Keyner Martinez

P San Jose Giants

Age 22 RHP 6'1" / 209 lbs A Svc 0.0 · Ctrl thru 2033 peak 1.1 · 2030

Overview

APROSPECTMiLBFA 2034

OGV OFP45OGV rank#91ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	19	ROKSF	19	0	33	3.03	3.96	16.3%	11.3%	—	K 11.1% · BB 14.2% · FIP 4.89
2025	20	MIX2 levels	21	11	69	2.21	1.77	34.2%	7.4%	—	K 23.9% · BB 9.0% · FIP 2.83
2026	21	ASF	22	22	94	4.61	3.27	33.6%	11.8%	—	K 24.9% · BB 13.9% · FIP 4.73
2027PROJ	22	MLBSF	—	—	0	4.53	4.53	25.0%	11.8%	—
2028PROJ49% MLB	23	MLBSF	10	10	53	4.25	4.16	25.4%	10.4%	0.7
2029PROJ70% MLB	24	MLBSF	15	15	85	4.10	4.01	25.7%	9.4%	1.3

Next 3 projected WAR 2.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2033Service0.0First FA2034

2027MiLB2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Pre-Arb$0.8M2031Arb-1$4M2032Arb-2$7M2033Arb-3$9M

Career WAR0.0 WAR median (P10 -0.3 / P90 9.5, comp-based) · star 5% · didn't stick 80%

CompsBrandon Bailey (age 22) · Michael Knorr (age 23) · Ian Bedell (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 119111vR 103

ERA4.53

FIP4.53

K%25.0%

BB%11.8%

K-BB%13.1%

Proj IP90

Value2027 · WAR

Runs saved vs league avg · 90 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$49M ctrl surplus

Contract

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

Status MiLB

MLB Debut 2028

Service 0 yrs (est)

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2028
2028	Pre-Arb	$0.8M	+0.7	$3M	+$2M
2029	Pre-Arb	$0.8M	+1.3	$9M	+$8M
2030	Pre-Arb	$0.8M	+1.7	$11M	+$10M
2031	Arb-1	$4M	+1.9	$11M	+$8M
2032	Arb-2	$7M	+1.8	$10M	+$6M
2033	Arb-3	$9M	+1.7	$9M	+$4M
Totals		$23M		$52M	+$38M

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)
2024	19	ROK MLE	ACL Giants	19	0	33	141	23	16	2	0%	1.7	11.1%	14.2%	-3.1%	1.7%	3.03	4.89	—
2024	19	ROK MLE	ACL Giants	19	0	33	141	23	16	2	0%	1.7	11.1%	14.2%	-3.1%	1.7%	3.03	4.89	—
2024	19	ROK RAW	ACL Giants	19	0	33	141	23	16	2	0%	1.7	16.3%	11.3%	5.0%	1.4%	3.03	3.96	—
2025	20	MIX MLE	2 levels	21	11	69	284	97	21	3	52%	3.3	23.9%	9.0%	14.9%	1.1%	2.21	2.83	—
2025	20	MIX MLE	2 levels	21	11	69	284	97	21	3	52%	3.3	23.9%	9.0%	14.9%	1.1%	2.21	2.83	—
2025	20	MIX RAW	2 levels	21	11	69	284	97	21	3	52%	3.3	34.2%	7.4%	26.8%	1.1%	2.21	1.77	—
2026	21	A MLE	San Jose Giants	22	22	94	399	134	47	11	100%	4.3	24.9%	13.9%	11.0%	3.6%	4.61	4.73	—
2026	21	A MLE	San Jose Giants	22	22	94	399	134	47	11	100%	4.3	24.9%	13.9%	11.0%	3.6%	4.61	4.73	—
2026	21	A RAW	San Jose Giants	22	22	94	399	134	47	11	100%	4.3	33.6%	11.8%	21.8%	2.8%	4.61	3.27	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	22	MLB	SF	—	—	0	—	—	—	—	—	—	25.0%	11.8%	13.1%	3.0%	4.53	4.53	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	23	MLB MLE	SF	20	20	108	458	116	47	14	100%	5.4	25.4%	10.4%	15.0%	3.0%	4.37	4.28	+1.4
2029	24	MLB MLE	SF	22	22	122	517	133	49	15	100%	5.6	25.7%	9.4%	16.3%	3.0%	4.22	4.13	+1.8
2030	25	MLB MLE	SF	22	22	131	553	143	49	16	100%	6.0	25.9%	8.9%	17.0%	2.9%	4.11	4.03	+2.1
2031	26	MLB MLE	SF	22	22	131	551	143	49	16	100%	5.9	26.0%	8.8%	17.2%	2.9%	4.06	4.01	+2.2
2032	27	MLB MLE	SF	21	21	128	540	140	48	16	100%	6.1	26.0%	8.9%	17.1%	3.0%	4.06	4.05	+2.0
2033	28	MLB MLE	SF	20	20	122	517	134	47	16	100%	6.1	25.9%	9.0%	16.8%	3.1%	4.11	4.14	+1.8
2034	29	MLB MLE	SF	19	19	114	483	124	45	16	100%	6.0	25.6%	9.3%	16.4%	3.2%	4.20	4.27	+1.5
2035	30	MLB MLE	SF	17	17	104	440	111	42	15	100%	6.1	25.3%	9.6%	15.7%	3.4%	4.35	4.44	+1.2
2036	31	MLB MLE	SF	16	16	93	393	98	39	14	100%	5.8	24.9%	9.9%	15.0%	3.7%	4.53	4.65	+0.8
2037	32	MLB MLE	SF	14	14	82	346	85	36	14	100%	5.9	24.4%	10.3%	14.1%	3.9%	4.74	4.87	+0.5
2038	33	MLB MLE	SF	12	12	71	301	72	32	13	100%	6.0	23.9%	10.8%	13.2%	4.2%	4.97	5.12	+0.2
2028	23	MLB CTX	SF	10	10	53	224	57	23	6	100%	5.3	25.4%	10.4%	15.0%	2.8%	4.25	4.16	+0.7
2029	24	MLB CTX	SF	15	15	85	359	92	34	10	100%	5.7	25.7%	9.4%	16.3%	2.7%	4.10	4.01	+1.3
2030	25	MLB CTX	SF	18	18	106	448	116	40	12	100%	5.9	25.9%	8.9%	17.0%	2.7%	3.99	3.91	+1.7
2031	26	MLB CTX	SF	19	19	114	481	125	42	13	100%	6.0	26.0%	8.8%	17.2%	2.7%	3.94	3.89	+1.9
2032	27	MLB CTX	SF	19	19	115	486	126	43	13	100%	6.1	26.0%	8.9%	17.1%	2.8%	3.94	3.93	+1.8
2033	28	MLB CTX	SF	19	19	113	477	123	43	14	100%	5.9	25.9%	9.0%	16.8%	2.9%	3.98	4.01	+1.7
2034	29	MLB CTX	SF	18	18	106	448	115	41	13	100%	5.9	25.6%	9.3%	16.4%	3.0%	4.07	4.14	+1.4
2035	30	MLB CTX	SF	16	16	97	410	104	39	13	100%	6.1	25.3%	9.6%	15.7%	3.2%	4.21	4.30	+1.1
2036	31	MLB CTX	SF	15	15	88	372	92	37	13	100%	5.9	24.9%	9.9%	15.0%	3.4%	4.38	4.50	+0.8
2037	32	MLB CTX	SF	13	13	78	329	80	34	12	100%	6.0	24.4%	10.3%	14.1%	3.6%	4.58	4.71	+0.5
2038	33	MLB CTX	SF	11	11	68	287	69	31	11	100%	6.2	23.9%	10.8%	13.2%	3.9%	4.80	4.95	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		173	173	1025	4329	1102	409	131	100%	5.9	25.5%	9.4%	16.0%	3.0%	4.16	3.80	+19.7
/ 200 IP	—	RAW		34	34	200	844	215	80	26	100%	5.9	25.5%	9.4%	16.0%	3.0%	4.16	3.80	+3.8
Career	—	MLE		62	33	196	824	183	101	20	53%	3.2	22.2%	12.2%	9.9%	2.4%	3.50	4.10	+15.6
/ 200 IP	—	MLE		63	34	200	842	187	103	20	53%	3.2	22.2%	12.2%	9.9%	2.4%	3.50	4.10	+2.6

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.

2026 ASan Jose Giants · 94 IPFIP 3.27 → 4.73 (+1.46)K% 33.6% → 24.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.58%	—	×0.740	24.85%
BB% (unintentional) /BF	11.78%	—	×1.180	13.90%
HR / BF /BF	2.76%	÷1.000	×1.300	3.58%

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 100).

Result: FIP 3.27 → 4.73, 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 ROKACL Giants · 47 IPFIP 1.06 → 2.26 (+1.20)K% 35.6% → 24.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.64%	—	×0.680	24.23%
BB% (unintentional) /BF	5.32%	—	×1.250	6.65%
HR / BF /BF	0.53%	÷1.128	×1.400	0.66%

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 126).

Result: FIP 1.06 → 2.26, 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 ASan Jose Giants · 22 IPFIP 3.06 → 3.95 (+0.90)K% 31.2% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.25%	—	×0.740	23.12%
BB% (unintentional) /BF	11.46%	—	×1.180	13.52%
HR / BF /BF	2.08%	÷1.358	×1.300	1.99%

Result: FIP 3.06 → 3.95, 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 · 33 IPFIP 3.94 → 4.89 (+0.95)K% 16.3% → 11.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.31%	—	×0.680	11.09%
BB% (unintentional) /BF	11.35%	—	×1.250	14.18%
HR / BF /BF	1.42%	÷1.178	×1.400	1.69%

Result: FIP 3.94 → 4.89, 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).

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
Keyner Martinez (OGILVIE)	—	—	—	—	—	3.0%	—	4.14	25.7%	16.2%	362	-0.39	—	—	—
Brandon Bailey R 2017 · 3.54 FIP	22	SP-	3.54	24.6%	9.9%	2.3%	.290	4.44	21.2%	9.6%	215	+0.90	3.54	306	88
Michael Knorr R 2023 · 4.30 FIP	23	SP-	4.30	23.6%	11.1%	3.3%	.312	5.15	22.0%	9.5%	123	+0.85	4.30	181	86
Ian Bedell R 2023 · 3.73 FIP	23	SP-	3.73	21.0%	10.1%	2.1%	.285	5.56	18.8%	9.0%	178	+1.83	3.73	274	85
Michael Forret R 2024 · 4.00 FIP	20	SP-	4.00	21.8%	11.8%	2.3%	.302	3.45	22.8%	12.9%	190	-0.55	2.65	289	84
Zach Peek R 2021 · 3.62 FIP	23	SP-	3.62	22.8%	10.1%	2.1%	.339	3.51	17.5%	9.8%	45	-0.11	3.51	256	84
Jake Lyons R 2021 · 4.46 FIP	22	SP-	4.46	21.8%	13.9%	2.6%	.325	4.64	19.4%	9.2%	105	+0.18	4.13	174	84
Javi Rivera R 2022 · 3.78 FIP	22	SP-	3.78	22.3%	7.9%	2.9%	.259	3.72	18.6%	9.0%	93	-0.06	2.81	274	83
J.C. Flowers R 2021 · 3.59 FIP	23	SP-	3.59	21.3%	8.7%	2.1%	.330	4.84	16.4%	2.8%	184	+1.25	3.59	281	82
Trace Bright R 2023 · 4.26 FIP	22	SP-	4.26	26.3%	14.7%	2.8%	.297	4.85	19.4%	6.3%	322	+0.59	4.26	422	82
Noah Denoyer R 2021 · 4.51 FIP	23	SP-	4.51	21.5%	12.1%	3.1%	.275	4.10	25.7%	15.7%	121	-0.41	3.26	181	82
Spencer Arrighetti R 2022 · 3.97 FIP	22	SP-	3.97	24.9%	13.2%	2.4%	.357	4.09	24.4%	13.5%	305	+0.12	3.89	543	82
Brandon Young R 2021 · 4.13 FIP	22	SP	4.13	24.5%	12.3%	2.8%	.297	3.48	22.2%	14.6%	150	-0.65	3.03	492	81
Nolan DeVos R 2023 · 4.21 FIP	22	SP-	4.21	21.1%	14.0%	2.0%	.302	5.66	19.0%	8.3%	111	+1.45	4.21	210	81
Chris Campos R 2023 · 4.91 FIP	22	SP-	4.91	21.0%	11.8%	3.8%	.364	4.57	18.6%	11.6%	249	-0.34	4.54	318	81
Anderson Brito R 2024 · 3.50 FIP	20	SP-	3.50	27.5%	11.9%	2.2%	.231	3.85	23.2%	7.4%	82	+0.35	3.28	135	80
Sam Benschoter R 2022 · 3.71 FIP	24	SP-	3.71	26.3%	9.2%	3.0%	.344	4.96	18.7%	8.6%	306	+1.25	3.61	441	80
Jackson Nezuh R 2024 · 3.89 FIP	22	SP-	3.89	22.5%	11.2%	2.3%	.290	4.40	21.3%	10.9%	176	+0.51	3.89	296	80
Tanner Hall R 2024 · 4.67 FIP	22	SP-	4.67	18.8%	11.2%	3.2%	.295	5.33	10.1%	-4.6%	72	+0.66	4.67	137	80
Austin Hansen R 2019 · 3.81 FIP	22	SP-	3.81	25.1%	15.0%	1.7%	.230	7.74	19.8%	-0.3%	26	+3.93	3.81	204	80
Zach Messinger R 2022 · 3.99 FIP	22	SP-	3.99	23.0%	14.7%	1.8%	.317	4.28	18.7%	7.6%	314	+0.29	3.70	470	79

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	6.5	108	25.4%	9.6%	1.25	4.31
Frankie Montas ('25)	3.9	98	23.6%	8.2%	1.20	4.20
Tylor Megill ('25)	2.0	82	24.3%	9.1%	1.27	4.46
Jose DeLeon ('83-'95, 22 WAR*)	9.5	146	25.8%*	10.4%*	1.01*	4.17*
Nate Karns ('19)	1.6	105	24.0%	9.3%	1.34	4.30
Fred Norman ('62-'80, 16 WAR*)	9.7	162	22.3%*	9.7%*	1.34*	4.33*
Lynn McGlothen ('72-'82, 13 WAR*)	7.5	150	21.2%*	8.7%*	1.26*	4.50*