Eloy Jiménez

LF Buffalo Bisons

Age 30 R/R 6'4" / 250 lbs AAA Svc 4.459 · Ctrl thru 2028

Overview

AAAArb-2FA 2029

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	27	MLBBAL	349	.238/.290/.336	6	3	74	-0.7
2025	28	AAA/ROK/INTL3 orgs	354	.247/.329/.378	8	2	76	—	.212/.272/.282
2026	29	AAATOR	133	.286/.356/.361	1	0	73	—	.252/.303/.317
2026	29	MLBTOR	35	.290/.353/.290	0	0	83	-0.2
2027PROJ10% MLB	30	MLBTOR	14	.251/.305/.355	0	0	86	-0.0
2028PROJ	31	MLBTOR	126	.246/.299/.344	2	0	82	-0.5

Last 3 seasons WAR -0.9 · Next 2 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2028Service4.459First FA2029

2027Arb-2$0.4M2028Arb-3$0.6M

Skills · percentileStatcast 2023-2026

Avg EV82

Bat Spd67

Barrel%52

xwOBA49

Speed20

CompsBrian Barden (age 30) · Guillermo Heredia (age 29) · Gregorio Petit (age 30)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 8786vR 80

AVG/OBP/SLG.251 / .305 / .355

PA14

HR0

K%21

BB%7

BABIP303

ISO77

MLB%10%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$1M ctrl surplus

Tools · Splits · ContractCON 50 / POW 45

Toolsscout grade · Statcast %ile · 2023-2026

CONTACT50

xAVG

450.247

POWER45

Barrel%

528.5

Avg EV

8291.3

Bat Spd

6773.1

EYE40

scouting grade only

SPEED35

Sprint

2026.0

Platoon Splits2024-2026 · 370 PA

vs LHP

vs RHP

Edge

276

—

wRC+

▶▶R

wOBA

256

292

▶R

ISO

056

106

▶▶R

BABIP

292

294

—

18.1%

20.6%

◀L

BB%

5.3%

6.9%

▶▶R

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

Status Arb-2

MLB Debut 2019

Service 4.459 yrs.days

Team Control Through 2028

First FA Year 2029

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-2	$0.4M	—	—	—
2028	Arb-3	$0.6M	—	—	—
Totals		$0.0M		$-2M	+$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)
2014	17	ROK	AZL Cubs	—	164	150	34	8	2	3	10	32	0	3	1	227	275	367	642	140	261	20	6	279	25	—	—	—	—	—	—
2016	19	A	South Bend Cubs	—	464	432	142	40	3	14	25	94	4	8	3	329	371	532	903	204	391	20	5	394	103	—	—	—	—	—	—
2016	19	INTL	Mesa Solar Sox	—	62	55	14	4	0	3	6	11	0	0	0	255	328	491	819	236	262	18	10	353	125	—	—	—	—	—	—
2017	20	AA	Birmingham Barons	—	73	68	24	5	0	3	5	16	0	1	1	353	397	559	956	206	429	22	7	420	131	—	—	—	—	—	—
2017	20	A+	Winston-Salem Dash	—	296	265	80	17	3	16	30	56	1	0	2	302	375	570	945	268	332	19	10	410	91	—	—	—	—	—	—
2017	20	INTL	Gigantes del Cibao	—	79	68	25	5	2	4	10	16	0	1	0	368	449	676	1.125	309	429	20	13	476	208	—	—	—	—	—	—
2018	21	AAA	Charlotte Knights	—	228	211	75	13	1	12	14	30	2	0	1	355	401	597	998	242	371	13	6	434	119	—	—	—	—	—	—
2018	21	AA	Birmingham Barons	—	228	205	65	15	2	10	18	39	1	0	0	317	375	556	931	239	344	17	8	399	123	—	—	—	—	—	—
2018	21	INTL	Gigantes del Cibao	—	32	29	13	3	0	2	3	7	0	0	0	448	500	759	1.259	310	550	22	9	542	253	—	—	—	—	—	—
2019	22	MLB	Chicago White Sox	—	504	468	125	18	2	31	30	134	4	0	0	267	317	513	830	246	308	27	6	360	128	+17	+0	-13	-6	+11	0.9
2019	22	AAA	Charlotte Knights	—	22	22	7	1	0	1	0	5	0	0	0	318	318	500	818	182	375	23	0	359	77	—	—	—	—	—	—
2019	22	INTL	Gigantes del Cibao	—	40	36	8	0	0	0	4	4	0	0	0	222	300	222	522		250	10	10	251	56	—	—	—	—	—	—
2020	23	MLB	Chicago White Sox	—	226	213	63	14	0	14	12	56	0	0	0	296	333	559	892	263	340	25	5	386	145	+12	+0	-4	-2	+5	1.1
2021	24	MLB	Chicago White Sox	—	231	213	53	10	0	10	16	57	1	0	0	249	304	437	741	188	293	25	7	326	106	+2	+0	-1	-3	+5	0.2
2021	24	AAA	Charlotte Knights	—	41	38	10	2	0	1	2	14	0	0	0	263	300	395	695	132	375	34	5	302	50	—	—	—	—	—	—
2022	25	MLB	Chicago White Sox	—	327	292	86	12	0	16	28	72	3	0	0	295	362	500	862	205	337	22	9	376	139	+15	+0	-3	-4	+7	1.5
2022	25	AAA	Charlotte Knights	—	63	57	14	0	0	2	6	12	0	0	0	246	317	351	668	105	279	19	10	305	48	—	—	—	—	—	—
2023	26	MLB	Chicago White Sox	—	489	456	124	23	0	18	30	93	1	0	0	272	318	441	759	169	305	19	6	335	110	+6	+0	-1	-5	+11	1.0
2024	27	MLB	Baltimore Orioles	—	349	324	77	14	0	6	22	70	2	3	0	238	290	336	627	99	285	20	6	283	74	-11	+1	-0	-4	+8	-0.7
2024	27	ROK	ACL White Sox	—	19	18	8	1	0	1	1	2	0	0	0	444	474	667	1.140	222	467	11	5	500	118	—	—	—	—	—	—
2025	28	AAA	Buffalo Bisons	—	188	169	45	10	0	3	16	34	1	1	0	266	333	379	712	112	313	18	9	319	64	—	—	—	—	—	—
2025	28	ROK	FCL Rays	—	27	21	2	0	0	0	6	3	0	0	0	95	296	95	392		111	11	22	222	-17	—	—	—	—	—	—
2025	28	INTL	Toros del Este	—	139	122	30	7	0	5	15	28	0	1	0	246	328	426	755	180	275	20	11	332	111	—	—	—	—	—	—
2026	29	MLB	Toronto Blue Jays	—	35	31	9	0	0	0	3	7	0	0	0	290	353	290	643		360	20	9	293	83	-1	+0	+0	-2	+1	-0.2
2026	29	AAA	Buffalo Bisons	—	133	119	34	6	0	1	11	21	2	0	0	286	356	361	717	76	337	16	8	326	73	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	2161	1997	537	91	2	95	141	489	11	3	0	269	321	459	780	190	310	23	7	342	118	+46	+1	-22	-27	+47	4.6
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2014	17	ROK MLE	AZL Cubs	—	164	154	26	6	1	2	6	46	0	3	1	169	200	260	460	91	209	28	4	205	25	—	—	—	—	—	—
2016	19	A MLE	South Bend Cubs	—	464	441	122	33	3	11	16	131	4	8	3	277	308	440	748	163	363	28	3	320	103	—	—	—	—	—	—
2017	20	AA MLE	Birmingham Barons	—	73	70	23	5	0	3	3	20	0	1	1	329	356	529	885	200	407	27	4	362	131	—	—	—	—	—	—
2017	20	A+ MLE	Winston-Salem Dash	—	296	280	67	13	3	11	15	82	1	0	2	239	280	425	705	186	296	28	5	303	91	—	—	—	—	—	—
2018	21	AAA MLE	Charlotte Knights	—	228	217	64	10	1	8	8	36	2	0	1	295	326	461	787	166	325	16	4	344	119	—	—	—	—	—	—
2018	21	AA MLE	Birmingham Barons	—	228	210	60	15	2	9	13	47	1	0	0	286	330	505	835	219	312	21	6	350	123	—	—	—	—	—	—
2019	22	MLB MLE	Chicago White Sox	—	504	468	124	18	2	30	30	134	4	0	0	265	315	504	819	239	308	27	6	358	128	+17	+0	-13	-6	+11	0.9
2019	22	AAA MLE	Charlotte Knights	—	22	22	6	1	0	1	0	6	0	0	0	273	273	455	727	182	341	27	0	282	77	—	—	—	—	—	—
2020	23	MLB MLE	Chicago White Sox	—	226	213	63	14	0	14	12	56	0	0	0	296	333	559	892	263	340	25	5	383	145	+12	+0	-4	-2	+5	1.1
2021	24	MLB MLE	Chicago White Sox	—	231	213	53	10	0	10	16	57	1	0	0	249	304	437	741	188	293	25	7	324	106	+2	+0	-1	-3	+5	0.2
2021	24	AAA MLE	Charlotte Knights	—	41	39	9	1	0	1	1	17	0	0	0	231	250	333	583	103	341	41	2	242	50	—	—	—	—	—	—
2022	25	MLB MLE	Chicago White Sox	—	327	292	86	12	0	16	28	72	3	0	0	295	362	500	862	205	337	22	9	374	139	+15	+0	-3	-4	+7	1.5
2022	25	AAA MLE	Charlotte Knights	—	63	59	13	0	0	1	4	15	0	0	0	220	270	271	541	51	270	24	6	239	48	—	—	—	—	—	—
2023	26	MLB MLE	Chicago White Sox	—	489	458	124	23	0	18	28	93	1	0	0	271	314	439	753	168	305	19	6	330	110	+6	+0	-1	-5	+11	1.0
2024	27	MLB MLE	Baltimore Orioles	—	349	325	75	13	0	6	21	70	2	3	0	231	282	326	608	95	285	20	6	277	74	-11	+1	-0	-4	+8	-0.7
2024	27	ROK MLE	ACL White Sox	—	19	18	7	1	0	1	1	3	0	0	0	389	421	611	1.032	222	348	16	5	342	118	—	—	—	—	—	—
2025	28	AAA MLE	Buffalo Bisons	—	188	174	40	8	0	2	11	41	1	1	0	230	280	310	590	80	280	22	6	263	64	—	—	—	—	—	—
2025	28	ROK MLE	FCL Rays	—	27	23	2	0	0	0	4	4	0	0	0	87	222	87	309		84	15	15	143	-17	—	—	—	—	—	—
2026	29	MLB MLE	Toronto Blue Jays	—	35	31	9	0	0	0	3	7	0	0	0	290	353	290	643		360	20	9	291	83	-1	+0	+0	-2	+1	-0.2
2026	29	AAA MLE	Buffalo Bisons	—	133	123	31	5	0	1	7	25	2	0	0	252	303	317	620	65	308	19	5	276	73	—	—	—	—	—	—
2014	17	ROK MLE	AZL Cubs	—	164	154	26	6	1	2	6	46	0	3	1	169	200	260	460	91	218	28	4	205	25	—	—	—	—	—	—
2014	17	ROK RAW	AZL Cubs	—	164	150	34	8	2	3	10	32	0	3	1	227	275	367	642	140	261	20	6	279	25	—	—	—	—	—	—
2016	19	A MLE	2 teams	—	526	500	137	37	3	12	18	149	4	8	3	274	305	432	737	158	364	28	3	320	103	—	—	—	—	—	—
2016	19	A RAW	2 teams	—	526	487	156	44	3	17	31	105	4	8	3	320	366	528	894	207	377	20	6	389	103	—	—	—	—	—	—
2017	20	A+ MLE	3 teams	—	448	424	108	21	3	17	22	124	1	2	3	255	293	439	732	184	320	28	5	315	99	—	—	—	—	—	—
2017	20	A+ RAW	3 teams	—	448	401	129	27	5	23	45	88	1	2	3	322	391	586	978	264	364	20	10	423	99	—	—	—	—	—	—
2018	21	AAA MLE	3 teams	—	488	457	133	27	3	18	23	90	3	0	1	291	329	481	811	190	325	18	5	347	121	—	—	—	—	—	—
2018	21	AAA RAW	3 teams	—	488	445	153	31	3	24	35	76	3	0	1	344	395	589	984	245	369	16	7	425	121	—	—	—	—	—	—
2019	22	MLB MLE	3 teams	—	566	528	140	20	2	34	32	151	4	0	0	265	312	504	816	239	307	27	6	355	126	+18	+0	-13	-6	+12	1.2
2019	22	MLB RAW	3 teams	—	566	526	140	19	2	32	34	143	4	0	0	266	316	492	808	226	306	25	6	353	126	+18	+0	-13	-6	+12	1.2
2020	23	MLB MLE	Chicago White Sox	—	226	213	63	14	0	14	12	56	0	0	0	296	333	559	892	263	340	25	5	383	145	+12	+0	-4	-2	+5	1.1
2020	23	MLB RAW	Chicago White Sox	—	226	213	63	14	0	14	12	56	0	0	0	296	333	559	892	263	340	25	5	386	145	+12	+0	-4	-2	+5	1.1
2021	24	MLB MLE	2 teams	—	272	252	61	11	0	10	17	74	1	0	0	242	293	405	697	163	300	27	6	312	97	-1	+0	-1	-3	+6	0.1
2021	24	MLB RAW	2 teams	—	272	251	63	12	0	11	18	71	1	0	0	251	304	430	734	179	304	26	7	323	97	-1	+0	-1	-3	+6	0.1
2022	25	MLB MLE	2 teams	—	390	351	99	12	0	17	32	87	3	0	0	282	347	462	809	179	327	22	8	352	124	+11	+0	-3	-4	+8	1.3
2022	25	MLB RAW	2 teams	—	390	349	100	12	0	18	34	84	3	0	0	287	355	476	831	189	327	22	9	364	124	+11	+0	-3	-4	+8	1.3
2023	26	MLB MLE	Chicago White Sox	—	489	458	124	23	0	18	28	93	1	0	0	271	314	439	753	168	304	19	6	330	110	+6	+0	-1	-5	+11	1.0
2023	26	MLB RAW	Chicago White Sox	—	489	456	124	23	0	18	30	93	1	0	0	272	318	441	759	169	305	19	6	335	110	+6	+0	-1	-5	+11	1.0
2024	27	MLB MLE	2 teams	—	368	343	82	14	0	7	22	73	2	3	0	239	289	341	630	102	284	20	6	280	76	-11	+1	-0	-4	+8	-0.6
2024	27	MLB RAW	2 teams	—	368	342	85	15	0	7	23	72	2	3	0	249	300	354	654	105	295	20	6	294	76	-11	+1	-0	-4	+8	-0.6
2025	28	AAA MLE	3 teams	—	354	325	69	13	0	4	24	75	1	2	0	212	269	289	558	77	260	21	7	248	54	—	—	—	—	—	—
2025	28	AAA RAW	3 teams	—	354	312	77	17	0	8	37	65	1	2	0	247	329	378	707	131	284	18	10	317	54	—	—	—	—	—	—
2026	29	AAA MLE	2 teams	—	168	154	40	5	0	1	10	32	2	0	0	260	313	312	625	52	317	19	6	279	75	—	—	—	—	—	—
2026	29	AAA RAW	2 teams	—	168	150	43	6	0	1	14	28	2	0	0	287	355	347	702	60	341	17	8	319	75	—	—	—	—	—	—
2014	17	ROK MLE	AZL Cubs	—	164	157	26	6	1	2	6	46	0	3	1	166	200	255	455	89	209	28	4	205	25	—	—	—	—	—	—
2016	19	A MLE	2 teams	—	526	499	137	37	3	12	18	149	4	8	3	275	305	433	737	158	363	28	3	320	103	—	—	—	—	—	—
2017	20	A+ MLE	3 teams	—	448	422	108	21	3	17	22	124	1	2	3	256	293	441	734	185	318	28	5	315	99	—	—	—	—	—	—
2018	21	AAA MLE	3 teams	—	488	459	133	27	3	18	23	90	3	0	1	290	329	479	808	190	319	18	5	347	121	—	—	—	—	—	—
2019	22	MLB MLE	3 teams	—	566	525	140	20	2	34	32	151	4	0	0	267	312	507	819	240	310	27	6	355	126	—	—	—	—	—	—
2020	23	MLB MLE	Chicago White Sox	—	226	212	63	14	0	14	12	56	0	0	0	297	333	561	895	264	340	25	5	383	145	—	—	—	—	—	—
2021	24	MLB MLE	2 teams	—	272	252	61	11	0	10	17	74	1	0	0	242	293	405	697	163	300	27	6	312	97	—	—	—	—	—	—
2022	25	MLB MLE	2 teams	—	390	352	99	12	0	17	32	87	3	0	0	281	347	460	807	179	326	22	8	352	124	—	—	—	—	—	—
2023	26	MLB MLE	Chicago White Sox	—	489	457	124	23	0	18	28	93	1	0	0	271	314	440	754	168	305	19	6	330	110	—	—	—	—	—	—
2024	27	MLB MLE	2 teams	—	368	341	82	14	0	7	22	73	2	3	0	240	289	343	632	103	288	20	6	280	76	—	—	—	—	—	—
2025	28	AAA MLE	3 teams	—	354	326	69	13	0	4	24	75	1	2	0	212	269	288	557	77	255	21	7	248	54	—	—	—	—	—	—
2026	29	AAA MLE	2 teams	—	168	154	40	5	0	1	10	32	2	0	0	260	313	312	625	52	319	19	6	279	75	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	27	MLB MLE	2 teams	—	368	341	82	14	0	7	22	73	2	3	0	240	289	343	632	103	288	20	6	280	76	—	—	—	—	—	—
2025	28	AAA MLE	3 teams	—	354	326	69	13	0	4	24	75	1	2	0	212	269	288	557	77	255	21	7	248	54	—	—	—	—	—	—
2026	29	AAA MLE	2 teams	—	168	154	40	5	0	1	10	32	2	0	0	260	313	312	625	52	319	19	6	279	75	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	30	MLB MLE	TOR	10%	218	200	50	9	0	4	14	45	2	2	1	250	304	354	658	104	302	21	6	295	86	-4	+0	-0	-2	+5	0.0
▸ 2027 — real world (MLB)
2027	30	MLB CTX	TOR	10%	14	13	3	1	0	0	1	3	0	0	0	251	305	355	660	104	303	21	7	296	86	-0	+0	-0	-0	+0	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	31	MLB MLE	TOR	100%	126	116	28	5	0	2	8	27	1	0	0	246	299	344	642	98	299	21	6	289	82	-3	+0	-3	-1	+3	-0.5
2028	31	MLB CTX	TOR	100%	126	116	29	5	0	2	8	27	1	0	0	246	299	344	644	98	300	21	6	289	82	-3	+0	-3	-1	+3	-0.5
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2287	2113	566	96	2	97	149	516	12	3	0	268	320	453	773	185	310	23	7	340	101	+43	+1	-25	-28	+50	4.1
/ 162G	—	A+C		—	650	601	161	27	1	28	42	147	3	1	0	268	319	456	775	188	309	23	6	340	101	+12	+0	-7	-8	+14	1.2
Career	—	MLE		—	4720	4400	1140	213	12	158	262	1105	24	19	8	259	304	421	725	162	310	23	6	317	101	+41	+1	-25	-29	+52	4.0
/ 162G	—	MLE		—	650	606	157	29	2	22	36	152	3	3	1	259	304	422	726	163	309	23	6	317	101	+11	+0	-7	-8	+14	1.1

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 AAABuffalo Bisons · 133 PAwOBA .320 → .276 (−44)K% 15.8% → 18.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.79%	÷1.000	×1.200	—	—	18.95%
BB% (unintentional) /PA	8.27%	÷1.000	×0.690	—	×0.972	5.55%
HBP% /PA	1.50%	—	×0.940	—	×0.972	1.37%
Singles /BIP	27.55%	÷1.000	×0.930	×1.036	×0.972	25.81%
Doubles /BIP	6.12%	÷1.000	×0.830	×1.036	×0.972	5.12%
Triples /BIP	0.00%	÷1.000	×0.970	×1.036	×0.972	0.00%
Home runs /BIP	1.02%	÷1.000	×0.700	—	×0.972	0.69%

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 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 ×1.036.

Result: wOBA .320 → .276; ISO .076 → .060; BABIP .337 → .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).

2025 AAABuffalo Bisons · 188 PAwOBA .314 → .263 (−51)K% 18.1% → 22.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.09%	÷0.988	×1.200	—	—	21.97%
BB% (unintentional) /PA	8.51%	÷0.984	×0.690	—	×0.982	5.86%
HBP% /PA	0.53%	—	×0.940	—	×0.982	0.49%
Singles /BIP	23.70%	÷1.007	×0.930	×1.033	×0.982	22.19%
Doubles /BIP	7.41%	÷1.098	×0.830	×1.033	×0.982	5.68%
Triples /BIP	0.00%	÷0.986	×0.970	×1.033	×0.982	0.00%
Home runs /BIP	2.22%	÷0.847	×0.700	—	×0.982	1.80%

Factors used: league row International League. Park (home-season share, regressed): HR 69, 1B 101, 2B 120, 3B 97, K 98, BB 97 — applied at half strength. Age: age 29 vs a level average of 27.2 → −1.8% on BB/HBP/hit rates (1.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.033.

Result: wOBA .314 → .263; ISO .112 → .088; BABIP .313 → .280. 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 ROKFCL Rays · 27 PAwOBA .219 → .143 (−76)K% 11.1% → 16.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.11%	÷0.985	×1.440	—	—	16.25%
BB% (unintentional) /PA	22.22%	÷0.991	×0.620	—	×0.940	13.07%
HBP% /PA	0.00%	—	×0.720	—	×0.940	0.00%
Singles /BIP	11.11%	÷1.018	×0.820	—	×0.940	8.41%
Doubles /BIP	0.00%	÷1.026	×0.720	—	×0.940	0.00%
Triples /BIP	0.00%	÷1.150	×0.720	—	×0.940	0.00%
Home runs /BIP	0.00%	÷0.809	×0.780	—	×0.940	0.00%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 62, 1B 104, 2B 105, 3B 130, K 97, BB 98 — applied at half strength. Age: age 29 vs a level average of 19.5 → −6.0% on BB/HBP/hit rates (9.5 yr older than average).

Result: wOBA .219 → .143; ISO .000 → .000; BABIP .111 → .084. 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 ROKACL White Sox · 19 PAwOBA .485 → .342 (−143)K% 10.5% → 15.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.53%	÷0.990	×1.440	—	—	15.31%
BB% (unintentional) /PA	5.26%	÷1.017	×0.620	—	×0.940	3.02%
HBP% /PA	0.00%	—	×0.720	—	×0.940	0.00%
Singles /BIP	37.50%	÷0.993	×0.820	—	×0.940	29.10%
Doubles /BIP	6.25%	÷1.012	×0.720	—	×0.940	4.18%
Triples /BIP	0.00%	÷0.900	×0.720	—	×0.940	0.00%
Home runs /BIP	6.25%	÷1.076	×0.780	—	×0.940	4.26%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 115, 1B 99, 2B 102, 3B 80, K 98, BB 103 — applied at half strength. Age: age 28 vs a level average of 19.5 → −6.0% on BB/HBP/hit rates (8.5 yr older than average).

Result: wOBA .485 → .342; ISO .222 → .146; BABIP .467 → .348. 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 AAACharlotte Knights · 63 PAwOBA .297 → .239 (−58)K% 19.0% → 23.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.05%	÷0.975	×1.200	—	—	23.45%
BB% (unintentional) /PA	9.52%	÷1.028	×0.690	—	×1.018	6.51%
HBP% /PA	0.00%	—	×0.940	—	×1.018	0.00%
Singles /BIP	26.67%	÷1.003	×0.930	×1.049	×1.018	26.41%
Doubles /BIP	0.00%	÷1.028	×0.830	×1.049	×1.018	0.00%
Triples /BIP	0.00%	÷0.900	×0.970	×1.049	×1.018	0.00%
Home runs /BIP	4.44%	÷1.421	×0.700	—	×1.018	2.23%

Factors used: league row International League. Park (home-season share, regressed): HR 184, 1B 101, 2B 106, 3B 80, K 95, BB 106 — applied at half strength. Age: age 26 vs a level average of 27.2 → +1.8% on BB/HBP/hit rates (1.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.049.

Result: wOBA .297 → .239; ISO .105 → .052; BABIP .279 → .270. 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).

2021 AAACharlotte Knights · 41 PAwOBA .301 → .242 (−59)K% 34.1% → 40.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	34.15%	÷1.011	×1.200	—	—	40.54%
BB% (unintentional) /PA	4.88%	÷1.053	×0.690	—	×1.033	3.30%
HBP% /PA	0.00%	—	×0.940	—	×1.033	0.00%
Singles /BIP	29.17%	÷0.986	×0.930	—	×1.033	28.41%
Doubles /BIP	8.33%	÷1.128	×0.830	—	×1.033	6.33%
Triples /BIP	0.00%	÷1.020	×0.920	—	×1.033	0.00%
Home runs /BIP	4.17%	÷1.190	×0.700	—	×1.033	2.53%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 138, 1B 97, 2B 126, 3B 104, K 102, BB 111 — 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 .301 → .242; ISO .132 → .084; BABIP .375 → .341. 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).

2019 AAACharlotte Knights · 22 PAwOBA .348 → .282 (−66)K% 22.7% → 28.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.73%	÷0.962	×1.200	—	—	28.36%
BB% (unintentional) /PA	0.00%	÷1.077	×0.690	—	×1.050	0.00%
HBP% /PA	0.00%	—	×0.940	—	×1.050	0.00%
Singles /BIP	29.41%	÷1.061	×0.930	—	×1.050	27.07%
Doubles /BIP	5.88%	÷0.921	×0.830	—	×1.050	5.56%
Triples /BIP	0.00%	÷0.900	×0.970	—	×1.050	0.00%
Home runs /BIP	5.88%	÷1.212	×0.840	—	×1.050	4.28%

Factors used: league row IL. Park (home-season share, regressed): HR 142, 1B 112, 2B 84, 3B 80, K 92, BB 115 — 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).

Result: wOBA .348 → .282; ISO .182 → .132; BABIP .375 → .341. 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 AAACharlotte Knights · 228 PAwOBA .421 → .344 (−77)K% 13.2% → 16.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.16%	÷0.986	×1.200	—	—	16.01%
BB% (unintentional) /PA	5.26%	÷1.030	×0.690	—	×1.050	3.70%
HBP% /PA	0.88%	—	×0.940	—	×1.050	0.87%
Singles /BIP	27.07%	÷1.030	×0.930	×0.977	×1.050	25.06%
Doubles /BIP	7.18%	÷1.077	×0.830	×0.977	×1.050	5.68%
Triples /BIP	0.55%	÷1.150	×0.970	×0.977	×1.050	0.48%
Home runs /BIP	6.63%	÷1.319	×0.840	—	×1.050	4.43%

Factors used: league row IL. Park (home-season share, regressed): HR 164, 1B 106, 2B 115, 3B 130, K 97, BB 106 — 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 ×0.977.

Result: wOBA .421 → .344; ISO .242 → .171; BABIP .371 → .325. 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
#1Corey Dickersonlast yr '23 career totals — 11 seasons, 3,938 PA	5.9	3,938	136	30	280	323	476	-42	-38	12.7	12.5
/162	664	23	5	-7.1	-6.5	2.1	pk7: 12
#2Keith Moreland'78-'89 * career totals — 11 seasons, 5,082 PA	7.7	5,082	121	28	275*	334*	443*	-32	-33	10.5	10.6
/162	664	16	4	-4.2	-4.3	1.4	pk7: 11
#3Juan Riveralast yr '12 career totals — 10 seasons, 3,739 PA	5.6	3,739	130	17	274	324	443	-42	-22	9.5	10.4
/162	664	23	3	-7.5	-3.9	1.7	pk7: 11
#4Mike Marshall'81-'91 * career totals — 10 seasons, 3,908 PA	5.9	3,908	148	26	268*	321*	481*	-48	-39	9.3	9.4
/162	664	25	4	-8.2	-6.6	1.6	pk7: 9
#5Jay Gibbonslast yr '11 career totals — 9 seasons, 3,177 PA	4.8	3,177	127	2	260	315	453	-30	-30	7.7	8.1
/162	664	27	0	-6.3	-6.3	1.6	pk7: 9
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 7 projected seasons	3.4	2,266	97	3	269	317	458	-24	-32	8.1	8.1
/162	664	29	1	-6.9	-9.4	2.4	pk7: 8
#6Mike Ivie'71-'83 * career totals — 8 seasons, 2,962 PA	4.5	2,962	81	22	262*	319*	451*	-46	-22	5.8	6.7
/162	664	18	5	-10.2	-4.9	1.3	pk7: 8

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
Eloy Jiménez (OGILVIE)	30	50	45	35	40	248/302/351	103	302	2	1	21%	6%	86	+0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Brian Barden 2011 · MLB	30	51→53	43→45	39→45	43	245/296/353	108	309	10	6	24%	6%	84	+0.1	253/301/368	115	312	10	6	21%	6%	89	+0.5	252/301/351	99	306	7	2	19%	5%	84	+0.1
✕Guillermo Heredia 2020 · MLB	29	48→58	44→45	37→45	49	233/308/351	118	278	11	6	20%	8%	89	+0.5	224/301/365	141	283	14	6	25%	8%	90	+0.6	217/302/349	133	278	9	0	23%	8%	87	+0.2
✕Gregorio Petit 2015 · MLB	30	50→56	42→45	39→50	41	241/278/346	104	290	9	4	20%	4%	75	-0.5	227/261/327	100	280	8	5	21%	4%	64	-1.3	216/245/305	89	268	5	3	21%	4%	51	-1.0
✕Omar De La Torre 2010 · AAA	30	53→58	46→50	38→45	42	262/296/398	135	303	13	4	18%	4%	94	+0.9	241/273/353	112	287	11	3	19%	4%	75	-0.5	228/258/323	95	273	9	1	20%	3%	61	-0.9
✕Abraham Valencia 2010 · AAA	30	51→50	45	37→45	44	253/308/378	124	285	13	6	17%	4%	95	+0.9	243/299/370	127	273	14	6	17%	5%	90	+0.6	236/292/364	128	273	16	2	19%	4%	83	+0.1
✕Mike Vento 2007 · MLB	29	51	45	38→30	46	252/306/375	123	298	12	5	20%	6%	93	+0.8	232/279/356	124	285	12	6	22%	5%	78	-0.3	217/255/338	121	266	12	2	23%	4%	63	-0.6
✕Neil Sellers 2011 · AAA	29	48→57	44→50	37→40	45	238/286/359	121	277	12	3	19%	6%	82	-0.0	208/266/323	115	255	11	6	22%	7%	66	-1.1	147/216/250	103	172	9	0	21%	7%	30	-1.2
✕Kevin Flores 2015 · AAA	30	54→49	40	36→45	45	259/301/345	86	299	8	3	16%	5%	84	+0.1	235/278/313	78	288	5	5	20%	4%	68	-1.0	223/265/287	64	277	3	3	20%	4%	54	-1.0
✕Jose Castaneda 2015 · AAA	30	45→48	41→45	39→40	42	222/268/316	95	273	9	5	22%	5%	65	-1.2	204/257/306	102	276	11	8	29%	6%	59	-1.7	155/214/237	82	213	12	3	33%	6%	24	-1.3
✕Taylor Davis 2019 · AAA	29	50→53	39→45	37→40	48	237/287/325	87	275	7	3	16%	6%	74	-0.6	221/281/309	88	263	9	4	19%	7%	68	-1.0	209/274/265	56	248	6	0	18%	8%	54	-0.7
✕Brian Hernandez 2019 · AAA	30	53→59	42→45	42→40	44	256/299/358	102	309	9	5	20%	5%	86	+0.3	263/304/379	116	297	11	5	15%	5%	93	+0.8	282/318/393	111	313	10	1	13%	5%	97	+0.9
✕Ed Easley 2016 · AAA	30	48→42	41→45	37→40	47	231/289/331	100	274	9	4	19%	7%	76	-0.4	211/271/303	92	256	9	7	20%	7%	63	-1.3	157/211/186	29	187	4	0	18%	6%	13	-1.1
✕Wes Bankston 2014 · AAA	30	46→56	47→50	37→40	48	234/297/372	138	268	15	3	19%	7%	89	+0.5	231/294/355	124	287	12	7	23%	7%	84	+0.1	214/275/276	62	285	3	0	24%	7%	55	-0.4
✕Ruben Agramon 2015 · AAA	30	55→56	39→45	41→45	44	262/304/353	91	314	6	5	18%	5%	86	+0.3	236/273/304	68	308	4	6	24%	4%	63	-1.3	226/258/266	40	306	2	4	26%	3%	46	-1.3
✕Hernando Arredondo 2008 · AAA	31	48→53	43→50	38→50	43	237/274/346	109	268	11	6	17%	4%	74	-0.6	242/276/352	110	270	12	9	15%	4%	76	-0.4	252/280/369	116	280	14	10	15%	3%	78	-0.2
✕Ryan Rohlinger 2014 · AAA	30	45→47	41→50	42→40	49	218/285/310	92	262	8	5	20%	8%	70	-0.8	198/262/282	84	230	8	4	17%	7%	56	-1.9	172/239/240	68	193	7	0	15%	7%	36	-1.9
✕Pedro Diaz 2009 · AAA	30	54→47	43→45	40→45	47	261/311/379	118	292	10	6	15%	6%	95	+1.0	245/293/347	102	289	9	6	18%	5%	81	-0.1	237/280/323	86	285	8	3	19%	5%	69	-0.4
✕Ramiro Pena 2014 · MLB	29	49→55	41→45	39→50	46	236/287/336	101	287	9	5	21%	6%	76	-0.4	242/285/343	101	286	9	5	18%	5%	77	-0.3	254/287/354	100	286	9	5	14%	4%	80	-0.1
●Matt Hague 2015 · MLB	29	50→60	44→45	40→45	47	245/305/360	115	294	11	4	20%	7%	89	+0.5	263/321/377	114	303	11	6	16%	7%	99	+1.2	260/321/354	93	298	8	5	15%	7%	91	+0.5
✕Yancarlo Angulo 2017 · AAA	30	48→54	40→45	42→55	42	230/289/320	90	295	7	7	24%	5%	74	-0.6	225/288/320	95	278	7	9	20%	6%	74	-0.6	215/284/303	87	256	4	6	16%	7%	65	-0.6

Eloy Jiménez

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps