Emilio Pagán

P Cincinnati Reds

Age 36 RHP 6'2" / 208 lbs MLB peak 0.3 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	33	MIX2 levels	41	1	41	4.61	3.51	27.8%	6.5%	0.5	K 27.8% · BB 7.0% · FIP 3.56
2025	34	MLBCIN	70	0	69	2.88	3.60	30.0%	8.1%	0.8
2026	35	MIX2 levels	47	1	45	3.22	3.79	25.0%	5.6%	0.4	K 25.9% · BB 5.7% · FIP 3.69
2027PROJ	36	MLBCIN	44	0	46	3.77	3.87	27.7%	7.0%	0.4
2028PROJ	37	MLBCIN	32	0	34	4.07	4.27	26.6%	7.6%	0.1

Last 3 seasons WAR 1.7 · Next 2 projected WAR 0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs77

K%70

FB Velo55

Form1.69 ERA (proj 3.77) · K 26.5% (proj 27.7%) · BB 3.6% (proj 7.0%) · last 90d · 21 IP through Oct 27

CompsSeunghwan Oh (age 36) · Matt Bush (age 36) · Rafael Martín (age 35)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10092vR 84

ERA3.77

FIP3.87

K%27.7%

BB%7.0%

K-BB%20.7%

Proj IP46

Value2027 · WAR

Runs saved vs league avg · 46 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p5594.9

Whiff%

p5425.9%

p7025.9%

xwOBA vs

p770.286

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	A+ MLE	Bakersfield Blaze	42	0	78	326	88	26	5	0%	1.9	20.8%	9.2%	11.6%	1.8%	2.53	3.48	—
2015	24	A+ RAW	Bakersfield Blaze	42	0	78	326	88	26	5	0%	1.9	27.0%	8.0%	19.0%	1.5%	2.53	2.68	—
2016	25	MIX MLE	2 levels	41	0	65	270	84	29	7	0%	1.6	26.2%	11.5%	14.7%	3.2%	2.49	4.08	—
2016	25	MIX RAW	2 levels	41	0	65	270	84	29	7	0%	1.6	31.1%	10.7%	20.4%	2.6%	2.49	3.25	—
2017	26	MIX MLE	2 levels	57	0	82	321	92	16	7	0%	1.4	27.3%	5.1%	22.2%	2.2%	2.96	2.67	+1.9
2017	26	MIX RAW	2 levels	57	0	82	321	92	16	7	0%	1.4	28.7%	5.0%	23.7%	2.2%	2.96	2.55	+2.0
2018	27	MIX MLE	2 levels	60	0	68	286	74	18	15	0%	1.1	24.0%	6.9%	17.2%	5.5%	4.24	4.93	-0.3
2018	27	MIX RAW	2 levels	60	0	68	286	74	18	15	0%	1.1	25.9%	6.3%	19.6%	5.2%	4.24	4.59	-0.0
2019	28	MIX MLE	2 levels	70	1	76	293	106	16	12	1%	1.1	36.0%	4.5%	31.5%	4.6%	2.13	3.17	+1.3
2019	28	MIX RAW	2 levels	70	1	76	293	106	16	12	1%	1.1	36.2%	5.5%	30.7%	4.1%	2.13	2.99	+1.4
2020	29	MLB MLE	San Diego Padres	22	0	22	87	23	9	4	0%	1.0	26.4%	10.3%	16.1%	4.5%	4.50	4.64	-0.0
2020	29	MLB RAW	San Diego Padres	22	0	22	87	23	9	4	0%	1.0	26.4%	10.3%	16.1%	4.6%	4.50	4.60	-0.0
2021	30	MLB MLE	San Diego Padres	67	0	63	263	69	18	16	0%	0.9	26.2%	6.8%	19.4%	5.9%	4.83	5.01	-0.3
2021	30	MLB RAW	San Diego Padres	67	0	63	263	69	18	16	0%	0.9	26.2%	6.8%	19.4%	6.1%	4.83	5.06	-0.4
2022	31	MLB MLE	Minnesota Twins	59	0	63	274	84	24	12	0%	1.1	30.7%	8.8%	21.9%	4.4%	4.43	4.01	+0.4
2022	31	MLB RAW	Minnesota Twins	59	0	63	274	84	24	12	0%	1.1	30.7%	8.8%	21.9%	4.4%	4.43	4.05	+0.4
2023	32	MLB MLE	Minnesota Twins	66	1	69	273	65	19	5	2%	1.1	23.8%	7.0%	16.8%	1.8%	2.99	2.97	+1.3
2023	32	MLB RAW	Minnesota Twins	66	1	69	273	65	19	5	2%	1.1	23.8%	7.0%	16.8%	1.8%	2.99	2.98	+1.3
2024	33	MIX MLE	2 levels	41	1	41	169	47	11	6	2%	1.0	27.8%	7.0%	20.9%	3.5%	4.61	3.56	+0.5
2024	33	MIX MLE	2 levels	41	1	41	169	47	11	6	2%	1.0	27.8%	7.0%	20.9%	3.5%	4.61	3.56	+0.5
2024	33	MIX RAW	2 levels	41	1	41	169	47	11	6	2%	1.0	27.8%	6.5%	21.3%	3.6%	4.61	3.51	+0.5
2025	34	MLB MLE	Cincinnati Reds	70	0	69	270	81	22	10	0%	1.0	30.0%	8.1%	21.9%	3.4%	2.88	3.48	+0.9
2025	34	MLB MLE	Cincinnati Reds	70	0	69	270	81	22	10	0%	1.0	30.0%	8.1%	21.9%	3.4%	2.88	3.48	+0.9
2025	34	MLB RAW	Cincinnati Reds	70	0	69	270	81	22	10	0%	1.0	30.0%	8.1%	21.9%	3.7%	2.88	3.60	+0.8
2026	35	MIX MLE	2 levels	47	1	45	180	45	10	7	2%	1.0	25.9%	5.7%	20.1%	3.7%	3.22	3.69	+0.5
2026	35	MIX MLE	2 levels	47	1	45	180	45	10	7	2%	1.0	25.9%	5.7%	20.1%	3.7%	3.22	3.69	+0.5
2026	35	MIX RAW	2 levels	47	1	45	180	45	10	7	2%	1.0	25.0%	5.6%	19.4%	3.9%	3.22	3.79	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			522	2	549	2224	626	151	92	0%	1.1	28.1%	6.8%	21.4%	4.1%	3.64	3.82	+4.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	CIN	44	0	46	194	54	13	7	0%	1.0	27.7%	7.0%	20.7%	3.4%	3.77	3.87	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	CIN	32	0	34	142	38	11	5	0%	1.1	26.6%	7.6%	19.0%	3.8%	4.07	4.27	+0.1
2028	37	MLB CTX	CIN	32	0	34	144	38	11	5	0%	1.1	26.6%	7.6%	19.0%	3.8%	4.07	4.27	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		554	2	583	2366	664	162	97	0%	1.1	28.1%	6.8%	21.2%	4.1%	3.66	3.86	+4.8
/ 200 IP	—	RAW		190	1	200	812	228	56	33	0%	1.1	28.1%	6.8%	21.2%	4.1%	3.66	3.86	+1.6
Career	—	MLE		642	4	741	3012	816	224	109	1%	1.2	27.1%	7.4%	19.6%	3.6%	3.34	3.74	+4.8
/ 200 IP	—	MLE		173	1	200	813	220	60	29	1%	1.2	27.1%	7.4%	19.6%	3.6%	3.34	3.74	+1.7

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 AAADurham Bulls · 6 IPFIP 1.80 → 2.29 (+0.49)K% 38.5% → 33.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.46%	—	×0.880	33.85%
BB% (unintentional) /BF	15.38%	—	×1.050	16.15%
HR / BF /BF	0.00%	÷1.128	×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 126).

Result: FIP 1.80 → 2.29, 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 AAANashville Sounds · 6 IPFIP 3.80 → 4.79 (+0.98)K% 45.8% → 40.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	45.83%	—	×0.880	40.33%
BB% (unintentional) /BF	0.00%	—	×1.050	0.00%
HR / BF /BF	8.33%	÷0.988	×1.100	9.28%

Result: FIP 3.80 → 4.79, 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).

2017 AAATacoma Rainiers · 32 IPFIP 1.48 → 1.81 (+0.33)K% 28.8% → 25.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.80%	—	×0.880	25.34%
BB% (unintentional) /BF	6.40%	—	×1.050	6.72%
HR / BF /BF	0.00%	÷0.963	×1.100	0.00%

Result: FIP 1.48 → 1.81, 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).

2016 AAATacoma Rainiers · 34 IPFIP 4.67 → 5.54 (+0.87)K% 26.9% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.90%	—	×0.880	23.67%
BB% (unintentional) /BF	12.41%	—	×1.050	13.03%
HR / BF /BF	4.14%	÷0.896	×1.100	5.08%

Result: FIP 4.67 → 5.54, 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 AAJackson Generals · 31 IPFIP 1.61 → 2.39 (+0.78)K% 36.0% → 29.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.00%	—	×0.810	29.16%
BB% (unintentional) /BF	8.80%	—	×1.100	9.68%
HR / BF /BF	0.80%	÷0.992	×1.200	0.97%

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 98).

Result: FIP 1.61 → 2.39, 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+Bakersfield Blaze · 78 IPFIP 2.67 → 3.48 (+0.81)K% 27.0% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.99%	—	×0.770	20.79%
BB% (unintentional) /BF	7.98%	—	×1.150	9.17%
HR / BF /BF	1.53%	÷1.077	×1.250	1.78%

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 115).

Result: FIP 2.67 → 3.48, 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
Emilio Pagán (OGILVIE)	—	—	—	—	—	3.4%	—	4.27	26.6%	19.0%	34	+0.40	—	—	—
Seunghwan Oh R 2018 · 2.83 FIP	36	SU	2.83	28.8%	5.8%	2.6%	.257	5.75	18.2%	11.4%	18	+2.92	1.87	226	76
Matt Bush R 2022 · 3.73 FIP	36	SU	3.73	30.3%	6.6%	4.3%	.224	3.79	26.2%	17.5%	36	+0.06	2.87	249	63
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	62
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	59
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	58
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	57
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	55
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	55
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	52
Peter Moylan R 2015 · 3.11 FIP	36	SU	3.11	18.4%	8.2%	0.9%	.259	3.84	18.2%	9.1%	145	+0.73	2.54	431	50
Daniel Bard R 2021 · 3.62 FIP	36	SU	3.62	26.3%	11.5%	2.3%	.337	3.64	24.6%	10.3%	110	+0.02	2.56	456	50
Roy Corcoran R 2015 · 2.87 FIP	35	SU	2.87	17.7%	8.2%	0.4%	.359	—	—	—	—	—	2.87	129	50
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	49
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	48
Koji Uehara R 2011 · 2.95 FIP	36	SU	2.95	35.0%	3.3%	4.3%	.194	2.13	34.9%	32.1%	175	-0.82	1.28	481	48
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	45
Yoshihisa Hirano R 2020 · 5.02 FIP	36	SU	5.02	17.5%	12.7%	3.3%	.381	—	—	—	—	—	3.45	132	43
Kazuhisa Makita R 2019 · 2.81 FIP	34	SU	2.81	18.9%	3.7%	1.5%	.291	—	—	—	—	—	2.81	132	42
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	42
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	42

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	52	28.0%	7.1%	1.57	3.67
Shawn Kelley ('19)	2.3	46	27.0%	7.3%	1.47	3.80
Chad Green ('25)	2.5	62	30.0%	6.4%	1.42	3.43
Joel Peralta ('16)	3.2	54	23.0%	7.0%	1.32	4.03
Joe Hoerner ('63-'77, 8 WAR*)	2.8	51	23.2%*	7.9%*	1.21*	3.52*
Bob Patterson ('85-'98, 4 WAR*)	3.1	51	23.0%*	6.7%*	1.32*	4.33*
Tom Niedenfuer ('81-'90, 8 WAR*)	3.3	65	23.1%*	8.1%*	1.19*	3.80*