Carlos Rodón

P New York Yankees

Age 34 LHP 6'2" / 255 lbs MLB Svc 11.0 · Ctrl thru 2028 peak 1.5 · 2027

Overview

MLBSP40-MANExtFA 2028

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	31	MLBNYY	32	32	175	3.96	4.15	26.5%	7.7%	2.6
2025	32	MLBNYY	33	33	195	3.09	3.61	25.7%	9.3%	4.3
2026	33	MIX4 levels	21	21	107	2.85	3.46	27.3%	10.2%	2.5	K 26.8% · BB 11.2% · FIP 3.31
2027PROJ	34	MLBNYY	14	14	83	3.81	3.94	26.5%	9.8%	1.4
2028PROJ	35	MLBNYY	14	14	82	4.20	4.39	25.5%	10.3%	1.1
2029PROJ	36	MLBNYY	11	11	64	4.54	4.77	24.5%	10.9%	0.6

Last 3 seasons WAR 9.4 · Next 3 projected WAR 3.1Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2028Service11.977First FA2028NTC

2027Ext$27M2028Ext$27M

Skills · percentileStatcast 2026

K%75

xwOBA vs58

FB Velo47

Form1.80 ERA (proj 3.81) · K 29.5% (proj 26.5%) · BB 7.1% (proj 9.8%) ▲ last 60d · 30 IP through Oct 27

CompsOrlando Lara (age 34) · Daniel Rodriguez (age 34) · Marlon Arias (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 8997vR 105

ERA3.81

FIP3.94

K%26.5%

BB%9.8%

K-BB%16.7%

Proj IP83

Value2027 · WAR

Runs saved vs league avg · 83 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control-$34M ctrl surplus

Statcast · Contract

Statcast Percentiles

FB Velo

p4794.3

Whiff%

p8030.0%

p7526.8%

xwOBA vs

p580.304

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status FA

MLB Debut 2015

Service 11.977 yrs.days

Team Control Through 2028

First FA Year 2028

NTC

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$27M	+1.4	$11M	-$16M
2028	Ext	$27M	+1.1	$8M	-$16M
Totals		$54M		$19M	-$32M

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	22	MIX MLE	2 levels	28	25	149	650	152	75	11	89%	5.3	22.9%	11.7%	11.2%	1.8%	3.74	3.63	+3.2
2015	22	MIX RAW	2 levels	28	25	149	650	152	75	11	89%	5.3	23.4%	11.5%	11.8%	1.7%	3.74	3.53	+3.4
2016	23	MIX MLE	2 levels	29	29	169	733	171	53	24	100%	5.8	23.5%	7.1%	16.4%	3.2%	4.06	3.75	+3.4
2016	23	MIX RAW	2 levels	29	29	169	733	171	53	24	100%	5.8	23.3%	7.2%	16.1%	3.3%	4.06	3.86	+3.1
2017	24	MIX MLE	3 levels	16	16	86	379	93	40	13	100%	5.4	23.6%	10.6%	13.0%	3.2%	5.32	4.23	+1.2
2017	24	MIX RAW	3 levels	16	16	86	379	93	40	13	100%	5.4	24.5%	10.6%	14.0%	3.4%	5.32	4.29	+1.1
2018	25	MIX MLE	3 levels	24	24	138	578	118	59	15	100%	5.8	19.5%	10.6%	8.9%	2.6%	3.84	4.23	+1.9
2018	25	MIX RAW	3 levels	24	24	138	578	118	59	15	100%	5.8	20.4%	10.2%	10.2%	2.6%	3.84	4.08	+2.2
2019	26	MLB MLE	Chicago White Sox	7	7	35	158	46	17	4	100%	5.0	29.1%	10.8%	18.4%	2.5%	5.19	3.37	+0.9
2019	26	MLB RAW	Chicago White Sox	7	7	35	158	46	17	4	100%	5.0	29.1%	10.8%	18.4%	2.5%	5.19	3.42	+0.8
2020	27	MLB MLE	Chicago White Sox	4	2	8	35	6	3	1	50%	1.9	17.1%	8.6%	8.6%	2.9%	8.22	4.31	+0.1
2020	27	MLB RAW	Chicago White Sox	4	2	8	35	6	3	1	50%	1.9	17.1%	8.6%	8.6%	2.9%	8.22	4.40	+0.1
2021	28	MLB MLE	Chicago White Sox	24	24	133	534	185	35	13	100%	5.5	34.6%	6.6%	28.1%	2.4%	2.37	2.32	+5.3
2021	28	MLB RAW	Chicago White Sox	24	24	133	534	185	35	13	100%	5.5	34.6%	6.6%	28.1%	2.4%	2.37	2.38	+5.2
2022	29	MLB MLE	San Francisco Giants	31	31	178	710	237	52	12	100%	5.7	33.4%	7.3%	26.1%	1.8%	2.88	2.21	+7.4
2022	29	MLB RAW	San Francisco Giants	31	31	178	710	237	52	12	100%	5.7	33.4%	7.3%	26.1%	1.7%	2.88	2.19	+7.5
2023	30	MIX MLE	3 levels	17	17	75	324	81	31	15	100%	4.4	22.4%	9.8%	12.6%	4.9%	6.00	5.15	+0.2
2023	30	MIX RAW	3 levels	17	17	75	324	81	31	15	100%	4.4	25.0%	9.6%	15.4%	4.6%	6.00	4.78	+0.5
2024	31	MLB MLE	New York Yankees	32	32	175	736	195	57	31	100%	5.5	26.5%	7.7%	18.8%	3.9%	3.96	4.01	+2.9
2024	31	MLB MLE	New York Yankees	32	32	175	736	195	57	31	100%	5.5	26.5%	7.7%	18.8%	3.9%	3.96	4.01	+2.9
2024	31	MLB RAW	New York Yankees	32	32	175	736	195	57	31	100%	5.5	26.5%	7.7%	18.8%	4.2%	3.96	4.15	+2.6
2025	32	MLB MLE	New York Yankees	33	33	195	789	203	73	22	100%	5.9	25.7%	9.3%	16.5%	2.6%	3.09	3.53	+4.5
2025	32	MLB MLE	New York Yankees	33	33	195	789	203	73	22	100%	5.9	25.7%	9.3%	16.5%	2.6%	3.09	3.53	+4.5
2025	32	MLB RAW	New York Yankees	33	33	195	789	203	73	22	100%	5.9	25.7%	9.3%	16.5%	2.8%	3.09	3.61	+4.3
2026	33	MIX MLE	4 levels	21	21	107	432	118	44	11	100%	5.1	26.8%	11.2%	15.6%	1.9%	2.85	3.31	+2.8
2026	33	MIX MLE	4 levels	21	21	107	432	118	44	11	100%	5.1	26.8%	11.2%	15.6%	1.9%	2.85	3.31	+2.8
2026	33	MIX RAW	4 levels	21	21	107	432	118	44	11	100%	5.1	27.3%	10.2%	17.1%	2.5%	2.85	3.46	+2.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			247	242	1366	5718	1500	510	166	98%	5.5	26.2%	8.9%	17.3%	2.9%	3.67	3.60	+29.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	NYY	14	14	83	350	93	34	9	100%	5.9	26.5%	9.8%	16.7%	2.7%	3.81	3.94	+1.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	NYY	14	14	82	348	89	36	10	100%	5.9	25.5%	10.3%	15.2%	3.0%	4.09	4.28	+1.1
2029	36	MLB MLE	NYY	11	11	64	269	66	29	9	100%	5.8	24.5%	10.9%	13.6%	3.4%	4.42	4.65	+0.6
2028	35	MLB CTX	NYY	14	14	82	346	88	36	11	100%	5.9	25.5%	10.3%	15.2%	3.2%	4.20	4.39	+1.1
2029	36	MLB CTX	NYY	11	11	64	270	66	30	10	100%	5.8	24.5%	10.9%	13.6%	3.6%	4.54	4.77	+0.6
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		271	266	1513	6335	1655	575	187	98%	5.6	26.1%	9.1%	17.0%	2.9%	3.73	3.66	+31.8
/ 200 IP	—	RAW		36	35	200	838	219	76	25	98%	5.6	26.1%	9.1%	17.0%	2.9%	3.73	3.66	+4.2
Career	—	MLE		266	261	1448	6058	1583	546	167	98%	5.4	26.1%	9.0%	17.1%	2.8%	3.70	3.55	+31.4
/ 200 IP	—	MLE		37	36	200	837	219	75	23	98%	5.4	26.1%	9.0%	17.1%	2.8%	3.70	3.55	+4.2

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 AAAScranton/Wilkes-Barre RailRiders · 9 IPFIP 6.79 → 7.32 (+0.52)K% 20.0% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.860	17.20%
BB% (unintentional) /BF	10.00%	—	×0.900	9.00%
HR / BF /BF	7.50%	÷1.000	×1.100	8.25%

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 6.79 → 7.32, 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).

2026 AASomerset Patriots · 10 IPFIP 1.46 → 2.47 (+1.01)K% 41.7% → 33.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.67%	—	×0.810	33.75%
BB% (unintentional) /BF	2.78%	—	×1.100	3.06%
HR / BF /BF	2.78%	÷1.000	×1.200	3.33%

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 100).

Result: FIP 1.46 → 2.47, 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).

2023 AASomerset Patriots · 7 IPFIP 0.35 → 1.03 (+0.68)K% 39.1% → 31.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.13%	—	×0.810	31.70%
BB% (unintentional) /BF	4.35%	—	×1.100	4.78%
HR / BF /BF	0.00%	÷1.033	×1.200	0.00%

Result: FIP 0.35 → 1.03, 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 AAACharlotte Knights · 13 IPFIP 0.65 → 1.16 (+0.51)K% 44.0% → 38.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	44.00%	—	×0.880	38.72%
BB% (unintentional) /BF	10.00%	—	×1.050	10.50%
HR / BF /BF	0.00%	÷1.319	×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 164).

Result: FIP 0.65 → 1.16, 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 AAACharlotte Knights · 14 IPFIP 3.04 → 3.27 (+0.24)K% 16.7% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.67%	—	×0.880	14.67%
BB% (unintentional) /BF	10.61%	—	×1.050	11.14%
HR / BF /BF	0.00%	÷1.150	×1.100	0.00%

Result: FIP 3.04 → 3.27, 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 AAACharlotte Knights · 10 IPFIP 1.73 → 2.09 (+0.37)K% 30.2% → 26.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.23%	—	×0.880	26.60%
BB% (unintentional) /BF	9.30%	—	×1.050	9.77%
HR / BF /BF	0.00%	÷1.306	×1.100	0.00%

Result: FIP 1.73 → 2.09, 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
Carlos Rodón (OGILVIE)	—	—	—	—	—	2.7%	—	4.44	25.0%	14.5%	146	+0.50	—	—	—
Orlando Lara L 2019 · 4.09 FIP	34	SP	4.09	22.0%	7.8%	3.4%	.329	—	—	—	—	—	3.85	426	48
Daniel Rodriguez L 2019 · 4.77 FIP	34	SP	4.77	20.8%	7.8%	4.5%	.329	—	—	—	—	—	2.89	391	46
Marlon Arias L 2019 · 4.83 FIP	34	SP	4.83	19.8%	11.2%	3.6%	.273	—	—	—	—	—	3.73	154	41
Francisley Bueno L 2015 · 3.77 FIP	34	SP	3.77	14.8%	7.1%	1.9%	.315	3.99	13.3%	6.6%	110	+0.22	2.43	188	40
Tsuyoshi Wada L 2015 · 3.66 FIP	34	SP	3.66	16.8%	7.1%	2.0%	.307	—	—	—	—	—	3.60	188	39
Oscar Rivera L 2015 · 3.68 FIP	34	SP	3.68	14.2%	6.9%	1.7%	.298	4.66	10.4%	3.0%	129	+0.98	3.68	237	37
Mauricio Lara L 2015 · 3.62 FIP	36	SP	3.62	13.9%	6.9%	1.5%	.310	3.69	12.1%	5.1%	220	+0.07	3.62	444	36
Kwang Hyun Kim L 2021 · 4.21 FIP	33	SP-	4.21	17.7%	8.2%	2.9%	.266	—	—	—	—	—	3.76	146	34
Orlando Hernandez R 2004 · 3.77 FIP	34	SP	3.77	23.4%	10.0%	2.5%	.278	4.34	20.5%	11.7%	438	+0.57	3.35	1,315	33
Chris Narveson L 2016 · 4.59 FIP	34	SP-	4.59	16.2%	8.5%	3.2%	.253	4.59	12.2%	1.8%	103	+0.00	4.00	625	32
Merrill Kelly R 2023 · 3.73 FIP	34	SP	3.73	25.9%	9.6%	2.9%	.276	4.36	19.7%	12.0%	420	+0.63	3.60	1,170	31
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	31
Jorge Castillo L 2016 · 4.94 FIP	34	SP	4.94	13.0%	4.6%	4.3%	.246	4.93	16.8%	9.2%	179	-0.01	4.50	408	29
Arturo Lopez L 2017 · 4.34 FIP	34	SP	4.34	10.3%	5.4%	2.6%	.342	5.46	12.2%	5.4%	117	+1.12	4.34	445	28
Hiroki Kuroda R 2009 · 3.54 FIP	34	SP	3.54	17.9%	4.7%	2.5%	.270	3.43	19.1%	14.2%	618	-0.11	2.96	1,319	25
Jose Oyervides R 2016 · 3.09 FIP	34	SP	3.09	24.9%	8.2%	1.9%	.318	5.55	17.0%	7.8%	195	+2.46	3.01	407	25
Hisashi Iwakuma R 2015 · 3.74 FIP	34	SP	3.74	21.5%	3.9%	3.6%	.270	4.44	16.9%	11.2%	230	+0.70	3.19	884	24
Jose Contreras R 2006 · 3.83 FIP	34	SP	3.83	16.1%	6.1%	2.4%	.277	4.08	14.7%	7.3%	442	+0.25	2.43	1,279	21
Josh Lowey R 2019 · 3.45 FIP	34	SP	3.45	22.4%	6.8%	2.5%	.303	—	—	—	—	—	2.22	426	20
Manuel Flores R 2019 · 4.32 FIP	33	SP	4.32	17.1%	7.4%	3.1%	.291	—	—	—	—	—	3.46	515	19

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	8.0	114	26.1%	9.2%	1.13	3.73
Jose DeLeon ('83-'95, 22 WAR*)	9.5	146	25.8%*	10.4%*	1.01*	4.17*
Jose Rijo ('84-'02, 33 WAR*)	9.4	145	25.9%*	8.4%*	0.93*	3.56*
Danny Duffy ('21)	5.9	107	21.1%	8.7%	1.11	3.95
Don Gullett ('70-'78, 21 WAR*)	7.0	154	22.8%*	8.5%*	1.16*	3.77*
James Paxton ('24)	4.8	95	25.3%	7.9%	1.05	3.77
Lance Lynn ('24)	10.0	154	23.7%	8.3%	1.04	3.74