Kendry Chirinos

3B Vancouver Canadians

Age 22 R/R 5'11" / 170 lbs A+ Svc 0.0 · Ctrl thru 2036

Overview

A+PROSPECTMiLBFA 2037

ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	19	ROKTOR	164	.300/.402/.443	2	7	63	—	.212/.299/.315
2025	20	ATOR	382	.255/.363/.370	6	0	63	—	.210/.292/.293
2026	21	A+TOR	195	.194/.290/.294	3	0	28	—	.154/.233/.229
2027PROJMLE	22	MLBTOR	1	.192/.268/.273	0	0	54	-0.0
2028PROJ35% MLB	23	MLBTOR	54	.198/.275/.293	1	0	61	-0.1
2029PROJ46% MLB	24	MLBTOR	109	.203/.280/.307	2	1	66	-0.1

Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2036Service0.0First FA2037

2027MiLB2028MiLB2029MiLB2030MiLB2031Ext$0.9M2032Ext$0.9M2033Ext$0.9M2034Ext$3M+2

Skills · percentileMiLB Statcast 2026 A+

Chase%68

BB%31

ISO25

Z-Con%23

Whiff%22

Speed21

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsGilbert Gomez (age 22) · Zack Raabe (age 22) · Braulio Vasquez (age 22)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†54

AVG/OBP/SLG.192 / .268 / .273

PA1

HR0

K%36

BB%8

BABIP301

ISO74

MLB%0%

Value2027 · WAR

trajectory · projected WAR by year

Tools · ContractCON 40 / POW 30

Toolsscout grade

CONTACT40

scouting grade only

POWER30

scouting grade only

EYE50

scouting grade only

SPEED40

scouting grade only

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

Status MiLB

MLB Debut 2031

Service 0 yrs (est)

Team Control Through 2036

First FA Year 2037

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2031
2028	MiLB	still in minors · estimated debut 2031
2029	MiLB	still in minors · estimated debut 2031
2030	MiLB	still in minors · estimated debut 2031
2031	Ext	beyond projection horizon · no WAR estimate
2032	Ext	beyond projection horizon · no WAR estimate
2033	Ext	beyond projection horizon · no WAR estimate
2034	Ext	beyond projection horizon · no WAR estimate
2035	Ext	beyond projection horizon · no WAR estimate
2036	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$0.0M	+$0.0M

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 these numbers are built

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2027 = full-season projection (no games played yet). 2028+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	MLB%	PA	AB	H	2B	3B	HR	BB	SO	HBP	SB	CS	AVG	OBP	SLG	OPS	ISO	BABIP	K%	BB%	wOBA	wRC+	BAT	RUN	FLD	POS	REP	WAR
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
2022	17	ROK	DSL Blue Jays	—	177	133	24	10	0	1	35	48	7	0	0	180	377	278	655	98	267	27	20	318	31	—	—	—	—	—	—
2023	18	A	Dunedin Blue Jays	—	15	10	0	0	0	0	5	5	0	0	0		333		333			33	33	233	-8	—	—	—	—	—	—
2023	18	ROK	FCL Blue Jays	—	138	96	19	0	0	2	37	46	4	2	1	198	438	260	698	63	347	33	27	350	51	—	—	—	—	—	—
2024	19	ROK	FCL Blue Jays	—	164	140	42	8	3	2	16	41	8	7	2	300	402	443	845	143	412	25	10	382	63	—	—	—	—	—	—
2025	20	A	Dunedin Blue Jays	—	382	322	82	13	3	6	49	97	6	0	1	255	363	370	733	115	339	25	13	332	63	—	—	—	—	—	—
2026	21	A+	Vancouver Canadians	—	195	170	33	4	2	3	19	60	4	0	0	194	290	294	584	100	275	31	10	269	28	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2022	17	ROK MLE	DSL Blue Jays	—	177	144	16	7	0	0	24	58	7	0	0	111	269	160	428	49	175	33	14	214	31	—	—	—	—	—	—
2023	18	A MLE	Dunedin Blue Jays	—	15	12	0	0	0	0	3	7	0	0	0		200		200			47	20	156	-8	—	—	—	—	—	—
2023	18	ROK MLE	FCL Blue Jays	—	138	110	15	0	0	1	23	66	4	2	1	136	307	164	470	27	308	48	17	243	51	—	—	—	—	—	—
2024	19	ROK MLE	FCL Blue Jays	—	164	146	31	5	2	2	10	59	8	7	2	212	299	315	614	103	332	36	6	261	63	—	—	—	—	—	—
2025	20	A MLE	Dunedin Blue Jays	—	382	338	71	10	3	4	33	136	6	0	1	210	292	293	585	83	320	36	9	261	63	—	—	—	—	—	—
2026	21	A+ MLE	Vancouver Canadians	—	195	175	27	3	2	2	14	81	4	0	0	154	233	229	462	74	259	42	7	210	28	—	—	—	—	—	—
2022	17	ROK MLE	DSL Blue Jays	—	177	144	16	7	0	0	24	58	7	0	0	111	269	160	428	49	182	33	14	214	31	—	—	—	—	—	—
2022	17	ROK RAW	DSL Blue Jays	—	177	133	24	10	0	1	35	48	7	0	0	180	377	278	655	98	267	27	20	318	31	—	—	—	—	—	—
2023	18	ROK MLE	2 teams	—	153	122	15	0	0	1	26	73	4	2	1	123	296	148	444	25	286	48	17	234	45	—	—	—	—	—	—
2023	18	ROK RAW	2 teams	—	153	106	19	0	0	2	42	51	4	2	1	179	428	236	663	57	315	33	27	338	45	—	—	—	—	—	—
2024	19	ROK MLE	FCL Blue Jays	—	164	146	31	5	2	2	10	59	8	7	2	212	299	315	614	103	341	36	6	261	63	—	—	—	—	—	—
2024	19	ROK RAW	FCL Blue Jays	—	164	140	42	8	3	2	16	41	8	7	2	300	402	443	845	143	412	25	10	382	63	—	—	—	—	—	—
2025	20	A MLE	Dunedin Blue Jays	—	382	338	71	10	3	4	33	136	6	0	1	210	292	293	585	83	330	36	9	261	63	—	—	—	—	—	—
2025	20	A RAW	Dunedin Blue Jays	—	382	322	82	13	3	6	49	97	6	0	1	255	363	370	733	115	339	25	13	332	63	—	—	—	—	—	—
2026	21	A+ MLE	Vancouver Canadians	—	195	175	27	3	2	2	14	81	4	0	0	154	233	229	462	74	266	42	7	210	28	—	—	—	—	—	—
2026	21	A+ RAW	Vancouver Canadians	—	195	170	33	4	2	3	19	60	4	0	0	194	290	294	584	100	275	31	10	269	28	—	—	—	—	—	—
2022	17	ROK MLE	DSL Blue Jays	—	177	144	16	7	0	0	24	58	7	0	0	111	269	160	428	49	175	33	14	214	31	—	—	—	—	—	—
2023	18	ROK MLE	2 teams	—	153	122	15	0	0	1	26	73	4	2	1	123	296	148	444	25	278	48	17	234	45	—	—	—	—	—	—
2024	19	ROK MLE	FCL Blue Jays	—	164	145	31	5	2	2	10	59	8	7	2	214	299	317	616	103	332	36	6	261	63	—	—	—	—	—	—
2025	20	A MLE	Dunedin Blue Jays	—	382	340	71	10	3	4	33	136	6	0	1	209	292	291	583	82	320	36	9	261	63	—	—	—	—	—	—
2026	21	A+ MLE	Vancouver Canadians	—	195	175	27	3	2	2	14	81	4	0	0	154	233	229	462	74	259	42	7	210	28	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	19	ROK MLE	FCL Blue Jays	—	164	145	31	5	2	2	10	59	8	7	2	214	299	317	616	103	332	36	6	261	63	—	—	—	—	—	—
2025	20	A MLE	Dunedin Blue Jays	—	382	340	71	10	3	4	33	136	6	0	1	209	292	291	583	82	320	36	9	261	63	—	—	—	—	—	—
2026	21	A+ MLE	Vancouver Canadians	—	195	175	27	3	2	2	14	81	4	0	0	154	233	229	462	74	259	42	7	210	28	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	TOR	0%	324	291	55	9	2	3	25	116	5	2	1	191	267	272	539	80	299	36	8	249	54	-18	+0	+0	+1	+7	-0.3
▸ 2027 — real world (MLB)
2027	22	MLB CTX	TOR	0%	1	1	0	0	0	0	0	0	0	0	0	192	268	273	541	81	301	0	0	249	54	-0	+0	+0	+0	+0	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	TOR	35%	157	141	27	4	1	2	13	54	2	1	0	198	274	291	565	94	300	34	8	259	61	-7	+0	+0	+1	+3	-0.3
2029	24	MLB MLE	TOR	46%	235	211	43	7	2	4	19	80	3	1	0	202	279	305	584	103	300	34	8	266	66	-9	+0	+0	+1	+5	-0.3
2030	25	MLB MLE	TOR	52%	298	268	55	9	2	5	24	99	4	2	1	206	282	314	596	109	300	33	8	271	70	-11	+0	+0	+1	+6	-0.3
2028	23	MLB CTX	TOR	35%	54	49	10	2	0	1	4	19	1	0	0	198	275	293	567	94	301	35	7	260	61	-2	+0	+0	+0	+1	-0.1
2029	24	MLB CTX	TOR	46%	109	97	20	3	1	2	9	37	2	1	0	203	280	307	586	103	302	34	8	267	66	-4	+0	+0	+0	+2	-0.1
2030	25	MLB CTX	TOR	52%	154	138	29	5	1	3	13	51	2	1	0	206	283	316	598	109	301	33	8	272	70	-6	+0	+0	+1	+3	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	317	284	59	10	2	6	26	107	5	2	0	208	286	320	606	113	306	34	8	268	56	-12	+0	+0	+1	+7	-0.4
/ 162G	—	A+C		—	650	582	121	21	4	12	53	219	10	4	0	208	285	320	604	112	307	34	8	268	56	-25	+1	+0	+2	+14	-0.8
Career	—	MLE		—	1881	1653	305	48	13	21	172	683	40	14	5	185	277	267	545	83	295	36	9	250	56	-34	+1	+0	+3	+18	-1.3
/ 162G	—	MLE		—	650	571	105	17	4	7	59	236	14	5	2	184	276	264	541	81	294	36	9	250	56	-27	+0	+0	+2	+14	-1.0

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+Vancouver Canadians · 195 PAwOBA .266 → .210 (−55)K% 30.8% → 41.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.77%	÷1.000	×1.350	—	—	41.54%
BB% (unintentional) /PA	9.74%	÷1.000	×0.710	—	×1.012	7.00%
HBP% /PA	2.05%	—	×0.810	—	×1.012	1.68%
Singles /BIP	21.82%	÷1.000	×0.910	×1.050	×1.012	21.10%
Doubles /BIP	3.64%	÷1.000	×0.830	×1.050	×1.012	3.21%
Triples /BIP	1.82%	÷1.000	×0.820	×1.050	×1.012	1.58%
Home runs /BIP	2.73%	÷1.000	×0.830	—	×1.012	2.29%

Factors used: level-wide A+ factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 22 vs a level average of 22.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .266 → .210; ISO .100 → .076; BABIP .275 → .259. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2025 ADunedin Blue Jays · 382 PAwOBA .328 → .261 (−67)K% 25.4% → 35.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.39%	÷0.968	×1.360	—	—	35.67%
BB% (unintentional) /PA	12.57%	÷1.015	×0.690	—	×1.015	8.67%
HBP% /PA	1.57%	—	×0.780	—	×1.015	1.24%
Singles /BIP	26.67%	÷1.006	×0.920	×1.049	×1.015	25.95%
Doubles /BIP	5.78%	÷1.047	×0.830	×1.049	×1.015	4.88%
Triples /BIP	1.33%	÷0.900	×0.910	×1.049	×1.015	1.44%
Home runs /BIP	2.67%	÷1.284	×0.800	—	×1.015	1.69%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 157, 1B 101, 2B 109, 3B 80, K 94, BB 103 — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.049.

Result: wOBA .328 → .261; ISO .115 → .083; BABIP .339 → .320. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2024 ROKFCL Blue Jays · 164 PAwOBA .372 → .261 (−111)K% 25.0% → 35.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷1.009	×1.440	—	—	35.69%
BB% (unintentional) /PA	9.76%	÷1.042	×0.620	—	×0.995	5.77%
HBP% /PA	4.88%	—	×0.720	—	×0.995	3.49%
Singles /BIP	29.29%	÷1.016	×0.820	×1.048	×0.995	24.66%
Doubles /BIP	8.08%	÷1.012	×0.720	×1.048	×0.995	5.99%
Triples /BIP	3.03%	÷1.150	×0.720	×1.048	×0.995	1.98%
Home runs /BIP	2.02%	÷0.925	×0.780	—	×0.995	1.69%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 85, 1B 103, 2B 102, 3B 130, K 102, BB 108 — applied at half strength. Age: age 20 vs a level average of 19.5 → −0.5% on BB/HBP/hit rates (0.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.048.

Result: wOBA .372 → .261; ISO .143 → .097; BABIP .412 → .332. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2023 ROKFCL Blue Jays · 138 PAwOBA .346 → .243 (−103)K% 33.3% → 47.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	33.33%	÷1.006	×1.440	—	—	47.74%
BB% (unintentional) /PA	26.81%	÷1.000	×0.620	—	×1.008	16.75%
HBP% /PA	2.90%	—	×0.720	—	×1.008	2.10%
Singles /BIP	34.00%	÷0.968	×0.820	×1.050	×1.008	30.47%
Doubles /BIP	0.00%	÷1.008	×0.720	×1.050	×1.008	0.00%
Triples /BIP	0.00%	÷1.042	×0.720	×1.050	×1.008	0.00%
Home runs /BIP	4.00%	÷1.005	×0.780	—	×1.008	3.13%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 101, 1B 94, 2B 102, 3B 108, K 101, BB 100 — applied at half strength. Age: age 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .346 → .243; ISO .062 → .045; BABIP .347 → .308. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2023 ADunedin Blue Jays · 15 PAwOBA .230 → .156 (−74)K% 33.3% → 44.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	33.33%	÷1.018	×1.360	—	—	44.55%
BB% (unintentional) /PA	33.33%	÷1.062	×0.690	—	×1.045	22.64%
HBP% /PA	0.00%	—	×0.780	—	×1.045	0.00%
Singles /BIP	0.00%	÷0.988	×0.920	—	×1.045	0.00%
Doubles /BIP	0.00%	÷1.034	×0.830	—	×1.045	0.00%
Triples /BIP	0.00%	÷1.111	×0.910	—	×1.045	0.00%
Home runs /BIP	0.00%	÷1.279	×0.800	—	×1.045	0.00%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 156, 1B 98, 2B 107, 3B 122, K 104, BB 112 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average).

Result: wOBA .230 → .156; ISO .000 → .000; BABIP .000 → .000. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2022 DSLDSL Blue Jays · 177 PAwOBA .315 → .214 (−101)K% 27.1% → 32.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.12%	÷1.008	×1.220	—	—	32.84%
BB% (unintentional) /PA	19.77%	÷1.034	×0.700	—	×1.008	13.49%
HBP% /PA	3.95%	—	×0.700	—	×1.008	2.79%
Singles /BIP	15.29%	÷1.011	×0.680	×1.001	×1.008	10.38%
Doubles /BIP	11.76%	÷0.960	×0.600	×1.001	×1.008	7.41%
Triples /BIP	0.00%	÷1.000	×0.600	×1.001	×1.008	0.00%
Home runs /BIP	1.18%	÷1.130	×0.470	—	×1.008	0.49%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 126, 1B 102, 2B 92, 3B 100, K 102, BB 107 — applied at half strength. Age: age 18 vs a level average of 18.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.001.

Result: wOBA .315 → .214; ISO .098 → .060; BABIP .267 → .175. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Ryan Goinslast yr '19 career totals — 7 seasons, 1,680 PA	2.5	1,680	22	6	230	279	335	+9	+21	2.0	2.0
/162	664	9	2	+3.7	+8.5	0.8	pk7: 2
#2Doug Strange'89-'98 * career totals — 8 seasons, 2,067 PA	3.1	2,067	31	14	225*	286*	340*	+5	-0	-1.5	0.0
/162	664	10	4	+1.6	-0.1	-0.5	pk7: 1
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 1 projected seasons	0.5	318	5	2	204	277	308	+1	+0	-0.2	-0.1
/162	664	11	4	+2.4	+1.0	-0.4	pk7: 0
#3Abraham Torolast yr '25 career totals — 6 seasons, 1,561 PA	2.4	1,561	39	16	220	282	351	-1	-8	-0.5	-0.5
/162	664	17	7	-0.2	-3.2	-0.2	pk7: -0
#4Hector Torres'68-'77 * career totals — 9 seasons, 1,889 PA	2.8	1,889	18	7	215*	262*	312*	+16	+3	-2.1	-0.9
/162	664	6	2	+5.7	+1.2	-0.7	pk7: 0
#5Alexi Amaristalast yr '17 career totals — 7 seasons, 1,901 PA	2.9	1,901	21	39	231	275	323	+14	-6	-1.1	-1.1
/162	664	7	14	+4.9	-2.1	-0.4	pk7: -1
#6Vic Harris'72-'80 * career totals — 8 seasons, 1,805 PA	2.7	1,805	13	36	215*	286*	325*	+4	-7	-1.9	-1.1
/162	664	5	13	+1.5	-2.7	-0.7	pk7: -0

Career Path Comps

What happened to players with a similar stat profile at this age · Y-axis: wRC+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

		Scouting				At Match Age									Next 3 Yrs									Peak 3 Yrs
Comp	Age	HIT	PWR	SPD	EYE	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR
Kendry Chirinos (OGILVIE)	22	40	30	40	50	189/265/269	80	299	1	1	36%	8%	54	-0.4	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Gilbert Gomez 2014 · A	22	44→39	36→40	40→50	44	202/273/268	66	310	3	7	34%	8%	56	-1.9	184/265/264	80	287	4	8	34%	10%	53	-2.1	159/251/242	83	245	4	8	33%	11%	41	-1.4
✕Zack Raabe 2022 · A	22	45	36→30	45	44	203/279/265	62	321	4	6	35%	9%	58	-1.7	202/291/267	65	281	3	7	26%	10%	63	-1.3	184/289/233	49	251	0	7	24%	12%	54	-1.2
✕Braulio Vasquez 2021 · A	22	42	39→40	44→65	38	197/260/278	81	313	6	7	37%	6%	53	-2.1	207/282/301	94	302	7	30	31%	8%	68	-1.0	200/280/292	92	287	6	42	30%	8%	62	-0.6
✕Yeison Santana 2022 · A	21	43	37→30	45→55	39	200/262/271	71	316	5	10	36%	7%	52	-2.2	221/289/285	64	313	3	15	28%	8%	66	-1.1	229/310/271	42	311	2	22	24%	10%	67	-0.6
✕Eduardo Torrealba 2021 · A	22	44	36→30	43→50	40	210/265/276	66	292	4	6	28%	6%	55	-2.0	219/273/295	76	269	6	14	20%	6%	62	-1.4	210/266/272	62	255	5	17	19%	6%	52	-1.0
✕Brett Tanos 2011 · A	22	42→47	36→40	44→45	42	196/258/270	74	285	3	6	30%	7%	51	-2.3	214/294/309	95	283	7	6	25%	9%	74	-0.6	215/302/313	98	277	8	6	23%	10%	75	-0.4
✕Kyle Overstreet 2016 · A	22	40→45	37→40	42→30	44	190/254/259	69	264	4	4	28%	7%	47	-2.6	223/279/316	93	282	8	3	22%	7%	69	-0.9	224/268/313	89	272	9	1	21%	5%	62	-1.0
✕Glenn Santiago 2023 · A	22	42	41→40	46→45	40	203/258/299	95	286	8	8	31%	6%	57	-1.8	200/263/285	85	289	7	9	31%	7%	56	-1.9	185/254/258	73	266	7	8	31%	7%	46	-1.1
✕Edgar Garzon 2009 · A	22	44	37→40	41→40	42	208/269/280	72	284	4	4	27%	6%	57	-1.8	236/279/332	96	300	7	3	23%	5%	72	-0.7	263/295/376	113	314	10	0	19%	3%	85	+0.1
✕J.C. Millan 2018 · A	22	40	37→40	45→30	36	195/236/271	76	279	4	8	31%	4%	42	-2.9	220/267/316	96	272	9	6	22%	6%	64	-1.3	226/273/320	94	265	9	4	18%	6%	64	-0.5
✕Randy César 2017 · A	22	38→48	40	45→40	35	188/229/270	82	284	8	3	36%	5%	39	-3.1	230/272/320	90	342	8	4	33%	5%	67	-1.1	237/283/328	91	347	8	2	32%	6%	69	-0.6
✕Dionmy Salon 2024 · A	22	43	37→30	41→40	40	200/271/265	65	304	5	5	34%	7%	55	-1.9	195/262/257	62	263	4	8	25%	6%	50	-2.3	170/240/205	35	217	1	7	21%	6%	28	-1.0
✕Daurys Mercedes 2012 · A	22	38	35→40	46→45	42	179/250/239	60	285	2	7	36%	8%	40	-3.0	178/242/245	67	330	3	6	43%	7%	39	-3.1	127/201/181	54	254	2	4	47%	7%	7	-1.7
✕J.J. D'Orazio 2023 · A	21	42→49	38→40	41→30	43	199/266/279	80	295	5	3	32%	8%	56	-1.9	216/265/310	94	296	8	3	28%	6%	62	-1.4	197/245/276	79	263	9	1	28%	5%	45	-1.0
✕Brian Schales 2018 · A	22	42→50	37→45	39→40	44	201/269/268	67	280	5	3	28%	7%	55	-2.0	213/279/328	115	312	10	4	33%	7%	72	-0.7	211/278/342	131	306	11	3	33%	7%	73	-0.4
✕Jesse Hodges 2016 · A	22	37→44	40	43→40	37	185/240/272	87	276	7	4	35%	6%	45	-2.7	202/252/293	91	297	7	4	33%	6%	53	-2.1	190/241/292	102	273	9	2	33%	5%	47	-1.4
✕Kenneth Betancourt 2022 · A	22	40→50	35→30	44→50	38	193/232/253	60	274	3	8	30%	5%	36	-3.4	236/279/307	71	306	4	9	23%	5%	66	-1.1	248/290/313	65	315	4	10	21%	5%	69	-0.6
✕Rafael P Valera 2017 · A	22	48	36→30	44→55	46	221/290/298	77	312	2	6	28%	8%	69	-0.9	207/269/296	89	315	5	6	33%	7%	61	-1.5	166/231/236	69	265	3	2	36%	5%	32	-1.0
✕Victor Duarte 2023 · A	22	42	41→30	48→45	37	198/265/297	99	310	9	5	37%	6%	60	-1.6	198/267/273	75	277	5	8	28%	7%	55	-1.9	182/251/245	63	250	5	11	28%	7%	41	-0.8
✕Claudio Finol 2022 · A	22	40	38→30	46→45	41	195/255/280	85	272	5	6	29%	6%	52	-2.2	197/255/281	84	276	6	9	29%	6%	52	-2.2	202/270/282	80	285	9	12	31%	7%	57	-0.4

Kendry Chirinos

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps