Rico Garcia

P Baltimore Orioles

Age 33 RHP 5'9" / 215 lbs MLB peak 0.4 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	30	AAAWSH	55	0	62	3.94	3.47	34.1%	10.7%	—	K 29.3% · BB 9.7% · FIP 3.96
2025	31	MIX2 levels	53	3	65	3.76	4.54	27.1%	10.5%	0.0	K 25.2% · BB 9.7% · FIP 4.46
2026	32	MLBBAL	75	0	67	3.09	3.67	25.7%	7.2%	0.7
2027PROJ	33	MLBBAL	60	0	63	3.73	3.86	27.3%	7.2%	0.5
2028PROJ93% MLB	34	MLBBAL	46	0	48	3.99	4.16	26.4%	7.8%	0.2
2029PROJ88% MLB	35	MLBBAL	32	0	34	4.29	4.50	25.5%	8.3%	0.0

Last 3 seasons WAR 0.7 · Next 3 projected WAR 0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs90

K%69

FB Velo62

Form3.10 ERA (proj 3.73) · K 22.4% (proj 27.3%) · BB 9.4% (proj 7.2%) ▼▼ last 90d · 20 IP through Oct 27

CompsJoe Nelson (age 33) · Tony Barnette (age 33) · Jim Henderson (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9587vR 79

ERA3.73

FIP3.86

K%27.3%

BB%7.2%

K-BB%20.1%

Proj IP65

Value2027 · WAR

Runs saved vs league avg · 65 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL5555

CMD6060

K†6565

Statcast Percentiles

FB Velo

p6295.4

Whiff%

p9031.9%

p6925.7%

xwOBA vs

p900.265

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	23	A MLE	Asheville Tourists	8	4	28	118	30	7	2	50%	3.5	18.8%	7.0%	11.8%	1.8%	2.57	3.37	—
2017	23	A RAW	Asheville Tourists	8	4	28	118	30	7	2	50%	3.5	25.4%	5.9%	19.5%	1.7%	2.57	2.64	—
2018	24	MIX MLE	2 levels	27	26	167	680	162	42	20	96%	6.2	18.7%	7.0%	11.7%	2.6%	2.96	3.84	—
2018	24	MIX RAW	2 levels	27	26	167	680	162	42	20	96%	6.2	23.8%	6.2%	17.6%	2.9%	2.96	3.47	—
2019	25	MIX MLE	3 levels	28	27	135	572	140	56	21	96%	4.8	21.3%	10.1%	11.2%	3.2%	4.52	4.36	+1.6
2019	25	MIX RAW	3 levels	28	27	135	572	140	56	21	96%	4.8	24.5%	9.8%	14.7%	3.7%	4.52	4.29	+1.8
2020	26	MLB MLE	San Francisco Giants	12	0	10	44	7	4	1	0%	0.8	15.9%	9.1%	6.8%	2.3%	5.40	4.16	+0.0
2020	26	MLB RAW	San Francisco Giants	12	0	10	44	7	4	1	0%	0.8	15.9%	9.1%	6.8%	2.3%	5.40	4.20	+0.0
2022	28	MIX MLE	4 levels	30	3	53	218	62	21	8	10%	1.8	25.0%	10.4%	14.5%	4.8%	2.36	4.96	-0.3
2022	28	MIX RAW	4 levels	30	3	53	218	62	21	8	10%	1.8	28.4%	9.6%	18.8%	3.7%	2.36	3.91	+0.4
2023	29	MIX MLE	2 levels	34	0	39	182	46	26	8	0%	1.2	22.5%	13.2%	9.3%	4.5%	4.81	5.32	-0.4
2023	29	MIX RAW	2 levels	34	0	39	182	46	26	8	0%	1.2	25.3%	14.3%	11.0%	4.4%	4.81	5.39	-0.4
2024	30	AAA MLE	Rochester Red Wings	55	0	62	261	89	28	9	0%	1.1	29.3%	9.7%	19.7%	3.8%	3.94	3.96	—
2024	30	AAA MLE	Rochester Red Wings	55	0	62	261	89	28	9	0%	1.1	29.3%	9.7%	19.7%	3.8%	3.94	3.96	—
2024	30	AAA RAW	Rochester Red Wings	55	0	62	261	89	28	9	0%	1.1	34.1%	10.7%	23.4%	3.4%	3.94	3.47	—
2025	31	MIX MLE	2 levels	53	3	65	277	75	29	12	6%	1.2	25.2%	9.7%	15.5%	4.1%	3.76	4.46	+0.1
2025	31	MIX MLE	2 levels	53	3	65	277	75	29	12	6%	1.2	25.2%	9.7%	15.5%	4.1%	3.76	4.46	+0.1
2025	31	MIX RAW	2 levels	53	3	65	277	75	29	12	6%	1.2	27.1%	10.5%	16.6%	4.3%	3.76	4.54	+0.0
2026	32	MLB MLE	Baltimore Orioles	75	0	67	265	68	19	9	0%	0.9	25.7%	7.2%	18.5%	3.2%	3.09	3.63	+0.7
2026	32	MLB MLE	Baltimore Orioles	75	0	67	265	68	19	9	0%	0.9	25.7%	7.2%	18.5%	3.2%	3.09	3.63	+0.7
2026	32	MLB RAW	Baltimore Orioles	75	0	67	265	68	19	9	0%	0.9	25.7%	7.2%	18.5%	3.4%	3.09	3.67	+0.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			134	2	137	576	127	46	25	1%	1.0	22.0%	8.0%	14.1%	4.3%	4.20	4.63	-0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	BAL	60	0	63	266	73	19	9	0%	1.1	27.3%	7.2%	20.1%	3.2%	3.73	3.86	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	BAL	49	0	52	218	58	17	8	0%	1.1	26.4%	7.8%	18.7%	3.5%	3.99	4.16	+0.2
2029	35	MLB MLE	BAL	36	0	38	162	41	13	6	0%	1.1	25.5%	8.3%	17.2%	3.9%	4.29	4.50	+0.0
2028	34	MLB CTX	BAL	46	0	48	203	54	16	7	0%	1.0	26.4%	7.8%	18.7%	3.5%	3.99	4.16	+0.2
2029	35	MLB CTX	BAL	32	0	34	144	37	12	6	0%	1.1	25.5%	8.3%	17.2%	3.9%	4.29	4.50	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		212	2	219	920	217	73	38	1%	1.0	23.5%	8.0%	15.6%	4.1%	4.17	4.37	+0.5
/ 200 IP	—	RAW		194	2	200	842	199	67	35	1%	1.0	23.5%	8.0%	15.6%	4.1%	4.17	4.37	+0.4
Career	—	MLE		322	63	626	2617	588	235	88	20%	1.9	22.5%	9.0%	13.5%	3.4%	3.58	4.19	+0.1
/ 200 IP	—	MLE		103	20	200	836	188	75	28	20%	1.9	22.5%	9.0%	13.5%	3.4%	3.58	4.19	+0.1

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 AAASyracuse Mets · 30 IPFIP 5.51 → 5.48 (−0.03)K% 27.4% → 23.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.41%	—	×0.860	23.57%
BB% (unintentional) /BF	14.81%	—	×0.900	13.33%
HR / BF /BF	5.19%	÷1.167	×1.100	4.89%

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 133).

Result: FIP 5.51 → 5.48, 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 AAARochester Red Wings · 62 IPFIP 3.47 → 3.96 (+0.49)K% 34.1% → 29.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.10%	—	×0.860	29.33%
BB% (unintentional) /BF	10.73%	—	×0.900	9.66%
HR / BF /BF	3.45%	÷0.986	×1.100	3.85%

Result: FIP 3.47 → 3.96, 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 AAARochester Red Wings · 28 IPFIP 4.03 → 4.23 (+0.20)K% 29.5% → 25.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.51%	—	×0.860	25.38%
BB% (unintentional) /BF	16.39%	—	×0.900	14.75%
HR / BF /BF	2.46%	÷1.058	×1.100	2.56%

Result: FIP 4.03 → 4.23, 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 AAANorfolk Tides · 35 IPFIP 4.30 → 4.96 (+0.66)K% 28.4% → 25.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.37%	—	×0.880	24.96%
BB% (unintentional) /BF	9.93%	—	×1.050	10.43%
HR / BF /BF	4.26%	÷0.970	×1.100	4.83%

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 94).

Result: FIP 4.30 → 4.96, 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 AABowie Baysox · 7 IPFIP 1.64 → 2.43 (+0.78)K% 37.9% → 30.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.93%	—	×0.810	30.72%
BB% (unintentional) /BF	13.79%	—	×1.100	15.17%
HR / BF /BF	0.00%	÷1.170	×1.200	0.00%

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 134).

Result: FIP 1.64 → 2.43, 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).

2019 AAAAlbuquerque Isotopes · 61 IPFIP 5.54 → 5.70 (+0.16)K% 18.0% → 15.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.96%	—	×0.880	15.80%
BB% (unintentional) /BF	9.86%	—	×1.050	10.35%
HR / BF /BF	4.93%	÷1.136	×1.100	4.77%

Result: FIP 5.54 → 5.70, 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).

2019 AAHartford Yard Goats · 68 IPFIP 2.23 → 2.89 (+0.66)K% 33.7% → 27.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.72%	—	×0.810	27.31%
BB% (unintentional) /BF	8.91%	—	×1.100	9.81%
HR / BF /BF	1.55%	÷1.190	×1.200	1.56%

Result: FIP 2.23 → 2.89, 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+Lancaster JetHawks · 100 IPFIP 3.30 → 3.59 (+0.28)K% 24.5% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.46%	—	×0.770	18.83%
BB% (unintentional) /BF	5.33%	—	×1.150	6.13%
HR / BF /BF	2.91%	÷1.531	×1.250	2.37%

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 206).

Result: FIP 3.30 → 3.59, 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
Rico Garcia (OGILVIE)	—	—	3.86	27.3%	7.2%	3.2%	—	4.30	26.0%	18.0%	90	+0.44	—	—	—
Joe Nelson R 2008 · 3.08 FIP	33	SU	3.08	26.1%	7.8%	2.2%	.252	5.35	19.8%	5.5%	40	+2.27	3.08	139	77
Tony Barnette R 2017 · 3.56 FIP	33	SU	3.56	22.6%	7.1%	2.7%	.335	2.61	25.0%	20.2%	26	-0.95	2.61	144	76
Jim Henderson R 2016 · 4.55 FIP	33	SU	4.55	25.8%	9.0%	4.5%	.287	—	—	—	—	—	1.86	167	73
Dale Thayer R 2014 · 3.56 FIP	33	SU	3.56	23.4%	4.9%	3.3%	.243	4.34	15.8%	8.8%	38	+0.78	2.75	239	72
Blake Parker R 2018 · 4.12 FIP	33	SU	4.12	25.4%	6.5%	4.3%	.290	4.12	24.9%	16.5%	121	+0.00	2.52	406	70
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	69
Kazuhiro Sasaki R 2001 · 2.79 FIP	33	SU	2.79	23.8%	3.4%	2.3%	.228	2.95	25.8%	18.5%	94	+0.16	2.76	223	69
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	68
Spencer Patton R 2021 · 3.04 FIP	33	SU	3.04	27.9%	8.7%	2.2%	.305	4.97	21.2%	10.4%	88	+1.93	2.79	239	68
Brendan Donnelly R 2004 · 3.05 FIP	33	SU	3.05	32.6%	8.7%	2.9%	.302	3.88	19.0%	11.8%	150	+0.83	2.23	385	68
Adrian Ramirez R 2019 · 4.29 FIP	31	SU	4.29	21.7%	6.3%	4.0%	.327	—	—	—	—	—	3.04	137	67
Bob Wells R 2000 · 3.93 FIP	33	SU	3.93	21.7%	3.7%	4.0%	.266	4.57	14.2%	8.6%	127	+0.64	3.93	627	67
Huascar Brazobán R 2023 · 3.52 FIP	33	SU	3.52	25.3%	11.3%	2.1%	.304	3.54	21.9%	11.8%	195	+0.02	3.08	370	67
Scott McGough R 2023 · 4.57 FIP	33	SU	4.57	28.6%	9.3%	4.9%	.266	4.23	19.4%	9.4%	126	-0.34	3.55	429	67
Rafael Betancourt R 2008 · 4.12 FIP	33	SU	4.12	20.7%	6.5%	3.6%	.304	2.37	31.4%	27.3%	181	-1.75	1.79	686	66
Tim Dillard R 2016 · 3.13 FIP	33	SU	3.13	22.6%	8.2%	1.7%	.358	4.14	13.7%	6.9%	250	+1.01	2.92	432	66
Arcenio Leon R 2019 · 3.61 FIP	32	SU	3.61	21.4%	8.1%	2.4%	.314	—	—	—	—	—	3.00	115	66
Jon Edwards R 2019 · 4.43 FIP	31	SU	4.43	25.1%	11.6%	3.6%	.290	—	—	—	—	—	2.40	132	66
Marcos Mateo R 2015 · 3.12 FIP	31	SU	3.12	28.0%	8.0%	2.5%	.247	—	—	—	—	—	3.12	104	66
Neil Wagner R 2017 · 3.11 FIP	33	SU	3.11	20.7%	8.6%	1.2%	.257	—	—	—	—	—	3.11	135	66

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	1.5	58	24.5%	8.1%	1.50	4.07
Michael Tonkin ('25)	1.6	55	23.2%	8.1%	1.28	4.23
Noé Ramirez ('22)	1.5	59	24.8%	9.4%	1.42	4.21
Shawn Tolleson ('16)	1.1	54	23.1%	8.3%	1.28	3.92
Pete Ladd ('79-'86, 0 WAR*)	1.4	72	24.6%*	7.8%*	1.53*	4.42*
Julio Navarro ('62-'70, 1 WAR*)	1.1	53	21.7%*	7.8%*	1.55*	4.13*
Buddy Schultz ('75-'79, 2 WAR*)	1.2	60	27.4%*	8.5%*	1.21*	4.14*