Wandy Peralta

P San Diego Padres

Age 36 LHP 6'0" / 227 lbs MLB peak 0.2 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	33	MIX3 levels	49	1	42	3.67	4.71	14.5%	7.5%	-0.1	K 13.6% · BB 8.0% · FIP 4.95
2025	34	MLBSD	71	1	72	3.14	3.38	20.1%	8.6%	1.0
2026	35	MLBSD	65	5	77	3.61	3.84	15.6%	6.9%	0.7
2027PROJ	36	MLBSD	49	0	51	4.15	4.21	18.1%	7.6%	0.2
2028PROJ	37	MLBSD	22	0	23	4.43	4.62	17.0%	8.2%	-0.0
2029PROJ	38	MLBSD	9	0	9	4.80	5.05	15.8%	8.9%	-0.1

Last 3 seasons WAR 1.6 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo77

xwOBA vs44

K%10

Form4.63 ERA (proj 4.15) · K 16.7% (proj 18.1%) · BB 2.1% (proj 7.6%) ▲ last 90d · 23 IP through Oct 27

CompsBrian Shouse (age 36) · Heriberto Ruelas (age 35) · Hisanori Takahashi (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 96104vR 112

ERA4.15

FIP4.21

K%18.1%

BB%7.6%

K-BB%10.5%

Proj IP51

Value2027 · WAR

Runs saved vs league avg · 51 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p7796.4

Whiff%

p2922.3%

p1015.6%

xwOBA vs

p440.319

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	24	AA MLE	Pensacola Blue Wahoos	29	20	117	524	80	60	7	69%	4.0	12.4%	12.6%	-0.2%	1.5%	5.09	4.50	—
2015	24	AA RAW	Pensacola Blue Wahoos	29	20	117	524	80	60	7	69%	4.0	15.3%	11.5%	3.8%	1.3%	5.09	4.05	—
2016	25	MIX MLE	3 levels	60	2	83	346	63	33	4	3%	1.4	16.2%	8.9%	7.2%	1.2%	3.04	3.55	+1.0
2016	25	MIX RAW	3 levels	60	2	83	346	63	33	4	3%	1.4	18.2%	9.5%	8.7%	1.2%	3.04	3.40	+1.1
2017	26	MLB MLE	Cincinnati Reds	69	0	65	263	57	23	8	0%	0.9	21.7%	8.7%	12.9%	2.8%	3.76	3.92	+0.5
2017	26	MLB RAW	Cincinnati Reds	69	0	65	263	57	23	8	0%	0.9	21.7%	8.7%	12.9%	3.0%	3.76	4.01	+0.4
2018	27	MIX MLE	2 levels	72	0	60	286	41	36	3	0%	0.8	13.9%	12.7%	1.2%	1.0%	4.83	4.10	+0.3
2018	27	MIX RAW	2 levels	72	0	60	286	41	36	3	0%	0.8	14.3%	12.6%	1.7%	1.0%	4.83	4.19	+0.3
2019	28	MIX MLE	2 levels	59	0	51	216	39	14	11	0%	0.9	18.6%	7.6%	11.0%	6.9%	5.15	6.28	-1.0
2019	28	MIX RAW	2 levels	59	0	51	216	39	14	11	0%	0.9	18.1%	6.5%	11.6%	5.1%	5.15	5.21	-0.4
2020	29	MLB MLE	San Francisco Giants	25	0	27	114	25	11	3	0%	1.1	21.9%	9.6%	12.3%	2.8%	3.29	4.03	+0.2
2020	29	MLB RAW	San Francisco Giants	25	0	27	114	25	11	3	0%	1.1	21.9%	9.6%	12.3%	2.6%	3.29	3.90	+0.2
2021	30	MIX MLE	2 levels	59	2	54	231	48	21	6	3%	0.9	19.6%	9.1%	10.5%	2.6%	3.15	4.01	+0.3
2021	30	MIX RAW	2 levels	59	2	54	231	48	21	6	3%	0.9	20.8%	9.1%	11.7%	2.6%	3.15	3.93	+0.4
2022	31	MLB MLE	New York Yankees	56	0	56	223	47	16	2	0%	1.0	21.1%	7.2%	13.9%	0.8%	2.72	2.69	+1.3
2022	31	MLB RAW	New York Yankees	56	0	56	223	47	16	2	0%	1.0	21.1%	7.2%	13.9%	0.9%	2.72	2.74	+1.2
2023	32	MLB MLE	New York Yankees	63	0	54	227	51	30	7	0%	0.9	22.5%	13.2%	9.3%	2.9%	2.83	4.46	+0.1
2023	32	MLB RAW	New York Yankees	63	0	54	227	51	30	7	0%	0.9	22.5%	13.2%	9.3%	3.1%	2.83	4.56	-0.0
2024	33	MIX MLE	3 levels	49	1	42	173	25	13	6	2%	0.9	13.6%	8.0%	5.6%	3.6%	3.67	4.95	-0.2
2024	33	MIX MLE	3 levels	49	1	42	173	25	13	6	2%	0.9	13.6%	8.0%	5.6%	3.6%	3.67	4.95	-0.2
2024	33	MIX RAW	3 levels	49	1	42	173	25	13	6	2%	0.9	14.5%	7.5%	6.9%	3.5%	3.67	4.71	-0.1
2025	34	MLB MLE	San Diego Padres	71	1	72	313	63	27	5	1%	1.0	20.1%	8.6%	11.5%	1.6%	3.14	3.35	+1.0
2025	34	MLB MLE	San Diego Padres	71	1	72	313	63	27	5	1%	1.0	20.1%	8.6%	11.5%	1.6%	3.14	3.35	+1.0
2025	34	MLB RAW	San Diego Padres	71	1	72	313	63	27	5	1%	1.0	20.1%	8.6%	11.5%	1.6%	3.14	3.38	+1.0
2026	35	MLB MLE	San Diego Padres	65	5	77	321	50	22	7	8%	1.2	15.6%	6.9%	8.7%	2.1%	3.61	3.82	+0.7
2026	35	MLB MLE	San Diego Padres	65	5	77	321	50	22	7	8%	1.2	15.6%	6.9%	8.7%	2.1%	3.61	3.82	+0.7
2026	35	MLB RAW	San Diego Padres	65	5	77	321	50	22	7	8%	1.2	15.6%	6.9%	8.7%	2.2%	3.61	3.84	+0.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			567	7	533	2280	426	211	58	1%	0.9	18.7%	9.3%	9.4%	2.5%	3.75	4.10	+2.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	SD	49	0	51	215	39	16	5	0%	1.0	18.1%	7.6%	10.5%	2.4%	4.15	4.21	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	SD	22	0	23	96	16	8	3	0%	1.0	17.0%	8.2%	8.8%	2.8%	4.43	4.62	-0.0
2029	38	MLB MLE	SD	9	0	9	39	6	3	1	0%	1.0	15.8%	8.9%	6.9%	3.2%	4.80	5.05	-0.1
2030	39	MLB MLE	SD	4	0	4	16	2	2	1	0%	0.9	14.7%	9.6%	5.1%	3.7%	5.21	5.48	-0.0
2028	37	MLB CTX	SD	22	0	23	97	16	8	3	0%	1.0	17.0%	8.2%	8.8%	2.8%	4.43	4.62	-0.0
2029	38	MLB CTX	SD	9	0	9	38	6	3	1	0%	1.0	15.8%	8.9%	6.9%	3.2%	4.80	5.05	-0.1
2030	39	MLB CTX	SD	4	0	4	17	2	2	1	0%	1.0	14.7%	9.6%	5.1%	3.7%	5.21	5.48	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		601	7	569	2432	451	224	63	1%	0.9	18.5%	9.2%	9.3%	2.6%	3.80	4.11	+2.9
/ 200 IP	—	RAW		211	2	200	855	159	79	22	1%	0.9	18.5%	9.2%	9.3%	2.6%	3.80	4.11	+1.0
Career	—	MLE		677	31	757	3237	563	314	73	5%	1.1	17.4%	9.7%	7.7%	2.3%	3.78	4.10	+2.7
/ 200 IP	—	MLE		179	8	200	855	149	83	19	5%	1.1	17.4%	9.7%	7.7%	2.3%	3.78	4.10	+0.9

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.

2019 AAALouisville Bats · 11 IPFIP 2.04 → 2.22 (+0.18)K% 15.9% → 14.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.91%	—	×0.880	14.00%
BB% (unintentional) /BF	2.27%	—	×1.050	2.39%
HR / BF /BF	0.00%	÷0.957	×1.100	0.00%

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 91).

Result: FIP 2.04 → 2.22, 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 AAALouisville Bats · 14 IPFIP 4.10 → 4.45 (+0.35)K% 16.9% → 14.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.95%	—	×0.880	14.92%
BB% (unintentional) /BF	11.86%	—	×1.050	12.46%
HR / BF /BF	1.69%	÷0.988	×1.100	1.89%

Result: FIP 4.10 → 4.45, 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).

2016 AAALouisville Bats · 58 IPFIP 3.44 → 3.79 (+0.34)K% 16.2% → 14.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.24%	—	×0.880	14.29%
BB% (unintentional) /BF	9.83%	—	×1.050	10.32%
HR / BF /BF	0.85%	÷0.882	×1.100	1.07%

Result: FIP 3.44 → 3.79, 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).

2016 AAPensacola Blue Wahoos · 18 IPFIP 2.06 → 2.77 (+0.72)K% 27.4% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.40%	—	×0.810	22.19%
BB% (unintentional) /BF	4.11%	—	×1.100	4.52%
HR / BF /BF	1.37%	÷0.924	×1.200	1.78%

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 85).

Result: FIP 2.06 → 2.77, 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 AAPensacola Blue Wahoos · 117 IPFIP 3.99 → 4.50 (+0.51)K% 15.3% → 12.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.27%	—	×0.810	12.37%
BB% (unintentional) /BF	11.45%	—	×1.100	12.60%
HR / BF /BF	1.34%	÷1.037	×1.200	1.55%

Result: FIP 3.99 → 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).

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
Wandy Peralta (OGILVIE)	—	—	—	—	—	2.4%	—	4.62	17.0%	8.8%	23	+0.41	—	—	—
Brian Shouse L 2005 · 4.24 FIP	36	SU	4.24	15.0%	6.0%	3.0%	.271	3.35	15.0%	9.6%	137	-0.89	2.32	339	81
Heriberto Ruelas L 2017 · 3.42 FIP	35	SU	3.42	17.2%	6.7%	1.7%	.294	—	—	—	—	—	2.95	117	75
Hisanori Takahashi L 2011 · 3.64 FIP	36	SU	3.64	18.5%	6.0%	2.4%	.249	4.04	24.5%	18.4%	50	+0.40	3.50	240	73
Brandon Mann L 2018 · 3.59 FIP	34	SU	3.59	17.8%	11.4%	1.0%	.232	—	—	—	—	—	3.59	190	65
Tim Byrdak L 2010 · 4.48 FIP	36	SU	4.48	17.1%	11.8%	2.4%	.308	2.92	27.6%	18.1%	68	-1.56	2.85	320	65
Raul Valdes L 2013 · 4.07 FIP	35	SU	4.07	24.3%	5.3%	4.3%	.350	—	—	—	—	—	2.29	160	61
Juan Pablo Perez L 2015 · 3.68 FIP	36	SU	3.68	26.5%	15.3%	1.6%	.295	—	—	—	—	—	1.75	104	57
Mike Zagurski L 2018 · 3.12 FIP	35	SU	3.12	30.4%	9.3%	2.6%	.330	—	—	—	—	—	2.94	120	44
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	39
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	39
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	37
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	37
Erubiel Gonzalez R 2015 · 3.43 FIP	36	SU	3.43	12.4%	6.0%	1.1%	.328	3.26	14.8%	10.4%	69	-0.17	2.99	119	36
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	34
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	33
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	33
Jesus Adrian Castillo R 2019 · 5.13 FIP	35	SU	5.13	13.1%	7.8%	3.9%	.319	—	—	—	—	—	2.23	173	33
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	32
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	32
Pete Walker R 2005 · 4.79 FIP	36	SU	4.79	12.0%	9.2%	2.8%	.261	4.45	19.6%	11.6%	30	-0.34	4.45	327	32

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	3.1	44	18.5%	9.5%	0.99	3.83
Guillermo Mota ('12)	4.3	61	19.3%	9.2%	0.95	3.94
Trever Miller ('11)	2.6	48	18.7%	10.2%	0.93	4.18
Mike Fetters ('89-'04, 6 WAR*)	3.6	55	20.3%*	10.4%*	0.83*	3.70*
Bryan Shaw ('24)	3.8	64	20.8%	9.1%	0.97	3.96
Rich Rodriguez ('90-'03, 3 WAR*)	3.2	64	17.3%*	9.3%*	1.05*	4.00*
Tony Fossas ('88-'99, 2 WAR*)	2.1	42	21.9%*	9.3%*	0.99*	3.88*