Jorge Polanco

2B New York Mets

Age 34 S/R 6'0" / 208 lbs MLB H -5% Svc 10.140 · Ctrl thru 2027 ILInjured 60-Day (D60)

Overview

MLBIL-6040-MANExtFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	31	MLBSEA	469	.213/.298/.355	16	4	85	-0.4
2025	32	MLBSEA	524	.265/.329/.495	26	6	129	2.9
2026	33	AAANYM	27	.091/.259/.364	2	0	13	—	.042/.148/.167
2026	33	MLBNYM	145	.148/.201/.230	2	0	23	-1.4
2027PROJ	34	MLBNYM	123	.241/.308/.424	5	1	109	0.3
2028PROJ	35	MLBNYM	167	.230/.295/.399	6	1	98	-0.3

Last 3 seasons WAR 1.1 · Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service10.140First FA2028Options5

2027Ext$20M

Skills · percentileStatcast 2024-2026

xwOBA56

Barrel%55

Avg EV50

Bat Spd33

Speed22

CompsAsdrúbal Cabrera (age 34) · Stephen Vogt (age 35) · Fernando Tatis (age 34)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 109109vR 109

AVG/OBP/SLG.241 / .308 / .424

PA123

HR5

K%20

BB%8

BABIP268

ISO180

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

350.239

POWER

Barrel%

558.9

Avg EV

5089.2

Bat Spd

3369.5

SPEED

Sprint

2226.1

Platoon Splits2024-2026 · 1037 PA

vs LHP

vs RHP

Edge

244

793

—

wRC+

113

103

◀L

wOBA

335

320

◀L

ISO

180

188

▶R

BABIP

312

257

◀◀L

19.7%

22.4%

◀L

BB%

5.3%

9.5%

▶▶R

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

Status FA

MLB Debut 2016

Service 10.140 yrs.days

Team Control Through 2027

First FA Year 2028

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$20M	+0.4	$2M	-$18M
Totals		$20M		$2M	-$18M

Options · projected decision
2028	MUTUAL OPT	$20.0M / $0.0M buyout	DECLINE
2029	MUTUAL OPT	$8.0M / $0.0M buyout	DECLINE
2030	PLAYER OPT	$8.0M / $0.0M buyout	EXERCISE
2031	CLUB OPT	$25.0M / $0.0M buyout	DECLINE
2032	CLUB OPT	$10.5M / $1.0M buyout	DECLINE

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)
2010	17	ROK	GCL Twins	—	187	163	38	7	0	1	18	18	0	3	7	233	309	294	604	61	250	10	10	272	33	—	—	—	—	—	—
2011	18	ROK	GCL Twins	—	193	172	43	8	3	1	15	24	3	6	4	250	321	349	670	99	284	12	8	300	38	—	—	—	—	—	—
2012	19	ROK	Elizabethton Twins	—	204	173	55	15	2	5	20	26	3	6	3	318	398	514	912	197	340	13	10	387	87	—	—	—	—	—	—
2013	20	A	Cedar Rapids Kernels	—	523	465	143	32	10	5	42	59	3	4	4	308	369	452	820	144	336	11	8	356	102	—	—	—	—	—	—
2013	20	INTL	Leones del Escogido	—	208	180	53	9	2	1	21	29	0	4	2	294	368	383	751	89	338	14	10	330	109	—	—	—	—	—	—
2014	21	AA	New Britain Rock Cats	—	157	146	41	6	0	1	9	28	0	7	3	281	323	342	665	62	342	18	6	298	70	—	—	—	—	—	—
2014	21	A+	Fort Myers Miracle	—	432	378	110	17	6	6	46	60	1	10	8	291	369	415	785	124	327	14	11	348	87	—	—	—	—	—	—
2014	21	INTL	Leones del Escogido	—	102	89	29	4	3	1	12	15	1	3	0	326	412	472	884	146	384	15	12	394	153	—	—	—	—	—	—
2015	22	AAA	Rochester Red Wings	—	94	88	25	6	0	0	4	10	0	1	0	284	315	352	667	68	312	11	4	295	73	—	—	—	—	—	—
2015	22	AA	Chattanooga Lookouts	—	431	394	114	17	3	6	35	63	0	18	10	289	347	393	741	104	330	15	8	332	80	—	—	—	—	—	—
2015	22	INTL	Leones del Escogido	—	151	129	30	1	3	1	18	31	0	0	2	233	327	310	637	78	290	21	12	287	81	—	—	—	—	—	—
2016	23	MLB	Minnesota Twins	—	270	245	69	15	4	4	17	46	3	4	3	282	336	424	760	143	328	17	6	332	111	+4	-0	-3	+7	+6	1.4
2016	23	AAA	Rochester Red Wings	—	325	293	81	14	6	9	27	51	1	5	4	276	340	457	797	181	304	16	8	348	92	—	—	—	—	—	—
2016	23	INTL	Leones del Escogido	—	103	89	21	1	2	1	11	19	0	2	0	236	320	326	646	90	286	18	11	288	81	—	—	—	—	—	—
2017	24	MLB	Minnesota Twins	—	544	488	125	30	3	13	41	78	2	13	5	256	316	410	726	154	278	14	8	316	99	-1	+1	+3	+6	+12	2.1
2018	25	MLB	Minnesota Twins	—	333	302	87	18	3	6	25	62	2	7	7	288	347	427	774	139	345	19	8	341	117	+7	-1	-1	+4	+7	1.5
2018	25	AAA	Rochester Red Wings	—	15	13	6	0	1	0	2	2	0	0	0	462	533	615	1.149	154	545	13	13	502	181	—	—	—	—	—	—
2019	26	MLB	Minnesota Twins	—	704	631	186	40	7	22	60	116	4	4	3	295	360	485	845	190	328	16	9	368	134	+28	-0	-13	+8	+15	3.9
2020	27	MLB	Minnesota Twins	—	226	209	54	8	0	4	13	35	1	4	2	258	305	354	659	96	292	15	6	294	85	-4	+0	+2	+2	+5	0.5
2021	28	MLB	Minnesota Twins	—	644	588	158	35	2	33	45	118	5	11	6	269	326	503	829	235	282	18	7	360	129	+22	-0	-2	+2	+14	3.7
2022	29	MLB	Minnesota Twins	—	445	375	88	16	0	16	64	95	2	3	3	235	349	405	755	171	269	21	14	339	114	+7	-1	-6	+2	+10	1.2
2023	30	MLB	Minnesota Twins	—	343	302	77	18	0	14	36	88	2	4	0	255	338	454	792	199	310	26	10	349	122	+9	+1	-3	+1	+7	1.5
2023	30	AAA	St. Paul Saints	—	38	32	9	1	0	1	5	10	1	0	0	281	395	406	801	125	381	26	13	366	74	—	—	—	—	—	—
2023	30	A	Fort Myers Mighty Mussels	—	22	18	5	1	0	0	3	6	0	0	0	278	381	333	714	56	385	27	14	318	59	—	—	—	—	—	—
2024	31	MLB	Seattle Mariners	—	469	417	89	11	0	16	46	137	4	4	2	213	298	355	653	141	274	29	10	295	85	-8	+0	-7	+2	+10	-0.4
2024	31	AAA	Tacoma Rainiers	—	19	15	5	1	0	3	4	4	0	0	0	333	474	1.000	1.474	667	250	21	21	591	150	—	—	—	—	—	—
2025	32	MLB	Seattle Mariners	—	524	471	125	30	0	26	42	82	3	6	3	265	329	495	824	229	269	16	8	356	129	+18	+0	-3	+2	+11	2.9
2026	33	MLB	New York Mets	—	145	135	20	5	0	2	9	36	0	0	0	148	201	230	431	81	186	25	6	197	23	-13	+0	-0	-3	+3	-1.4
2026	33	AAA	Syracuse Mets	—	27	22	2	0	0	2	5	2	0	0	0	91	259	364	623	273		7	19	283	13	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4647	4163	1078	226	19	156	398	893	28	60	34	259	328	435	763	176	293	19	9	335	113	+71	-2	-34	+33	+101	17.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2010	17	ROK MLE	GCL Twins	—	187	169	32	5	0	1	12	26	0	3	7	189	243	237	480	47	209	14	6	217	33	—	—	—	—	—	—
2011	18	ROK MLE	GCL Twins	—	193	178	35	6	2	1	9	35	3	6	4	197	247	270	517	73	229	18	5	224	38	—	—	—	—	—	—
2012	19	ROK MLE	Elizabethton Twins	—	204	180	44	11	1	4	13	37	3	6	3	244	306	383	689	139	262	18	6	297	87	—	—	—	—	—	—
2013	20	A MLE	Cedar Rapids Kernels	—	523	480	139	28	9	4	27	84	3	4	4	290	331	410	742	121	325	16	5	319	102	—	—	—	—	—	—
2014	21	AA MLE	New Britain Rock Cats	—	157	149	41	5	0	1	6	35	0	7	3	275	303	329	632	54	344	22	4	272	70	—	—	—	—	—	—
2014	21	A+ MLE	Fort Myers Miracle	—	432	390	98	16	5	5	34	85	1	10	8	251	313	356	669	105	298	20	8	297	87	—	—	—	—	—	—
2015	22	AAA MLE	Rochester Red Wings	—	94	89	24	5	0	0	3	12	0	1	0	270	293	326	619	56	299	13	3	276	73	—	—	—	—	—	—
2015	22	AA MLE	Chattanooga Lookouts	—	431	406	108	16	3	4	23	78	0	18	10	266	305	350	655	84	315	18	5	286	80	—	—	—	—	—	—
2016	23	MLB MLE	Minnesota Twins	—	270	245	69	15	4	4	17	46	3	4	3	282	336	424	760	143	328	17	6	332	111	+4	-0	-3	+7	+6	1.4
2016	23	AAA MLE	Rochester Red Wings	—	325	300	75	10	6	8	20	61	1	5	4	250	299	403	702	153	278	19	6	304	92	—	—	—	—	—	—
2017	24	MLB MLE	Minnesota Twins	—	544	489	125	30	3	13	40	78	2	13	5	256	315	409	723	153	278	14	7	315	99	-1	+1	+3	+6	+12	2.1
2018	25	MLB MLE	Minnesota Twins	—	333	302	87	18	3	6	25	62	2	7	7	288	347	427	774	139	345	19	8	341	117	+7	-1	-1	+4	+7	1.5
2018	25	AAA MLE	Rochester Red Wings	—	15	14	6	0	1	0	1	2	0	0	0	429	467	571	1.038	143	506	13	7	436	181	—	—	—	—	—	—
2019	26	MLB MLE	Minnesota Twins	—	704	633	186	40	7	22	58	116	4	4	3	294	357	483	840	190	328	16	8	366	134	+28	-0	-13	+8	+15	3.9
2020	27	MLB MLE	Minnesota Twins	—	226	209	54	8	0	4	13	35	1	4	2	258	305	354	659	96	292	15	6	294	85	-4	+0	+2	+2	+5	0.5
2021	28	MLB MLE	Minnesota Twins	—	644	588	158	35	2	33	45	118	5	11	6	269	326	503	829	235	282	18	7	359	129	+22	-0	-2	+2	+14	3.7
2022	29	MLB MLE	Minnesota Twins	—	445	376	88	16	0	16	63	95	2	3	3	234	347	404	751	170	269	21	14	337	114	+7	-1	-6	+2	+10	1.2
2023	30	MLB MLE	Minnesota Twins	—	343	302	77	18	0	14	36	88	2	4	0	255	338	454	792	199	310	26	10	348	122	+9	+1	-3	+1	+7	1.5
2023	30	AAA MLE	St. Paul Saints	—	38	34	8	1	0	1	3	12	1	0	0	235	316	353	669	118	336	32	8	278	74	—	—	—	—	—	—
2023	30	A MLE	Fort Myers Mighty Mussels	—	22	19	5	1	0	0	2	8	0	0	0	263	333	316	649	53	340	36	9	255	59	—	—	—	—	—	—
2024	31	MLB MLE	Seattle Mariners	—	469	420	89	11	0	16	43	137	4	4	2	212	291	352	644	140	274	29	9	294	85	-8	+0	-7	+2	+10	-0.4
2024	31	AAA MLE	Tacoma Rainiers	—	19	16	4	1	0	2	3	5	0	0	0	250	368	688	1.056	438	181	26	16	390	150	—	—	—	—	—	—
2025	32	MLB MLE	Seattle Mariners	—	524	472	126	30	0	27	41	82	3	6	3	267	329	502	832	235	269	16	8	359	129	+18	+0	-3	+2	+11	2.9
2026	33	MLB MLE	New York Mets	—	145	135	20	5	0	2	9	36	0	0	0	148	201	230	431	81	186	25	6	202	23	-13	+0	-0	-3	+3	-1.4
2026	33	AAA MLE	Syracuse Mets	—	27	24	1	0	0	1	3	2	0	0	0	42	148	167	315	125		7	11	188	13	—	—	—	—	—	—
2010	17	ROK MLE	GCL Twins	—	187	169	32	5	0	1	12	26	0	3	7	189	243	237	480	47	212	14	6	217	33	—	—	—	—	—	—
2010	17	ROK RAW	GCL Twins	—	187	163	38	7	0	1	18	18	0	3	7	233	309	294	604	61	250	10	10	272	33	—	—	—	—	—	—
2011	18	ROK MLE	GCL Twins	—	193	178	35	6	2	1	9	35	3	6	4	197	247	270	517	73	238	18	5	224	38	—	—	—	—	—	—
2011	18	ROK RAW	GCL Twins	—	193	172	43	8	3	1	15	24	3	6	4	250	321	349	670	99	284	12	8	300	38	—	—	—	—	—	—
2012	19	ROK MLE	Elizabethton Twins	—	204	180	44	11	1	4	13	37	3	6	3	244	306	383	689	139	278	18	6	297	87	—	—	—	—	—	—
2012	19	ROK RAW	Elizabethton Twins	—	204	173	55	15	2	5	20	26	3	6	3	318	398	514	912	197	340	13	10	387	87	—	—	—	—	—	—
2013	20	A MLE	2 teams	—	731	671	194	39	13	5	37	118	3	8	6	289	329	408	737	119	336	16	5	319	102	—	—	—	—	—	—
2013	20	A RAW	2 teams	—	731	645	196	41	12	6	63	88	3	8	6	304	368	433	801	129	336	12	9	348	102	—	—	—	—	—	—
2014	21	A+ MLE	3 teams	—	691	633	163	25	6	7	47	140	2	20	11	258	311	349	660	92	317	20	7	290	83	—	—	—	—	—	—
2014	21	A+ RAW	3 teams	—	691	613	180	27	9	8	67	103	2	20	11	294	365	406	771	113	339	15	10	343	83	—	—	—	—	—	—
2015	22	AA MLE	3 teams	—	676	634	169	27	3	5	34	115	0	19	12	267	304	342	646	76	315	17	5	284	78	—	—	—	—	—	—
2015	22	AA RAW	3 teams	—	676	611	169	24	6	7	57	104	0	19	12	277	338	370	708	93	320	15	8	317	78	—	—	—	—	—	—
2016	23	AAA MLE	3 teams	—	698	639	170	29	12	15	43	125	4	11	7	266	316	419	736	153	306	18	6	317	101	—	—	—	—	—	—
2016	23	AAA RAW	3 teams	—	698	627	171	30	12	14	55	116	4	11	7	273	335	426	761	153	311	17	8	333	101	—	—	—	—	—	—
2017	24	MLB MLE	Minnesota Twins	—	544	489	125	30	3	13	40	78	2	13	5	256	315	409	723	153	277	14	7	315	99	-1	+1	+3	+6	+12	2.1
2017	24	MLB RAW	Minnesota Twins	—	544	488	125	30	3	13	41	78	2	13	5	256	316	410	726	154	278	14	8	316	99	-1	+1	+3	+6	+12	2.1
2018	25	MLB MLE	2 teams	—	348	316	93	18	4	6	26	64	2	7	7	294	352	434	785	139	352	18	7	345	120	+8	-1	-1	+4	+8	1.7
2018	25	MLB RAW	2 teams	—	348	315	93	18	4	6	27	64	2	7	7	295	355	435	790	140	354	18	8	348	120	+8	-1	-1	+4	+8	1.7
2019	26	MLB MLE	Minnesota Twins	—	704	633	186	40	7	22	58	116	4	4	3	294	357	483	840	190	327	16	8	366	134	+28	-0	-13	+8	+15	3.9
2019	26	MLB RAW	Minnesota Twins	—	704	631	186	40	7	22	60	116	4	4	3	295	360	485	845	190	328	16	9	368	134	+28	-0	-13	+8	+15	3.9
2020	27	MLB MLE	Minnesota Twins	—	226	209	54	8	0	4	13	35	1	4	2	258	305	354	659	96	292	15	6	294	85	-4	+0	+2	+2	+5	0.5
2020	27	MLB RAW	Minnesota Twins	—	226	209	54	8	0	4	13	35	1	4	2	258	305	354	659	96	292	15	6	294	85	-4	+0	+2	+2	+5	0.5
2021	28	MLB MLE	Minnesota Twins	—	644	588	158	35	2	33	45	118	5	11	6	269	326	503	829	235	282	18	7	359	129	+22	-0	-2	+2	+14	3.7
2021	28	MLB RAW	Minnesota Twins	—	644	588	158	35	2	33	45	118	5	11	6	269	326	503	829	235	282	18	7	360	129	+22	-0	-2	+2	+14	3.7
2022	29	MLB MLE	Minnesota Twins	—	445	376	88	16	0	16	63	95	2	3	3	234	347	404	751	170	268	21	14	337	114	+7	-1	-6	+2	+10	1.2
2022	29	MLB RAW	Minnesota Twins	—	445	375	88	16	0	16	64	95	2	3	3	235	349	405	755	171	269	21	14	339	114	+7	-1	-6	+2	+10	1.2
2023	30	MLB MLE	3 teams	—	403	355	89	19	0	15	41	109	3	4	0	251	333	431	764	180	315	27	10	336	114	+7	+1	-3	+1	+9	1.4
2023	30	MLB RAW	3 teams	—	403	352	91	20	0	15	44	104	3	4	0	259	346	443	789	185	321	26	11	349	114	+7	+1	-3	+1	+9	1.4
2024	31	MLB MLE	2 teams	—	488	436	93	12	0	18	46	142	4	4	2	213	294	365	659	151	270	29	9	298	88	-7	+0	-7	+2	+11	-0.2
2024	31	MLB RAW	2 teams	—	488	432	94	12	0	19	50	141	4	4	2	218	305	377	682	160	274	29	10	307	88	-7	+0	-7	+2	+11	-0.2
2025	32	MLB MLE	Seattle Mariners	—	524	472	126	30	0	27	41	82	3	6	3	267	329	502	832	235	269	16	8	359	129	+18	+0	-3	+2	+11	2.9
2025	32	MLB RAW	Seattle Mariners	—	524	471	125	30	0	26	42	82	3	6	3	265	329	495	824	229	269	16	8	356	129	+18	+0	-3	+2	+11	2.9
2026	33	MLB MLE	2 teams	—	172	159	21	5	0	3	12	38	0	0	0	132	193	220	413	88	153	22	7	200	22	-16	+0	-0	-3	+4	-1.6
2026	33	MLB RAW	2 teams	—	172	157	22	5	0	4	14	38	0	0	0	140	211	248	459	108	157	22	8	211	22	-16	+0	-0	-3	+4	-1.6
2010	17	ROK MLE	GCL Twins	—	187	173	32	5	0	1	12	26	0	3	7	185	243	231	474	46	209	14	6	217	33	—	—	—	—	—	—
2011	18	ROK MLE	GCL Twins	—	193	179	35	6	2	1	9	35	3	6	4	196	247	268	516	73	229	18	5	224	38	—	—	—	—	—	—
2012	19	ROK MLE	Elizabethton Twins	—	204	186	44	11	1	4	13	37	3	6	3	237	306	371	677	134	262	18	6	297	87	—	—	—	—	—	—
2013	20	A MLE	2 teams	—	731	685	194	39	13	5	37	118	3	8	6	283	329	400	729	117	325	16	5	319	102	—	—	—	—	—	—
2014	21	A+ MLE	3 teams	—	691	637	163	25	6	7	47	140	2	20	11	256	311	347	658	91	310	20	7	290	83	—	—	—	—	—	—
2015	22	AA MLE	3 teams	—	676	637	169	27	3	5	34	115	0	19	12	265	304	341	645	75	312	17	5	284	78	—	—	—	—	—	—
2016	23	AAA MLE	3 teams	—	698	646	170	29	12	15	43	125	4	11	7	263	316	415	731	152	301	18	6	317	101	—	—	—	—	—	—
2017	24	MLB MLE	Minnesota Twins	—	544	497	125	30	3	13	40	78	2	13	5	252	315	402	717	151	278	14	7	315	99	—	—	—	—	—	—
2018	25	MLB MLE	2 teams	—	348	317	93	18	4	6	26	64	2	7	7	293	352	432	784	139	352	18	7	345	120	—	—	—	—	—	—
2019	26	MLB MLE	Minnesota Twins	—	704	636	186	40	7	22	58	116	4	4	3	292	357	481	838	189	328	16	8	366	134	—	—	—	—	—	—
2020	27	MLB MLE	Minnesota Twins	—	226	210	54	8	0	4	13	35	1	4	2	257	305	352	657	95	292	15	6	294	85	—	—	—	—	—	—
2021	28	MLB MLE	Minnesota Twins	—	644	589	158	35	2	33	45	118	5	11	6	268	326	503	829	234	282	18	7	359	129	—	—	—	—	—	—
2022	29	MLB MLE	Minnesota Twins	—	445	377	88	16	0	16	63	95	2	3	3	233	347	403	750	170	269	21	14	337	114	—	—	—	—	—	—
2023	30	MLB MLE	3 teams	—	403	356	89	19	0	15	41	109	3	4	0	250	333	430	763	180	314	27	10	336	114	—	—	—	—	—	—
2024	31	MLB MLE	2 teams	—	488	435	93	12	0	18	46	142	4	4	2	214	294	366	660	152	271	29	9	298	88	—	—	—	—	—	—
2025	32	MLB MLE	Seattle Mariners	—	524	475	126	30	0	27	41	82	3	6	3	265	329	499	828	234	269	16	8	359	129	—	—	—	—	—	—
2026	33	MLB MLE	2 teams	—	172	158	21	5	0	3	12	38	0	0	0	133	193	222	415	89	156	22	7	200	22	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	31	MLB MLE	2 teams	—	488	435	93	12	0	18	46	142	4	4	2	214	294	366	660	152	271	29	9	298	88	—	—	—	—	—	—
2025	32	MLB MLE	Seattle Mariners	—	524	475	126	30	0	27	41	82	3	6	3	265	329	499	828	234	269	16	8	359	129	—	—	—	—	—	—
2026	33	MLB MLE	2 teams	—	172	158	21	5	0	3	12	38	0	0	0	133	193	222	415	89	156	22	7	200	22	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	34	MLB MLE	NYM	100%	296	268	66	14	0	12	24	61	2	3	1	248	315	435	749	186	277	21	8	330	109	+3	+0	-3	+1	+6	0.4
▸ 2027 — real world (MLB)
2027	34	MLB CTX	NYM	100%	123	111	26	5	0	5	10	25	1	1	0	241	308	424	733	183	268	20	8	323	109	+1	+0	-1	+0	+3	0.3
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	35	MLB MLE	NYM	100%	167	151	35	7	0	6	13	36	1	1	0	236	301	408	710	172	267	22	8	314	98	-0	+0	-8	+1	+4	-0.3
2028	35	MLB CTX	NYM	100%	167	151	35	7	0	6	13	36	1	1	0	230	295	399	694	169	258	22	8	307	98	-0	+0	-8	+1	+4	-0.3
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	4814	4314	1113	233	19	162	411	929	29	61	34	258	327	433	760	175	292	19	9	334	100	+71	-1	-42	+33	+104	16.9
/ 162G	—	A+C		—	650	582	150	31	3	22	55	125	4	8	5	258	326	435	760	177	291	19	8	334	100	+10	-0	-6	+5	+14	2.3
Career	—	MLE		—	8168	7399	1903	368	53	206	603	1534	43	131	81	257	317	405	722	148	296	19	7	316	100	+72	-1	-43	+34	+107	17.2
/ 162G	—	MLE		—	650	589	151	29	4	16	48	122	3	10	6	256	316	401	716	144	295	19	7	316	100	+9	-0	-6	+4	+14	2.3

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 AAASyracuse Mets · 27 PAwOBA .276 → .188 (−89)K% 7.4% → 8.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	7.41%	÷1.000	×1.200	—	—	8.89%
BB% (unintentional) /PA	18.52%	÷1.000	×0.690	—	×0.942	12.04%
HBP% /PA	0.00%	—	×0.940	—	×0.942	0.00%
Singles /BIP	0.00%	÷1.000	×0.930	—	×0.942	0.00%
Doubles /BIP	0.00%	÷1.000	×0.830	—	×0.942	0.00%
Triples /BIP	0.00%	÷1.000	×0.970	—	×0.942	0.00%
Home runs /BIP	10.00%	÷1.000	×0.700	—	×0.942	6.59%

Factors used: league row International League. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 33 vs a level average of 27.2 → −5.8% on BB/HBP/hit rates (5.8 yr older than average).

Result: wOBA .276 → .188; ISO .273 → .192; 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).

2024 AAATacoma Rainiers · 19 PAwOBA .574 → .390 (−184)K% 21.1% → 25.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.05%	÷1.004	×1.200	—	—	25.17%
BB% (unintentional) /PA	21.05%	÷1.011	×0.690	—	×0.962	13.83%
HBP% /PA	0.00%	—	×0.940	—	×0.962	0.00%
Singles /BIP	9.09%	÷1.010	×0.930	—	×0.962	8.05%
Doubles /BIP	9.09%	÷1.014	×0.830	—	×0.962	7.15%
Triples /BIP	0.00%	÷0.900	×0.970	—	×0.962	0.00%
Home runs /BIP	27.27%	÷1.142	×0.700	—	×0.962	16.08%

Factors used: league row International League. Park (home-season share, regressed): HR 128, 1B 102, 2B 103, 3B 80, K 101, BB 102 — applied at half strength. Age: age 31 vs a level average of 27.2 → −3.8% on BB/HBP/hit rates (3.8 yr older than average).

Result: wOBA .574 → .390; ISO .667 → .428; BABIP .250 → .181. 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 AAASt. Paul Saints · 38 PAwOBA .357 → .278 (−79)K% 26.3% → 32.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.32%	÷0.973	×1.200	—	—	32.44%
BB% (unintentional) /PA	13.16%	÷1.067	×0.690	—	×0.972	8.27%
HBP% /PA	2.63%	—	×0.940	—	×0.972	2.40%
Singles /BIP	31.82%	÷0.964	×0.930	—	×0.972	29.83%
Doubles /BIP	4.55%	÷1.341	×0.830	—	×0.972	2.74%
Triples /BIP	0.00%	÷0.977	×0.970	—	×0.972	0.00%
Home runs /BIP	4.55%	÷1.009	×0.700	—	×0.972	3.07%

Factors used: league row International League. Park (home-season share, regressed): HR 102, 1B 93, 2B 168, 3B 95, K 95, BB 113 — applied at half strength. Age: age 30 vs a level average of 27.2 → −2.8% on BB/HBP/hit rates (2.8 yr older than average).

Result: wOBA .357 → .278; ISO .125 → .081; BABIP .381 → .336. 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 AFort Myers Mighty Mussels · 22 PAwOBA .325 → .255 (−71)K% 27.3% → 38.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.27%	÷0.969	×1.360	—	—	38.28%
BB% (unintentional) /PA	13.64%	÷1.050	×0.690	—	×0.940	8.42%
HBP% /PA	0.00%	—	×0.780	—	×0.940	0.00%
Singles /BIP	33.33%	÷0.938	×0.920	—	×0.940	30.72%
Doubles /BIP	8.33%	÷1.053	×0.830	—	×0.940	6.17%
Triples /BIP	0.00%	÷0.900	×0.910	—	×0.940	0.00%
Home runs /BIP	0.00%	÷0.976	×0.800	—	×0.940	0.00%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 95, 1B 88, 2B 111, 3B 80, K 94, BB 110 — applied at half strength. Age: age 30 vs a level average of 22.0 → −6.0% on BB/HBP/hit rates (8.0 yr older than average).

Result: wOBA .325 → .255; ISO .056 → .040; BABIP .385 → .340. 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).

2018 AAARochester Red Wings · 15 PAwOBA .490 → .436 (−54)K% 13.3% → 16.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.33%	÷0.978	×1.200	—	—	16.36%
BB% (unintentional) /PA	13.33%	÷1.008	×0.690	—	×1.033	9.42%
HBP% /PA	0.00%	—	×0.940	—	×1.033	0.00%
Singles /BIP	45.45%	÷1.023	×0.930	—	×1.033	42.68%
Doubles /BIP	0.00%	÷1.009	×0.830	—	×1.033	0.00%
Triples /BIP	9.09%	÷1.150	×0.970	—	×1.033	7.92%
Home runs /BIP	0.00%	÷0.879	×0.840	—	×1.033	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 76, 1B 105, 2B 102, 3B 130, K 96, BB 102 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average).

Result: wOBA .490 → .436; ISO .154 → .136; BABIP .545 → .506. 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).

2016 AAARochester Red Wings · 325 PAwOBA .342 → .304 (−38)K% 15.7% → 18.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.69%	÷1.007	×1.200	—	—	18.69%
BB% (unintentional) /PA	8.00%	÷0.968	×0.690	—	×1.050	5.99%
HBP% /PA	0.31%	—	×0.940	—	×1.050	0.30%
Singles /BIP	21.49%	÷0.953	×0.930	×0.950	×1.050	20.93%
Doubles /BIP	5.79%	÷1.224	×0.830	×0.950	×1.050	3.91%
Triples /BIP	2.48%	÷0.971	×0.970	×0.950	×1.050	2.47%
Home runs /BIP	3.72%	÷0.951	×0.840	—	×1.050	3.45%

Factors used: league row IL. Park (home-season share, regressed): HR 90, 1B 90, 2B 145, 3B 94, K 101, BB 94 — applied at half strength. Age: age 23 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (4.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .342 → .304; ISO .181 → .160; BABIP .304 → .278. 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).

2015 AAChattanooga Lookouts · 431 PAwOBA .325 → .286 (−39)K% 14.6% → 18.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.62%	÷0.988	×1.220	—	—	18.04%
BB% (unintentional) /PA	8.12%	÷1.059	×0.680	—	×1.042	5.43%
HBP% /PA	0.00%	—	×0.840	—	×1.042	0.00%
Singles /BIP	26.59%	÷0.980	×0.920	×0.987	×1.042	25.67%
Doubles /BIP	5.14%	÷0.999	×0.910	×0.987	×1.042	4.81%
Triples /BIP	0.91%	÷1.020	×0.880	×0.987	×1.042	0.80%
Home runs /BIP	1.81%	÷1.232	×0.800	—	×1.042	1.23%

Factors used: league row SL. Park (home-season share, regressed): HR 146, 1B 96, 2B 100, 3B 104, K 98, BB 112 — applied at half strength. Age: age 22 vs a level average of 24.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.987.

Result: wOBA .325 → .286; ISO .104 → .085; BABIP .330 → .315. 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).

2015 AAARochester Red Wings · 94 PAwOBA .293 → .276 (−17)K% 10.6% → 12.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.64%	÷1.030	×1.200	—	—	12.39%
BB% (unintentional) /PA	4.26%	÷0.980	×0.690	—	×1.050	3.15%
HBP% /PA	0.00%	—	×0.940	—	×1.050	0.00%
Singles /BIP	24.36%	÷0.979	×0.930	×0.987	×1.050	23.99%
Doubles /BIP	7.69%	÷0.987	×0.830	×0.987	×1.050	6.70%
Triples /BIP	0.00%	÷0.932	×0.970	×0.987	×1.050	0.00%
Home runs /BIP	0.00%	÷0.956	×0.840	—	×1.050	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 91, 1B 96, 2B 97, 3B 86, K 106, BB 96 — applied at half strength. Age: age 22 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (5.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.987.

Result: wOBA .293 → .276; ISO .068 → .060; BABIP .312 → .299. 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).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Pablo Sandovallast yr '21 career totals — 13 seasons, 5,045 PA	7.6	5,045	153	12	278	330	444	+11	+1	24.9	24.6
/162	664	20	2	+1.4	+0.1	3.3	pk7: 24
#2Rickie Weeks Jr.last yr '17 career totals — 13 seasons, 5,098 PA	7.7	5,098	161	132	246	344	420	+12	-40	23.3	22.4
/162	664	21	17	+1.5	-5.2	3.0	pk7: 22
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 13 projected seasons	7.5	4,951	168	62	258	322	434	+18	-25	22.5	21.5
/162	664	22	8	+2.4	-3.3	3.0	pk7: 20
#3Kelly Johnsonlast yr '16 career totals — 11 seasons, 5,139 PA	7.7	5,139	155	87	251	330	422	+8	-3	22.3	21.3
/162	664	20	11	+1.0	-0.4	2.9	pk7: 20
#4Davey Johnson'65-'78 * career totals — 12 seasons, 5,465 PA	8.2	5,465	136	33	267*	345*	449*	+10	-28	22.8	20.8
/162	664	17	4	+1.3	-3.5	2.8	pk7: 19
#5Rich Aurilia'95-'09 * career totals — 14 seasons, 6,278 PA	9.5	6,278	186	23	264*	315*	419*	+35	-46	18.9	19.7
/162	664	20	2	+3.7	-4.8	2.0	pk7: 20
#6Ronnie Belliard'98-'10 * career totals — 12 seasons, 5,641 PA	8.5	5,641	114	43	262*	325*	401*	+14	-15	15.9	15.7
/162	664	13	5	+1.7	-1.7	1.9	pk7: 16

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
Jorge Polanco (OGILVIE)	34	—	—	—	—	246/312/431	185	277	5	1	21%	8%	109	+0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Asdrúbal Cabrera 2020 · MLB	34	51→61	53→60	48→50	52	262/331/440	178	297	20	4	19%	9%	117	+2.6	242/317/408	166	286	17	4	21%	9%	105	+1.7	231/308/390	159	275	15	1	21%	10%	97	+0.5
✕Stephen Vogt 2020 · MLB	35	47→57	56→60	47→40	49	246/306/449	203	282	22	6	22%	8%	110	+2.1	216/287/381	165	257	19	5	23%	9%	88	+0.4	179/259/328	149	204	20	1	24%	9%	66	-0.4
✕Fernando Tatis 2009 · MLB	34	47→52	52→55	47→45	48	241/305/410	169	278	20	7	21%	8%	101	+1.4	250/310/410	160	287	17	7	19%	7%	103	+1.5	273/327/425	151	304	13	6	14%	5%	113	+1.4
✕Dexter Fowler 2020 · MLB	34	45→55	53→55	45→55	57	231/330/403	172	275	20	9	24%	12%	109	+2.0	243/327/399	156	303	19	10	25%	10%	107	+1.8	236/319/400	165	293	26	6	28%	10%	106	+0.3
✕Jason Kipnis 2021 · MLB	34	46→56	50→55	49→55	52	234/308/394	160	270	18	8	21%	9%	99	+1.2	234/309/390	156	295	18	7	26%	8%	98	+1.2	215/293/362	147	274	17	2	27%	8%	83	+0.0
✕Dioner Navarro 2016 · MLB	32	52→61	49→50	47→45	51	262/315/401	140	284	17	4	15%	7%	102	+1.5	227/287/357	130	268	14	5	20%	7%	82	-0.0	195/261/292	97	238	9	1	21%	8%	57	-0.7
✕Jorge Cantu 2016 · AAA	34	51→58	55	48→40	47	264/320/449	185	285	23	6	18%	6%	116	+2.5	226/282/349	123	273	13	6	22%	6%	78	-0.3	201/259/306	105	251	12	3	24%	6%	59	-0.9
✕Eduardo Escobar 2023 · MLB	34	47→57	55→60	43→50	47	246/301/439	193	282	23	2	22%	7%	106	+1.8	237/290/391	154	292	17	6	24%	7%	91	+0.6	224/269/341	117	286	11	4	25%	6%	71	-0.4
✕Yan Gomes 2021 · MLB	34	48→53	53→55	50→40	46	247/308/419	172	293	20	5	23%	7%	104	+1.6	249/294/408	159	282	20	4	19%	5%	97	+1.1	249/292/399	150	282	19	2	19%	4%	94	+0.6
✕Rickie Weeks Jr. 2017 · MLB	34	47→57	53→55	50→55	50	240/324/415	175	297	21	10	26%	9%	109	+2.0	235/321/397	162	339	18	10	33%	10%	104	+1.6	205/311/338	133	377	13	5	43%	11%	88	+0.1
✕Yadiel Hernandez 2022 · MLB	34	49→54	53→55	46→45	46	254/308/422	168	300	23	7	24%	7%	105	+1.7	249/297/389	140	311	16	7	24%	6%	93	+0.8	266/311/405	139	325	16	4	23%	6%	103	+0.8
✕Ryan Doumit 2014 · MLB	33	51→61	50→55	46→45	48	256/311/417	161	289	18	2	18%	7%	105	+1.7	235/289/386	151	285	18	6	24%	7%	89	+0.5	196/230/322	126	247	20	4	30%	4%	53	-0.6
✕Abraham Almonte 2023 · MLB	34	47→55	51→55	46→55	55	239/329/403	164	293	19	10	25%	11%	108	+1.9	216/298/373	157	285	20	10	30%	10%	90	+0.6	153/248/296	143	191	23	6	34%	11%	54	-0.8
✕Ramon Castro 2010 · MLB	34	45	58→55	46→40	49	244/306/444	200	273	27	4	22%	8%	109	+2.0	247/311/445	198	288	27	6	24%	8%	112	+2.2	252/309/461	209	269	36	4	22%	8%	115	+0.6
✕Nick Hundley 2019 · MLB	35	48→45	52→55	46→40	42	245/290/418	172	303	20	4	26%	6%	97	+1.1	226/277/380	154	301	18	7	30%	6%	84	+0.1	161/196/283	123	228	14	0	36%	3%	31	-0.8
✕Zack Cozart 2019 · MLB	33	50→56	53→60	52→50	55	256/333/443	186	279	19	4	16%	9%	118	+2.7	219/290/349	130	248	13	6	17%	8%	82	-0.0	121/178/142	21	144	0	0	15%	5%	-8	-1.2
✕Jose Lobatón 2019 · MLB	34	44	48→45	49→30	48	225/293/367	142	275	16	5	24%	8%	86	+0.3	198/260/333	135	271	15	5	31%	7%	67	-1.1	158/215/279	120	214	15	1	33%	6%	34	-2.2
✕Doug Mirabelli 2005 · MLB	34	50	57→50	46→30	50	262/335/468	206	305	24	4	23%	9%	125	+3.2	234/309/410	176	301	22	5	28%	9%	103	+1.5	205/283/362	157	268	21	3	31%	8%	83	+0.0
✕Kurt Suzuki 2018 · MLB	34	51→60	53→60	46→45	48	259/315/432	173	266	21	2	13%	5%	110	+2.1	264/328/453	189	269	24	3	12%	6%	120	+2.8	263/330/444	181	268	23	1	12%	6%	119	+1.3
✕Neil Walker 2019 · MLB	33	48→57	50→55	41→45	55	246/327/401	155	280	19	2	20%	10%	107	+1.9	250/325/391	141	305	14	6	21%	10%	103	+1.6	269/349/411	142	326	13	5	20%	11%	118	+1.7

Jorge Polanco

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps