Jesse Winker

LF New York Mets

Age 33 L/L 6'2" / 206 lbs MLB H -5% Svc 10.000 · Ctrl thru 2027

Overview

MLBExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2023	29	AAA/A+MIL	108	.301/.463/.494	4	0	117	—	.252/.370/.396
2023	29	MLBMIL	197	.199/.321/.247	1	0	73	-0.5
2024	30	MLBNYM	508	.253/.362/.405	14	14	122	1.4
2025	31	MLBNYM	81	.229/.316/.400	1	1	97	0.1
2026	32	No MLB games played
2027PROJ	33	MLBNYM	169	.238/.335/.392	4	3	112	0.4
2028PROJ	34	MLBNYM	142	.226/.324/.368	3	1	102	-0.4

Last 3 seasons WAR 0.9 · Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service10.000First FA2028

2027Ext / FA-deal$3M

Skills · percentileStatcast 2023-2025

xwOBA55

Bat Spd48

Barrel%39

Avg EV38

Speed16

CompsTodd Hollandsworth (age 32) · Michael Tucker (age 34) · Ben Gamel (age 32)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 96112vR 117

AVG/OBP/SLG.238 / .335 / .392

PA169

HR4

K%21

BB%11

BABIP284

ISO144

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · ContractCON 50 / POW 45

Toolsscout grade · Statcast %ile · 2023-2025

CONTACT50

xAVG

230.229

POWER45

Barrel%

396.8

Avg EV

3888.2

Bat Spd

4871.1

EYE60

scouting grade only

SPEED40

Sprint

1625.8

Platoon Splits2024-2025 · 584 PA

vs LHP

vs RHP

Edge

104

480

—

wRC+

118

▶▶R

wOBA

307

343

▶R

ISO

101

163

▶▶R

BABIP

328

298

◀L

26.9%

20.2%

▶▶R

BB%

10.6%

12.1%

▶R

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

Status FA

MLB Debut 2017

Service 10.000 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$3M	+0.4	$2M	-$1M
Totals		$3M		$2M	-$1M

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)
2012	18	ROK	Billings Mustangs	—	275	228	77	16	3	5	40	50	4	1	2	338	445	500	945	162	414	18	15	417	96	—	—	—	—	—	—
2013	19	A	Dayton Dragons	—	486	417	117	18	5	16	63	75	4	6	1	281	380	463	843	182	308	15	13	374	91	—	—	—	—	—	—
2014	20	AA	Pensacola Blue Wahoos	—	92	77	16	5	0	2	14	22	0	0	0	208	330	351	680	143	259	24	15	310	65	—	—	—	—	—	—
2014	20	A+	Bakersfield Blaze	—	249	205	65	15	0	13	40	46	1	5	1	317	431	580	1.011	263	349	18	16	435	110	—	—	—	—	—	—
2014	20	INTL	Surprise Saguaros	—	84	68	23	4	1	3	14	17	0	1	2	338	451	559	1.010	221	400	20	17	433	179	—	—	—	—	—	—
2015	21	AA	Pensacola Blue Wahoos	—	526	443	125	24	2	13	74	83	6	8	4	282	392	433	825	151	320	16	14	371	111	—	—	—	—	—	—
2016	22	AAA	Louisville Bats	—	448	380	115	22	0	3	59	59	4	0	0	303	402	384	786	82	347	13	13	357	113	—	—	—	—	—	—
2016	22	ROK	AZL Reds	—	15	13	6	0	0	2	2	4	0	0	0	462	533	923	1.456	462	571	27	13	612	158	—	—	—	—	—	—
2017	23	MLB	Cincinnati Reds	—	137	121	36	7	0	7	15	24	0	1	1	298	375	529	904	231	322	18	11	394	146	+7	-0	-1	-5	+3	0.4
2017	23	AAA	Louisville Bats	—	347	299	94	22	0	2	38	46	5	2	4	314	401	408	809	94	359	13	11	363	97	—	—	—	—	—	—
2018	24	MLB	Cincinnati Reds	—	334	281	84	16	0	7	49	46	2	0	0	299	407	431	837	132	336	14	15	377	132	+13	+0	-6	-4	+7	1.1
2019	25	MLB	Cincinnati Reds	—	384	338	91	17	2	16	38	60	8	0	2	269	357	473	830	204	286	16	10	368	127	+13	-1	-7	-4	+8	0.9
2020	26	MLB	Cincinnati Reds	—	183	149	38	7	0	12	28	46	5	1	0	255	390	544	934	289	283	25	15	406	152	+11	+0	-1	-2	+4	1.3
2021	27	MLB	Cincinnati Reds	—	485	423	129	32	1	24	53	75	9	1	0	305	394	556	949	251	324	15	11	415	160	+35	+0	-8	-5	+11	3.3
2022	28	MLB	Seattle Mariners	—	547	456	100	15	0	14	84	103	4	0	0	219	346	344	690	125	251	19	15	318	103	+2	+0	-9	-6	+12	-0.2
2023	29	MLB	Milwaukee Brewers	—	197	166	33	5	0	1	26	51	4	0	0	199	321	247	568	48	278	26	13	274	73	-6	+0	-0	-3	+4	-0.5
2023	29	AAA	Nashville Sounds	—	93	70	20	3	0	4	23	13	0	0	3	286	462	500	962	214	302	14	25	430	119	—	—	—	—	—	—
2023	29	A+	Wisconsin Timber Rattlers	—	15	13	5	1	0	0	2	2	0	0	0	385	467	462	928	77	455	13	13	420	107	—	—	—	—	—	—
2024	30	MLB	New York Mets	—	508	430	109	23	0	14	63	106	10	14	4	253	362	405	766	151	304	21	12	345	122	+13	+1	-7	-5	+11	1.4
2025	31	MLB	New York Mets	—	81	70	16	5	2	1	9	21	0	1	0	229	316	400	716	171	300	26	11	312	97	-0	+0	-0	-1	+2	0.1
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	2856	2434	636	127	5	96	365	532	42	18	7	261	367	436	803	175	297	19	13	359	129	+99	+1	-39	-35	+62	9.0
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	18	ROK MLE	Billings Mustangs	—	275	245	63	12	2	4	23	72	4	1	2	257	331	371	702	114	343	26	8	310	96	—	—	—	—	—	—
2013	19	A MLE	Dayton Dragons	—	486	437	104	16	5	11	43	100	4	6	1	238	312	373	685	135	281	21	9	302	91	—	—	—	—	—	—
2014	20	AA MLE	Pensacola Blue Wahoos	—	92	82	16	5	0	2	9	26	0	0	0	195	275	329	604	134	253	28	10	265	65	—	—	—	—	—	—
2014	20	A+ MLE	Bakersfield Blaze	—	249	214	52	12	0	8	31	64	1	5	1	243	341	411	753	168	297	26	12	331	110	—	—	—	—	—	—
2015	21	AA MLE	Pensacola Blue Wahoos	—	526	471	130	25	2	11	46	104	6	8	4	276	348	408	756	132	327	20	9	332	111	—	—	—	—	—	—
2016	22	AAA MLE	Louisville Bats	—	448	400	120	19	0	3	39	72	4	0	0	300	368	370	738	70	350	16	9	335	113	—	—	—	—	—	—
2016	22	ROK MLE	AZL Reds	—	15	14	4	0	0	1	1	6	0	0	0	286	333	500	833	214	422	40	7	401	158	—	—	—	—	—	—
2017	23	MLB MLE	Cincinnati Reds	—	137	121	35	7	0	6	15	24	0	1	1	289	368	496	864	207	322	18	11	384	146	+7	-0	-1	-5	+3	0.4
2017	23	AAA MLE	Louisville Bats	—	347	312	86	18	0	2	25	56	5	2	4	276	339	353	692	77	321	16	7	312	97	—	—	—	—	—	—
2018	24	MLB MLE	Cincinnati Reds	—	334	285	83	16	0	6	45	46	2	0	0	291	392	411	802	119	336	14	13	363	132	+13	+0	-6	-4	+7	1.1
2019	25	MLB MLE	Cincinnati Reds	—	384	340	90	17	2	15	36	60	8	0	2	265	349	459	808	194	286	16	9	357	127	+13	-1	-7	-4	+8	0.9
2020	26	MLB MLE	Cincinnati Reds	—	183	149	37	7	0	11	28	46	5	1	0	248	385	517	901	268	283	25	15	394	152	+11	+0	-1	-2	+4	1.3
2021	27	MLB MLE	Cincinnati Reds	—	485	424	128	33	1	22	52	75	9	1	0	302	390	540	930	238	324	15	11	405	160	+35	+0	-8	-5	+11	3.3
2022	28	MLB MLE	Seattle Mariners	—	547	457	100	15	0	14	83	103	4	0	0	219	344	344	687	125	251	19	15	320	103	+2	+0	-9	-6	+12	-0.2
2023	29	MLB MLE	Milwaukee Brewers	—	197	166	33	5	0	1	26	51	4	0	0	199	321	247	568	48	278	26	13	277	73	-6	+0	-0	-3	+4	-0.5
2023	29	AAA MLE	Nashville Sounds	—	93	77	19	3	0	3	16	16	0	0	3	247	376	403	779	156	269	17	17	344	119	—	—	—	—	—	—
2023	29	A+ MLE	Wisconsin Timber Rattlers	—	15	14	4	1	0	0	1	3	0	0	0	286	333	357	690	71	382	20	7	327	107	—	—	—	—	—	—
2024	30	MLB MLE	New York Mets	—	508	432	112	24	0	14	61	106	10	14	4	259	364	412	776	153	304	21	12	349	122	+13	+1	-7	-5	+11	1.4
2025	31	MLB MLE	New York Mets	—	81	71	16	5	2	1	8	21	0	1	0	225	304	394	698	169	300	26	10	312	97	-0	+0	-0	-1	+2	0.1
2012	18	ROK MLE	Billings Mustangs	—	275	245	63	12	2	4	23	72	4	1	2	257	331	371	702	114	347	26	8	310	96	—	—	—	—	—	—
2012	18	ROK RAW	Billings Mustangs	—	275	228	77	16	3	5	40	50	4	1	2	338	445	500	945	162	414	18	15	417	96	—	—	—	—	—	—
2013	19	A MLE	Dayton Dragons	—	486	437	104	16	5	11	43	100	4	6	1	238	312	373	685	135	284	21	9	302	91	—	—	—	—	—	—
2013	19	A RAW	Dayton Dragons	—	486	417	117	18	5	16	63	75	4	6	1	281	380	463	843	182	308	15	13	374	91	—	—	—	—	—	—
2014	20	A+ MLE	3 teams	—	425	368	85	21	0	13	50	113	1	6	3	231	325	394	719	163	290	27	12	313	98	—	—	—	—	—	—
2014	20	A+ RAW	3 teams	—	425	350	104	24	1	18	68	85	1	6	3	297	413	526	939	229	340	20	16	408	98	—	—	—	—	—	—
2015	21	AA MLE	Pensacola Blue Wahoos	—	526	471	130	25	2	11	46	104	6	8	4	276	348	408	756	132	331	20	9	332	111	—	—	—	—	—	—
2015	21	AA RAW	Pensacola Blue Wahoos	—	526	443	125	24	2	13	74	83	6	8	4	282	392	433	825	151	320	16	14	371	111	—	—	—	—	—	—
2016	22	AAA MLE	2 teams	—	463	413	124	19	0	4	41	78	4	0	0	300	369	375	744	75	357	17	9	337	114	—	—	—	—	—	—
2016	22	AAA RAW	2 teams	—	463	393	121	22	0	5	61	63	4	0	0	308	406	402	808	94	352	14	13	365	114	—	—	—	—	—	—
2017	23	AAA MLE	2 teams	—	484	433	122	26	0	8	40	80	5	3	5	282	349	397	747	115	326	17	8	332	111	—	—	—	—	—	—
2017	23	AAA RAW	2 teams	—	484	420	130	29	0	9	53	70	5	3	5	310	393	443	836	133	350	14	11	372	111	—	—	—	—	—	—
2018	24	MLB MLE	Cincinnati Reds	—	334	285	83	16	0	6	45	46	2	0	0	291	392	411	802	119	329	14	13	363	132	+13	+0	-6	-4	+7	1.1
2018	24	MLB RAW	Cincinnati Reds	—	334	281	84	16	0	7	49	46	2	0	0	299	407	431	837	132	336	14	15	377	132	+13	+0	-6	-4	+7	1.1
2019	25	MLB MLE	Cincinnati Reds	—	384	340	90	17	2	15	36	60	8	0	2	265	349	459	808	194	283	16	9	357	127	+13	-1	-7	-4	+8	0.9
2019	25	MLB RAW	Cincinnati Reds	—	384	338	91	17	2	16	38	60	8	0	2	269	357	473	830	204	286	16	10	368	127	+13	-1	-7	-4	+8	0.9
2020	26	MLB MLE	Cincinnati Reds	—	183	149	37	7	0	11	28	46	5	1	0	248	385	517	901	268	280	25	15	394	152	+11	+0	-1	-2	+4	1.3
2020	26	MLB RAW	Cincinnati Reds	—	183	149	38	7	0	12	28	46	5	1	0	255	390	544	934	289	283	25	15	406	152	+11	+0	-1	-2	+4	1.3
2021	27	MLB MLE	Cincinnati Reds	—	485	424	128	33	1	22	52	75	9	1	0	302	390	540	930	238	324	15	11	405	160	+35	+0	-8	-5	+11	3.3
2021	27	MLB RAW	Cincinnati Reds	—	485	423	129	32	1	24	53	75	9	1	0	305	394	556	949	251	324	15	11	415	160	+35	+0	-8	-5	+11	3.3
2022	28	MLB MLE	Seattle Mariners	—	547	457	100	15	0	14	83	103	4	0	0	219	344	344	687	125	251	19	15	320	103	+2	+0	-9	-6	+12	-0.2
2022	28	MLB RAW	Seattle Mariners	—	547	456	100	15	0	14	84	103	4	0	0	219	346	344	690	125	251	19	15	318	103	+2	+0	-9	-6	+12	-0.2
2023	29	MLB MLE	3 teams	—	305	257	57	9	0	4	43	70	4	0	3	222	342	304	646	82	288	23	14	300	89	-4	-1	-0	-3	+7	-0.2
2023	29	MLB RAW	3 teams	—	305	249	58	9	0	5	51	66	4	0	3	233	372	329	701	96	296	22	17	329	89	-4	-1	-0	-3	+7	-0.2
2024	30	MLB MLE	New York Mets	—	508	432	112	24	0	14	61	106	10	14	4	259	364	412	776	153	311	21	12	349	122	+13	+1	-7	-5	+11	1.4
2024	30	MLB RAW	New York Mets	—	508	430	109	23	0	14	63	106	10	14	4	253	362	405	766	151	304	21	12	345	122	+13	+1	-7	-5	+11	1.4
2025	31	MLB MLE	New York Mets	—	81	71	16	5	2	1	8	21	0	1	0	225	304	394	698	169	294	26	10	312	97	-0	+0	-0	-1	+2	0.1
2025	31	MLB RAW	New York Mets	—	81	70	16	5	2	1	9	21	0	1	0	229	316	400	716	171	300	26	11	312	97	-0	+0	-0	-1	+2	0.1
2012	18	ROK MLE	Billings Mustangs	—	275	246	63	12	2	4	23	72	4	1	2	256	331	370	701	114	343	26	8	310	96	—	—	—	—	—	—
2013	19	A MLE	Dayton Dragons	—	486	436	104	16	5	11	43	100	4	6	1	239	312	374	686	135	281	21	9	302	91	—	—	—	—	—	—
2014	20	A+ MLE	3 teams	—	425	371	85	21	0	13	50	113	1	6	3	229	325	391	715	162	285	27	12	313	98	—	—	—	—	—	—
2015	21	AA MLE	Pensacola Blue Wahoos	—	526	469	130	25	2	11	46	104	6	8	4	277	348	409	757	132	327	20	9	332	111	—	—	—	—	—	—
2016	22	AAA MLE	2 teams	—	463	415	124	19	0	4	41	78	4	0	0	299	369	373	742	75	352	17	9	337	114	—	—	—	—	—	—
2017	23	AAA MLE	2 teams	—	484	436	122	26	0	8	40	80	5	3	5	280	349	394	744	115	321	17	8	332	111	—	—	—	—	—	—
2018	24	MLB MLE	Cincinnati Reds	—	334	284	83	16	0	6	45	46	2	0	0	292	392	412	804	120	336	14	13	363	132	—	—	—	—	—	—
2019	25	MLB MLE	Cincinnati Reds	—	384	337	90	17	2	15	36	60	8	0	2	267	349	463	812	196	286	16	9	357	127	—	—	—	—	—	—
2020	26	MLB MLE	Cincinnati Reds	—	183	148	37	7	0	11	28	46	5	1	0	250	385	520	905	270	283	25	15	394	152	—	—	—	—	—	—
2021	27	MLB MLE	Cincinnati Reds	—	485	421	128	33	1	22	52	75	9	1	0	304	390	544	934	240	324	15	11	405	160	—	—	—	—	—	—
2022	28	MLB MLE	Seattle Mariners	—	547	455	100	15	0	14	83	103	4	0	0	220	344	345	689	125	251	19	15	320	103	—	—	—	—	—	—
2023	29	MLB MLE	3 teams	—	305	255	57	9	0	4	43	70	4	0	3	224	342	306	648	82	281	23	14	300	89	—	—	—	—	—	—
2024	30	MLB MLE	New York Mets	—	508	432	112	24	0	14	61	106	10	14	4	259	364	412	776	153	304	21	12	349	122	—	—	—	—	—	—
2025	31	MLB MLE	New York Mets	—	81	73	16	5	2	1	8	21	0	1	0	219	304	384	687	164	300	26	10	312	97	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	30	MLB MLE	New York Mets	—	508	432	112	24	0	14	61	106	10	14	4	259	364	412	776	153	304	21	12	349	122	—	—	—	—	—	—
2025	31	MLB MLE	New York Mets	—	81	73	16	5	2	1	8	21	0	1	0	219	304	384	687	164	300	26	10	312	97	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	33	MLB MLE	NYM	100%	272	235	58	13	2	7	31	58	4	5	2	245	342	403	745	158	294	21	11	333	112	+4	+0	-1	-3	+6	0.4
▸ 2027 — real world (MLB)
2027	33	MLB CTX	NYM	100%	169	146	34	7	1	4	19	36	2	3	1	238	335	392	727	154	284	21	11	327	112	+2	+0	-1	-2	+4	0.4
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	34	MLB MLE	NYM	100%	142	123	28	6	1	3	16	31	2	1	1	233	330	379	709	146	283	22	11	319	102	+0	-0	-5	-2	+3	-0.4
2028	34	MLB CTX	NYM	100%	142	123	28	6	1	3	16	31	2	1	1	226	324	368	692	142	274	22	11	313	102	+0	-0	-5	-2	+3	-0.4
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2998	2557	664	133	6	99	381	563	44	19	8	260	365	433	798	173	296	19	13	357	114	+100	+1	-44	-37	+65	8.6
/ 162G	—	A+C		—	650	554	143	29	1	21	83	122	10	4	2	258	365	428	793	170	295	19	13	357	114	+22	+0	-10	-8	+14	1.9
Career	—	MLE		—	5797	5051	1314	259	16	145	634	1141	70	45	26	260	351	404	755	144	308	20	11	337	114	+102	+1	-45	-39	+69	9.0
/ 162G	—	MLE		—	650	566	147	29	2	16	71	128	8	5	3	260	350	403	753	143	308	20	11	337	114	+21	+0	-9	-8	+14	1.8

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.

2023 AAANashville Sounds · 93 PAwOBA .420 → .344 (−76)K% 14.0% → 17.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.98%	÷0.978	×1.200	—	—	17.16%
BB% (unintentional) /PA	24.73%	÷0.995	×0.690	—	×0.972	16.67%
HBP% /PA	0.00%	—	×0.940	—	×0.972	0.00%
Singles /BIP	22.81%	÷0.953	×0.930	×0.981	×0.972	21.23%
Doubles /BIP	5.26%	÷0.971	×0.830	×0.981	×0.972	4.29%
Triples /BIP	0.00%	÷0.900	×0.970	×0.981	×0.972	0.00%
Home runs /BIP	7.02%	÷0.905	×0.700	—	×0.972	5.28%

Factors used: league row International League. Park (home-season share, regressed): HR 81, 1B 91, 2B 94, 3B 80, K 96, BB 99 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.981.

Result: wOBA .420 → .344; ISO .214 → .177; BABIP .302 → .269. 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 A+Wisconsin Timber Rattlers · 15 PAwOBA .410 → .327 (−83)K% 13.3% → 17.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.33%	÷0.955	×1.270	—	—	17.73%
BB% (unintentional) /PA	13.33%	÷1.024	×0.710	—	×0.940	8.69%
HBP% /PA	0.00%	—	×0.790	—	×0.940	0.00%
Singles /BIP	36.36%	÷1.013	×0.920	—	×0.940	31.05%
Doubles /BIP	9.09%	÷0.966	×0.810	—	×0.940	7.17%
Triples /BIP	0.00%	÷1.150	×0.850	—	×0.940	0.00%
Home runs /BIP	0.00%	÷1.033	×0.800	—	×0.940	0.00%

Factors used: league row Midwest League. Park (home-season share, regressed): HR 107, 1B 103, 2B 93, 3B 130, K 91, BB 105 — applied at half strength. Age: age 30 vs a level average of 22.8 → −6.0% on BB/HBP/hit rates (7.2 yr older than average).

Result: wOBA .410 → .327; ISO .077 → .061; BABIP .455 → .382. 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).

2017 AAALouisville Bats · 347 PAwOBA .356 → .312 (−45)K% 13.3% → 16.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.26%	÷0.985	×1.200	—	—	16.16%
BB% (unintentional) /PA	10.09%	÷1.015	×0.690	—	×1.048	7.18%
HBP% /PA	1.44%	—	×0.940	—	×1.048	1.42%
Singles /BIP	27.67%	÷1.038	×0.930	×0.980	×1.048	25.46%
Doubles /BIP	8.70%	÷1.051	×0.830	×0.980	×1.048	7.05%
Triples /BIP	0.00%	÷1.113	×0.970	×0.980	×1.048	0.00%
Home runs /BIP	0.79%	÷1.042	×0.840	—	×1.048	0.67%

Factors used: league row IL. Park (home-season share, regressed): HR 108, 1B 108, 2B 110, 3B 123, K 97, BB 103 — applied at half strength. Age: age 24 vs a level average of 27.2 → +4.8% on BB/HBP/hit rates (3.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.980.

Result: wOBA .356 → .312; ISO .094 → .079; BABIP .359 → .321. 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 AAALouisville Bats · 448 PAwOBA .348 → .335 (−13)K% 13.2% → 16.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.17%	÷0.984	×1.200	—	—	16.05%
BB% (unintentional) /PA	11.83%	÷0.978	×0.690	—	×1.050	8.77%
HBP% /PA	0.89%	—	×0.940	—	×1.050	0.88%
Singles /BIP	28.04%	÷0.952	×0.930	×1.021	×1.050	29.36%
Doubles /BIP	6.85%	÷1.053	×0.830	×1.021	×1.050	5.79%
Triples /BIP	0.00%	÷1.150	×0.970	×1.021	×1.050	0.00%
Home runs /BIP	0.93%	÷0.882	×0.840	—	×1.050	0.93%

Factors used: league row IL. Park (home-season share, regressed): HR 76, 1B 90, 2B 111, 3B 130, K 97, BB 96 — 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 ×1.021.

Result: wOBA .348 → .335; ISO .082 → .075; BABIP .347 → .350. 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 ROKAZL Reds · 15 PAwOBA .594 → .401 (−193)K% 26.7% → 38.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.67%	÷1.000	×1.440	—	—	38.40%
BB% (unintentional) /PA	13.33%	÷1.000	×0.620	—	×0.965	7.98%
HBP% /PA	0.00%	—	×0.720	—	×0.965	0.00%
Singles /BIP	44.44%	÷1.000	×0.820	—	×0.965	35.17%
Doubles /BIP	0.00%	÷1.000	×0.720	—	×0.965	0.00%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.965	0.00%
Home runs /BIP	22.22%	÷1.000	×0.780	—	×0.965	16.73%

Factors used: level-wide ROK 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 23 vs a level average of 19.5 → −3.5% on BB/HBP/hit rates (3.5 yr older than average).

Result: wOBA .594 → .401; ISO .462 → .310; BABIP .571 → .422. 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 AAPensacola Blue Wahoos · 526 PAwOBA .361 → .332 (−29)K% 15.8% → 19.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.78%	÷0.979	×1.220	—	—	19.67%
BB% (unintentional) /PA	13.31%	÷1.087	×0.680	—	×1.042	8.68%
HBP% /PA	1.14%	—	×0.840	—	×1.042	1.00%
Singles /BIP	23.89%	÷0.965	×0.920	×1.041	×1.042	24.70%
Doubles /BIP	6.67%	÷0.979	×0.910	×1.041	×1.042	6.72%
Triples /BIP	0.56%	÷0.903	×0.880	×1.041	×1.042	0.59%
Home runs /BIP	3.61%	÷1.037	×0.800	—	×1.042	2.90%

Factors used: league row SL. Park (home-season share, regressed): HR 107, 1B 93, 2B 96, 3B 81, K 96, BB 117 — 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 ×1.041.

Result: wOBA .361 → .332; ISO .151 → .139; BABIP .320 → .327. 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).

2014 A+Bakersfield Blaze · 249 PAwOBA .429 → .331 (−98)K% 18.5% → 25.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.47%	÷0.961	×1.340	—	—	25.77%
BB% (unintentional) /PA	16.06%	÷0.944	×0.710	—	×1.027	12.41%
HBP% /PA	0.40%	—	×0.790	—	×1.027	0.33%
Singles /BIP	23.27%	÷1.031	×0.910	×0.987	×1.027	20.83%
Doubles /BIP	9.43%	÷1.005	×0.820	×0.987	×1.027	7.81%
Triples /BIP	0.00%	÷0.900	×0.760	×0.987	×1.027	0.00%
Home runs /BIP	8.18%	÷1.421	×0.920	—	×1.027	5.44%

Factors used: league row CAL. Park (home-season share, regressed): HR 184, 1B 106, 2B 101, 3B 80, K 92, BB 89 — applied at half strength. Age: age 21 vs a level average of 22.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.987.

Result: wOBA .429 → .331; ISO .263 → .180; BABIP .349 → .297. 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).

2014 AAPensacola Blue Wahoos · 92 PAwOBA .306 → .265 (−40)K% 23.9% → 28.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.91%	÷1.014	×1.220	—	—	28.78%
BB% (unintentional) /PA	15.22%	÷1.051	×0.680	—	×1.050	10.34%
HBP% /PA	0.00%	—	×0.840	—	×1.050	0.00%
Singles /BIP	16.36%	÷0.971	×0.920	×1.002	×1.050	16.31%
Doubles /BIP	9.09%	÷1.012	×0.910	×1.002	×1.050	8.60%
Triples /BIP	0.00%	÷1.150	×0.880	×1.002	×1.050	0.00%
Home runs /BIP	3.64%	÷0.970	×0.800	—	×1.050	3.15%

Factors used: league row SL. Park (home-season share, regressed): HR 94, 1B 94, 2B 102, 3B 130, K 103, BB 110 — applied at half strength. Age: age 21 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.002.

Result: wOBA .306 → .265; ISO .143 → .131; BABIP .259 → .253. 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
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 11 projected seasons	4.8	3,167	104	23	261	362	435	-34	-54	15.4	15.2
/162	664	22	5	-7.1	-11.4	3.2	pk7: 15
#1Willie Crawford'64-'77 * career totals — 10 seasons, 3,925 PA	5.9	3,925	86	47	265*	346*	445*	-41	-12	14.3	13.9
/162	664	15	8	-6.9	-2.1	2.4	pk7: 14
#2Seth Smithlast yr '17 career totals — 10 seasons, 4,076 PA	6.1	4,076	126	22	260	343	445	-44	-36	14.0	13.3
/162	664	21	4	-7.1	-5.9	2.3	pk7: 13
#3Mark Canhalast yr '25 career totals — 10 seasons, 4,084 PA	6.2	4,084	118	50	250	349	410	-38	-50	11.0	11.9
/162	664	19	8	-6.1	-8.2	1.8	pk7: 13
#4Frank Catalanotto'97-'10 * career totals — 12 seasons, 4,292 PA	6.5	4,292	84	45	279*	346*	433*	-50	-27	11.4	11.1
/162	664	13	7	-7.7	-4.1	1.8	pk7: 11
#5Craig Wilsonlast yr '07 career totals — 7 seasons, 2,311 PA	3.5	2,311	99	14	262	353	474	-25	-49	8.1	8.1
/162	664	28	4	-7.2	-14.0	2.3	pk7: 8
#6Al Ferrara'63-'71 * career totals — 7 seasons, 1,573 PA	2.4	1,573	51	0	257*	344*	455*	-17	-14	5.8	5.8
/162	664	22	0	-7.1	-6.0	2.4	pk7: 6

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
Jesse Winker (OGILVIE)	33	50	45	40	60	243/339/399	157	294	4	3	21%	11%	112	+0.6	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Todd Hollandsworth 2005 · MLB	32	54→55	52→55	43→50	50	271/329/453	182	312	19	7	19%	8%	119	+2.7	248/297/406	158	293	16	6	20%	6%	97	+1.1	242/284/392	150	288	14	4	21%	5%	89	+0.3
✕Michael Tucker 2005 · MLB	34	51	49→55	48→55	56	251/332/410	159	294	15	11	20%	11%	110	+2.1	229/315/360	131	272	12	9	19%	11%	93	+0.8	208/300/322	114	250	9	9	20%	11%	78	-0.2
✕Ben Gamel 2024 · MLB	32	48→58	47→50	44→50	53	234/318/375	140	297	14	8	25%	10%	97	+1.1	223/311/359	136	312	13	6	30%	11%	92	+0.7	204/300/329	125	300	11	4	33%	11%	78	-0.1
✕Roberto Mendez 2006 · AAA	33	53→56	50→45	43→45	56	267/345/426	158	304	18	6	18%	10%	119	+2.7	254/336/377	123	296	13	8	18%	11%	104	+1.6	245/332/350	105	284	11	8	17%	11%	96	+0.7
✕Brian Myrow 2010 · MLB	33	51→57	48→50	43→40	54	252/334/397	146	299	16	4	21%	10%	109	+2.0	217/298/335	118	271	12	8	23%	9%	82	-0.0	174/266/260	86	222	9	6	24%	10%	51	-1.4
✕Daniel Descalso 2019 · MLB	32	46→56	51→50	48→45	58	232/334/401	168	284	17	4	24%	13%	109	+2.0	201/297/334	133	273	14	6	29%	12%	81	-0.1	159/261/244	85	219	9	5	30%	12%	48	-0.9
✕John Jaso 2017 · MLB	33	54→57	48→50	36→45	56	266/347/421	155	308	14	3	18%	10%	118	+2.7	241/333/415	174	283	18	5	21%	11%	113	+2.3	209/322/404	195	238	21	2	22%	13%	107	+0.9
✕Alejandro De Aza 2017 · MLB	33	49→59	46→50	48→55	48	239/311/378	139	299	13	12	24%	8%	95	+1.0	230/295/350	120	278	11	10	21%	7%	83	+0.1	229/290/342	113	276	9	10	20%	7%	78	-0.1
✕Kosuke Fukudome 2012 · MLB	35	53→54	46→50	39→50	59	257/345/393	136	299	12	7	18%	12%	111	+2.1	239/325/351	112	287	10	7	19%	11%	95	+0.9	207/318/270	63	257	5	2	19%	14%	75	-0.2
✕Kolten Wong 2024 · MLB	33	47→57	48→50	49→55	50	236/312/381	145	271	15	14	19%	8%	97	+1.1	224/292/346	122	271	13	11	22%	7%	81	-0.1	199/253/270	71	252	6	8	23%	5%	47	-0.5
●Matt Lawton III 2005 · MLB	33	52→62	50	47→55	60	263/351/418	155	271	19	16	12%	11%	120	+2.8	258/349/400	142	280	15	16	13%	11%	115	+2.4	252/355/393	141	275	13	18	13%	12%	117	+2.5
✕Francisco Mendez 2011 · AAA	33	53→59	46→45	41→40	56	259/340/384	126	309	13	3	20%	11%	107	+1.9	228/308/343	115	290	12	3	24%	10%	87	+0.4	214/291/320	106	293	12	2	29%	9%	75	-0.3
✕Juan Miranda 2016 · AAA	33	52→58	48→55	45→40	54	256/356/393	137	308	16	5	21%	10%	117	+2.6	230/318/351	121	287	13	7	23%	9%	93	+0.8	208/289/323	115	262	12	4	24%	9%	73	-0.3
✕Mike Tauchman 2024 · MLB	33	49→59	46→55	49→55	58	238/339/367	128	299	13	10	23%	12%	104	+1.6	243/340/369	126	302	13	7	22%	12%	105	+1.7	244/345/366	122	304	13	5	22%	12%	106	+1.2
✕Nick Hundley 2017 · MLB	33	51→45	49→55	42→40	46	257/304/407	150	304	16	5	21%	6%	99	+1.3	241/284/407	166	304	19	4	26%	6%	93	+0.8	229/267/395	166	295	19	2	29%	5%	84	+0.1
✕Jason Kipnis 2020 · MLB	33	45→55	51→55	48→55	51	232/299/393	161	256	19	8	18%	8%	95	+0.9	233/308/390	157	286	18	7	24%	9%	97	+1.1	221/310/373	152	292	16	3	28%	10%	93	+0.3
●Denard Span 2018 · MLB	34	56→64	47→50	49→55	53	273/332/416	143	294	13	13	12%	8%	112	+2.2	260/334/416	156	291	14	11	15%	9%	112	+2.2	259/344/418	159	294	14	11	16%	10%	117	+2.1
✕Rafael Ortega 2023 · MLB	32	50→55	48→55	48→55	54	248/326/390	142	292	16	18	20%	10%	103	+1.6	217/303/341	124	268	13	21	22%	11%	84	+0.2	200/296/311	111	248	11	26	23%	12%	74	-0.4
✕Mike Kinkade 2005 · MLB	32	49→58	50→45	42→45	47	246/343/402	156	286	17	8	20%	7%	115	+2.4	252/319/385	133	290	12	8	17%	5%	101	+1.4	259/324/387	128	299	11	7	17%	4%	101	+1.0
✕Michael McKenry 2017 · MLB	32	45→47	48→55	44→40	54	221/316/371	150	289	15	7	27%	11%	97	+1.1	201/287/318	117	283	11	6	30%	10%	74	-0.6	159/252/243	84	230	7	0	31%	10%	42	-1.3

Jesse Winker

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps