Riley O'Brien

P St. Louis Cardinals

Age 32 RHP 6'4" / 180 lbs MLB peak 0.5 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MIX2 levels	22	21	5.06	4.27	20.4%	13.3%	0.1	K 14.9% · BB 8.7% · FIP 2.94
2025	30	MIX2 levels	61	67	2.27	2.64	27.0%	9.8%	1.5	K 25.4% · BB 9.5% · FIP 2.82
2026	31	MLBSTL	66	64	4.08	3.29	23.2%	9.1%	1.0
2027PROJ	32	MLBSTL	51	54	3.94	3.89	25.3%	10.1%	0.4
2028PROJ95% MLB	33	MLBSTL	37	39	4.08	4.17	24.5%	10.5%	0.2
2029PROJ90% MLB	34	MLBSTL	24	25	4.32	4.47	23.6%	11.0%	0.0

Last 3 seasons WAR 2.6 · Next 3 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo90

K%55

xwOBA vs26

Form5.06 ERA (proj 3.94) · K 20.9% (proj 25.3%) · BB 12.1% (proj 10.1%) ▼▼ last 90d · 21 IP through Oct 27

CompsJohn Axford (age 32) · Hirokazu Sawamura (age 33) · Jumbo Diaz (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 113105vR 97

ERA3.94

FIP3.89

K%25.3%

BB%10.1%

K-BB%15.3%

Proj IP58

Value2027 · WAR

Runs saved vs league avg · 58 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL3535

CMD4545

K†6060

Statcast Percentiles

FB Velo

p9097.7

Whiff%

p6026.8%

p5523.2%

xwOBA vs

p260.340

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)
2017	22	ROK MLE	Princeton Rays	11	10	41	159	40	17	1	91%	3.7	17.1%	13.4%	3.7%	0.9%	2.20	3.83	—
2017	22	ROK RAW	Princeton Rays	11	10	41	159	40	17	1	91%	3.7	25.2%	10.7%	14.5%	0.6%	2.20	2.71	—
2018	23	MIX MLE	2 levels	25	13	88	357	103	41	4	52%	3.5	21.7%	13.4%	8.3%	1.5%	2.75	3.77	—
2018	23	MIX RAW	2 levels	25	13	88	357	103	41	4	52%	3.5	28.9%	11.5%	17.4%	1.1%	2.75	2.75	—
2019	24	MIX MLE	2 levels	20	17	103	429	107	44	6	85%	5.1	19.9%	11.5%	8.4%	1.8%	3.16	3.88	—
2019	24	MIX RAW	2 levels	20	17	103	429	107	44	6	85%	5.1	24.9%	10.3%	14.7%	1.4%	3.16	3.06	—
2021	26	MIX MLE	2 levels	24	23	114	499	123	57	18	96%	4.8	21.7%	11.6%	10.2%	3.3%	4.66	4.54	+1.1
2021	26	MIX RAW	2 levels	24	23	114	499	123	57	18	96%	4.8	24.6%	11.4%	13.2%	3.6%	4.66	4.49	+1.2
2022	27	MIX MLE	2 levels	34	1	41	201	48	31	5	3%	1.2	21.1%	16.1%	5.0%	2.5%	6.86	4.70	-0.1
2022	27	MIX RAW	2 levels	34	1	41	201	48	31	5	3%	1.2	23.9%	15.4%	8.5%	2.5%	6.86	4.62	-0.0
2023	28	AAA MLE	Tacoma Rainiers	51	3	55	228	86	30	2	6%	1.1	32.4%	11.8%	20.6%	0.8%	2.29	2.32	—
2023	28	AAA RAW	Tacoma Rainiers	51	3	55	228	86	30	2	6%	1.1	37.7%	13.2%	24.6%	0.9%	2.29	2.08	—
2024	29	MIX MLE	2 levels	22	0	21	98	20	13	2	0%	1.0	14.9%	8.7%	6.2%	0.0%	5.06	2.94	+0.4
2024	29	MIX MLE	2 levels	22	0	21	98	20	13	2	0%	1.0	14.9%	8.7%	6.2%	0.0%	5.06	2.94	+0.4
2024	29	MIX RAW	2 levels	22	0	21	98	20	13	2	0%	1.0	20.4%	13.3%	7.1%	2.0%	5.06	4.27	+0.1
2025	30	MIX MLE	2 levels	61	0	67	285	77	28	3	0%	1.1	25.4%	9.5%	15.9%	1.2%	2.27	2.82	+1.4
2025	30	MIX MLE	2 levels	61	0	67	285	77	28	3	0%	1.1	25.4%	9.5%	15.9%	1.2%	2.27	2.82	+1.4
2025	30	MIX RAW	2 levels	61	0	67	285	77	28	3	0%	1.1	27.0%	9.8%	17.2%	1.1%	2.27	2.64	+1.5
2026	31	MLB MLE	St. Louis Cardinals	66	0	64	276	64	25	5	0%	1.0	23.2%	9.1%	14.1%	1.9%	4.08	3.36	+0.9
2026	31	MLB MLE	St. Louis Cardinals	66	0	64	276	64	25	5	0%	1.0	23.2%	9.1%	14.1%	1.9%	4.08	3.36	+0.9
2026	31	MLB RAW	St. Louis Cardinals	66	0	64	276	64	25	5	0%	1.0	23.2%	9.1%	14.1%	1.8%	4.08	3.29	+1.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			118	1	122	535	123	57	11	1%	1.0	23.0%	10.7%	12.3%	2.1%	3.83	3.66	+1.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	STL	51	0	54	228	58	23	5	0%	1.1	25.3%	10.1%	15.3%	2.3%	3.94	3.89	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	STL	40	0	42	175	43	18	5	0%	1.0	24.5%	10.5%	14.0%	2.6%	4.08	4.17	+0.2
2029	34	MLB MLE	STL	27	0	28	118	28	13	3	0%	1.0	23.6%	11.0%	12.6%	2.9%	4.32	4.47	+0.0
2028	33	MLB CTX	STL	37	0	39	165	40	17	4	0%	1.1	24.5%	10.5%	14.0%	2.6%	4.08	4.17	+0.2
2029	34	MLB CTX	STL	24	0	25	106	25	12	3	0%	1.0	23.6%	11.0%	12.6%	2.9%	4.32	4.47	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		180	1	187	808	189	86	18	1%	1.0	23.4%	10.7%	12.7%	2.3%	3.95	3.73	+1.8
/ 200 IP	—	RAW		192	1	200	864	202	92	19	1%	1.0	23.4%	10.7%	12.7%	2.3%	3.95	3.73	+1.9
Career	—	MLE		314	67	594	2532	566	296	47	21%	1.9	22.3%	11.7%	10.7%	1.8%	3.56	3.70	+1.5
/ 200 IP	—	MLE		106	23	200	852	190	100	16	21%	1.9	22.3%	11.7%	10.7%	1.8%	3.56	3.70	+1.6

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.

2025 AAAMemphis Redbirds · 19 IPFIP 1.77 → 2.27 (+0.49)K% 37.2% → 32.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.21%	—	×0.860	32.00%
BB% (unintentional) /BF	9.30%	—	×0.900	8.37%
HR / BF /BF	1.16%	÷0.869	×1.100	1.47%

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 74).

Result: FIP 1.77 → 2.27, 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).

2024 AAAMemphis Redbirds · 13 IPFIP 2.86 → 2.94 (+0.08)K% 17.3% → 14.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.31%	—	×0.860	14.88%
BB% (unintentional) /BF	9.62%	—	×0.900	8.65%
HR / BF /BF	0.00%	÷1.020	×1.100	0.00%

Result: FIP 2.86 → 2.94, 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 AAATacoma Rainiers · 55 IPFIP 2.06 → 2.32 (+0.26)K% 37.7% → 32.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.72%	—	×0.860	32.44%
BB% (unintentional) /BF	13.16%	—	×0.900	11.84%
HR / BF /BF	0.88%	÷1.157	×1.100	0.83%

Result: FIP 2.06 → 2.32, 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).

2022 AAATacoma Rainiers · 40 IPFIP 4.41 → 4.70 (+0.29)K% 24.0% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.98%	—	×0.880	21.10%
BB% (unintentional) /BF	15.31%	—	×1.050	16.07%
HR / BF /BF	2.55%	÷1.144	×1.100	2.45%

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 129).

Result: FIP 4.41 → 4.70, 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).

2021 AAALouisville Bats · 113 IPFIP 4.20 → 4.54 (+0.34)K% 24.7% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.69%	—	×0.880	21.73%
BB% (unintentional) /BF	11.02%	—	×1.050	11.57%
HR / BF /BF	3.27%	÷1.088	×1.100	3.30%

Result: FIP 4.20 → 4.54, 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).

2019 AAMontgomery Biscuits · 69 IPFIP 3.03 → 3.77 (+0.74)K% 24.2% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.24%	—	×0.810	19.64%
BB% (unintentional) /BF	9.76%	—	×1.100	10.74%
HR / BF /BF	1.35%	÷0.920	×1.200	1.76%

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 84).

Result: FIP 3.03 → 3.77, 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 A+Charlotte Stone Crabs · 34 IPFIP 3.13 → 4.14 (+1.01)K% 26.5% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.52%	—	×0.770	20.42%
BB% (unintentional) /BF	11.36%	—	×1.150	13.07%
HR / BF /BF	1.52%	÷0.939	×1.250	2.02%

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 88).

Result: FIP 3.13 → 4.14, 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 ABowling Green Hot Rods · 48 IPFIP 2.42 → 3.68 (+1.27)K% 35.7% → 26.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.68%	—	×0.740	26.40%
BB% (unintentional) /BF	11.35%	—	×1.180	13.39%
HR / BF /BF	1.62%	÷1.037	×1.300	2.03%

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 107).

Result: FIP 2.42 → 3.68, 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
Riley O'Brien (OGILVIE)	—	—	3.89	25.3%	10.1%	2.3%	—	4.29	24.1%	13.4%	70	+0.40	—	—	—
John Axford R 2015 · 3.20 FIP	32	SU	3.20	24.8%	11.2%	1.4%	.333	3.97	21.5%	11.1%	141	+0.77	1.90	518	74
Hirokazu Sawamura R 2021 · 4.48 FIP	33	SU	4.48	26.2%	11.2%	4.0%	.263	4.02	18.1%	6.8%	51	-0.46	4.02	104	72
Jumbo Diaz R 2016 · 3.85 FIP	32	SU	3.85	22.3%	9.2%	2.7%	.247	3.28	23.0%	13.8%	141	-0.57	2.80	319	70
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	67
James Hoyt R 2019 · 3.45 FIP	32	SU	3.45	22.2%	9.9%	1.8%	.355	5.63	22.1%	10.4%	50	+2.18	1.61	312	66
Fernando Cruz R 2022 · 2.89 FIP	32	SU	2.89	27.4%	10.0%	1.5%	.254	2.76	36.3%	25.3%	181	-0.13	2.50	371	65
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	65
Dan Winkler R 2022 · 3.87 FIP	32	SU	3.87	24.4%	14.0%	1.9%	.281	—	—	—	—	—	2.40	231	64
Brian Sanches R 2011 · 4.35 FIP	32	SU	4.35	19.6%	11.1%	2.7%	.250	—	—	—	—	—	3.39	229	64
Jose Veras R 2013 · 3.51 FIP	32	SU	3.51	23.6%	8.3%	2.5%	.234	4.28	21.9%	10.2%	65	+0.77	3.37	422	64
Jared Hughes R 2017 · 3.28 FIP	32	SU	3.28	19.7%	7.8%	1.6%	.260	3.99	19.3%	10.9%	172	+0.71	3.00	530	63
Huascar Brazobán R 2022 · 3.77 FIP	32	SU	3.77	28.5%	11.4%	3.0%	.275	3.49	23.3%	12.9%	187	-0.28	3.08	370	62
Jose Manuel Lopez R 2017 · 3.61 FIP	32	SU	3.61	20.4%	10.0%	1.8%	.331	6.14	17.9%	3.7%	41	+2.53	3.50	170	62
Jon Edwards R 2019 · 4.43 FIP	31	SU	4.43	25.1%	11.6%	3.6%	.290	—	—	—	—	—	2.40	132	62
Chris Hatcher R 2017 · 4.31 FIP	32	SU	4.31	24.5%	7.4%	4.3%	.291	5.32	18.0%	8.4%	36	+1.01	2.51	246	62
Scot Shields R 2007 · 3.58 FIP	32	SU	3.58	24.1%	10.3%	2.2%	.271	4.26	20.3%	7.3%	127	+0.68	2.77	686	61
Dale Thayer R 2013 · 3.62 FIP	32	SU	3.62	23.7%	7.4%	2.9%	.287	3.85	20.6%	15.0%	103	+0.23	2.75	239	61
Steve Delabar R 2015 · 3.74 FIP	32	SU	3.74	25.0%	9.9%	2.7%	.246	4.62	20.4%	4.8%	24	+0.88	2.43	229	61
Jeff Fulchino R 2011 · 4.44 FIP	31	SU	4.44	20.4%	11.1%	3.0%	.302	—	—	—	—	—	3.36	178	61
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	61

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	1.2	50	23.8%	11.1%	0.89	3.95
José Cisnero ('24)	1.4	46	24.0%	11.3%	1.01	4.16
Fernando Rodriguez Jr. ('16)	1.2	58	24.6%	11.1%	0.93	4.35
Chaz Roe ('21)	1.1	43	26.4%	11.1%	0.79	3.89
Ray Searage ('81-'90, 4 WAR*)	1.4	41	21.0%*	10.8%*	0.84*	3.70*
Dave Geisel ('78-'85, 2 WAR*)	1.0	42	23.5%*	10.6%*	0.84*	4.12*
Ed Vosberg ('86-'02, 1 WAR*)	1.2	47	21.0%*	9.6%*	0.86*	4.06*