Robbie Ray

P San Diego Padres

Age 35 LHP 6'2" / 220 lbs MLB peak 0.7 · 2027

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	32	MIX4 levels	17	16	60	4.05	3.38	36.7%	8.8%	1.5	K 33.3% · BB 11.6% · FIP 4.52
2025	33	MLBSF	32	32	182	3.65	3.83	24.6%	9.7%	3.4
2026	34	MLBSD	31	30	166	3.59	4.66	19.9%	12.0%	1.4
2027PROJ	35	MLBSD	16	16	98	4.39	4.75	21.7%	11.0%	0.7
2028PROJ	36	MLBSD	10	10	60	4.88	5.17	20.6%	11.6%	0.2
2029PROJ	37	MLBSD	6	6	33	5.30	5.57	19.5%	12.2%	-0.0

Last 3 seasons WAR 6.3 · Next 3 projected WAR 0.9Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%34

FB Velo30

xwOBA vs30

Form5.96 ERA (proj 4.39) · K 17.6% (proj 21.7%) · BB 13.7% (proj 11.0%) ▼▼ last 60d · 23 IP through Oct 27

CompsDaniel Rodriguez (age 34) · Orlando Lara (age 34) · Tsuyoshi Wada (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 106114vR 123

ERA4.39

FIP4.75

K%21.7%

BB%11.0%

K-BB%10.7%

Proj IP98

Value2027 · WAR

Runs saved vs league avg · 98 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p3093.1

Whiff%

p4524.6%

p3419.9%

xwOBA vs

p300.335

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)
2014	22	MLB MLE	Detroit Tigers	9	6	29	136	19	11	5	67%	3.2	14.0%	8.1%	5.9%	3.8%	8.16	5.05	+0.1
2014	22	MLB RAW	Detroit Tigers	9	6	29	136	19	11	5	67%	3.2	14.0%	8.1%	5.9%	3.7%	8.16	5.19	+0.1
2015	23	MIX MLE	2 levels	32	32	169	732	176	72	10	100%	5.3	23.1%	10.0%	13.1%	1.4%	3.56	3.17	+4.7
2015	23	MIX RAW	2 levels	32	32	169	732	176	72	10	100%	5.3	24.0%	9.8%	14.2%	1.4%	3.56	3.06	+4.9
2016	24	MLB MLE	Arizona Diamondbacks	32	32	174	776	218	67	24	100%	5.4	28.1%	8.6%	19.5%	3.1%	4.90	3.50	+4.0
2016	24	MLB RAW	Arizona Diamondbacks	32	32	174	776	218	67	24	100%	5.4	28.1%	8.6%	19.5%	3.1%	4.90	3.54	+3.9
2017	25	MIX MLE	2 levels	29	29	167	686	229	70	23	100%	5.7	32.8%	10.2%	22.6%	3.4%	2.92	3.51	+3.9
2017	25	MIX RAW	2 levels	29	29	167	686	229	70	23	100%	5.7	33.4%	10.2%	23.2%	3.4%	2.92	3.41	+4.1
2018	26	MIX MLE	3 levels	26	26	130	557	177	68	21	100%	5.0	31.4%	12.7%	18.6%	3.8%	3.94	4.16	+1.9
2018	26	MIX RAW	3 levels	26	26	130	557	177	68	21	100%	5.0	31.8%	12.2%	19.6%	3.8%	3.94	4.04	+2.1
2019	27	MLB MLE	Arizona Diamondbacks	33	33	174	747	235	79	30	100%	5.3	31.5%	10.6%	20.9%	4.2%	4.34	4.12	+2.7
2019	27	MLB RAW	Arizona Diamondbacks	33	33	174	747	235	79	30	100%	5.3	31.5%	10.6%	20.9%	4.0%	4.34	4.00	+2.9
2020	28	MLB MLE	Toronto Blue Jays	12	11	52	251	68	44	13	92%	4.3	27.1%	17.5%	9.6%	5.2%	6.62	5.88	-0.3
2020	28	MLB RAW	Toronto Blue Jays	12	11	52	251	68	44	13	92%	4.3	27.1%	17.5%	9.6%	5.2%	6.62	6.29	-0.5
2021	29	MLB MLE	Toronto Blue Jays	32	32	193	773	248	52	33	100%	6.0	32.1%	6.7%	25.4%	4.3%	2.84	3.59	+4.3
2021	29	MLB RAW	Toronto Blue Jays	32	32	193	773	248	52	33	100%	6.0	32.1%	6.7%	25.4%	4.3%	2.84	3.56	+4.3
2022	30	MLB MLE	Seattle Mariners	32	32	189	775	212	62	32	100%	5.9	27.4%	8.0%	19.4%	4.2%	3.71	4.13	+2.8
2022	30	MLB RAW	Seattle Mariners	32	32	189	775	212	62	32	100%	5.9	27.4%	8.0%	19.4%	4.1%	3.71	4.04	+3.1
2023	31	MLB MLE	Seattle Mariners	1	1	3	19	3	5	0	100%	3.3	15.8%	26.3%	-10.5%	0.0%	8.10	5.10	+0.0
2023	31	MLB RAW	Seattle Mariners	1	1	3	19	3	5	0	100%	3.3	15.8%	26.3%	-10.5%	0.0%	8.10	5.80	-0.0
2024	32	MIX MLE	4 levels	17	16	60	240	88	21	10	94%	3.5	33.3%	11.6%	21.7%	5.0%	4.05	4.52	+0.6
2024	32	MIX MLE	4 levels	17	16	60	240	88	21	10	94%	3.5	33.3%	11.6%	21.7%	5.0%	4.05	4.52	+0.6
2024	32	MIX RAW	4 levels	17	16	60	240	88	21	10	94%	3.5	36.7%	8.8%	27.9%	4.2%	4.05	3.38	+1.5
2025	33	MLB MLE	San Francisco Giants	32	32	182	755	186	73	22	100%	5.7	24.6%	9.7%	15.0%	3.2%	3.65	3.97	+3.1
2025	33	MLB MLE	San Francisco Giants	32	32	182	755	186	73	22	100%	5.7	24.6%	9.7%	15.0%	3.2%	3.65	3.97	+3.1
2025	33	MLB RAW	San Francisco Giants	32	32	182	755	186	73	22	100%	5.7	24.6%	9.7%	15.0%	2.9%	3.65	3.83	+3.4
2026	34	MLB MLE	San Diego Padres	31	30	166	702	140	84	22	97%	5.3	19.9%	12.0%	8.0%	3.1%	3.59	4.61	+1.5
2026	34	MLB MLE	San Diego Padres	31	30	166	702	140	84	22	97%	5.3	19.9%	12.0%	8.0%	3.1%	3.59	4.61	+1.5
2026	34	MLB RAW	San Diego Padres	31	30	166	702	140	84	22	97%	5.3	19.9%	12.0%	8.0%	3.1%	3.59	4.66	+1.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			296	291	1607	6799	1874	673	238	98%	5.4	27.6%	9.9%	17.7%	3.5%	3.90	3.95	+27.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	35	MLB	SD	16	16	98	414	90	45	13	100%	6.1	21.7%	11.0%	10.7%	3.1%	4.39	4.75	+0.7
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	36	MLB MLE	SD	10	10	60	253	52	29	9	100%	6.0	20.6%	11.6%	9.1%	3.5%	4.83	5.12	+0.2
2029	37	MLB MLE	SD	5	5	33	138	27	17	5	100%	6.5	19.5%	12.2%	7.3%	3.9%	5.25	5.52	-0.0
2028	36	MLB CTX	SD	10	10	60	253	52	29	9	100%	6.0	20.6%	11.6%	9.1%	3.6%	4.88	5.17	+0.2
2029	37	MLB CTX	SD	6	6	33	139	27	17	6	100%	5.5	19.5%	12.2%	7.3%	4.0%	5.30	5.57	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		311	306	1699	7190	1953	719	253	98%	5.5	27.2%	10.0%	17.2%	3.5%	3.97	4.00	+28.3
/ 200 IP	—	RAW		37	36	200	846	230	85	30	98%	5.5	27.2%	10.0%	17.2%	3.5%	3.97	4.00	+3.3
Career	—	MLE		318	312	1689	7149	1978	719	252	98%	5.3	27.7%	10.1%	17.6%	3.5%	3.89	3.97	+27.9
/ 200 IP	—	MLE		38	37	200	847	234	85	30	98%	5.3	27.7%	10.1%	17.6%	3.5%	3.89	3.97	+3.3

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.

2024 ASan Jose Giants · 12 IPFIP 2.72 → 4.61 (+1.89)K% 40.9% → 30.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.91%	—	×0.740	30.27%
BB% (unintentional) /BF	4.55%	—	×1.180	5.36%
HR / BF /BF	4.55%	÷0.959	×1.300	6.16%

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 92).

Result: FIP 2.72 → 4.61, 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).

2024 AAASacramento River Cats · 11 IPFIP 3.21 → 3.57 (+0.36)K% 30.8% → 26.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.77%	—	×0.860	26.46%
BB% (unintentional) /BF	10.26%	—	×0.900	9.23%
HR / BF /BF	2.56%	÷1.010	×1.100	2.79%

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 102).

Result: FIP 3.21 → 3.57, 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).

2024 ROKACL Giants · 7 IPFIP 0.54 → 2.35 (+1.82)K% 53.6% → 36.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	53.57%	—	×0.680	36.43%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
HR / BF /BF	3.57%	÷1.178	×1.400	4.25%

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 136).

Result: FIP 0.54 → 2.35, 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+Visalia Rawhide · 5 IPFIP -0.12 → 1.08 (+1.20)K% 52.4% → 40.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	52.38%	—	×0.770	40.33%
BB% (unintentional) /BF	9.52%	—	×1.150	10.95%
HR / BF /BF	0.00%	÷1.048	×1.250	0.00%

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 110).

Result: FIP -0.12 → 1.08, 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 AAAReno Aces · 42 IPFIP 2.58 → 3.00 (+0.42)K% 30.5% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.48%	—	×0.880	26.82%
BB% (unintentional) /BF	13.90%	—	×1.050	14.60%
HR / BF /BF	0.53%	÷1.027	×1.100	0.57%

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 105).

Result: FIP 2.58 → 3.00, 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
Robbie Ray (OGILVIE)	—	—	—	—	—	3.1%	—	5.26	20.2%	8.4%	93	+0.51	—	—	—
Daniel Rodriguez L 2019 · 4.77 FIP	34	SP	4.77	20.8%	7.8%	4.5%	.329	—	—	—	—	—	2.89	391	51
Orlando Lara L 2019 · 4.09 FIP	34	SP	4.09	22.0%	7.8%	3.4%	.329	—	—	—	—	—	3.85	426	50
Tsuyoshi Wada L 2015 · 3.66 FIP	34	SP	3.66	16.8%	7.1%	2.0%	.307	—	—	—	—	—	3.60	188	47
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	46
Marlon Arias L 2019 · 4.83 FIP	34	SP	4.83	19.8%	11.2%	3.6%	.273	—	—	—	—	—	3.73	154	42
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	42
Chris Narveson L 2017 · 4.59 FIP	35	SP	4.59	12.2%	10.4%	2.2%	.264	—	—	—	—	—	4.00	625	41
Jason Lane L 2015 · 5.56 FIP	38	SP	5.56	8.4%	6.2%	4.3%	.307	—	—	—	—	—	5.56	164	41
Kwang Hyun Kim L 2021 · 4.21 FIP	33	SP-	4.21	17.7%	8.2%	2.9%	.266	—	—	—	—	—	3.76	146	40
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	40
Oscar Rivera L 2016 · 4.10 FIP	35	SP	4.10	10.7%	7.2%	1.8%	.309	5.80	9.8%	2.0%	42	+1.70	3.68	237	36
Andrew Albers L 2021 · 4.60 FIP	35	SP	4.60	16.9%	3.7%	4.5%	.312	—	—	—	—	—	2.98	568	35
Masato Yoshii R 2000 · 5.32 FIP	35	SP	5.32	12.1%	6.5%	4.4%	.302	4.38	13.1%	8.0%	244	-0.94	4.15	757	32
Jose Contreras R 2007 · 4.23 FIP	35	SP	4.23	13.2%	7.1%	2.5%	.318	3.76	17.4%	10.1%	309	-0.47	2.43	1,279	31
Jorge Castillo L 2017 · 4.97 FIP	35	SP	4.97	11.2%	6.7%	3.6%	.337	4.91	19.6%	11.5%	119	-0.06	4.50	408	30
Tomas Solis L 2017 · 5.48 FIP	34	SP	5.48	11.3%	7.9%	4.2%	.322	6.44	8.9%	1.4%	57	+0.96	4.20	327	28
Hisashi Iwakuma R 2016 · 4.15 FIP	35	SP	4.15	17.6%	5.1%	3.4%	.307	6.31	12.5%	3.1%	31	+2.16	3.19	884	27
Jarrett Grube R 2017 · 4.41 FIP	35	SP	4.41	15.8%	8.1%	3.0%	.296	—	—	—	—	—	3.75	393	25
Yoanner Negrin R 2019 · 3.87 FIP	35	SP	3.87	17.5%	8.1%	2.2%	.280	—	—	—	—	—	3.15	485	25
Steve Sparks R 2000 · 3.78 FIP	35	SP-	3.78	11.9%	6.5%	1.6%	.283	4.37	11.6%	4.7%	528	+0.59	3.78	1,320	24

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	9.0	120	26.9%	10.3%	1.35	3.99
Jose DeLeon ('83-'95, 22 WAR*)	9.5	146	25.8%*	10.4%*	1.01*	4.17*
Dave Boswell ('64-'71, 11 WAR*)	5.3	133	24.7%*	10.5%*	1.28*	4.27*
Fred Norman ('62-'80, 16 WAR*)	9.7	162	22.3%*	9.7%*	1.34*	4.33*
Francisco Liriano ('19)	9.1	130	23.3%	10.5%	0.91	4.15
Frankie Montas ('25)	3.9	98	23.6%	8.2%	1.20	4.20
Danny Duffy ('21)	5.9	107	21.1%	8.7%	1.11	3.95