Alex Verdugo

LF Atlanta Braves

Age 31 L/L 6'0" / 209 lbs MLB 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	27	MLBBOS	602	.264/.327/.421	13	5	104	0.7
2024	28	MLBNYY	621	.233/.296/.356	13	2	80	-0.9
2025	29	AAAATL	33	.207/.303/.448	2	1	51	—	.161/.212/.290
2025	29	MLBATL	213	.239/.296/.289	0	1	69	-1.1
2026	30	No MLB games played
2027PROJ	31	MLBATL	289	.256/.318/.377	5	3	97	0.3
2028PROJ	32	MLBATL	266	.249/.310/.361	4	1	90	-0.4

Last 3 seasons WAR -1.4 · Next 2 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service10.000First FA2028

2027Ext / FA-deal$2M

Skills · percentileStatcast 2023-2025

xwOBA57

Avg EV47

Barrel%25

Speed22

Bat Spd13

CompsDaniel Fornes (age 30) · Ricardo Nanita (age 30) · Jeremy Reed (age 30)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 8397vR 102

AVG/OBP/SLG.256 / .318 / .377

PA289

HR5

K%16

BB%8

BABIP292

ISO118

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · Contract

ToolsStatcast %ile · 2023-2025

CONTACT

xAVG

620.261

POWER

Barrel%

255.0

Avg EV

4788.9

Bat Spd

1367.4

SPEED

Sprint

2226.1

Platoon Splits2024-2025 · 834 PA

vs LHP

vs RHP

Edge

223

611

—

wRC+

▶▶R

wOBA

261

289

▶R

ISO

046

125

▶▶R

BABIP

253

263

▶R

16.6%

14.2%

▶R

BB%

9.9%

6.7%

◀◀L

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	$2M	+0.3	$1M	-$1M
Totals		$2M		$1M	-$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)
2014	18	ROK	Ogden Raptors	—	216	190	67	15	3	3	20	18	4	11	0	353	425	511	936	158	374	8	9	411	107	—	—	—	—	—	—
2015	19	A+	Rancho Cucamonga Quakes	—	96	91	35	9	2	4	4	12	0	1	0	385	411	659	1.070	275	408	12	4	458	152	—	—	—	—	—	—
2015	19	A	Great Lakes Loons	—	444	421	123	23	2	5	17	53	2	13	5	292	323	392	715	100	323	12	4	317	72	—	—	—	—	—	—
2016	20	AA	Tulsa Drillers	—	529	477	130	23	1	13	44	67	4	2	6	273	339	407	746	134	292	13	8	333	89	—	—	—	—	—	—
2016	20	INTL	Glendale Desert Dogs	—	47	43	6	2	1	0	4	8	0	0	0	140	213	233	445	93	171	17	9	206	26	—	—	—	—	—	—
2017	21	MLB	Los Angeles Dodgers	—	25	23	4	0	0	1	2	4	0	0	1	174	240	304	544	130	167	16	8	248	54	-1	-0	+0	+2	+1	0.1
2017	21	AAA	Oklahoma City Dodgers	—	495	433	136	27	4	6	52	50	4	9	3	314	393	436	829	122	340	10	11	369	105	—	—	—	—	—	—
2018	22	MLB	Los Angeles Dodgers	—	86	77	20	6	0	1	8	14	0	0	0	260	329	377	706	117	306	16	9	315	105	+1	+0	-0	-5	+2	-0.3
2018	22	AAA	Oklahoma City Dodgers	—	379	343	113	19	0	10	34	47	1	8	2	329	392	472	864	143	359	12	9	384	110	—	—	—	—	—	—
2019	23	MLB	Los Angeles Dodgers	—	377	343	101	22	2	12	26	49	2	4	1	294	348	475	823	181	309	13	7	358	132	+14	+0	+3	+1	+8	2.7
2020	24	MLB	Boston Red Sox	—	221	201	62	16	0	6	17	45	2	4	0	308	368	478	846	169	371	20	8	374	129	+8	+1	+2	-2	+5	1.3
2021	25	MLB	Boston Red Sox	—	604	544	157	32	2	13	51	96	4	6	2	289	354	426	780	138	327	16	8	347	111	+8	+0	-6	-6	+13	0.9
2022	26	MLB	Boston Red Sox	—	644	593	166	39	1	11	42	86	3	1	3	280	331	405	735	125	309	13	7	326	99	-1	-1	-7	-7	+14	-0.2
2023	27	MLB	Boston Red Sox	—	602	546	144	37	5	13	45	93	6	5	3	264	327	421	748	158	294	15	7	331	104	+3	-0	-2	-6	+13	0.7
2024	28	MLB	New York Yankees	—	621	559	130	28	1	13	49	93	1	2	1	233	296	356	652	123	253	15	8	289	80	-15	+0	-1	-7	+13	-0.9
2025	29	MLB	Atlanta Braves	—	213	197	47	10	0	0	14	31	2	1	0	239	296	289	585	51	283	15	7	270	69	-8	+0	-5	-3	+5	-1.1
2025	29	AAA	Gwinnett Stripers	—	33	29	6	1	0	2	4	4	0	1	0	207	303	448	751	241	174	12	12	332	51	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	3393	3083	831	190	11	70	254	511	20	23	11	270	329	406	736	137	300	15	7	326	107	+27	+0	-17	-33	+74	5.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2014	18	ROK MLE	Ogden Raptors	—	216	197	57	12	2	2	13	26	4	11	0	289	346	401	747	112	317	12	6	327	107	—	—	—	—	—	—
2015	19	A+ MLE	Rancho Cucamonga Quakes	—	96	92	30	7	1	4	3	17	0	1	0	326	347	554	902	228	364	18	3	393	152	—	—	—	—	—	—
2015	19	A MLE	Great Lakes Loons	—	444	427	112	19	2	5	11	69	2	13	5	262	284	351	635	89	299	16	2	274	72	—	—	—	—	—	—
2016	20	AA MLE	Tulsa Drillers	—	529	490	126	22	1	11	31	82	4	2	6	257	307	373	680	116	285	16	6	300	89	—	—	—	—	—	—
2017	21	MLB MLE	Los Angeles Dodgers	—	25	23	4	0	0	1	2	4	0	0	1	174	240	304	544	130	167	16	8	248	54	-1	-0	+0	+2	+1	0.1
2017	21	AAA MLE	Oklahoma City Dodgers	—	495	447	129	23	3	5	38	64	4	9	3	289	350	387	737	98	319	13	8	324	105	—	—	—	—	—	—
2018	22	MLB MLE	Los Angeles Dodgers	—	86	77	20	6	0	1	8	14	0	0	0	260	329	377	706	117	306	16	9	324	105	+1	+0	-0	-5	+2	-0.3
2018	22	AAA MLE	Oklahoma City Dodgers	—	379	354	106	16	0	8	23	63	1	8	2	299	344	412	756	113	343	17	6	331	110	—	—	—	—	—	—
2019	23	MLB MLE	Los Angeles Dodgers	—	377	344	103	23	2	12	25	49	2	4	1	299	350	483	833	183	309	13	7	363	132	+14	+0	+3	+1	+8	2.7
2020	24	MLB MLE	Boston Red Sox	—	221	202	59	14	0	6	16	45	2	4	0	292	350	450	800	158	371	20	7	359	129	+8	+1	+2	-2	+5	1.3
2021	25	MLB MLE	Boston Red Sox	—	604	550	151	28	2	13	45	96	4	6	2	275	334	404	738	129	327	16	7	332	111	+8	+0	-6	-6	+13	0.9
2022	26	MLB MLE	Boston Red Sox	—	644	595	160	35	1	11	40	86	3	1	3	269	318	387	705	118	309	13	6	314	99	-1	-1	-7	-7	+14	-0.2
2023	27	MLB MLE	Boston Red Sox	—	602	547	140	33	6	13	44	93	6	5	3	256	318	410	728	154	294	15	7	321	104	+3	-0	-2	-6	+13	0.7
2024	28	MLB MLE	New York Yankees	—	621	559	129	28	1	12	49	93	1	2	1	231	294	349	643	118	253	15	8	286	80	-15	+0	-1	-7	+13	-0.9
2025	29	MLB MLE	Atlanta Braves	—	213	197	47	10	0	0	14	31	2	1	0	239	296	289	585	51	283	15	7	270	69	-8	+0	-5	-3	+5	-1.1
2025	29	AAA MLE	Gwinnett Stripers	—	33	31	5	1	0	1	2	5	0	1	0	161	212	290	502	129	150	15	6	244	51	—	—	—	—	—	—
2014	18	ROK MLE	Ogden Raptors	—	216	197	57	12	2	2	13	26	4	11	0	289	346	401	747	112	322	12	6	327	107	—	—	—	—	—	—
2014	18	ROK RAW	Ogden Raptors	—	216	190	67	15	3	3	20	18	4	11	0	353	425	511	936	158	374	8	9	411	107	—	—	—	—	—	—
2015	19	A MLE	2 teams	—	540	519	143	26	3	9	14	86	2	14	5	276	297	389	686	114	314	16	3	295	86	—	—	—	—	—	—
2015	19	A RAW	2 teams	—	540	512	158	32	4	9	21	65	2	14	5	309	338	439	778	131	338	12	4	342	86	—	—	—	—	—	—
2016	20	AA MLE	2 teams	—	576	535	138	24	1	12	33	89	4	2	6	258	306	374	680	116	288	15	6	300	89	—	—	—	—	—	—
2016	20	AA RAW	2 teams	—	576	520	136	25	2	13	48	75	4	2	6	262	329	392	721	131	282	13	8	322	89	—	—	—	—	—	—
2017	21	AAA MLE	2 teams	—	520	470	133	23	3	6	40	68	4	9	4	283	344	383	727	100	317	13	8	320	103	—	—	—	—	—	—
2017	21	AAA RAW	2 teams	—	520	456	140	27	4	7	54	54	4	9	4	307	385	430	815	123	333	10	10	363	103	—	—	—	—	—	—
2018	22	AAA MLE	2 teams	—	465	431	126	22	0	9	31	77	1	8	2	292	341	406	747	114	338	17	7	330	109	—	—	—	—	—	—
2018	22	AAA RAW	2 teams	—	465	420	133	25	0	11	42	61	1	8	2	317	380	455	835	138	350	13	9	372	109	—	—	—	—	—	—
2019	23	MLB MLE	Los Angeles Dodgers	—	377	344	103	23	2	12	25	49	2	4	1	299	350	483	833	183	315	13	7	363	132	+14	+0	+3	+1	+8	2.7
2019	23	MLB RAW	Los Angeles Dodgers	—	377	343	101	22	2	12	26	49	2	4	1	294	348	475	823	181	309	13	7	358	132	+14	+0	+3	+1	+8	2.7
2020	24	MLB MLE	Boston Red Sox	—	221	202	59	14	0	6	16	45	2	4	0	292	350	450	800	158	349	20	7	359	129	+8	+1	+2	-2	+5	1.3
2020	24	MLB RAW	Boston Red Sox	—	221	201	62	16	0	6	17	45	2	4	0	308	368	478	846	169	371	20	8	374	129	+8	+1	+2	-2	+5	1.3
2021	25	MLB MLE	Boston Red Sox	—	604	550	151	28	2	13	45	96	4	6	2	275	334	404	738	129	309	16	7	332	111	+8	+0	-6	-6	+13	0.9
2021	25	MLB RAW	Boston Red Sox	—	604	544	157	32	2	13	51	96	4	6	2	289	354	426	780	138	327	16	8	347	111	+8	+0	-6	-6	+13	0.9
2022	26	MLB MLE	Boston Red Sox	—	644	595	160	35	1	11	40	86	3	1	3	269	318	387	705	118	296	13	6	314	99	-1	-1	-7	-7	+14	-0.2
2022	26	MLB RAW	Boston Red Sox	—	644	593	166	39	1	11	42	86	3	1	3	280	331	405	735	125	309	13	7	326	99	-1	-1	-7	-7	+14	-0.2
2023	27	MLB MLE	Boston Red Sox	—	602	547	140	33	6	13	44	93	6	5	3	256	318	410	728	154	285	15	7	321	104	+3	-0	-2	-6	+13	0.7
2023	27	MLB RAW	Boston Red Sox	—	602	546	144	37	5	13	45	93	6	5	3	264	327	421	748	158	294	15	7	331	104	+3	-0	-2	-6	+13	0.7
2024	28	MLB MLE	New York Yankees	—	621	559	129	28	1	12	49	93	1	2	1	231	294	349	643	118	252	15	8	286	80	-15	+0	-1	-7	+13	-0.9
2024	28	MLB RAW	New York Yankees	—	621	559	130	28	1	13	49	93	1	2	1	233	296	356	652	123	253	15	8	289	80	-15	+0	-1	-7	+13	-0.9
2025	29	MLB MLE	2 teams	—	246	228	52	11	0	1	16	36	2	2	0	228	285	289	574	61	267	15	7	267	67	-10	+0	-5	-3	+5	-1.2
2025	29	MLB RAW	2 teams	—	246	226	53	11	0	2	18	35	2	2	0	235	297	310	606	75	270	14	7	279	67	-10	+0	-5	-3	+5	-1.2
2014	18	ROK MLE	Ogden Raptors	—	216	197	57	12	2	2	13	26	4	11	0	289	346	401	747	112	317	12	6	327	107	—	—	—	—	—	—
2015	19	A MLE	2 teams	—	540	519	143	26	3	9	14	86	2	14	5	276	297	389	686	114	311	16	3	295	86	—	—	—	—	—	—
2016	20	AA MLE	2 teams	—	576	534	138	24	1	12	33	89	4	2	6	258	306	375	680	116	285	15	6	300	89	—	—	—	—	—	—
2017	21	AAA MLE	2 teams	—	520	471	133	23	3	6	40	68	4	9	4	282	344	382	727	100	312	13	8	320	103	—	—	—	—	—	—
2018	22	AAA MLE	2 teams	—	465	430	126	22	0	9	31	77	1	8	2	293	341	407	748	114	336	17	7	330	109	—	—	—	—	—	—
2019	23	MLB MLE	Los Angeles Dodgers	—	377	347	103	23	2	12	25	49	2	4	1	297	350	478	829	182	309	13	7	363	132	—	—	—	—	—	—
2020	24	MLB MLE	Boston Red Sox	—	221	201	59	14	0	6	16	45	2	4	0	294	350	453	803	159	371	20	7	359	129	—	—	—	—	—	—
2021	25	MLB MLE	Boston Red Sox	—	604	550	151	28	2	13	45	96	4	6	2	275	334	404	738	129	327	16	7	332	111	—	—	—	—	—	—
2022	26	MLB MLE	Boston Red Sox	—	644	596	160	35	1	11	40	86	3	1	3	268	318	386	704	117	309	13	6	314	99	—	—	—	—	—	—
2023	27	MLB MLE	Boston Red Sox	—	602	547	140	33	6	13	44	93	6	5	3	256	318	410	728	154	294	15	7	321	104	—	—	—	—	—	—
2024	28	MLB MLE	New York Yankees	—	621	566	129	28	1	12	49	93	1	2	1	228	294	345	638	117	253	15	8	286	80	—	—	—	—	—	—
2025	29	MLB MLE	2 teams	—	246	226	52	11	0	1	16	36	2	2	0	230	285	292	577	62	265	15	7	267	67	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	28	MLB MLE	New York Yankees	—	621	566	129	28	1	12	49	93	1	2	1	228	294	345	638	117	253	15	8	286	80	—	—	—	—	—	—
2025	29	MLB MLE	2 teams	—	246	226	52	11	0	1	16	36	2	2	0	230	285	292	577	62	265	15	7	267	67	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	31	MLB MLE	ATL	100%	394	358	92	20	1	7	31	64	2	4	1	256	318	377	695	121	292	16	8	311	97	-2	+0	+0	-4	+9	0.3
▸ 2027 — real world (MLB)
2027	31	MLB CTX	ATL	100%	289	263	67	14	1	5	22	47	2	3	1	256	318	377	695	121	292	16	8	311	97	-1	+0	+0	-3	+6	0.3
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	32	MLB MLE	ATL	100%	266	243	61	13	1	4	20	44	1	1	1	249	310	361	671	112	286	17	8	301	90	-3	-0	-3	-3	+6	-0.4
2028	32	MLB CTX	ATL	100%	266	243	61	13	1	4	20	44	1	1	1	249	310	361	671	112	286	17	8	301	90	-3	-0	-3	-3	+6	-0.4
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3659	3326	892	203	12	74	274	555	21	24	12	268	328	403	731	135	300	15	7	324	99	+24	+0	-20	-36	+79	4.8
/ 162G	—	A+C		—	650	591	158	36	2	13	49	99	4	4	2	267	328	401	729	134	299	15	8	324	99	+4	+0	-4	-6	+14	0.9
Career	—	MLE		—	6187	5683	1519	306	23	115	408	935	38	72	29	267	321	390	711	123	300	15	7	315	99	+23	+0	-20	-39	+86	5.1
/ 162G	—	MLE		—	650	597	159	32	2	12	43	98	4	8	3	266	320	387	707	121	299	15	7	315	99	+4	+0	-3	-6	+14	0.8

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.

2025 AAAGwinnett Stripers · 33 PAwOBA .323 → .244 (−79)K% 12.1% → 14.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.12%	÷0.976	×1.200	—	—	14.90%
BB% (unintentional) /PA	12.12%	÷1.140	×0.690	—	×0.982	7.20%
HBP% /PA	0.00%	—	×0.940	—	×0.982	0.00%
Singles /BIP	12.00%	÷0.968	×0.930	—	×0.982	11.32%
Doubles /BIP	4.00%	÷1.162	×0.830	—	×0.982	2.81%
Triples /BIP	0.00%	÷0.900	×0.970	—	×0.982	0.00%
Home runs /BIP	8.00%	÷0.961	×0.700	—	×0.982	5.72%

Factors used: league row International League. Park (home-season share, regressed): HR 92, 1B 94, 2B 132, 3B 80, K 95, BB 128 — 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).

Result: wOBA .323 → .244; ISO .241 → .177; BABIP .174 → .150. 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 AAAOklahoma City Dodgers · 379 PAwOBA .373 → .331 (−42)K% 12.4% → 16.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.40%	÷0.970	×1.290	—	—	16.50%
BB% (unintentional) /PA	8.44%	÷1.021	×0.710	—	×1.050	6.16%
HBP% /PA	0.26%	—	×0.980	—	×1.050	0.27%
Singles /BIP	28.38%	÷0.992	×0.900	×1.035	×1.050	27.97%
Doubles /BIP	6.42%	÷1.029	×0.810	×1.035	×1.050	5.49%
Triples /BIP	0.00%	÷1.020	×0.810	×1.035	×1.050	0.00%
Home runs /BIP	3.38%	÷1.020	×0.780	—	×1.050	2.71%

Factors used: league row PCL. Park (home-season share, regressed): HR 104, 1B 98, 2B 106, 3B 104, K 94, BB 104 — 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 ×1.035.

Result: wOBA .373 → .331; ISO .143 → .116; BABIP .359 → .343. 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 AAAOklahoma City Dodgers · 495 PAwOBA .362 → .324 (−38)K% 10.1% → 13.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.10%	÷1.000	×1.290	—	—	13.03%
BB% (unintentional) /PA	10.30%	÷1.017	×0.710	—	×1.050	7.55%
HBP% /PA	0.81%	—	×0.980	—	×1.050	0.83%
Singles /BIP	25.85%	÷0.978	×0.900	×1.012	×1.050	25.29%
Doubles /BIP	7.05%	÷1.038	×0.810	×1.012	×1.050	5.85%
Triples /BIP	1.04%	÷1.150	×0.810	×1.012	×1.050	0.78%
Home runs /BIP	1.57%	÷0.989	×0.780	—	×1.050	1.30%

Factors used: league row PCL. Park (home-season share, regressed): HR 98, 1B 96, 2B 108, 3B 130, K 100, BB 103 — applied at half strength. Age: age 21 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (6.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.012.

Result: wOBA .362 → .324; ISO .122 → .102; BABIP .340 → .319. 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 AATulsa Drillers · 529 PAwOBA .323 → .300 (−23)K% 12.7% → 15.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.67%	÷0.996	×1.220	—	—	15.51%
BB% (unintentional) /PA	7.37%	÷0.935	×0.700	—	×1.050	5.79%
HBP% /PA	0.76%	—	×0.870	—	×1.050	0.69%
Singles /BIP	22.68%	÷0.990	×0.920	×1.011	×1.050	22.38%
Doubles /BIP	5.61%	÷0.926	×0.840	×1.011	×1.050	5.40%
Triples /BIP	0.24%	÷0.900	×0.940	×1.011	×1.050	0.27%
Home runs /BIP	3.17%	÷1.020	×0.800	—	×1.050	2.61%

Factors used: league row TL. Park (home-season share, regressed): HR 104, 1B 98, 2B 85, 3B 80, K 99, BB 87 — applied at half strength. Age: age 20 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (4.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.011.

Result: wOBA .323 → .300; ISO .134 → .119; BABIP .292 → .285. 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 AGreat Lakes Loons · 444 PAwOBA .308 → .274 (−33)K% 11.9% → 15.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.94%	÷1.039	×1.360	—	—	15.62%
BB% (unintentional) /PA	3.38%	÷1.028	×0.690	—	×1.045	2.37%
HBP% /PA	0.45%	—	×0.780	—	×1.045	0.37%
Singles /BIP	25.27%	÷1.028	×0.920	×1.008	×1.045	23.82%
Doubles /BIP	6.25%	÷1.026	×0.830	×1.008	×1.045	5.32%
Triples /BIP	0.54%	÷0.978	×0.910	×1.008	×1.045	0.53%
Home runs /BIP	1.36%	÷0.894	×0.800	—	×1.045	1.27%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 79, 1B 106, 2B 105, 3B 96, K 108, BB 106 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.008.

Result: wOBA .308 → .274; ISO .100 → .088; BABIP .323 → .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).

2015 A+Rancho Cucamonga Quakes · 96 PAwOBA .450 → .393 (−56)K% 12.5% → 17.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.50%	÷0.970	×1.340	—	—	17.27%
BB% (unintentional) /PA	4.17%	÷0.958	×0.710	—	×1.050	3.24%
HBP% /PA	0.00%	—	×0.790	—	×1.050	0.00%
Singles /BIP	25.32%	÷1.046	×0.910	×1.033	×1.050	23.90%
Doubles /BIP	11.39%	÷1.109	×0.820	×1.033	×1.050	9.14%
Triples /BIP	2.53%	÷1.150	×0.760	×1.033	×1.050	1.81%
Home runs /BIP	5.06%	÷0.898	×0.920	—	×1.050	5.44%

Factors used: league row CAL. Park (home-season share, regressed): HR 80, 1B 109, 2B 122, 3B 130, K 94, BB 92 — applied at half strength. Age: age 19 vs a level average of 22.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.033.

Result: wOBA .450 → .393; ISO .275 → .244; BABIP .408 → .364. 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 ROKOgden Raptors · 216 PAwOBA .404 → .327 (−78)K% 8.3% → 12.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.33%	÷1.000	×1.440	—	—	12.00%
BB% (unintentional) /PA	9.26%	÷1.000	×0.610	—	×1.022	5.78%
HBP% /PA	1.85%	—	×0.720	—	×1.022	1.36%
Singles /BIP	26.74%	÷1.000	×0.820	×1.050	×1.022	23.54%
Doubles /BIP	8.72%	÷1.000	×0.720	×1.050	×1.022	6.74%
Triples /BIP	1.74%	÷1.000	×0.720	×1.050	×1.022	1.35%
Home runs /BIP	1.74%	÷1.000	×0.750	—	×1.022	1.34%

Factors used: league row PIO. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 18 vs a level average of 19.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .404 → .327; ISO .158 → .124; BABIP .374 → .317. 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
#1Josh Reddicklast yr '21 career totals — 13 seasons, 4,879 PA	7.3	4,879	146	61	262	321	426	-52	-8	13.1	13.0
/162	664	20	8	-7.1	-1.1	1.8	pk7: 13
#2Juan 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
#3Ollie Brown'65-'77 * career totals — 12 seasons, 4,012 PA	6.0	4,012	102	30	263*	324*	430*	-45	-4	8.8	9.4
/162	664	17	5	-7.4	-0.7	1.5	pk7: 10
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 10 projected seasons	5.9	3,923	79	27	268	324	403	-42	-24	8.4	8.8
/162	664	13	5	-7.1	-4.1	1.4	pk7: 9
#4Troy O'Leary'93-'03 * career totals — 10 seasons, 4,418 PA	6.7	4,418	127	17	261*	317*	432*	-46	-9	7.4	8.1
/162	664	19	3	-7.0	-1.4	1.1	pk7: 9
#5Avisaíl Garcíalast yr '24 career totals — 13 seasons, 4,298 PA	6.5	4,298	140	51	263	316	417	-43	-35	6.6	8.0
/162	664	22	8	-6.7	-5.4	1.0	pk7: 9
#6Danny Cater'64-'75 * career totals — 11 seasons, 4,785 PA	7.2	4,785	66	26	285*	323*	420*	-59	-6	7.5	7.4
/162	664	9	4	-8.2	-0.8	1.0	pk7: 7

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
Alex Verdugo (OGILVIE)	31	—	—	—	—	254/316/374	120	292	5	3	16%	8%	97	+0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Daniel Fornes 2010 · AAA	30	51→54	44→45	43→40	53	251/319/371	120	273	12	4	13%	8%	97	+1.1	226/281/333	107	250	11	5	14%	6%	74	-0.5	209/261/302	93	229	10	3	14%	6%	61	-0.8
✕Ricardo Nanita 2011 · AAA	30	54→58	44→45	41→50	46	262/300/379	117	292	11	8	15%	5%	91	+0.7	256/293/367	111	285	12	10	14%	5%	86	+0.3	252/289/354	102	279	11	9	14%	4%	79	-0.1
✕Jeremy Reed 2011 · MLB	30	51→59	42→45	42→50	48	248/296/354	107	285	9	7	17%	6%	84	+0.1	222/277/334	112	261	10	11	19%	7%	72	-0.7	176/229/254	78	206	3	15	16%	6%	33	-0.8
✕Brock Holt 2019 · MLB	31	50→60	44→45	42→50	53	245/325/362	117	294	11	10	20%	9%	97	+1.1	247/324/355	108	309	8	8	21%	9%	95	+1.0	240/318/331	91	304	5	7	21%	9%	87	+0.2
✕Matt Beaty 2024 · MLB	31	48→58	43→50	45	47	234/320/343	109	283	11	4	20%	7%	92	+0.7	233/306/343	110	269	11	6	17%	7%	86	+0.3	228/298/302	74	255	9	0	14%	5%	70	-0.3
✕Nick Martini 2021 · MLB	31	52→58	43→50	48→45	54	249/334/361	112	314	9	5	22%	11%	100	+1.3	229/311/360	131	290	14	5	24%	9%	92	+0.7	218/301/366	148	269	17	1	24%	8%	88	+0.3
✕Troy O'Leary 2001 · MLB	31	52→53	48→50	40→30	52	256/314/405	150	277	14	3	14%	8%	103	+1.5	250/311/399	149	282	15	4	17%	8%	100	+1.3	245/308/388	143	278	14	3	17%	7%	97	+0.6
✕Christian Marrero 2017 · AA	31	48→54	44→50	43→50	54	235/312/355	121	277	12	4	20%	10%	91	+0.7	232/306/363	131	277	14	5	21%	8%	91	+0.6	225/304/361	136	258	17	0	19%	7%	89	+0.2
✕Matt Hague 2017 · MLB	31	55→62	44→45	46→45	49	270/328/391	121	307	12	6	16%	7%	105	+1.7	237/298/332	95	275	9	7	16%	7%	80	-0.2	232/295/314	82	268	7	5	16%	8%	73	-0.4
✕Conor Gillaspie 2017 · MLB	30	51→58	47→50	42→40	46	254/294/399	145	284	13	4	16%	5%	94	+0.9	233/278/362	129	258	13	9	15%	5%	79	-0.2	210/246/300	89	231	7	8	12%	4%	50	-0.8
✕Leobardo Arauz 2007 · AAA	30	50→56	45	41→45	53	246/324/365	118	286	13	6	18%	9%	97	+1.1	251/323/374	123	275	13	9	14%	9%	99	+1.3	253/331/370	117	274	12	7	12%	10%	101	+1.1
✕Ben Gamel 2023 · MLB	31	48→58	47→50	43→50	54	236/323/379	143	298	14	7	24%	11%	101	+1.4	234/321/377	143	310	14	7	27%	11%	99	+1.3	227/319/369	142	309	14	6	29%	11%	95	+0.4
✕Fernando Valenzuela 2014 · AAA	31	57→60	42→45	40	46	273/314/383	109	301	9	3	13%	5%	97	+1.1	257/295/360	103	282	9	6	12%	5%	84	+0.2	274/307/377	102	287	9	4	8%	4%	95	+0.6
✕Gonzalo Meza 2009 · AAA	30	55→54	42→45	43→40	49	265/313/365	100	301	9	5	16%	6%	93	+0.8	252/304/332	80	289	6	4	14%	7%	81	-0.1	251/308/316	64	288	4	2	14%	7%	79	-0.1
✕Sean Burroughs 2012 · MLB	31	55→63	43→40	44→45	46	268/301/381	114	296	9	7	13%	5%	92	+0.7	228/274/314	86	261	5	7	14%	6%	66	-1.1	208/256/271	62	241	1	4	13%	5%	46	-1.0
✕Corban Joseph 2019 · MLB	30	52→57	45→50	45	50	255/301/378	123	273	13	6	12%	6%	91	+0.7	252/299/382	130	280	12	4	14%	6%	91	+0.7	259/304/390	131	289	11	0	14%	5%	93	+0.4
✕Gerardo Parra 2019 · MLB	32	55→63	43→50	44→55	46	268/313/376	109	310	10	10	17%	6%	95	+1.0	243/302/371	128	289	14	12	20%	7%	91	+0.6	222/286/354	132	267	14	12	22%	7%	81	-0.0
✕Oscar Ramirez 2010 · AAA	31	53→58	42→45	39→45	48	251/329/358	106	311	8	5	21%	8%	98	+1.2	244/311/346	102	304	9	5	21%	8%	88	+0.5	245/311/335	90	305	9	2	21%	8%	84	+0.1
✕Joe Thurston 2011 · MLB	31	48→57	44→45	45→50	46	237/283/353	116	268	11	10	17%	5%	78	-0.3	228/289/346	118	267	11	11	19%	6%	80	-0.1	231/297/330	99	271	8	11	17%	7%	76	-0.3
●Yonder Alonso 2017 · MLB	30	53→59	43→55	42→45	54	257/321/376	119	285	10	5	14%	8%	99	+1.2	251/327/427	176	286	22	3	20%	10%	113	+2.3	241/323/427	186	273	25	1	22%	10%	113	+1.8

Alex Verdugo

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps