Miguel Vargas

3B Chicago White Sox

Age 27 R/R 6'2" / 225 lbs MLB HR +4% Svc 3.587 · Ctrl thru 2029

Overview

MLB40-MANArb-1FA 2030

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	24	AAAOklahoma City…	191	.290/.449/.566	8	8	139	—	.256/.380/.487
2024	24	MLBCWS	237	.150/.252/.257	5	3	46	-1.2
2025	25	MLBCWS	569	.234/.318/.401	16	6	102	1.2
2026	26	MLBCWS	704	.250/.366/.474	33	22	131	4.8
2027PROJ	27	MLBCWS	614	.247/.351/.450	25	17	125	3.0
2028PROJ	28	MLBCWS	614	.245/.349/.445	25	15	123	2.8
2029PROJ	29	MLBCWS	614	.242/.346/.438	24	12	120	2.5

Last 3 seasons WAR 4.7 · Next 3 projected WAR 8.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2029Service3.587First FA2030

2027Arb-1$6M2028Arb-2$10M2029Arb-3$14M

Skills · percentileStatcast 2024-2026

Speed79

xwOBA76

Bat Spd65

Barrel%64

Avg EV53

Form.248/.358/.421 · rolling true talent (45d window) · proj .245/.347/.446

CompsChris Young (age 27) · Eli Marrero (age 27) · Lars Nootbaar (age 26)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 129125vR 113

AVG/OBP/SLG.247 / .351 / .450

PA614

HR25

SB17

K%18

BB%13

BABIP265

ISO200

MLB%100%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$37M ctrl surplus

Tools · Recent Form · Splits · ContractCON 45 / POW 50

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT45

xAVG

350.239

POWER50

Barrel%

6410.3

Avg EV

5389.3

Bat Spd

6572.9

EYE60

scouting grade only

SPEED50

Sprint

7928.6

Recent Formrolling true talent ⓘ

K%17%▲15% over 60 PA (45d) · proj 18%

BB%14%▲15% over 121 PA (60d) · proj 13%

ISO.173▼.129 over 101 AB (60d) · proj .201

HR/BB5.6%·5.1% over 78 BBE (60d) · proj 5.9%

BABIP.266·.284 over 74 BIP (60d) · proj .264

SLASH.248/.358/.421·proj .245/.347/.446

Platoon Splits2024-2026 · 922 PA

vs LHP

vs RHP

Edge

281

641

—

wRC+

104

◀◀L

wOBA

322

291

◀L

ISO

179

149

◀◀L

BABIP

268

215

◀◀L

16.7%

19.8%

◀◀L

BB%

10.0%

11.2%

▶R

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

Status Arb-1

MLB Debut 2022

Service 3.587 yrs.days

Team Control Through 2029

First FA Year 2030

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-1	$6M	+3.0	$27M	+$21M
2028	Arb-2	$10M	+2.8	$22M	+$13M
2029	Arb-3	$14M	+2.5	$17M	+$6M
Totals		$30M		$67M	+$40M

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)
2018	18	A	Great Lakes Loons	—	89	75	16	1	1	0	10	20	1	0	0	213	314	253	567	40	281	22	11	262	45	—	—	—	—	—	—
2018	18	ROK	Ogden Raptors	—	140	125	50	14	2	2	13	16	2	7	1	400	464	592	1.056	192	449	11	9	463	114	—	—	—	—	—	—
2019	19	A+	Rancho Cucamonga Quakes	—	236	211	60	18	1	2	20	40	3	4	3	284	355	408	762	123	341	17	8	340	72	—	—	—	—	—	—
2019	19	A	Great Lakes Loons	—	323	280	91	20	2	5	35	43	3	9	1	325	406	464	870	139	363	13	11	383	104	—	—	—	—	—	—
2021	21	AA	Tulsa Drillers	—	370	327	105	16	1	16	36	57	2	7	1	321	392	523	915	202	344	15	10	398	113	—	—	—	—	—	—
2021	21	A+	Great Lakes Loons	—	172	156	49	11	1	7	9	32	5	4	0	314	371	532	903	218	353	19	5	392	102	—	—	—	—	—	—
2022	22	MLB	Los Angeles Dodgers	—	50	47	8	1	0	1	2	13	0	1	0	170	204	255	459	85	206	26	4	204	25	-4	+0	-1	-6	+1	-1.1
2022	22	AAA	Oklahoma City Dodgers	—	520	438	133	32	4	17	71	76	6	16	5	304	408	511	919	208	331	15	14	402	112	—	—	—	—	—	—
2023	23	MLB	Los Angeles Dodgers	—	304	256	50	15	4	7	38	61	4	3	2	195	308	367	675	172	224	20	12	301	95	-2	-0	-5	+2	+7	0.2
2023	23	AAA	Oklahoma City Dodgers	—	285	236	68	15	0	10	46	57	2	8	0	288	408	479	887	191	341	20	16	395	103	—	—	—	—	—	—
2024	24	MLB	Chicago White Sox	—	237	206	31	7	0	5	25	57	3	3	1	150	252	257	509	107	177	24	11	237	46	-15	+0	-4	+2	+5	-1.2
2024	24	AAA	Oklahoma City Baseball Club	—	191	145	42	14	1	8	38	33	4	8	6	290	449	566	1.015	276	315	17	20	434	139	—	—	—	—	—	—
2025	25	MLB	Chicago White Sox	—	569	504	118	32	2	16	56	100	6	6	0	234	318	401	719	167	261	18	10	321	102	+1	+1	-6	+2	+12	1.2
2026	26	MLB	Chicago White Sox	—	704	588	147	31	1	33	101	126	7	22	2	250	366	474	840	224	261	18	14	369	131	+26	+4	-1	+3	+15	4.8
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1864	1601	354	86	7	62	222	357	20	35	5	221	323	400	723	179	243	19	12	322	104	+9	+5	-16	+2	+40	4.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2018	18	A MLE	Great Lakes Loons	—	89	78	16	1	1	0	7	27	1	0	0	205	279	244	523	38	277	30	8	235	45	—	—	—	—	—	—
2018	18	ROK MLE	Ogden Raptors	—	140	130	38	10	1	1	8	23	2	7	1	292	343	408	751	115	352	16	6	336	114	—	—	—	—	—	—
2019	19	A+ MLE	Rancho Cucamonga Quakes	—	236	217	51	15	1	2	14	54	3	4	3	235	291	341	632	106	294	23	6	274	72	—	—	—	—	—	—
2019	19	A MLE	Great Lakes Loons	—	323	291	82	18	2	4	24	57	3	9	1	282	343	399	741	117	322	18	7	322	104	—	—	—	—	—	—
2021	21	AA MLE	Tulsa Drillers	—	370	338	94	14	1	14	25	72	2	7	1	278	332	450	781	172	304	19	7	335	113	—	—	—	—	—	—
2021	21	A+ MLE	Great Lakes Loons	—	172	159	42	9	1	6	6	43	5	4	0	264	312	447	758	182	307	25	3	319	102	—	—	—	—	—	—
2022	22	MLB MLE	Los Angeles Dodgers	—	50	47	8	1	0	1	2	13	0	1	0	170	204	255	459	85	206	26	4	206	25	-4	+0	-1	-6	+1	-1.1
2022	22	AAA MLE	Oklahoma City Dodgers	—	520	462	121	29	4	13	47	90	6	16	5	262	338	426	764	165	293	17	9	334	112	—	—	—	—	—	—
2023	23	MLB MLE	Los Angeles Dodgers	—	304	258	52	16	5	7	37	61	4	3	2	202	311	384	695	182	224	20	12	309	95	-2	-0	-5	+2	+7	0.2
2023	23	AAA MLE	Oklahoma City Dodgers	—	285	248	60	13	0	7	34	68	2	8	0	242	338	379	717	137	304	24	12	321	103	—	—	—	—	—	—
2024	24	MLB MLE	Chicago White Sox	—	237	206	31	7	0	5	25	57	3	3	1	150	252	257	509	107	177	24	11	236	46	-15	+0	-4	+2	+5	-1.2
2024	24	AAA MLE	Oklahoma City Baseball Club	—	191	156	40	13	1	7	27	40	4	8	6	256	380	487	867	231	282	21	14	373	139	—	—	—	—	—	—
2025	25	MLB MLE	Chicago White Sox	—	569	504	118	32	2	16	56	100	6	6	0	234	318	401	719	167	261	18	10	319	102	+1	+1	-6	+2	+12	1.2
2026	26	MLB MLE	Chicago White Sox	—	704	594	146	31	1	32	96	126	7	22	2	246	357	463	820	217	261	18	14	362	131	+26	+4	-1	+3	+15	4.8
2018	18	ROK MLE	2 teams	—	229	208	54	11	2	1	15	50	3	7	1	260	319	346	665	87	333	22	7	297	87	—	—	—	—	—	—
2018	18	ROK RAW	2 teams	—	229	200	66	15	3	2	23	36	3	7	1	330	407	465	872	135	390	16	10	385	87	—	—	—	—	—	—
2019	19	A MLE	2 teams	—	559	508	132	33	2	6	38	111	6	13	4	260	319	368	687	108	317	20	7	302	90	—	—	—	—	—	—
2019	19	A RAW	2 teams	—	559	491	151	38	3	7	55	83	6	13	4	308	384	440	824	132	354	15	10	365	90	—	—	—	—	—	—
2021	21	AA MLE	2 teams	—	542	497	135	22	2	20	31	114	7	11	1	272	323	445	768	173	311	21	6	330	109	—	—	—	—	—	—
2021	21	AA RAW	2 teams	—	542	483	154	27	2	23	45	89	7	11	1	319	385	526	911	207	347	16	8	396	109	—	—	—	—	—	—
2022	22	AAA MLE	2 teams	—	570	509	129	30	4	14	49	103	6	17	5	253	326	411	737	157	289	18	9	323	105	—	—	—	—	—	—
2022	22	AAA RAW	2 teams	—	570	485	141	33	4	18	73	89	6	17	5	291	390	487	877	196	320	16	13	385	105	—	—	—	—	—	—
2023	23	MLB MLE	2 teams	—	589	506	112	29	5	14	71	129	6	11	2	221	324	381	706	160	266	22	12	315	99	-1	+1	-5	+2	+13	1.1
2023	23	MLB RAW	2 teams	—	589	492	118	30	4	17	84	118	6	11	2	240	357	421	778	181	279	20	14	346	99	-1	+1	-5	+2	+13	1.1
2024	24	MLB MLE	2 teams	—	428	362	71	20	1	12	52	97	7	11	7	196	309	356	665	160	227	23	12	297	87	-6	-1	-4	+2	+9	0.0
2024	24	MLB RAW	2 teams	—	428	351	73	21	1	13	63	90	7	11	7	208	340	385	724	177	235	21	15	325	87	-6	-1	-4	+2	+9	0.0
2025	25	MLB MLE	Chicago White Sox	—	569	504	118	32	2	16	56	100	6	6	0	234	318	401	719	167	261	18	10	319	102	+1	+1	-6	+2	+12	1.2
2025	25	MLB RAW	Chicago White Sox	—	569	504	118	32	2	16	56	100	6	6	0	234	318	401	719	167	261	18	10	321	102	+1	+1	-6	+2	+12	1.2
2026	26	MLB MLE	Chicago White Sox	—	704	594	146	31	1	32	96	126	7	22	2	246	357	463	820	217	257	18	14	362	131	+26	+4	-1	+3	+15	4.8
2026	26	MLB RAW	Chicago White Sox	—	704	588	147	31	1	33	101	126	7	22	2	250	366	474	840	224	261	18	14	369	131	+26	+4	-1	+3	+15	4.8
2018	18	ROK MLE	2 teams	—	229	209	54	11	2	1	15	50	3	7	1	258	319	344	663	86	323	22	7	297	87	—	—	—	—	—	—
2019	19	A MLE	2 teams	—	559	510	132	33	2	6	38	111	6	13	4	259	319	367	686	108	310	20	7	302	90	—	—	—	—	—	—
2021	21	AA MLE	2 teams	—	542	499	135	22	2	20	31	114	7	11	1	271	323	443	766	172	305	21	6	330	109	—	—	—	—	—	—
2022	22	AAA MLE	2 teams	—	570	510	129	30	4	14	49	103	6	17	5	253	326	410	736	157	285	18	9	323	105	—	—	—	—	—	—
2023	23	MLB MLE	2 teams	—	589	507	112	29	5	14	71	129	6	11	2	221	324	381	705	160	263	22	12	315	99	—	—	—	—	—	—
2024	24	MLB MLE	2 teams	—	428	366	71	20	1	12	52	97	7	11	7	194	309	352	661	158	224	23	12	297	87	—	—	—	—	—	—
2025	25	MLB MLE	Chicago White Sox	—	569	502	118	32	2	16	56	100	6	6	0	235	318	402	720	167	261	18	10	319	102	—	—	—	—	—	—
2026	26	MLB MLE	Chicago White Sox	—	704	595	146	31	1	32	96	126	7	22	2	245	357	462	819	217	261	18	14	362	131	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	24	MLB MLE	2 teams	—	428	366	71	20	1	12	52	97	7	11	7	194	309	352	661	158	224	23	12	297	87	—	—	—	—	—	—
2025	25	MLB MLE	Chicago White Sox	—	569	502	118	32	2	16	56	100	6	6	0	235	318	402	720	167	261	18	10	319	102	—	—	—	—	—	—
2026	26	MLB MLE	Chicago White Sox	—	704	595	146	31	1	32	96	126	7	22	2	245	357	462	819	217	261	18	14	362	131	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	27	MLB MLE	CWS	100%	624	534	130	28	1	25	79	113	6	17	4	245	350	446	795	200	264	18	13	352	125	+18	+2	-6	+2	+14	3.0
▸ 2027 — real world (MLB)
2027	27	MLB CTX	CWS	100%	614	525	129	28	1	25	78	111	6	17	4	247	351	450	801	203	265	18	13	354	125	+18	+2	-6	+2	+13	3.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	28	MLB MLE	CWS	100%	614	525	127	28	1	24	78	113	6	15	3	243	348	441	788	197	263	18	13	349	123	+17	+2	-6	+2	+13	2.8
2029	29	MLB MLE	CWS	100%	614	526	127	28	1	24	77	115	6	12	3	240	345	434	778	193	261	19	13	346	120	+15	+1	-7	+2	+13	2.5
2030	30	MLB MLE	CWS	100%	614	526	124	27	1	23	77	117	6	9	3	237	341	425	765	188	259	19	13	341	117	+12	+1	-8	+2	+13	2.1
2031	31	MLB MLE	CWS	100%	614	527	123	27	1	23	76	119	6	5	2	232	335	413	748	181	255	19	12	334	112	+9	+0	-8	+2	+13	1.6
2032	32	MLB MLE	CWS	100%	594	511	115	25	0	21	73	118	5	1	1	225	328	397	725	173	249	20	12	325	106	+4	-0	-9	+2	+13	1.0
2033	33	MLB MLE	CWS	100%	492	425	91	19	0	16	60	100	4	0	1	216	319	378	697	162	242	20	12	314	99	-1	-0	-9	+2	+11	0.3
2034	34	MLB MLE	CWS	100%	436	378	78	16	0	14	52	92	3	0	1	206	308	356	664	150	233	21	12	301	90	-5	-0	-9	+2	+9	-0.4
2028	28	MLB CTX	CWS	100%	614	525	128	28	1	25	78	113	6	15	3	245	349	445	794	200	264	18	13	351	123	+17	+2	-6	+2	+13	2.8
2029	29	MLB CTX	CWS	100%	614	526	127	28	1	24	77	115	6	12	3	242	346	438	784	196	262	19	13	348	120	+15	+1	-7	+2	+13	2.5
2030	30	MLB CTX	CWS	100%	614	526	125	27	1	24	77	117	6	9	3	238	342	429	770	191	260	19	13	342	117	+12	+1	-8	+2	+13	2.1
2031	31	MLB CTX	CWS	100%	614	527	123	27	1	23	76	119	6	5	2	233	336	417	753	184	256	19	12	336	112	+9	+0	-8	+2	+13	1.6
2032	32	MLB CTX	CWS	100%	594	511	115	25	0	21	73	118	5	1	1	226	329	401	730	175	250	20	12	327	106	+4	-0	-9	+2	+13	1.0
2033	33	MLB CTX	CWS	100%	492	425	92	19	0	17	60	100	4	0	1	218	320	382	702	164	243	20	12	316	99	-1	-0	-9	+2	+11	0.3
2034	34	MLB CTX	CWS	100%	436	378	78	16	0	14	52	92	3	0	1	207	309	360	668	153	234	21	12	302	90	-5	-0	-9	+2	+9	-0.4
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	5842	5019	1142	256	11	210	715	1131	56	77	19	228	330	408	739	181	251	19	12	330	108	+59	+8	-72	+16	+127	14.1
/ 162G	—	A+C		—	650	558	126	28	1	23	80	126	6	9	2	226	329	403	732	177	249	19	12	330	108	+7	+1	-8	+2	+14	1.6
Career	—	MLE		—	8782	7631	1811	406	24	285	979	1715	90	157	40	237	331	409	740	172	268	20	11	328	108	+77	+10	-77	+18	+140	17.1
/ 162G	—	MLE		—	650	565	134	30	2	21	72	127	7	12	3	237	331	409	740	172	268	20	11	328	108	+8	+1	-8	+2	+14	1.7

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.

2024 AAAOklahoma City Baseball Club · 191 PAwOBA .432 → .373 (−60)K% 17.3% → 20.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.28%	÷0.990	×1.200	—	—	20.93%
BB% (unintentional) /PA	19.90%	÷1.021	×0.690	—	×1.033	13.88%
HBP% /PA	2.09%	—	×0.940	—	×1.033	2.03%
Singles /BIP	16.96%	÷0.977	×0.930	×0.950	×1.033	15.85%
Doubles /BIP	12.50%	÷0.930	×0.830	×0.950	×1.033	10.95%
Triples /BIP	0.89%	÷1.126	×0.970	×0.950	×1.033	0.75%
Home runs /BIP	7.14%	÷0.896	×0.700	—	×1.033	5.76%

Factors used: league row International League. Park (home-season share, regressed): HR 79, 1B 95, 2B 86, 3B 125, K 98, BB 104 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .432 → .373; ISO .276 → .247; BABIP .315 → .282. 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 AAAOklahoma City Dodgers · 285 PAwOBA .386 → .321 (−65)K% 20.0% → 23.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.00%	÷1.003	×1.200	—	—	23.93%
BB% (unintentional) /PA	16.14%	÷0.976	×0.690	—	×1.048	11.96%
HBP% /PA	0.70%	—	×0.940	—	×1.048	0.69%
Singles /BIP	24.02%	÷1.021	×0.930	×0.968	×1.048	22.19%
Doubles /BIP	8.38%	÷0.983	×0.830	×0.968	×1.048	7.17%
Triples /BIP	0.00%	÷1.150	×0.970	×0.968	×1.048	0.00%
Home runs /BIP	5.59%	÷1.006	×0.700	—	×1.048	4.07%

Factors used: league row International League. Park (home-season share, regressed): HR 101, 1B 104, 2B 97, 3B 130, K 101, BB 95 — 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 ×0.968.

Result: wOBA .386 → .321; ISO .191 → .149; BABIP .341 → .304. 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 AAAOklahoma City Dodgers · 520 PAwOBA .395 → .334 (−62)K% 14.6% → 17.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.62%	÷1.009	×1.200	—	—	17.38%
BB% (unintentional) /PA	13.46%	÷1.073	×0.690	—	×1.050	9.09%
HBP% /PA	1.15%	—	×0.940	—	×1.050	1.14%
Singles /BIP	22.10%	÷1.027	×0.930	×0.950	×1.050	19.96%
Doubles /BIP	8.84%	÷0.958	×0.830	×0.950	×1.050	7.64%
Triples /BIP	1.10%	÷0.955	×0.970	×0.950	×1.050	1.12%
Home runs /BIP	4.70%	÷0.997	×0.700	—	×1.050	3.46%

Factors used: league row International League. Park (home-season share, regressed): HR 99, 1B 105, 2B 92, 3B 91, K 102, 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .395 → .334; ISO .208 → .174; BABIP .331 → .293. 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 AATulsa Drillers · 370 PAwOBA .392 → .335 (−57)K% 15.4% → 19.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.41%	÷0.966	×1.220	—	—	19.45%
BB% (unintentional) /PA	9.73%	÷1.051	×0.690	—	×1.042	6.66%
HBP% /PA	0.54%	—	×0.850	—	×1.042	0.48%
Singles /BIP	26.67%	÷1.030	×0.940	×0.950	×1.042	24.08%
Doubles /BIP	5.93%	÷1.026	×0.870	×0.950	×1.042	4.97%
Triples /BIP	0.37%	÷0.900	×0.920	×0.950	×1.042	0.37%
Home runs /BIP	5.93%	÷0.935	×0.780	—	×1.042	5.15%

Factors used: level-wide AA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 87, 1B 106, 2B 105, 3B 80, K 93, BB 110 — 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 ×0.950.

Result: wOBA .392 → .335; ISO .202 → .176; BABIP .344 → .304. 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 A+Great Lakes Loons · 172 PAwOBA .385 → .319 (−67)K% 18.6% → 24.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.60%	÷1.013	×1.350	—	—	24.79%
BB% (unintentional) /PA	5.23%	÷1.042	×0.710	—	×1.012	3.61%
HBP% /PA	2.91%	—	×0.810	—	×1.012	2.38%
Singles /BIP	24.19%	÷0.978	×0.910	×0.950	×1.012	21.65%
Doubles /BIP	8.87%	÷0.952	×0.830	×0.950	×1.012	7.43%
Triples /BIP	0.81%	÷1.150	×0.820	×0.950	×1.012	0.55%
Home runs /BIP	5.65%	÷0.930	×0.830	—	×1.012	5.10%

Factors used: level-wide A+ factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 86, 1B 96, 2B 90, 3B 130, K 103, BB 108 — 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 ×0.950.

Result: wOBA .385 → .319; ISO .218 → .182; BABIP .353 → .307. 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 AGreat Lakes Loons · 323 PAwOBA .379 → .322 (−56)K% 13.3% → 17.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.31%	÷1.035	×1.360	—	—	17.49%
BB% (unintentional) /PA	10.53%	÷1.031	×0.690	—	×1.030	7.26%
HBP% /PA	0.93%	—	×0.780	—	×1.030	0.75%
Singles /BIP	27.00%	÷1.002	×0.920	×0.950	×1.030	24.25%
Doubles /BIP	8.44%	÷0.934	×0.830	×0.950	×1.030	7.34%
Triples /BIP	0.84%	÷1.061	×0.910	×0.950	×1.030	0.71%
Home runs /BIP	2.11%	÷1.018	×0.800	—	×1.030	1.71%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 104, 1B 100, 2B 87, 3B 112, K 107, BB 106 — applied at half strength. Age: age 20 vs a level average of 22.0 → +3.0% on BB/HBP/hit rates (2.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .379 → .322; ISO .139 → .119; BABIP .363 → .322. 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 A+Rancho Cucamonga Quakes · 236 PAwOBA .330 → .274 (−56)K% 16.9% → 22.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.95%	÷0.991	×1.340	—	—	22.92%
BB% (unintentional) /PA	7.63%	÷0.948	×0.710	—	×1.042	5.96%
HBP% /PA	1.27%	—	×0.790	—	×1.042	1.05%
Singles /BIP	22.81%	÷1.043	×0.910	×0.950	×1.042	19.69%
Doubles /BIP	10.53%	÷0.935	×0.820	×0.950	×1.042	9.14%
Triples /BIP	0.58%	÷1.049	×0.760	×0.950	×1.042	0.42%
Home runs /BIP	1.17%	÷0.969	×0.920	—	×1.042	1.16%

Factors used: league row CAL. Park (home-season share, regressed): HR 94, 1B 109, 2B 87, 3B 110, K 98, BB 90 — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .330 → .274; ISO .123 → .105; BABIP .341 → .294. 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 ROKOgden Raptors · 140 PAwOBA .451 → .336 (−115)K% 11.4% → 16.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.43%	÷1.000	×1.440	—	—	16.46%
BB% (unintentional) /PA	9.29%	÷1.000	×0.610	—	×1.008	5.71%
HBP% /PA	1.43%	—	×0.720	—	×1.008	1.04%
Singles /BIP	29.36%	÷1.000	×0.820	×0.994	×1.008	24.11%
Doubles /BIP	12.84%	÷1.000	×0.720	×0.994	×1.008	9.26%
Triples /BIP	1.83%	÷1.000	×0.720	×0.994	×1.008	1.32%
Home runs /BIP	1.83%	÷1.000	×0.750	—	×1.008	1.39%

Factors used: league row PIO. Park (home-season share, regressed): no park row on file (treated as neutral) — 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 ×0.994.

Result: wOBA .451 → .336; ISO .192 → .138; BABIP .449 → .352. 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
#1Howard Johnson'82-'95 * career totals — 14 seasons, 5,715 PA	8.6	5,715	228	231	246*	339*	473*	+18	-66	28.2	27.4
/162	664	26	27	+2.1	-7.7	3.3	pk7: 27
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 13 projected seasons	9.7	6,456	232	94	230	329	411	+23	-41	28.0	26.4
/162	664	24	10	+2.4	-4.2	2.9	pk7: 25
#2Todd Zeile'89-'04 * career totals — 16 seasons, 8,649 PA	13.0	8,649	253	53	255*	335*	422*	-4	-36	28.9	24.7
/162	664	19	4	-0.3	-2.7	2.2	pk7: 21
#3Rickie 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
#4Denis Menke'62-'74 * career totals — 12 seasons, 5,934 PA	8.9	5,934	101	34	250*	346*	403*	+30	-23	22.7	21.7
/162	664	11	4	+3.4	-2.6	2.5	pk7: 21
#5Kelly 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
#6Jeimer Candelariolast yr '25 career totals — 9 seasons, 3,576 PA	5.4	3,576	110	19	237	316	412	+8	-5	12.7	13.0
/162	664	20	4	+1.6	-0.9	2.4	pk7: 13

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
Miguel Vargas (OGILVIE)	27	45	50	50	60	243/347/442	199	264	25	17	18%	13%	125	+3.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Chris Young 2011 · MLB	27	47→48	54→60	52→55	54	242/323/430	188	287	21	18	24%	11%	112	+2.2	229/313/411	182	268	21	18	22%	11%	104	+1.6	240/309/422	183	276	21	9	21%	8%	107	+1.0
●Eli Marrero 2001 · MLB	27	46→48	55	57→50	52	241/316/425	183	251	23	17	16%	8%	109	+2.0	247/299/418	171	268	20	15	16%	7%	100	+1.3	266/317/443	178	290	21	13	17%	7%	114	+1.1
✕Lars Nootbaar 2024 · MLB	26	48→53	54→55	51→50	60	249/345/430	181	286	21	11	21%	13%	120	+2.8	238/330/393	155	281	17	8	21%	12%	106	+1.8	229/324/373	144	270	16	6	21%	12%	101	+1.1
✕Jordan Luplow 2021 · MLB	27	48→49	55→65	46→50	55	248/334/442	194	290	21	9	22%	11%	119	+2.7	214/308/416	202	248	26	8	25%	11%	104	+1.6	190/287/379	189	212	26	7	25%	11%	88	+0.2
●José Cruz Jr. 2001 · MLB	27	45→50	59→65	51→50	54	244/319/459	215	261	26	13	19%	10%	118	+2.6	254/324/467	213	285	26	16	20%	9%	121	+2.9	253/331/455	202	285	24	15	20%	10%	121	+2.9
★Rickie Weeks Jr. 2010 · MLB	27	48→58	53→55	55	56	246/345/433	187	290	20	18	22%	11%	121	+2.9	262/350/450	188	319	21	11	23%	10%	126	+3.2	256/348/440	184	314	21	11	24%	10%	125	+3.4
●Wil Myers 2018 · MLB	27	49→54	57→60	53→55	51	252/331/458	206	306	25	20	26%	10%	122	+2.9	252/324/459	207	330	24	18	29%	9%	119	+2.7	257/334/461	204	343	24	13	30%	10%	124	+2.1
●Gleyber Torres 2024 · MLB	27	51→55	52→60	46→50	53	262/329/429	166	292	20	12	18%	9%	114	+2.3	259/342/395	136	301	16	6	18%	11%	111	+2.1	256/349/376	120	302	14	3	19%	12%	110	+2.0
✕Daulton Varsho 2023 · MLB	27	43→50	58→60	51→50	48	234/300/439	205	265	27	14	24%	8%	106	+1.8	223/289/419	196	262	24	13	25%	8%	97	+1.1	215/282/416	201	251	25	12	26%	8%	95	+0.7
●Chas McCormick 2022 · MLB	27	48→52	54→55	48→55	47	246/318/417	171	309	23	11	28%	8%	107	+1.9	249/325/421	172	315	23	14	27%	9%	111	+2.1	242/322/405	163	303	22	17	26%	9%	107	+1.2
●Matt Joyce 2012 · MLB	27	50→52	55→60	50	53	254/329/448	195	295	21	12	22%	10%	118	+2.7	244/331/424	180	284	20	8	21%	11%	114	+2.3	234/345/446	212	261	26	3	21%	14%	124	+1.9
✕Gregory Polanco 2019 · MLB	27	48→57	57→60	53→55	51	251/318/458	207	277	24	13	20%	9%	116	+2.5	227/295/413	186	281	23	14	27%	9%	98	+1.2	208/275/375	168	263	22	17	29%	8%	82	+0.0
✕Bobby Estalella 2002 · MLB	27	44	54→60	52→45	54	228/321/423	194	280	21	6	26%	11%	110	+2.1	223/309/432	209	277	26	7	28%	10%	108	+1.9	195/288/425	230	228	30	4	30%	11%	100	+0.3
✕Paul DeJong 2021 · MLB	27	46→51	55→65	44→45	49	240/318/427	187	283	24	7	24%	9%	110	+2.1	208/282/386	178	251	25	7	28%	8%	88	+0.4	223/275/397	174	292	25	5	32%	5%	88	+0.3
●Josh Reddick 2014 · MLB	27	44→54	56→60	52→50	51	237/303/432	195	262	24	10	21%	8%	105	+1.7	262/320/439	177	284	21	9	16%	8%	113	+2.3	280/336/438	158	299	17	9	13%	8%	119	+2.4
●Dansby Swanson 2021 · MLB	27	50→55	52→55	49→55	48	252/318/424	171	306	19	11	24%	8%	109	+2.0	257/320/439	182	318	22	11	25%	8%	114	+2.3	254/320/434	179	313	23	11	25%	8%	113	+2.5
●Yasiel Puig 2018 · MLB	27	50→60	56→60	47→55	52	263/330/459	195	289	24	12	19%	9%	122	+2.9	264/326/466	202	297	26	17	20%	8%	122	+2.9	265/325/469	204	300	26	19	21%	7%	124	+2.7
●Jurickson Profar 2021 · MLB	28	47→55	54→55	54→50	54	244/320/428	183	253	22	13	15%	8%	111	+2.1	243/329/380	137	275	13	9	16%	10%	103	+1.5	259/353/423	164	286	18	7	16%	11%	123	+2.7
●Willy Adames 2024 · MLB	28	44→54	56→60	44→50	50	233/310/432	199	282	24	6	26%	10%	108	+1.9	238/317/440	202	287	26	12	26%	10%	112	+2.2	238/316/442	205	284	27	12	26%	10%	114	+2.4
●Sean Murphy 2021 · MLB	26	46→49	58→60	46→30	52	242/326/449	207	287	25	4	25%	10%	118	+2.6	239/328/436	197	281	24	2	23%	10%	116	+2.5	239/334/439	199	278	24	0	22%	10%	120	+2.3

Miguel Vargas

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps