Jose Chirinos

P Brooklyn Cyclones

Age 22 RHP 6'3" / 170 lbs A+ Svc 0.0 · Ctrl thru 2033 peak 1.0 · 2029

Overview

A+PROSPECTMiLBFA 2034

OGV OFP40OGV rank#259ETA2029MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	19	MIX2 levels	13	7	38	6.21	2.83	24.7%	14.6%	—	K 17.0% · BB 17.4% · FIP 3.87
2025	20	MIX2 levels	19	13	72	3.01	2.75	23.7%	11.7%	—	K 17.1% · BB 13.9% · FIP 3.69
2026	21	MIX2 levels	24	22	114	3.39	3.38	25.8%	8.7%	—	K 19.5% · BB 10.0% · FIP 4.43
2027PROJ	22	MLBNYM	1	1	1	4.94	4.94	19.3%	11.8%	0.0
2028PROJ35% MLB	23	MLBNYM	9	9	47	4.74	4.65	20.8%	10.7%	0.4
2029PROJ54% MLB	24	MLBNYM	13	13	73	4.57	4.48	21.7%	10.0%	0.8

Next 3 projected WAR 1.2Projected 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$2M2032Arb-2$4M2033Arb-3$5M

Career WAR0.0 WAR median (P10 -0.5 / P90 8.0, comp-based) · star 2% · didn't stick 84%

CompsJosh Bostick (age 22) · Nick Sinacola (age 22) · Miguel Almonte (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 127119vR 111

ERA4.94

FIP4.94

K%19.3%

BB%11.8%

K-BB%7.5%

Proj IP134

Value2027 · WAR

Runs saved vs league avg · 134 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$23M 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	+0.4	$1M	+$0.8M
2029	Pre-Arb	$0.8M	+0.8	$3M	+$2M
2030	Pre-Arb	$0.8M	+0.8	$3M	+$2M
2031	Arb-1	$2M	+0.9	$3M	+$1M
2032	Arb-2	$4M	+0.9	$2M	+$0.1M
2033	Arb-3	$5M	+0.8	$2M	+$0.0M (cut)
Totals		$9M		$14M	+$6M

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)
2022	17	ROK MLE	DSL Mets 2	12	8	33	149	29	18	6	67%	2.8	13.2%	15.1%	-1.9%	5.6%	4.91	6.99	—
2022	17	ROK RAW	DSL Mets 2	12	8	33	149	29	18	6	67%	2.8	19.5%	12.1%	7.4%	4.0%	4.91	5.34	—
2023	18	ROK MLE	DSL Mets Orange	11	11	39	183	51	17	1	100%	3.5	19.0%	11.6%	7.3%	0.7%	4.62	3.36	—
2023	18	ROK RAW	DSL Mets Orange	11	11	39	183	51	17	1	100%	3.5	27.9%	9.3%	18.6%	0.5%	4.62	2.13	—
2024	19	MIX MLE	2 levels	13	7	38	178	44	26	0	54%	2.9	17.0%	17.4%	-0.4%	0.0%	6.21	3.87	—
2024	19	MIX MLE	2 levels	13	7	38	178	44	26	0	54%	2.9	17.0%	17.4%	-0.4%	0.0%	6.21	3.87	—
2024	19	MIX RAW	2 levels	13	7	38	178	44	26	0	54%	2.9	24.7%	14.6%	10.1%	0.0%	6.21	2.83	—
2025	20	MIX MLE	2 levels	19	13	72	308	73	36	1	68%	3.8	17.1%	13.9%	3.2%	0.5%	3.01	3.69	—
2025	20	MIX MLE	2 levels	19	13	72	308	73	36	1	68%	3.8	17.1%	13.9%	3.2%	0.5%	3.01	3.69	—
2025	20	MIX RAW	2 levels	19	13	72	308	73	36	1	68%	3.8	23.7%	11.7%	12.0%	0.3%	3.01	2.75	—
2026	21	MIX MLE	2 levels	24	22	114	485	125	42	12	92%	4.8	19.5%	10.0%	9.5%	3.1%	3.39	4.43	—
2026	21	MIX MLE	2 levels	24	22	114	485	125	42	12	92%	4.8	19.5%	10.0%	9.5%	3.1%	3.39	4.43	—
2026	21	MIX RAW	2 levels	24	22	114	485	125	42	12	92%	4.8	25.8%	8.7%	17.1%	2.5%	3.39	3.38	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	22	MLB	NYM	1	1	1	4	1	0	0	100%	1.0	19.3%	11.8%	7.5%	2.9%	4.94	4.94	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	23	MLB MLE	NYM	25	25	134	566	118	60	16	100%	5.4	20.8%	10.7%	10.1%	2.9%	4.74	4.65	+1.2
2029	24	MLB MLE	NYM	24	24	134	566	123	57	16	100%	5.6	21.7%	10.0%	11.7%	2.9%	4.57	4.48	+1.4
2030	25	MLB MLE	NYM	17	17	100	421	94	41	12	100%	5.9	22.2%	9.7%	12.6%	2.8%	4.46	4.39	+1.2
2031	26	MLB MLE	NYM	17	17	99	419	94	40	12	100%	5.8	22.4%	9.6%	12.9%	2.8%	4.40	4.36	+1.2
2032	27	MLB MLE	NYM	16	16	97	408	91	39	12	100%	6.0	22.4%	9.6%	12.8%	2.9%	4.40	4.40	+1.1
2033	28	MLB MLE	NYM	15	15	92	389	87	38	12	100%	6.1	22.3%	9.8%	12.5%	3.0%	4.45	4.48	+1.0
2034	29	MLB MLE	NYM	14	14	86	361	80	36	11	100%	6.1	22.1%	10.0%	12.0%	3.1%	4.55	4.61	+0.8
2035	30	MLB MLE	NYM	13	13	78	328	71	34	11	100%	6.0	21.7%	10.3%	11.4%	3.3%	4.69	4.79	+0.5
2036	31	MLB MLE	NYM	12	12	70	294	63	31	11	100%	5.8	21.3%	10.7%	10.6%	3.6%	4.87	4.99	+0.3
2037	32	MLB MLE	NYM	10	10	62	262	55	29	10	100%	6.2	20.9%	11.1%	9.8%	3.8%	5.08	5.22	+0.1
2028	23	MLB CTX	NYM	9	9	47	198	41	21	6	100%	5.2	20.8%	10.7%	10.1%	2.9%	4.74	4.65	+0.4
2029	24	MLB CTX	NYM	13	13	73	308	67	31	9	100%	5.6	21.7%	10.0%	11.7%	2.8%	4.57	4.48	+0.8
2030	25	MLB CTX	NYM	11	11	67	283	63	27	8	100%	6.1	22.2%	9.7%	12.6%	2.8%	4.46	4.39	+0.8
2031	26	MLB CTX	NYM	13	13	76	321	72	31	9	100%	5.8	22.4%	9.6%	12.9%	2.8%	4.40	4.36	+0.9
2032	27	MLB CTX	NYM	13	13	79	334	75	32	10	100%	6.1	22.4%	9.6%	12.8%	2.9%	4.40	4.40	+0.9
2033	28	MLB CTX	NYM	13	13	78	329	73	32	10	100%	6.0	22.3%	9.8%	12.5%	3.0%	4.45	4.48	+0.8
2034	29	MLB CTX	NYM	12	12	75	317	70	32	10	100%	6.2	22.1%	10.0%	12.0%	3.1%	4.55	4.61	+0.7
2035	30	MLB CTX	NYM	12	12	69	291	63	30	10	100%	5.8	21.7%	10.3%	11.4%	3.3%	4.69	4.79	+0.5
2036	31	MLB CTX	NYM	10	10	63	266	57	28	9	100%	6.3	21.3%	10.7%	10.6%	3.6%	4.87	4.99	+0.3
2037	32	MLB CTX	NYM	10	10	57	241	50	27	9	100%	5.7	20.9%	11.1%	9.8%	3.8%	5.07	5.21	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		116	116	683	2885	631	291	89	100%	5.9	21.9%	10.1%	11.8%	3.1%	4.59	4.23	+9.4
/ 200 IP	—	RAW		34	34	200	844	185	85	26	100%	5.9	21.9%	10.1%	11.8%	3.1%	4.59	4.23	+2.8
Career	—	MLE		79	61	295	1303	232	166	26	77%	3.7	17.8%	12.8%	5.1%	2.0%	3.99	4.32	+8.9
/ 200 IP	—	MLE		53	41	200	882	157	113	18	77%	3.7	17.8%	12.8%	5.1%	2.0%	3.99	4.32	+1.9

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 A+Brooklyn Cyclones · 72 IPFIP 3.89 → 4.94 (+1.06)K% 24.4% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.37%	—	×0.770	18.76%
BB% (unintentional) /BF	10.13%	—	×1.150	11.65%
HR / BF /BF	2.85%	÷1.000	×1.250	3.56%

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 100).

Result: FIP 3.89 → 4.94, 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).

2026 ASt. Lucie Mets · 42 IPFIP 2.43 → 3.48 (+1.05)K% 28.4% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.40%	—	×0.740	21.02%
BB% (unintentional) /BF	5.92%	—	×1.180	6.98%
HR / BF /BF	1.78%	÷1.000	×1.300	2.31%

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 2.43 → 3.48, 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).

2025 ASt. Lucie Mets · 56 IPFIP 3.12 → 3.96 (+0.85)K% 20.6% → 15.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.65%	—	×0.740	15.28%
BB% (unintentional) /BF	12.15%	—	×1.180	14.33%
HR / BF /BF	0.40%	÷0.855	×1.300	0.62%

Result: FIP 3.12 → 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).

2025 ROKFCL Mets · 15 IPFIP 1.30 → 2.59 (+1.29)K% 36.1% → 24.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.07%	—	×0.680	24.52%
BB% (unintentional) /BF	9.84%	—	×1.250	12.30%
HR / BF /BF	0.00%	÷0.927	×1.400	0.00%

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 85).

Result: FIP 1.30 → 2.59, 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).

2024 ROKFCL Mets · 37 IPFIP 2.76 → 3.87 (+1.12)K% 25.0% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.680	17.00%
BB% (unintentional) /BF	13.95%	—	×1.250	17.44%
HR / BF /BF	0.00%	÷0.974	×1.400	0.00%

Result: FIP 2.76 → 3.87, 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 ROKDSL Mets Orange · 39 IPFIP 2.22 → 3.36 (+1.13)K% 27.9% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.87%	—	×0.680	18.95%
BB% (unintentional) /BF	9.29%	—	×1.250	11.61%
HR / BF /BF	0.55%	÷1.084	×1.400	0.71%

Result: FIP 2.22 → 3.36, 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 ROKDSL Mets 2 · 33 IPFIP 5.20 → 6.99 (+1.79)K% 19.5% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.46%	—	×0.680	13.23%
BB% (unintentional) /BF	12.08%	—	×1.250	15.10%
HR / BF /BF	4.03%	÷1.000	×1.400	5.64%

Result: FIP 5.20 → 6.99, 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
Jose Chirinos (OGILVIE)	—	—	—	—	—	2.9%	—	4.52	21.5%	11.4%	368	-0.42	—	—	—
Josh Bostick R 2024 · 4.65 FIP	22	SP	4.65	19.3%	11.2%	3.2%	.304	5.40	21.7%	12.6%	119	+0.75	4.65	226	89
Nick Sinacola R 2022 · 4.44 FIP	22	SP-	4.44	19.3%	10.4%	3.0%	.335	4.05	18.2%	10.0%	254	-0.39	3.56	357	86
Miguel Almonte R 2015 · 3.88 FIP	22	SP-	3.88	18.0%	10.1%	1.8%	.300	4.41	19.4%	7.9%	143	+0.53	3.06	247	86
Trevor Martin R 2023 · 4.25 FIP	22	SP	4.25	21.3%	10.6%	2.9%	.297	4.19	20.3%	11.0%	243	-0.06	3.94	353	86
Kyle Bradish R 2019 · 4.56 FIP	22	SP-	4.56	20.8%	13.7%	2.7%	.309	3.84	24.1%	14.7%	238	-0.72	2.20	750	86
Dinelson Lamet R 2015 · 4.36 FIP	23	SP	4.36	20.1%	11.8%	2.7%	.272	3.69	24.2%	13.1%	293	-0.67	2.11	778	85
Max Gamboa R 2018 · 3.99 FIP	22	SP-	3.99	17.3%	9.5%	2.1%	.334	3.99	26.5%	7.7%	61	+0.00	3.99	162	84
Derek True R 2024 · 4.90 FIP	23	SP-	4.90	18.5%	10.5%	3.7%	.333	4.95	17.6%	5.9%	73	+0.05	4.50	170	84
Chris McElvain R 2023 · 4.76 FIP	22	SP	4.76	15.8%	11.6%	2.8%	.275	5.24	15.8%	4.7%	198	+0.48	4.07	294	84
Jordan Jackson R 2022 · 4.15 FIP	23	SP	4.15	16.8%	9.7%	2.2%	.323	5.51	13.1%	1.7%	74	+1.36	4.15	193	83
Adam Hill R 2019 · 5.00 FIP	22	SP	5.00	15.6%	12.6%	3.0%	.297	6.06	19.6%	8.9%	91	+1.06	5.00	213	83
Jack Wenninger R 2024 · 4.33 FIP	22	SP-	4.33	20.9%	9.3%	3.3%	.309	4.29	21.1%	11.1%	251	-0.04	3.90	366	83
Adrian Houser R 2015 · 4.38 FIP	22	SP-	4.38	16.6%	8.8%	2.9%	.298	3.90	15.5%	7.4%	163	-0.48	3.45	1,221	83
Rorik Maltrud R 2024 · 3.91 FIP	24	SP-	3.91	20.4%	9.6%	2.4%	.300	4.40	18.6%	9.4%	193	+0.49	3.91	298	83
Jimmy Endersby R 2021 · 4.29 FIP	23	SP-	4.29	20.9%	14.1%	2.1%	.310	5.71	16.3%	4.2%	225	+1.42	2.86	357	83
Tyler Uberstine R 2022 · 4.19 FIP	23	SP-	4.19	19.5%	10.5%	2.6%	.302	4.27	22.8%	15.4%	121	+0.08	2.98	262	83
Jamison Hill R 2022 · 4.83 FIP	23	SP	4.83	18.4%	11.6%	3.3%	.280	5.02	16.1%	3.0%	202	+0.19	4.72	326	83
Chase Cohen R 2019 · 4.69 FIP	22	SP-	4.69	15.8%	13.0%	2.3%	.317	4.22	22.1%	9.2%	85	-0.47	3.52	263	83
Kenten Egbert R 2024 · 4.26 FIP	23	SP-	4.26	19.6%	9.6%	2.9%	.257	4.34	10.8%	3.5%	133	+0.08	4.04	231	83
Bryce Conley R 2018 · 4.71 FIP	23	SP-	4.71	20.2%	12.2%	3.2%	.269	4.88	17.4%	3.3%	197	+0.17	4.22	560	83

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	5.4	99	21.5%	10.3%	1.18	4.64
Dave Hamilton ('72-'80, 2 WAR*)	3.5	78	21.3%*	10.2%*	1.13*	4.58*
Bud Norris ('18)	6.1	122	21.7%	9.1%	1.15	4.45
Diego Segui ('62-'77, 10 WAR*)	9.0	121	22.2%*	9.9%*	1.19*	4.40*
Dan Spillner ('74-'85, 5 WAR*)	7.5	124	20.6%*	9.1%*	1.11*	4.64*
Scott Sanders ('99)	3.4	97	21.2%	9.3%	1.23	4.86
Jorge De La Rosa ('18)	7.6	109	19.1%	10.3%	1.05	4.58