Reiver Sanmartin

P Sacramento River Cats

Age 31 LHP 6'1" / 188 lbs AAA peak 0.1 · 2027

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	28	MIX3 levels	21	2	21	6.33	3.52	19.0%	7.0%	—	K 17.2% · BB 7.0% · FIP 3.74
2025	29	MIX2 levels	47	2	69	2.61	3.17	19.7%	6.2%	1.1	K 16.8% · BB 5.8% · FIP 3.60
2026	30	MIX3 levels	45	1	51	3.53	3.49	21.1%	4.8%	0.6	K 18.9% · BB 4.7% · FIP 3.87
2027PROJ	31	MLBSF	45	0	47	4.27	4.41	16.4%	5.3%	0.1
2028PROJ92% MLB	32	MLBSF	34	0	36	4.51	4.67	15.6%	5.7%	-0.0
2029PROJ93% MLB	33	MLBSF	28	0	29	4.77	4.95	14.8%	6.2%	-0.1

Last 3 seasons WAR 1.8 · Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs53

FB Velo18

K%16

Form3.50 ERA (proj 4.27) · K 15.4% (proj 16.4%) · BB 7.7% (proj 5.3%) ▼ last 90d · 18 IP through Oct 27

CompsJason Gurka (age 31) · Alejandro Soto (age 31) · Jeremy Bleich (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 101109vR 117

ERA4.27

FIP4.41

K%16.4%

BB%5.3%

K-BB%11.1%

Proj IP52

Value2027 · WAR

Runs saved vs league avg · 52 IP

Grades · Statcast · Contract

Scouting Grades

STUF4040

CTRL6060

CMD5050

K†4040

Statcast Percentiles

FB Velo

p1892.2

Whiff%

p2922.4%

p1617.2%

xwOBA vs

p530.309

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)
2015	19	ROK MLE	DSL Rangers 1	6	0	10	52	7	9	0	0%	1.7	9.2%	21.6%	-12.5%	0.0%	5.23	5.07	—
2015	19	ROK RAW	DSL Rangers 1	6	0	10	52	7	9	0	0%	1.7	13.5%	17.3%	-3.8%	0.0%	5.23	4.36	—
2016	20	ROK MLE	DSL Rangers 1	12	12	61	246	56	6	2	100%	5.1	15.5%	3.0%	12.4%	1.1%	2.35	2.80	—
2016	20	ROK RAW	DSL Rangers 1	12	12	61	246	56	6	2	100%	5.1	22.8%	2.4%	20.3%	0.8%	2.35	1.99	—
2017	21	A MLE	Hickory Crawdads	7	6	34	144	28	6	1	86%	4.9	14.4%	4.9%	9.5%	0.9%	2.62	2.99	—
2017	21	A RAW	Hickory Crawdads	7	6	34	144	28	6	1	86%	4.9	19.4%	4.2%	15.3%	0.7%	2.62	2.37	—
2018	22	MIX MLE	3 levels	11	10	60	245	45	4	2	91%	5.5	12.4%	2.6%	9.8%	1.7%	3.15	3.33	—
2018	22	MIX RAW	3 levels	11	10	60	245	45	4	2	91%	5.5	18.4%	1.6%	16.7%	0.8%	3.15	2.23	—
2019	23	MIX MLE	2 levels	25	25	122	531	114	31	11	100%	4.9	16.9%	6.6%	10.4%	2.5%	4.05	3.85	—
2019	23	MIX RAW	2 levels	25	25	122	531	114	31	11	100%	4.9	21.5%	5.8%	15.6%	2.1%	4.05	3.17	—
2021	25	MIX MLE	3 levels	27	19	112	456	123	30	6	70%	4.1	23.7%	7.2%	16.5%	1.5%	3.13	2.83	+3.6
2021	25	MIX RAW	3 levels	27	19	112	456	123	30	6	70%	4.1	27.0%	6.6%	20.4%	1.3%	3.13	2.40	+4.2
2022	26	MIX MLE	2 levels	52	6	75	337	73	31	10	12%	1.4	20.7%	9.3%	11.5%	2.7%	6.57	4.01	+0.5
2022	26	MIX RAW	2 levels	52	6	75	337	73	31	10	12%	1.4	21.7%	9.2%	12.5%	3.0%	6.57	4.12	+0.4
2023	27	MLB MLE	Cincinnati Reds	14	0	14	70	13	10	2	0%	1.0	18.6%	14.3%	4.3%	2.6%	7.07	4.79	-0.0
2023	27	MLB RAW	Cincinnati Reds	14	0	14	70	13	10	2	0%	1.0	18.6%	14.3%	4.3%	2.9%	7.07	5.24	-0.1
2024	28	MIX MLE	3 levels	21	2	21	100	19	7	2	10%	1.0	17.2%	7.0%	10.2%	2.2%	6.33	3.74	—
2024	28	MIX MLE	3 levels	21	2	21	100	19	7	2	10%	1.0	17.2%	7.0%	10.2%	2.2%	6.33	3.74	—
2024	28	MIX RAW	3 levels	21	2	21	100	19	7	2	10%	1.0	19.0%	7.0%	12.0%	2.0%	6.33	3.52	—
2025	29	MIX MLE	2 levels	47	2	69	289	57	18	5	4%	1.5	16.8%	5.8%	11.1%	2.2%	2.61	3.60	+0.8
2025	29	MIX MLE	2 levels	47	2	69	289	57	18	5	4%	1.5	16.8%	5.8%	11.1%	2.2%	2.61	3.60	+0.8
2025	29	MIX RAW	2 levels	47	2	69	289	57	18	5	4%	1.5	19.7%	6.2%	13.5%	1.7%	2.61	3.17	+1.1
2026	30	MIX MLE	3 levels	45	1	51	209	44	10	6	2%	1.1	18.9%	4.7%	14.2%	3.2%	3.53	3.87	+0.4
2026	30	MIX MLE	3 levels	45	1	51	209	44	10	6	2%	1.1	18.9%	4.7%	14.2%	3.2%	3.53	3.87	+0.4
2026	30	MIX RAW	3 levels	45	1	51	209	44	10	6	2%	1.1	21.1%	4.8%	16.3%	2.9%	3.53	3.49	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			86	6	106	474	89	45	13	7%	1.2	18.8%	9.5%	9.3%	2.7%	5.37	4.29	+0.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	SF	45	0	47	198	33	11	6	0%	1.0	16.4%	5.3%	11.1%	3.0%	4.27	4.41	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	SF	37	0	39	165	26	9	5	0%	1.1	15.6%	5.7%	9.9%	3.2%	4.51	4.67	-0.1
2029	33	MLB MLE	SF	29	0	31	130	19	8	5	0%	1.1	14.8%	6.2%	8.6%	3.5%	4.77	4.95	-0.1
2028	32	MLB CTX	SF	34	0	36	152	24	9	5	0%	1.1	15.6%	5.7%	9.9%	3.2%	4.51	4.67	-0.0
2029	33	MLB CTX	SF	28	0	29	122	18	8	4	0%	1.0	14.8%	6.2%	8.6%	3.5%	4.77	4.95	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		147	6	170	746	130	61	22	4%	1.2	17.5%	8.2%	9.3%	3.0%	5.09	4.29	+0.5
/ 200 IP	—	RAW		173	7	200	877	153	72	26	4%	1.2	17.5%	8.2%	9.3%	3.0%	5.09	4.29	+0.6
Career	—	MLE		267	83	631	2679	480	175	54	31%	2.4	17.9%	6.5%	11.4%	2.0%	3.82	3.52	+0.1
/ 200 IP	—	MLE		85	26	200	849	152	55	17	31%	2.4	17.9%	6.5%	11.4%	2.0%	3.82	3.52	+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.

2026 AAASacramento River Cats · 28 IPFIP 3.06 → 3.44 (+0.38)K% 23.6% → 20.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.64%	—	×0.860	20.33%
BB% (unintentional) /BF	3.64%	—	×0.900	3.27%
HR / BF /BF	2.73%	÷1.000	×1.100	3.00%

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 3.06 → 3.44, 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).

2025 AAALouisville Bats · 67 IPFIP 3.24 → 3.60 (+0.37)K% 19.6% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.57%	—	×0.860	16.83%
BB% (unintentional) /BF	6.41%	—	×0.900	5.77%
HR / BF /BF	1.78%	÷0.901	×1.100	2.17%

Result: FIP 3.24 → 3.60, 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 AAALouisville Bats · 18 IPFIP 3.62 → 3.74 (+0.13)K% 20.0% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.860	17.20%
BB% (unintentional) /BF	7.78%	—	×0.900	7.00%
HR / BF /BF	2.22%	÷1.111	×1.100	2.20%

Result: FIP 3.62 → 3.74, 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 AAALouisville Bats · 18 IPFIP 2.37 → 2.53 (+0.16)K% 32.1% → 28.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.10%	—	×0.880	28.25%
BB% (unintentional) /BF	4.94%	—	×1.050	5.19%
HR / BF /BF	2.47%	÷1.282	×1.100	2.12%

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 156).

Result: FIP 2.37 → 2.53, 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 · 82 IPFIP 2.72 → 3.03 (+0.32)K% 25.9% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.95%	—	×0.880	22.83%
BB% (unintentional) /BF	6.71%	—	×1.050	7.04%
HR / BF /BF	1.75%	÷1.088	×1.100	1.77%

Result: FIP 2.72 → 3.03, 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).

2021 AAChattanooga Lookouts · 18 IPFIP 1.12 → 1.77 (+0.66)K% 34.8% → 28.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.85%	—	×0.810	28.23%
BB% (unintentional) /BF	7.58%	—	×1.100	8.33%
HR / BF /BF	0.00%	÷0.950	×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 90).

Result: FIP 1.12 → 1.77, 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+Daytona Tortugas · 64 IPFIP 2.90 → 3.56 (+0.66)K% 21.8% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.82%	—	×0.770	16.80%
BB% (unintentional) /BF	5.09%	—	×1.150	5.85%
HR / BF /BF	1.82%	÷1.101	×1.250	2.06%

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 120).

Result: FIP 2.90 → 3.56, 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 AAChattanooga Lookouts · 58 IPFIP 3.45 → 4.16 (+0.71)K% 21.1% → 17.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.09%	—	×0.810	17.09%
BB% (unintentional) /BF	6.64%	—	×1.100	7.30%
HR / BF /BF	2.34%	÷0.979	×1.200	2.87%

Result: FIP 3.45 → 4.16, 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).

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
Reiver Sanmartin (OGILVIE)	—	—	4.41	16.4%	5.3%	3.0%	—	4.79	15.2%	9.3%	70	+0.38	—	—	—
Jason Gurka L 2019 · 5.13 FIP	31	SW	5.13	15.5%	7.6%	4.3%	.382	—	—	—	—	—	2.82	183	68
Alejandro Soto L 2017 · 4.36 FIP	31	SW	4.36	13.8%	3.3%	3.7%	.323	4.03	17.1%	10.2%	61	-0.33	3.96	280	64
Jeremy Bleich L 2018 · 3.69 FIP	31	SU	3.69	20.3%	6.6%	2.7%	.296	4.41	20.1%	13.1%	33	+0.72	3.20	241	64
Andrew Barbosa L 2017 · 4.67 FIP	29	SU	4.67	20.2%	9.6%	3.8%	.301	—	—	—	—	—	2.70	175	64
Raul Valdes L 2010 · 4.02 FIP	32	SU	4.02	21.4%	9.9%	2.7%	.301	3.14	27.4%	22.5%	78	-0.88	2.29	160	63
Nick Ramirez L 2021 · 3.63 FIP	31	SU	3.63	20.2%	8.0%	2.2%	.305	3.17	17.7%	11.9%	169	-0.46	2.91	478	63
Darin Downs L 2015 · 4.06 FIP	30	SU	4.06	12.9%	4.2%	2.8%	.288	—	—	—	—	—	2.83	107	61
Kraig Sitton L 2017 · 3.87 FIP	29	SU	3.87	14.7%	6.1%	2.2%	.312	—	—	—	—	—	2.81	166	61
Adam Liberatore L 2018 · 4.28 FIP	31	SU	4.28	18.6%	9.1%	2.9%	.354	—	—	—	—	—	2.38	124	61
Edgar Osuna L 2019 · 5.09 FIP	31	SW	5.09	10.0%	7.2%	3.5%	.373	—	—	—	—	—	5.05	175	60
Colt Hynes L 2016 · 3.55 FIP	31	SU	3.55	22.3%	4.8%	3.1%	.353	3.75	14.1%	9.5%	56	+0.20	3.42	169	59
Tommy Phelps L 2005 · 3.98 FIP	31	SU	3.98	13.2%	7.5%	1.9%	.280	—	—	—	—	—	3.39	120	59
Chad Zerbe L 2003 · 3.89 FIP	31	SU	3.89	7.8%	5.5%	1.4%	.306	—	—	—	—	—	3.75	145	59
Erasmo Ramirez L 2005 · 4.68 FIP	29	SU	4.68	6.2%	3.1%	3.1%	.250	—	—	—	—	—	3.59	108	58
Tommy Layne L 2016 · 3.43 FIP	31	SU	3.43	20.3%	9.6%	1.5%	.266	4.25	19.4%	10.0%	90	+0.82	0.55	218	57
Randy Flores L 2006 · 4.00 FIP	31	SU	4.00	20.4%	9.7%	2.5%	.333	3.30	18.1%	10.5%	93	-0.70	2.51	250	57
Nick Hagadone L 2017 · 3.74 FIP	31	SU	3.74	22.6%	9.3%	2.5%	.267	—	—	—	—	—	2.97	141	57
Tyler Alexander L 2021 · 5.27 FIP	29	SW	5.27	15.7%	10.7%	3.9%	.272	—	—	—	—	—	5.27	128	57
Vic Darensbourg L 2002 · 5.46 FIP	31	SU	5.46	14.2%	9.4%	4.3%	.304	4.11	9.4%	4.2%	22	-1.35	2.94	287	56
Tyler Olson L 2021 · 3.96 FIP	31	SU	3.96	21.6%	8.7%	2.9%	.250	—	—	—	—	—	3.15	263	56

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	1.1	46	17.2%	7.9%	1.15	4.89
Juan Gutierrez ('14)	1.4	57	19.4%	8.4%	1.04	4.49
Jeff Manship ('16)	1.1	32	16.5%	9.3%	1.05	4.82
Tyler Walker ('10)	1.5	50	18.9%	8.5%	1.11	4.23
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Tom Dukes ('67-'72, -2 WAR*)	1.1	43	22.7%*	8.7%*	1.16*	5.37*