Nathan Eovaldi

P Texas Rangers

Age 37 RHP 6'2" / 217 lbs MLB Svc 15.0 · Ctrl thru 2027 peak 2.2 · 2027

Overview

MLBSP40-MANExtFA 2028

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR
2024	34	MLBTEX	29	29	171	3.80	3.64	23.9%	6.0%	3.6
2025	35	MLBTEX	22	22	130	1.73	2.58	26.0%	4.0%	4.7
2026	36	MLBTEX	27	23	146	4.20	3.99	23.5%	5.7%	2.5
2027PROJ	37	MLBTEX	19	19	115	3.75	3.81	24.4%	5.4%	2.2
2028PROJ	38	MLBTEX	14	14	85	4.20	4.39	23.3%	6.1%	1.2
2029PROJ	39	MLBTEX	9	9	55	4.58	4.83	22.1%	6.8%	0.5

Last 3 seasons WAR 10.8 · Next 3 projected WAR 3.8Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service15.076First FA2028Options4NTC

2027Ext$25M

Skills · percentileStatcast 2026

K%57

FB Velo48

xwOBA vs44

Form5.01 ERA (proj 3.75) · K 13.2% (proj 24.4%) · BB 5.7% (proj 5.4%) ▼▼ last 90d · 23 IP through Oct 27

CompsHiroki Kuroda (age 37) · Masato Yoshii (age 37) · Yasutomo Kubo (age 38)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10799vR 91

ERA3.75

FIP3.81

K%24.4%

BB%5.4%

K-BB%19.0%

Proj IP115

Value2027 · WAR

Runs saved vs league avg · 115 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit option yr-$39M ctrl surplus

Statcast · Contract

Statcast Percentiles

FB Velo

p4894.4

Whiff%

p7629.4%

p5723.5%

xwOBA vs

p440.318

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

Status FA

MLB Debut 2011

Service 15.076 yrs.days

Team Control Through 2027

First FA Year 2028

NTCOPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$25M	+2.2	$18M	-$7M
Totals		$25M		$18M	-$7M

Options · projected decision
2028	PLAYER OPT	$25.0M / $0.0M buyout	EXERCISE
2029	PLAYER OPT	$20.0M / $0.0M buyout	EXERCISE
2030	CLUB OPT	$25.0M / $0.0M buyout	DECLINE
2031	CLUB OPT	$2.0M / $0.0M buyout	DECLINE

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)
2011	21	MLB MLE	Los Angeles Dodgers	10	6	35	146	23	20	2	60%	3.5	15.8%	13.7%	2.1%	1.3%	3.63	4.23	+0.5
2011	21	MLB RAW	Los Angeles Dodgers	10	6	35	146	23	20	2	60%	3.5	15.8%	13.7%	2.1%	1.4%	3.63	4.25	+0.5
2012	22	MLB MLE	Miami Marlins	22	22	119	526	78	44	10	100%	5.4	14.8%	8.4%	6.5%	2.0%	4.30	4.01	+2.0
2012	22	MLB RAW	Miami Marlins	22	22	119	526	78	44	10	100%	5.4	14.8%	8.4%	6.5%	1.9%	4.30	3.99	+2.0
2013	23	MLB MLE	Miami Marlins	18	18	106	451	78	37	7	100%	5.9	17.3%	8.2%	9.1%	1.6%	3.39	3.58	+2.4
2013	23	MLB RAW	Miami Marlins	18	18	106	451	78	37	7	100%	5.9	17.3%	8.2%	9.1%	1.6%	3.39	3.53	+2.4
2014	24	MLB MLE	Miami Marlins	33	33	200	854	142	38	14	100%	6.1	16.6%	4.4%	12.2%	1.7%	4.37	3.21	+5.5
2014	24	MLB RAW	Miami Marlins	33	33	200	854	142	38	14	100%	6.1	16.6%	4.4%	12.2%	1.6%	4.37	3.16	+5.6
2015	25	MLB MLE	New York Yankees	27	27	154	673	121	49	10	100%	5.7	18.0%	7.3%	10.7%	1.4%	4.20	3.27	+4.1
2015	25	MLB RAW	New York Yankees	27	27	154	673	121	49	10	100%	5.7	18.0%	7.3%	10.7%	1.5%	4.20	3.33	+3.9
2016	26	MLB MLE	New York Yankees	24	21	125	525	97	38	23	88%	5.2	18.5%	7.2%	11.2%	4.1%	4.76	4.71	+1.0
2016	26	MLB RAW	New York Yankees	24	21	125	525	97	38	23	88%	5.2	18.5%	7.2%	11.2%	4.4%	4.76	4.86	+0.8
2018	28	MIX MLE	3 levels	26	25	121	501	114	19	17	96%	4.7	22.2%	4.2%	18.0%	3.2%	4.31	3.49	+2.8
2018	28	MIX RAW	3 levels	26	25	121	501	114	19	17	96%	4.7	22.8%	3.8%	19.0%	3.4%	4.31	3.51	+2.8
2019	29	MIX MLE	2 levels	24	12	69	306	73	36	16	50%	2.9	23.2%	11.6%	11.6%	5.4%	5.90	5.59	-0.2
2019	29	MIX RAW	2 levels	24	12	69	306	73	36	16	50%	2.9	23.9%	11.8%	12.1%	5.2%	5.90	5.58	-0.1
2020	30	MLB MLE	Boston Red Sox	9	9	48	199	52	7	8	100%	5.4	26.1%	3.5%	22.6%	4.1%	3.72	3.60	+1.1
2020	30	MLB RAW	Boston Red Sox	9	9	48	199	52	7	8	100%	5.4	26.1%	3.5%	22.6%	4.0%	3.72	3.53	+1.1
2021	31	MLB MLE	Boston Red Sox	32	32	182	764	195	33	15	100%	5.7	25.5%	4.3%	21.2%	2.0%	3.75	2.60	+6.6
2021	31	MLB RAW	Boston Red Sox	32	32	182	764	195	33	15	100%	5.7	25.5%	4.3%	21.2%	2.0%	3.75	2.57	+6.6
2022	32	MIX MLE	2 levels	22	22	115	490	111	22	23	100%	5.2	22.4%	4.3%	18.0%	4.7%	4.06	4.33	+1.4
2022	32	MIX RAW	2 levels	22	22	115	490	111	22	23	100%	5.2	22.7%	4.5%	18.2%	4.7%	4.06	4.34	+1.4
2023	33	MLB MLE	Texas Rangers	25	25	144	577	132	47	15	100%	5.8	22.9%	8.1%	14.7%	2.4%	3.62	3.53	+3.3
2023	33	MLB RAW	Texas Rangers	25	25	144	577	132	47	15	100%	5.8	22.9%	8.1%	14.7%	2.6%	3.62	3.60	+3.2
2024	34	MLB MLE	Texas Rangers	29	29	171	696	166	42	23	100%	5.9	23.9%	6.0%	17.8%	3.1%	3.80	3.54	+3.9
2024	34	MLB MLE	Texas Rangers	29	29	171	696	166	42	23	100%	5.9	23.9%	6.0%	17.8%	3.1%	3.80	3.54	+3.9
2024	34	MLB RAW	Texas Rangers	29	29	171	696	166	42	23	100%	5.9	23.9%	6.0%	17.8%	3.3%	3.80	3.64	+3.6
2025	35	MLB MLE	Texas Rangers	22	22	130	496	129	20	10	100%	5.9	26.0%	4.0%	22.0%	1.9%	1.73	2.44	+5.0
2025	35	MLB MLE	Texas Rangers	22	22	130	496	129	20	10	100%	5.9	26.0%	4.0%	22.0%	1.9%	1.73	2.44	+5.0
2025	35	MLB RAW	Texas Rangers	22	22	130	496	129	20	10	100%	5.9	26.0%	4.0%	22.0%	2.0%	1.73	2.58	+4.7
2026	36	MLB MLE	Texas Rangers	27	23	146	613	144	35	24	85%	5.4	23.5%	5.7%	17.8%	3.6%	4.20	3.84	+2.7
2026	36	MLB MLE	Texas Rangers	27	23	146	613	144	35	24	85%	5.4	23.5%	5.7%	17.8%	3.6%	4.20	3.84	+2.7
2026	36	MLB RAW	Texas Rangers	27	23	146	613	144	35	24	85%	5.4	23.5%	5.7%	17.8%	3.9%	4.20	3.99	+2.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			343	320	1848	7737	1631	484	212	93%	5.4	21.1%	6.3%	14.8%	2.7%	3.92	3.61	+40.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	37	MLB	TEX	19	19	115	486	119	26	15	100%	6.1	24.4%	5.4%	19.0%	3.1%	3.75	3.81	+2.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	38	MLB MLE	TEX	14	14	85	361	84	22	13	100%	6.1	23.3%	6.1%	17.1%	3.6%	4.05	4.24	+1.2
2029	39	MLB MLE	TEX	9	9	55	231	51	16	9	100%	6.1	22.1%	6.8%	15.3%	4.0%	4.42	4.67	+0.5
2028	38	MLB CTX	TEX	14	14	85	359	83	22	14	100%	6.1	23.3%	6.1%	17.1%	3.8%	4.20	4.39	+1.2
2029	39	MLB CTX	TEX	9	9	55	232	51	16	10	100%	6.1	22.1%	6.8%	15.3%	4.3%	4.58	4.83	+0.5
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		366	343	1988	8329	1766	522	236	94%	5.4	21.2%	6.3%	14.9%	2.8%	3.95	3.66	+42.0
/ 200 IP	—	RAW		37	35	200	838	178	53	24	94%	5.4	21.2%	6.3%	14.9%	2.8%	3.95	3.66	+4.2
Career	—	MLE		350	326	1865	7817	1649	488	211	93%	5.3	21.1%	6.2%	14.9%	2.7%	3.96	3.59	+41.7
/ 200 IP	—	MLE		38	35	200	838	177	52	23	93%	5.3	21.1%	6.2%	14.9%	2.7%	3.96	3.59	+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.

2022 AAAWorcester Red Sox · 6 IPFIP 5.35 → 6.29 (+0.94)K% 26.7% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.67%	—	×0.880	23.47%
BB% (unintentional) /BF	6.67%	—	×1.050	7.00%
HR / BF /BF	6.67%	÷0.939	×1.100	7.81%

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 88).

Result: FIP 5.35 → 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).

2018 A+Charlotte Stone Crabs · 6 IPFIP 5.21 → 7.87 (+2.66)K% 29.2% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.17%	—	×0.770	22.46%
BB% (unintentional) /BF	0.00%	—	×1.150	0.00%
HR / BF /BF	8.33%	÷0.857	×1.250	12.15%

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 71).

Result: FIP 5.21 → 7.87, 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 AAADurham Bulls · 4 IPFIP 3.29 → 3.90 (+0.61)K% 27.3% → 24.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.27%	—	×0.880	24.00%
BB% (unintentional) /BF	0.00%	—	×1.050	0.00%
HR / BF /BF	4.55%	÷0.970	×1.100	5.16%

Result: FIP 3.29 → 3.90, 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
Nathan Eovaldi (OGILVIE)	—	—	—	—	—	3.1%	—	4.41	22.8%	16.4%	140	+0.60	—	—	—
Hiroki Kuroda R 2012 · 3.66 FIP	37	SP	3.66	18.7%	5.5%	2.6%	.277	3.42	18.0%	13.3%	400	-0.24	2.96	1,319	60
Masato Yoshii R 2002 · 4.15 FIP	37	SP-	4.15	13.4%	5.4%	2.7%	.295	—	—	—	—	—	4.15	757	52
Yasutomo Kubo R 2019 · 3.98 FIP	38	SP	3.98	20.4%	4.7%	3.6%	.327	—	—	—	—	—	3.98	152	50
Kenshin Kawakami R 2010 · 4.06 FIP	35	SP	4.06	15.1%	5.6%	2.8%	.293	—	—	—	—	—	3.97	244	47
Jarrett Grube R 2017 · 4.41 FIP	35	SP	4.41	15.8%	8.1%	3.0%	.296	—	—	—	—	—	3.75	393	40
Walter Silva R 2015 · 4.15 FIP	38	SP	4.15	14.8%	7.4%	2.5%	.311	3.91	10.4%	3.7%	209	-0.24	3.67	453	34
Pablo Ortega R 2015 · 4.52 FIP	38	SP	4.52	8.6%	7.3%	2.2%	.291	4.24	11.5%	6.0%	236	-0.28	4.01	375	27
Lorenzo Barcelo R 2015 · 3.28 FIP	37	SP	3.28	13.2%	3.6%	1.5%	.345	3.48	12.8%	11.7%	45	+0.20	3.14	259	26
Jon Leicester R 2015 · 3.76 FIP	36	SP	3.76	12.3%	5.9%	1.7%	.333	—	—	—	—	—	3.76	113	22
Jorge Castillo L 2019 · 4.91 FIP	37	SP	4.91	19.6%	8.1%	4.5%	.316	—	—	—	—	—	4.50	408	18
Mauricio Lara L 2016 · 3.68 FIP	37	SP-	3.68	12.1%	7.6%	1.1%	.294	4.34	12.2%	5.6%	219	+0.66	3.62	444	11
Logan Duran R 2019 · 3.66 FIP	37	SP-	3.66	15.5%	8.9%	1.4%	.427	—	—	—	—	—	3.42	187	10
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	9

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	10.5	117	21.4%	6.4%	1.09	3.93
Bruce Kison ('71-'85, 16 WAR*)	9.0	121	20.4%*	8.5%*	1.10*	4.16*
Aníbal Sánchez ('22)	10.1	126	20.6%	8.0%	1.06	4.06
Bryn Smith ('81-'93, 21 WAR*)	9.0	149	17.9%*	5.8%*	1.07*	4.08*
Nelson Briles ('65-'78, 21 WAR*)	10.6	151	17.8%*	6.4%*	1.21*	4.13*
Alex Wood ('24)	6.3	114	22.1%	7.1%	0.91	3.78
Jeff Samardzija ('20)	8.2	150	21.0%	7.1%	1.12	4.15