Jordan Romano

P Colorado Rockies

Age 34 RHP 6'5" / 210 lbs MLB peak 0.1 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	31	MIX2 levels	17	15	6.14	6.17	20.0%	10.0%	-0.3	K 21.0% · BB 4.8% · FIP 5.48
2025	32	MLBPHI	49	43	8.23	5.07	25.1%	8.6%	-0.3
2026	33	MIX3 levels	48	43	5.19	4.25	25.7%	9.9%	0.2	K 25.5% · BB 11.8% · FIP 3.71
2027PROJ	34	MLBCOL	36	38	4.61	4.36	25.5%	9.9%	0.1
2028PROJ95% MLB	35	MLBCOL	28	29	4.66	4.69	24.6%	10.4%	-0.0
2029PROJ86% MLB	36	MLBCOL	16	17	4.90	5.06	23.5%	11.0%	-0.1

Last 3 seasons WAR -0.4 · 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

K%68

xwOBA vs68

FB Velo38

Form5.21 ERA (proj 4.61) · K 22.2% (proj 25.5%) · BB 11.1% (proj 9.9%) ▼ last 90d · 19 IP through Oct 27

CompsFernando Rodriguez Jr. (age 34) · Mark Serrano (age 33) · Zack Segovia (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 108100vR 92

ERA4.61

FIP4.36

K%25.5%

BB%9.9%

K-BB%15.7%

Proj IP38

Value2027 · WAR

Runs saved vs league avg · 38 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p3893.7

Whiff%

p6928.2%

p6825.5%

xwOBA vs

p680.294

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)
2016	23	A MLE	Lansing Lugnuts	15	14	73	294	72	27	3	93%	4.8	18.1%	10.8%	7.3%	1.4%	2.11	3.69	—
2016	23	A RAW	Lansing Lugnuts	15	14	73	294	72	27	3	93%	4.8	24.5%	9.2%	15.3%	1.0%	2.11	2.77	—
2017	24	A+ MLE	Dunedin Blue Jays	28	26	138	612	138	54	2	93%	4.9	17.4%	10.1%	7.2%	0.3%	3.39	3.10	—
2017	24	A+ RAW	Dunedin Blue Jays	28	26	138	612	138	54	2	93%	4.9	22.5%	8.8%	13.7%	0.3%	3.39	2.46	—
2018	25	MIX MLE	2 levels	26	26	142	593	128	45	15	100%	5.5	17.7%	7.9%	9.8%	3.3%	4.11	4.43	—
2018	25	MIX RAW	2 levels	26	26	142	593	128	45	15	100%	5.5	21.6%	7.6%	14.0%	2.5%	4.11	3.62	—
2019	26	MIX MLE	3 levels	42	3	54	244	74	23	12	7%	1.3	28.1%	9.8%	18.2%	5.3%	6.17	4.89	-0.2
2019	26	MIX RAW	3 levels	42	3	54	244	74	23	12	7%	1.3	30.3%	9.4%	20.9%	4.9%	6.17	4.53	+0.0
2020	27	MLB MLE	Toronto Blue Jays	15	0	15	57	21	5	2	0%	1.0	36.8%	8.8%	28.1%	3.5%	1.23	3.03	+0.3
2020	27	MLB RAW	Toronto Blue Jays	15	0	15	57	21	5	2	0%	1.0	36.8%	8.8%	28.1%	3.5%	1.23	3.03	+0.3
2021	28	MLB MLE	Toronto Blue Jays	62	0	63	253	85	25	7	0%	1.0	33.6%	9.9%	23.7%	2.8%	2.14	3.03	+1.1
2021	28	MLB RAW	Toronto Blue Jays	62	0	63	253	85	25	7	0%	1.0	33.6%	9.9%	23.7%	2.8%	2.14	3.04	+1.1
2022	29	MLB MLE	Toronto Blue Jays	63	0	64	258	73	17	4	0%	1.0	28.3%	6.6%	21.7%	1.6%	2.11	2.40	+1.7
2022	29	MLB RAW	Toronto Blue Jays	63	0	64	258	73	17	4	0%	1.0	28.3%	6.6%	21.7%	1.6%	2.11	2.43	+1.6
2023	30	MIX MLE	2 levels	60	0	60	252	72	19	6	0%	1.0	29.0%	7.7%	21.4%	2.4%	2.85	2.95	+1.1
2023	30	MIX RAW	2 levels	60	0	60	252	72	19	6	0%	1.0	28.6%	7.5%	21.0%	2.4%	2.85	2.95	+1.1
2024	31	MIX MLE	2 levels	17	0	15	70	14	7	4	0%	0.9	21.0%	4.8%	16.1%	6.5%	6.14	5.48	-0.2
2024	31	MIX MLE	2 levels	17	0	15	70	14	7	4	0%	0.9	21.0%	4.8%	16.1%	6.5%	6.14	5.48	-0.2
2024	31	MIX RAW	2 levels	17	0	15	70	14	7	4	0%	0.9	20.0%	10.0%	10.0%	5.7%	6.14	6.17	-0.3
2025	32	MLB MLE	Philadelphia Phillies	49	0	43	187	47	16	10	0%	0.9	25.1%	8.6%	16.6%	5.0%	8.23	4.80	-0.1
2025	32	MLB MLE	Philadelphia Phillies	49	0	43	187	47	16	10	0%	0.9	25.1%	8.6%	16.6%	5.0%	8.23	4.80	-0.1
2025	32	MLB RAW	Philadelphia Phillies	49	0	43	187	47	16	10	0%	0.9	25.1%	8.6%	16.6%	5.3%	8.23	5.07	-0.3
2026	33	MIX MLE	3 levels	48	0	43	191	49	19	7	0%	0.9	25.5%	11.8%	13.7%	2.3%	5.19	3.71	+0.4
2026	33	MIX MLE	3 levels	48	0	43	191	49	19	7	0%	0.9	25.5%	11.8%	13.7%	2.3%	5.19	3.71	+0.4
2026	33	MIX RAW	3 levels	48	0	43	191	49	19	7	0%	0.9	25.7%	9.9%	15.7%	3.7%	5.19	4.25	+0.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			318	0	306	1293	371	112	41	0%	1.0	28.7%	8.7%	20.0%	3.2%	3.94	3.52	+3.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	COL	36	0	38	160	41	16	5	0%	1.1	25.5%	9.9%	15.7%	3.2%	4.61	4.36	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	COL	29	0	31	130	32	14	5	0%	1.1	24.6%	10.4%	14.1%	3.6%	4.66	4.69	-0.0
2029	36	MLB MLE	COL	19	0	20	84	20	9	3	0%	1.0	23.5%	11.0%	12.5%	4.0%	4.90	5.06	-0.1
2030	37	MLB MLE	COL	10	0	11	46	10	5	2	0%	1.1	22.4%	11.7%	10.8%	4.4%	5.24	5.46	-0.1
2028	35	MLB CTX	COL	28	0	29	122	30	13	4	0%	1.0	24.6%	10.4%	14.1%	3.6%	4.66	4.69	-0.0
2029	36	MLB CTX	COL	16	0	17	72	17	8	3	0%	1.1	23.5%	11.0%	12.5%	4.0%	4.90	5.06	-0.1
2030	37	MLB CTX	COL	8	0	8	34	8	4	1	0%	1.0	22.4%	11.7%	10.8%	4.4%	5.24	5.46	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		370	0	361	1525	426	137	50	0%	1.0	28.0%	9.0%	19.0%	3.3%	4.08	3.67	+3.8
/ 200 IP	—	RAW		205	0	200	845	236	76	28	0%	1.0	28.0%	9.0%	19.0%	3.3%	4.08	3.67	+2.1
Career	—	MLE		425	69	709	3011	696	273	76	16%	1.7	23.1%	9.1%	14.0%	2.5%	3.76	3.68	+3.5
/ 200 IP	—	MLE		120	19	200	849	196	77	21	16%	1.7	23.1%	9.1%	14.0%	2.5%	3.76	3.68	+1.9

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.

2026 AAAAlbuquerque Isotopes · 9 IPFIP 5.46 → 6.29 (+0.83)K% 29.4% → 25.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.41%	—	×0.860	25.29%
BB% (unintentional) /BF	0.00%	—	×0.900	0.00%
HR / BF /BF	8.82%	÷1.000	×1.100	9.71%

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 5.46 → 6.29, 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).

2019 AAABuffalo Bisons · 38 IPFIP 4.12 → 4.76 (+0.64)K% 31.9% → 28.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.93%	—	×0.880	28.10%
BB% (unintentional) /BF	8.43%	—	×1.050	8.86%
HR / BF /BF	4.82%	÷1.000	×1.100	5.30%

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 100).

Result: FIP 4.12 → 4.76, 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 AANew Hampshire Fisher Cats · 137 IPFIP 3.60 → 4.43 (+0.83)K% 21.9% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.89%	—	×0.810	17.73%
BB% (unintentional) /BF	7.18%	—	×1.100	7.90%
HR / BF /BF	2.63%	÷0.945	×1.200	3.34%

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 89).

Result: FIP 3.60 → 4.43, 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 AAABuffalo Bisons · 5 IPFIP 4.25 → 4.50 (+0.25)K% 13.6% → 12.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.64%	—	×0.880	12.00%
BB% (unintentional) /BF	18.18%	—	×1.050	19.09%
HR / BF /BF	0.00%	÷1.080	×1.100	0.00%

Result: FIP 4.25 → 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).

2017 A+Dunedin Blue Jays · 138 IPFIP 2.49 → 3.10 (+0.60)K% 22.5% → 17.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.55%	—	×0.770	17.36%
BB% (unintentional) /BF	8.82%	—	×1.150	10.15%
HR / BF /BF	0.33%	÷1.265	×1.250	0.32%

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 153).

Result: FIP 2.49 → 3.10, 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).

2016 ALansing Lugnuts · 73 IPFIP 2.76 → 3.69 (+0.94)K% 24.5% → 18.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.49%	—	×0.740	18.12%
BB% (unintentional) /BF	9.18%	—	×1.180	10.84%
HR / BF /BF	1.02%	÷0.968	×1.300	1.37%

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 94).

Result: FIP 2.76 → 3.69, 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
Jordan Romano (OGILVIE)	—	—	—	—	—	3.2%	—	4.94	23.9%	13.0%	62	+0.58	—	—	—
Fernando Rodriguez Jr. R 2018 · 4.07 FIP	34	SW	4.07	23.7%	9.9%	3.1%	.253	5.11	25.0%	13.8%	32	+1.04	3.34	335	74
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	72
Zack Segovia R 2016 · 3.33 FIP	33	SU	3.33	20.2%	5.9%	2.2%	.312	4.55	17.6%	4.0%	57	+1.22	3.33	144	72
Diego Moreno R 2021 · 4.75 FIP	34	SU	4.75	18.6%	9.4%	3.7%	.232	—	—	—	—	—	2.29	187	72
Jean Machi R 2016 · 4.36 FIP	34	SU	4.36	18.3%	6.6%	3.6%	.282	4.12	18.6%	12.0%	67	-0.24	2.16	306	71
Blake Parker R 2019 · 4.65 FIP	34	SU	4.65	25.5%	8.6%	4.8%	.258	4.26	24.9%	15.4%	87	-0.39	2.52	406	70
Josh Lueke R 2019 · 4.11 FIP	34	SU	4.11	20.4%	6.4%	3.5%	.311	—	—	—	—	—	2.29	191	69
Dustin Molleken R 2017 · 3.38 FIP	32	SU	3.38	24.3%	12.4%	1.4%	.311	—	—	—	—	—	3.38	129	68
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	68
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	67
Brendan Donnelly R 2005 · 4.02 FIP	34	SU	4.02	19.6%	5.9%	3.3%	.264	4.02	17.6%	8.5%	98	-0.00	2.23	385	67
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	66
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	65
Greg Burke R 2015 · 3.61 FIP	32	SU	3.61	22.1%	7.3%	2.7%	.241	—	—	—	—	—	3.61	139	65
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	64
Juan Sandoval R 2015 · 3.82 FIP	34	SU	3.82	15.4%	6.0%	2.3%	.294	3.33	17.4%	8.8%	116	-0.49	3.24	225	63
Scott McGough R 2024 · 4.56 FIP	34	SU	4.56	18.6%	12.2%	2.7%	.289	3.82	20.3%	13.1%	57	-0.74	3.55	429	63
Rodolfo Aguirre R 2019 · 4.50 FIP	34	SU	4.50	21.3%	5.1%	4.7%	.244	—	—	—	—	—	3.39	212	63
Yoshihisa Hirano R 2018 · 3.45 FIP	34	SU	3.45	22.5%	7.3%	2.4%	.242	3.97	24.6%	15.2%	65	+0.52	3.45	132	63
Rafael Martín R 2017 · 3.40 FIP	33	SU	3.40	20.4%	5.1%	2.5%	.305	4.71	22.5%	16.5%	47	+1.31	2.94	227	62

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	2.0	45	27.7%	9.8%	1.27	4.14
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Trevor May ('23)	2.3	50	26.8%	8.5%	1.20	4.24
Hansel Robles ('22)	2.1	61	25.3%	10.2%	1.20	4.11
Matt Barnes ('24)	2.3	52	29.0%	10.6%	1.02	4.21
Buddy Schultz ('75-'79, 2 WAR*)	1.2	60	27.4%*	8.5%*	1.21*	4.14*
Rob Murphy ('85-'95, 6 WAR*)	3.1	69	25.2%*	9.2%*	1.07*	3.94*