Cionel Pérez

P New York Mets

Age 31 LHP 6'0" / 175 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	28	MIX2 levels	64	0	56	4.50	2.98	19.0%	11.7%	1.1	K 19.3% · BB 11.8% · FIP 2.96
2025	29	MIX2 levels	40	0	44	7.57	4.74	19.7%	16.1%	-0.1	K 18.3% · BB 15.3% · FIP 4.49
2026	30	MIX3 levels	50	2	56	4.15	4.17	24.1%	10.0%	0.3	K 22.2% · BB 9.6% · FIP 4.38
2027PROJ	31	MLBNYM	39	0	41	4.78	4.76	21.8%	12.3%	-0.1
2028PROJ95% MLB	32	MLBNYM	22	0	23	4.92	5.01	21.0%	12.7%	-0.1
2029PROJ95% MLB	33	MLBNYM	13	0	14	5.14	5.29	20.1%	13.1%	-0.1

Last 3 seasons WAR 1.2 · Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo81

K%50

xwOBA vs21

CompsRaul Valdes (age 32) · George Sherrill (age 31) · Edward Paredes (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 109117vR 125

ERA4.78

FIP4.76

K%21.8%

BB%12.3%

K-BB%9.5%

Proj IP41

Value2027 · WAR

Runs saved vs league avg · 41 IP

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL2525

CMD3030

K†5050

Statcast Percentiles

FB Velo

p8196.7

Whiff%

p4124.0%

p5022.2%

xwOBA vs

p210.346

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	21	MIX MLE	3 levels	21	16	94	390	83	27	4	76%	4.5	16.1%	8.0%	8.0%	1.2%	4.13	3.42	—
2017	21	MIX RAW	3 levels	21	16	94	390	83	27	4	76%	4.5	21.3%	6.9%	14.4%	1.0%	4.13	2.75	—
2018	22	MIX MLE	3 levels	28	11	85	348	101	35	6	39%	3.0	24.3%	8.7%	15.5%	1.2%	2.33	2.83	+1.8
2018	22	MIX RAW	3 levels	28	11	85	348	101	35	6	39%	3.0	29.0%	10.1%	19.0%	1.7%	2.33	2.88	+1.7
2019	23	MIX MLE	4 levels	22	13	64	286	65	29	9	59%	2.9	17.8%	11.8%	5.9%	3.3%	5.65	4.89	+0.4
2019	23	MIX RAW	4 levels	22	13	64	286	65	29	9	59%	2.9	22.7%	10.1%	12.6%	3.1%	5.65	4.26	+0.9
2020	24	MLB MLE	Houston Astros	7	0	6	32	8	5	0	0%	0.9	25.0%	15.6%	9.4%	0.0%	2.84	2.97	+0.1
2020	24	MLB RAW	Houston Astros	7	0	6	32	8	5	0	0%	0.9	25.0%	15.6%	9.4%	0.0%	2.84	2.94	+0.1
2021	25	MIX MLE	2 levels	56	0	54	240	66	31	6	0%	1.0	25.4%	13.2%	12.3%	2.4%	4.64	3.91	+0.4
2021	25	MIX RAW	2 levels	56	0	54	240	66	31	6	0%	1.0	27.5%	12.9%	14.6%	2.5%	4.64	3.82	+0.5
2022	26	MLB MLE	Baltimore Orioles	66	0	58	234	55	20	2	0%	0.9	23.5%	8.5%	15.0%	0.9%	1.40	2.67	+1.3
2022	26	MLB RAW	Baltimore Orioles	66	0	58	234	55	20	2	0%	0.9	23.5%	8.5%	15.0%	0.9%	1.40	2.68	+1.3
2023	27	MIX MLE	2 levels	66	0	55	253	47	25	2	0%	0.8	17.8%	9.7%	8.1%	0.8%	3.44	3.27	+0.8
2023	27	MIX RAW	2 levels	66	0	55	253	47	25	2	0%	0.8	18.6%	9.9%	8.7%	0.8%	3.44	3.23	+0.9
2024	28	MIX MLE	2 levels	64	0	56	248	47	29	0	0%	0.9	19.3%	11.8%	7.6%	0.0%	4.50	2.96	+1.1
2024	28	MIX MLE	2 levels	64	0	56	248	47	29	0	0%	0.9	19.3%	11.8%	7.6%	0.0%	4.50	2.96	+1.1
2024	28	MIX RAW	2 levels	64	0	56	248	47	29	0	0%	0.9	19.0%	11.7%	7.3%	0.0%	4.50	2.98	+1.1
2025	29	MIX MLE	2 levels	40	0	44	223	44	36	4	0%	1.1	18.3%	15.3%	3.0%	1.8%	7.57	4.49	+0.0
2025	29	MIX MLE	2 levels	40	0	44	223	44	36	4	0%	1.1	18.3%	15.3%	3.0%	1.8%	7.57	4.49	+0.0
2025	29	MIX RAW	2 levels	40	0	44	223	44	36	4	0%	1.1	19.7%	16.1%	3.6%	1.8%	7.57	4.74	-0.1
2026	30	MIX MLE	3 levels	50	2	56	241	58	24	8	4%	1.1	22.2%	9.6%	12.6%	3.5%	4.15	4.38	+0.1
2026	30	MIX MLE	3 levels	50	2	56	241	58	24	8	4%	1.1	22.2%	9.6%	12.6%	3.5%	4.15	4.38	+0.1
2026	30	MIX RAW	3 levels	50	2	56	241	58	24	8	4%	1.1	24.1%	10.0%	14.1%	3.3%	4.15	4.17	+0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			297	2	282	1255	262	141	25	1%	1.0	20.9%	11.2%	9.6%	2.0%	4.30	3.89	+2.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	NYM	39	0	41	173	38	21	5	0%	1.1	21.8%	12.3%	9.5%	2.9%	4.78	4.76	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	NYM	23	0	25	104	22	13	3	0%	1.1	21.0%	12.7%	8.3%	3.1%	4.92	5.01	-0.1
2029	33	MLB MLE	NYM	14	0	14	61	12	8	2	0%	1.0	20.1%	13.1%	7.0%	3.4%	5.14	5.29	-0.1
2030	34	MLB MLE	NYM	8	0	8	35	7	5	1	0%	1.0	19.2%	13.6%	5.6%	3.7%	5.42	5.60	-0.1
2028	32	MLB CTX	NYM	22	0	23	97	20	12	3	0%	1.0	21.0%	12.7%	8.3%	3.1%	4.92	5.01	-0.1
2029	33	MLB CTX	NYM	13	0	14	59	12	8	2	0%	1.1	20.1%	13.1%	7.0%	3.4%	5.14	5.29	-0.1
2030	34	MLB CTX	NYM	7	0	7	30	6	4	1	0%	1.0	19.2%	13.6%	5.6%	3.7%	5.42	5.60	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		339	2	327	1443	300	165	31	1%	1.0	20.8%	11.5%	9.4%	2.2%	4.41	3.98	+2.2
/ 200 IP	—	RAW		208	1	200	883	184	101	19	1%	1.0	20.8%	11.5%	9.4%	2.2%	4.41	3.98	+1.4
Career	—	MLE		420	42	572	2495	509	263	41	10%	1.4	20.4%	10.5%	9.9%	1.6%	4.03	3.60	+1.8
/ 200 IP	—	MLE		147	15	200	872	178	92	14	10%	1.4	20.4%	10.5%	9.9%	1.6%	4.03	3.60	+1.1

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.

2026 AAASyracuse Mets · 9 IPFIP 3.78 → 4.11 (+0.33)K% 29.7% → 25.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.73%	—	×0.860	25.57%
BB% (unintentional) /BF	13.51%	—	×0.900	12.16%
HR / BF /BF	2.70%	÷1.000	×1.100	2.97%

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 3.78 → 4.11, 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).

2025 AAANorfolk Tides · 22 IPFIP 4.00 → 4.10 (+0.11)K% 20.4% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.35%	—	×0.860	17.50%
BB% (unintentional) /BF	16.81%	—	×0.900	15.13%
HR / BF /BF	0.88%	÷0.945	×1.100	1.03%

Result: FIP 4.00 → 4.10, 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 AAALouisville Bats · 30 IPFIP 2.02 → 2.41 (+0.39)K% 31.8% → 28.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.78%	—	×0.880	27.97%
BB% (unintentional) /BF	9.30%	—	×1.050	9.77%
HR / BF /BF	0.78%	÷1.088	×1.100	0.78%

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 118).

Result: FIP 2.02 → 2.41, 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).

2019 AAARound Rock Express · 47 IPFIP 4.37 → 4.89 (+0.52)K% 20.2% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.19%	—	×0.880	17.77%
BB% (unintentional) /BF	11.27%	—	×1.050	11.83%
HR / BF /BF	2.82%	÷0.948	×1.100	3.27%

Result: FIP 4.37 → 4.89, 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 ROKGCL Astros · 6 IPFIP -0.11 → 1.78 (+1.89)K% 56.0% → 38.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	56.00%	—	×0.680	38.08%
BB% (unintentional) /BF	12.00%	—	×1.250	15.00%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

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 100).

Result: FIP -0.11 → 1.78, 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 AACorpus Christi Hooks · 68 IPFIP 2.17 → 2.83 (+0.66)K% 30.0% → 24.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.96%	—	×0.810	24.27%
BB% (unintentional) /BF	7.94%	—	×1.100	8.74%
HR / BF /BF	1.08%	÷1.059	×1.200	1.23%

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 112).

Result: FIP 2.17 → 2.83, 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).

2018 AAAFresno Grizzlies · 5 IPFIP 4.07 → 4.45 (+0.38)K% 23.1% → 20.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.880	20.31%
BB% (unintentional) /BF	23.08%	—	×1.050	24.23%
HR / BF /BF	0.00%	÷0.951	×1.100	0.00%

Result: FIP 4.07 → 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).

2017 AQuad Cities River Bandits · 55 IPFIP 2.49 → 3.25 (+0.76)K% 24.2% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.23%	—	×0.740	17.93%
BB% (unintentional) /BF	7.49%	—	×1.180	8.84%
HR / BF /BF	0.88%	÷1.154	×1.300	0.99%

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 131).

Result: FIP 2.49 → 3.25, 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
Cionel Pérez (OGILVIE)	—	—	4.76	21.8%	12.3%	2.9%	—	5.11	20.7%	7.8%	39	+0.35	—	—	—
Raul Valdes L 2010 · 4.02 FIP	32	SU	4.02	21.4%	9.9%	2.7%	.301	3.14	27.4%	22.5%	78	-0.88	2.29	160	76
George Sherrill L 2008 · 3.86 FIP	31	SU	3.86	24.3%	11.3%	2.5%	.277	3.38	20.6%	12.4%	141	-0.48	2.74	323	74
Edward Paredes L 2018 · 3.81 FIP	31	SU	3.81	22.7%	11.9%	2.0%	.351	5.10	21.5%	14.2%	18	+1.29	2.36	130	74
Randy Flores L 2006 · 4.00 FIP	31	SU	4.00	20.4%	9.7%	2.5%	.333	3.30	18.1%	10.5%	93	-0.70	2.51	250	73
Nick Hagadone L 2017 · 3.74 FIP	31	SU	3.74	22.6%	9.3%	2.5%	.267	—	—	—	—	—	2.97	141	71
Andrew Barbosa L 2017 · 4.67 FIP	29	SU	4.67	20.2%	9.6%	3.8%	.301	—	—	—	—	—	2.70	175	70
Scott Sauerbeck L 2003 · 4.59 FIP	31	SU	4.59	19.2%	14.6%	2.3%	.247	4.29	18.9%	7.8%	61	-0.30	2.79	386	70
David Purcey L 2013 · 3.79 FIP	31	SU	3.79	20.4%	11.5%	1.7%	.227	—	—	—	—	—	3.60	206	70
Adam Liberatore L 2018 · 4.28 FIP	31	SU	4.28	18.6%	9.1%	2.9%	.354	—	—	—	—	—	2.38	124	69
Brian Fuentes L 2007 · 3.68 FIP	31	SU	3.68	22.0%	9.0%	2.4%	.235	3.19	25.4%	16.4%	166	-0.49	2.08	602	69
Juan Pablo Perez L 2007 · 5.32 FIP	28	SU	5.32	17.5%	14.0%	3.5%	.324	—	—	—	—	—	1.75	104	68
Pedro Feliciano L 2008 · 3.90 FIP	31	SU	3.90	21.1%	7.6%	2.9%	.309	3.02	22.1%	14.9%	122	-0.88	2.69	378	67
James Jones L 2019 · 4.28 FIP	30	SU	4.28	21.9%	13.0%	2.5%	.230	4.65	23.9%	8.8%	35	+0.37	3.58	127	67
Jeremy Bleich L 2018 · 3.69 FIP	31	SU	3.69	20.3%	6.6%	2.7%	.296	4.41	20.1%	13.1%	33	+0.72	3.20	241	67
Vic Darensbourg L 2002 · 5.46 FIP	31	SU	5.46	14.2%	9.4%	4.3%	.304	4.11	9.4%	4.2%	22	-1.35	2.94	287	66
Ryan O'Rourke L 2019 · 4.08 FIP	31	SU	4.08	22.1%	14.3%	1.9%	.290	—	—	—	—	—	3.05	145	66
Brian Shouse L 2002 · 5.54 FIP	33	SU	5.54	15.5%	11.3%	4.2%	.245	3.31	16.3%	10.7%	159	-2.23	2.32	339	66
Buddy Boshers L 2019 · 3.73 FIP	31	SU	3.73	25.3%	10.4%	2.6%	.294	—	—	—	—	—	2.76	239	64
Mike Zagurski L 2012 · 4.48 FIP	29	SU	4.48	20.9%	11.7%	3.0%	.305	—	—	—	—	—	2.94	120	64
Tommy Phelps L 2005 · 3.98 FIP	31	SU	3.98	13.2%	7.5%	1.9%	.280	—	—	—	—	—	3.39	120	63

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	1.9	37	20.9%	12.0%	0.87	4.45
Yorkis Perez ('02)	1.4	40	20.8%	11.8%	0.93	4.44
Mike Holtz ('06)	1.2	34	20.4%	12.0%	0.94	4.76
Jason Christiansen ('05)	2.2	43	20.1%	11.4%	0.77	4.30
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Mike Munoz ('89-'00, 1 WAR*)	1.8	46	17.6%*	10.2%*	0.93*	4.46*
Horacio Pina ('68-'78, 2 WAR*)	2.2	62	20.7%*	11.2%*	0.84*	4.01*