cincinnati Reds	69	3	67	288	109	33	9	4%	1.0	37.8%	11.5%	26.4%	3.1%	4.86	3.07	+1.2
2025	35	MIX MLE	3 levels	53	0	52	219	78	26	6	0%	1.0	36.0%	12.0%	24.0%	2.3%	4.18	2.87	+1.0
2025	35	MIX MLE	3 levels	53	0	52	219	78	26	6	0%	1.0	36.0%	12.0%	24.0%	2.3%	4.18	2.87	+1.0
2025	35	MIX RAW	3 levels	53	0	52	219	78	26	6	0%	1.0	35.6%	11.9%	23.7%	2.7%	4.18	3.10	+0.9
2026	36	MLB MLE	New York Yankees	61	0	55	234	67	30	7	0%	0.9	28.6%	12.8%	15.8%	2.8%	3.13	3.84	+0.5
2026	36	MLB MLE	New York Yankees	61	0	55	234	67	30	7	0%	0.9	28.6%	12.8%	15.8%	2.8%	3.13	3.84	+0.5
2026	36	MLB RAW	New York Yankees	61	0	55	234	67	30	7	0%	0.9	28.6%	12.8%	15.8%	3.0%	3.13	3.96	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			251	7	250	1065	367	124	28	3%	1.0	34.5%	11.6%	22.8%	2.6%	4.03	3.11	+4.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	37	MLB	NYY	28	0	29	122	41	15	4	0%	1.0	33.1%	11.9%	21.2%	2.9%	3.74	3.80	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	38	MLB MLE	NYY	32	0	34	142	46	18	5	0%	1.1	32.0%	12.6%	19.4%	3.4%	4.03	4.23	+0.1
2028	38	MLB CTX	NYY	28	0	29	122	39	15	4	0%	1.0	32.0%	12.6%	19.4%	3.4%	4.03	4.23	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		279	7	279	1187	406	139	32	3%	1.0	34.2%	11.7%	22.5%	2.7%	4.03	3.18	+4.5
/ 200 IP	—	RAW		200	5	200	851	291	100	23	3%	1.0	34.2%	11.7%	22.5%	2.7%	4.03	3.18	+3.3
Career	—	MLE		340	12	380	1627	483	185	41	4%	1.1	29.7%	11.4%	18.3%	2.5%	4.29	3.42	+4.4
/ 200 IP	—	MLE		179	6	200	856	254	97	22	4%	1.1	29.7%	11.4%	18.3%	2.5%	4.29	3.42	+3.1

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.

2022 AAALouisville Bats · 56 IPFIP 2.67 → 2.88 (+0.21)K% 29.3% → 25.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.33%	—	×0.880	25.81%
BB% (unintentional) /BF	8.44%	—	×1.050	8.87%
HR / BF /BF	1.78%	÷1.282	×1.100	1.53%

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 156).

Result: FIP 2.67 → 2.88, 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).

2015 AATennessee Smokies · 31 IPFIP 4.46 → 5.18 (+0.72)K% 21.2% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.23%	—	×0.810	17.20%
BB% (unintentional) /BF	13.01%	—	×1.100	14.32%
HR / BF /BF	2.74%	÷1.048	×1.200	3.14%

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 110).

Result: FIP 4.46 → 5.18, 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).

2015 A+Myrtle Beach Pelicans · 33 IPFIP 4.25 → 5.41 (+1.16)K% 18.0% → 13.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.99%	—	×0.770	13.85%
BB% (unintentional) /BF	8.63%	—	×1.150	9.93%
HR / BF /BF	2.88%	÷0.888	×1.250	4.05%

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 78).

Result: FIP 4.25 → 5.41, 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).

2015 AAAIowa Cubs · 4 IPFIP 10.31 → 11.83 (+1.51)K% 8.3% → 7.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	8.33%	—	×0.880	7.33%
BB% (unintentional) /BF	8.33%	—	×1.050	8.75%
HR / BF /BF	12.50%	÷0.916	×1.100	15.01%

Result: FIP 10.31 → 11.83, 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
Fernando Cruz (OGILVIE)	—	—	3.80	33.1%	11.9%	2.9%	—	4.23	32.0%	19.4%	34	+0.43	—	—	—
Matt Bush R 2023 · 3.79 FIP	37	SU	3.79	26.2%	8.7%	3.3%	.225	—	—	—	—	—	2.87	249	61
Pete Walker R 2006 · 4.45 FIP	37	SU	4.45	19.6%	8.0%	3.6%	.337	—	—	—	—	—	4.45	327	46
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	42
Juan Sandoval R 2017 · 3.42 FIP	36	SU	3.42	16.7%	7.2%	1.5%	.298	5.41	15.9%	8.7%	57	+1.99	3.24	225	41
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	40
Roy Corcoran R 2015 · 2.87 FIP	35	SU	2.87	17.7%	8.2%	0.4%	.359	—	—	—	—	—	2.87	129	39
Erubiel Gonzalez R 2016 · 2.99 FIP	37	SU	2.99	16.4%	6.5%	0.8%	.333	3.51	13.3%	10.8%	35	+0.52	2.99	119	37
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	36
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	36
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	36
Scott Atchison R 2013 · 3.80 FIP	37	SU	3.80	14.4%	6.2%	2.1%	.273	3.60	16.7%	12.9%	92	-0.20	2.52	340	33
Francisco Del Rosario R 2017 · 4.15 FIP	36	SU	4.15	16.4%	10.0%	2.1%	.267	6.35	11.9%	-0.6%	77	+2.20	3.93	194	33
Hisanori Takahashi L 2012 · 4.04 FIP	37	SU	4.04	24.5%	6.1%	4.1%	.295	—	—	—	—	—	3.50	240	32
Hector Navarro R 2017 · 3.53 FIP	37	SU	3.53	11.5%	5.6%	1.3%	.283	—	—	—	—	—	2.30	126	21
Heriberto Ruelas L 2017 · 3.42 FIP	35	SU	3.42	17.2%	6.7%	1.7%	.294	—	—	—	—	—	2.95	117	19
Tony Pena Jr. R 2017 · 3.43 FIP	36	SU	3.43	10.9%	4.3%	1.3%	.312	—	—	—	—	—	2.80	128	15
Brian Sweeney R 2010 · 4.63 FIP	36	SU	4.63	9.5%	3.4%	3.5%	.226	—	—	—	—	—	3.03	108	14
Logan Duran R 2019 · 3.66 FIP	37	SP-	3.66	15.5%	8.9%	1.4%	.427	—	—	—	—	—	3.42	187	12
Brian Shouse L 2006 · 4.19 FIP	37	SU	4.19	13.2%	7.5%	2.3%	.269	3.37	15.3%	11.0%	127	-0.82	2.32	339	10

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	1.6	53	34.1%	12.1%	1.06	4.00
Corey Knebel ('22)	1.5	51	31.7%	11.2%	1.00	3.26
Ernesto Frieri ('17)	1.5	51	30.1%	11.1%	1.25	3.59
Victor Cruz ('78-'83, 5 WAR*)	1.4	54	35.3%*	11.5%*	1.30*	3.24*
Matt Barnes ('24)	2.3	52	29.0%	10.6%	1.02	4.21
Rod Scurry ('80-'88, 5 WAR*)	2.3	58	29.6%*	13.6%*	0.91*	3.67*
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*