Willy Adames

SS San Francisco Giants

Age 31 R/R 6'0" / 216 lbs MLB HR -15%H -3% Svc 8.610 · Ctrl thru 2031

Overview

MLB40-MANExtFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	28	MLBMIL	688	.251/.333/.462	32	21	121	4.7
2025	29	MLBSF	686	.225/.322/.421	30	12	113	4.1
2026	30	MLBSF	505	.230/.290/.424	21	5	105	1.7
2027PROJ	31	MLBSF	489	.234/.312/.427	20	9	112	2.3
2028PROJ	32	MLBSF	614	.229/.305/.414	25	6	107	2.0
2029PROJ	33	MLBSF	516	.222/.297/.397	20	1	100	1.1

Last 3 seasons WAR 10.5 · Next 3 projected WAR 5.5Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2031Service8.610First FA2028NTC

2027Ext$26M2028Ext$26M2029Ext$26M2030Ext$26M2031Ext$26M

Skills · percentileStatcast 2024-2026

Barrel%71

xwOBA63

Bat Spd62

Speed58

Avg EV40

CompsBrad Miller (age 31) · Joe Dillon (age 31) · Adolis García (age 31)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 112112vR 110

AVG/OBP/SLG.234 / .312 / .427

PA489

HR20

SB9

K%26

BB%9

BABIP281

ISO189

MLB%100%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$58M ctrl surplus

Tools · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

230.229

POWER

Barrel%

7111.4

Avg EV

4088.4

Bat Spd

6272.7

SPEED

Sprint

5827.8

Platoon Splits2024-2026 · 1490 PA

vs LHP

vs RHP

Edge

392

1098

—

wRC+

121

▶▶R

wOBA

286

347

▶▶R

ISO

166

213

▶▶R

BABIP

230

298

▶▶R

27.0%

25.7%

▶R

BB%

11.2%

10.0%

◀L

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

Status FA

MLB Debut 2018

Service 8.610 yrs.days

Team Control Through 2031

First FA Year 2028

NTC

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$26M	+2.4	$19M	-$7M
2028	Ext	$26M	+2.0	$15M	-$9M
2029	Ext	$26M	+1.1	$8M	-$13M
2030	Ext	$26M	+0.3	$1.0M	-$18M
2031	Ext	beyond projection horizon · no WAR estimate
Totals		$104M		$43M	-$47M

Underwater contract
Projected production over the remaining contract is worth -$47M less than the salary owed. Most often this reflects an aging-curve fade that was visible at signing — the team paid a premium for the early years.

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)
2013	17	ROK	DSL Tigers	—	267	200	49	12	5	1	56	44	6	9	12	245	424	370	794	125	304	16	21	364	60	—	—	—	—	—	—
2014	18	A	Bowling Green Hot Rods	—	514	450	122	19	14	8	54	126	4	6	6	271	354	429	783	158	358	25	11	345	84	—	—	—	—	—	—
2015	19	A+	Charlotte Stone Crabs	—	456	396	102	24	6	4	54	123	0	10	1	258	347	379	725	121	356	27	12	325	69	—	—	—	—	—	—
2016	20	AA	Montgomery Biscuits	—	568	486	133	31	6	11	74	121	4	13	6	274	374	430	804	156	342	21	13	359	95	—	—	—	—	—	—
2016	20	INTL	Tigres del Licey	—	36	30	5	0	0	0	3	9	0	0	0	167	242	167	409		217	25	8	184	11	—	—	—	—	—	—
2017	21	AAA	Durham Bulls	—	578	506	140	30	5	10	65	132	3	11	5	277	362	415	777	138	354	23	11	348	88	—	—	—	—	—	—
2018	22	MLB	Tampa Bay Rays	—	323	288	80	7	0	10	31	95	1	6	5	278	350	406	756	128	378	29	10	338	110	+4	-1	-4	+6	+7	1.3
2018	22	AAA	Durham Bulls	—	278	245	70	9	5	4	27	66	1	3	3	286	359	412	771	127	367	24	10	340	85	—	—	—	—	—	—
2019	23	MLB	Tampa Bay Rays	—	584	531	135	25	1	20	46	153	3	4	2	254	317	418	735	164	320	26	8	326	106	+4	+0	+10	+6	+13	3.4
2020	24	MLB	Tampa Bay Rays	—	205	185	48	15	1	8	20	74	0	2	1	259	332	481	813	222	388	36	10	357	129	+7	+0	-2	+2	+4	1.2
2021	25	MLB	Milwaukee Brewers	—	555	497	130	32	1	25	57	156	0	5	4	262	338	481	818	219	331	28	10	360	130	+20	-1	-2	+6	+12	3.5
2022	26	MLB	Milwaukee Brewers	—	617	563	134	31	0	31	49	166	1	8	3	238	300	458	758	220	278	27	8	331	108	+6	+0	+11	+7	+13	3.8
2023	27	MLB	Milwaukee Brewers	—	638	553	120	29	2	24	71	165	6	5	3	217	312	407	719	190	259	26	11	318	102	+1	-0	+15	+7	+14	3.8
2024	28	MLB	Milwaukee Brewers	—	688	610	153	33	0	32	74	173	1	21	4	251	333	462	795	211	297	25	11	350	121	+17	+3	+4	+7	+15	4.7
2025	29	MLB	San Francisco Giants	—	686	591	133	22	2	30	80	179	5	12	4	225	322	421	743	196	263	26	12	328	113	+10	+1	+7	+7	+15	4.1
2026	30	MLB	San Francisco Giants	—	505	465	107	25	1	21	37	139	2	5	2	230	290	424	713	194	281	28	7	315	105	+3	+0	-3	+5	+11	1.7
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4801	4283	1040	219	8	201	465	1300	19	68	28	243	319	438	758	196	299	27	10	334	112	+70	+2	+36	+54	+104	27.3
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2013	17	ROK MLE	DSL Tigers	—	267	216	36	8	3	1	40	54	6	9	12	167	313	245	558	79	207	20	15	257	60	—	—	—	—	—	—
2014	18	A MLE	Bowling Green Hot Rods	—	514	469	113	17	14	6	35	173	4	6	6	241	299	375	674	134	358	34	7	292	84	—	—	—	—	—	—
2015	19	A+ MLE	Charlotte Stone Crabs	—	456	409	89	22	4	4	41	178	0	10	1	218	289	320	609	103	354	39	9	270	69	—	—	—	—	—	—
2016	20	AA MLE	Montgomery Biscuits	—	568	507	127	29	6	8	53	151	4	13	6	250	326	379	705	128	332	27	9	309	95	—	—	—	—	—	—
2017	21	AAA MLE	Durham Bulls	—	578	524	129	26	5	8	47	154	3	11	5	246	312	361	673	115	329	27	8	298	88	—	—	—	—	—	—
2018	22	MLB MLE	Tampa Bay Rays	—	323	291	79	7	0	10	28	95	1	6	5	271	338	399	736	127	378	29	9	330	110	+4	-1	-4	+6	+7	1.3
2018	22	AAA MLE	Durham Bulls	—	278	254	64	7	5	4	18	77	1	3	3	252	304	366	670	114	328	28	6	294	85	—	—	—	—	—	—
2019	23	MLB MLE	Tampa Bay Rays	—	584	532	135	26	1	21	45	153	3	4	2	254	316	425	740	171	320	26	8	325	106	+4	+0	+10	+6	+13	3.4
2020	24	MLB MLE	Tampa Bay Rays	—	205	185	48	15	1	8	20	74	0	2	1	259	332	481	813	222	388	36	10	359	129	+7	+0	-2	+2	+4	1.2
2021	25	MLB MLE	Milwaukee Brewers	—	555	498	131	34	1	24	56	156	0	5	4	263	338	480	817	217	331	28	10	360	130	+20	-1	-2	+6	+12	3.5
2022	26	MLB MLE	Milwaukee Brewers	—	617	566	135	33	0	30	46	166	1	8	3	239	297	456	753	217	278	27	7	328	108	+6	+0	+11	+7	+13	3.8
2023	27	MLB MLE	Milwaukee Brewers	—	638	556	121	31	2	23	70	165	6	5	3	218	312	405	716	187	259	26	11	318	102	+1	-0	+15	+7	+14	3.8
2024	28	MLB MLE	Milwaukee Brewers	—	688	613	153	35	0	30	71	173	1	21	4	250	328	454	782	204	297	25	10	347	121	+17	+3	+4	+7	+15	4.7
2025	29	MLB MLE	San Francisco Giants	—	686	594	136	22	2	32	78	179	5	12	4	229	323	434	758	205	263	26	11	335	113	+10	+1	+7	+7	+15	4.1
2026	30	MLB MLE	San Francisco Giants	—	505	465	110	25	1	23	37	139	2	5	2	237	296	443	739	206	281	28	7	323	105	+3	+0	-3	+5	+11	1.7
2013	17	ROK MLE	DSL Tigers	—	267	216	36	8	3	1	40	54	6	9	12	167	313	245	558	79	213	20	15	257	60	—	—	—	—	—	—
2013	17	ROK RAW	DSL Tigers	—	267	200	49	12	5	1	56	44	6	9	12	245	424	370	794	125	304	16	21	364	60	—	—	—	—	—	—
2014	18	A MLE	Bowling Green Hot Rods	—	514	469	113	17	14	6	35	173	4	6	6	241	299	375	674	134	366	34	7	292	84	—	—	—	—	—	—
2014	18	A RAW	Bowling Green Hot Rods	—	514	450	122	19	14	8	54	126	4	6	6	271	354	429	783	158	358	25	11	345	84	—	—	—	—	—	—
2015	19	A+ MLE	Charlotte Stone Crabs	—	456	409	89	22	4	4	41	178	0	10	1	218	289	320	609	103	365	39	9	270	69	—	—	—	—	—	—
2015	19	A+ RAW	Charlotte Stone Crabs	—	456	396	102	24	6	4	54	123	0	10	1	258	347	379	725	121	356	27	12	325	69	—	—	—	—	—	—
2016	20	AA MLE	2 teams	—	604	536	134	30	6	9	57	160	4	13	6	250	327	379	705	129	336	26	9	309	95	—	—	—	—	—	—
2016	20	AA RAW	2 teams	—	604	516	138	31	6	11	77	130	4	13	6	267	367	415	782	147	334	22	13	348	95	—	—	—	—	—	—
2017	21	AAA MLE	Durham Bulls	—	578	524	129	26	5	8	47	154	3	11	5	246	312	361	673	115	332	27	8	298	88	—	—	—	—	—	—
2017	21	AAA RAW	Durham Bulls	—	578	506	140	30	5	10	65	132	3	11	5	277	362	415	777	138	354	23	11	348	88	—	—	—	—	—	—
2018	22	MLB MLE	2 teams	—	601	545	143	14	5	14	46	172	2	9	8	262	322	383	706	121	352	29	8	314	98	-1	-1	-4	+6	+13	1.3
2018	22	MLB RAW	2 teams	—	601	533	150	16	5	14	58	161	2	9	8	281	354	409	763	128	373	27	10	339	98	-1	-1	-4	+6	+13	1.3
2019	23	MLB MLE	Tampa Bay Rays	—	584	532	135	26	1	21	45	153	3	4	2	254	316	425	740	171	318	26	8	325	106	+4	+0	+10	+6	+13	3.4
2019	23	MLB RAW	Tampa Bay Rays	—	584	531	135	25	1	20	46	153	3	4	2	254	317	418	735	164	320	26	8	326	106	+4	+0	+10	+6	+13	3.4
2020	24	MLB MLE	Tampa Bay Rays	—	205	185	48	15	1	8	20	74	0	2	1	259	332	481	813	222	388	36	10	359	129	+7	+0	-2	+2	+4	1.2
2020	24	MLB RAW	Tampa Bay Rays	—	205	185	48	15	1	8	20	74	0	2	1	259	332	481	813	222	388	36	10	357	129	+7	+0	-2	+2	+4	1.2
2021	25	MLB MLE	Milwaukee Brewers	—	555	498	131	34	1	24	56	156	0	5	4	263	338	480	817	217	335	28	10	360	130	+20	-1	-2	+6	+12	3.5
2021	25	MLB RAW	Milwaukee Brewers	—	555	497	130	32	1	25	57	156	0	5	4	262	338	481	818	219	331	28	10	360	130	+20	-1	-2	+6	+12	3.5
2022	26	MLB MLE	Milwaukee Brewers	—	617	566	135	33	0	30	46	166	1	8	3	239	297	456	753	217	281	27	7	328	108	+6	+0	+11	+7	+13	3.8
2022	26	MLB RAW	Milwaukee Brewers	—	617	563	134	31	0	31	49	166	1	8	3	238	300	458	758	220	278	27	8	331	108	+6	+0	+11	+7	+13	3.8
2023	27	MLB MLE	Milwaukee Brewers	—	638	556	121	31	2	23	70	165	6	5	3	218	312	405	716	187	262	26	11	318	102	+1	-0	+15	+7	+14	3.8
2023	27	MLB RAW	Milwaukee Brewers	—	638	553	120	29	2	24	71	165	6	5	3	217	312	407	719	190	259	26	11	318	102	+1	-0	+15	+7	+14	3.8
2024	28	MLB MLE	Milwaukee Brewers	—	688	613	153	35	0	30	71	173	1	21	4	250	328	454	782	204	298	25	10	347	121	+17	+3	+4	+7	+15	4.7
2024	28	MLB RAW	Milwaukee Brewers	—	688	610	153	33	0	32	74	173	1	21	4	251	333	462	795	211	297	25	11	350	121	+17	+3	+4	+7	+15	4.7
2025	29	MLB MLE	San Francisco Giants	—	686	594	136	22	2	32	78	179	5	12	4	229	323	434	758	205	265	26	11	335	113	+10	+1	+7	+7	+15	4.1
2025	29	MLB RAW	San Francisco Giants	—	686	591	133	22	2	30	80	179	5	12	4	225	322	421	743	196	263	26	12	328	113	+10	+1	+7	+7	+15	4.1
2026	30	MLB MLE	San Francisco Giants	—	505	465	110	25	1	23	37	139	2	5	2	237	296	443	739	206	286	28	7	323	105	+3	+0	-3	+5	+11	1.7
2026	30	MLB RAW	San Francisco Giants	—	505	465	107	25	1	21	37	139	2	5	2	230	290	424	713	194	281	28	7	315	105	+3	+0	-3	+5	+11	1.7
2013	17	ROK MLE	DSL Tigers	—	267	219	36	8	3	1	40	54	6	9	12	164	313	242	555	78	207	20	15	257	60	—	—	—	—	—	—
2014	18	A MLE	Bowling Green Hot Rods	—	514	470	113	17	14	6	35	173	4	6	6	240	299	374	674	134	358	34	7	292	84	—	—	—	—	—	—
2015	19	A+ MLE	Charlotte Stone Crabs	—	456	412	89	22	4	4	41	178	0	10	1	216	289	318	607	102	354	39	9	270	69	—	—	—	—	—	—
2016	20	AA MLE	2 teams	—	604	538	134	30	6	9	57	160	4	13	6	249	327	377	704	128	332	26	9	309	95	—	—	—	—	—	—
2017	21	AAA MLE	Durham Bulls	—	578	523	129	26	5	8	47	154	3	11	5	247	312	361	673	115	329	27	8	298	88	—	—	—	—	—	—
2018	22	MLB MLE	2 teams	—	601	548	143	14	5	14	46	172	2	9	8	261	322	381	703	120	355	29	8	314	98	—	—	—	—	—	—
2019	23	MLB MLE	Tampa Bay Rays	—	584	531	135	26	1	21	45	153	3	4	2	254	316	426	741	171	320	26	8	325	106	—	—	—	—	—	—
2020	24	MLB MLE	Tampa Bay Rays	—	205	183	48	15	1	8	20	74	0	2	1	262	332	486	818	224	388	36	10	359	129	—	—	—	—	—	—
2021	25	MLB MLE	Milwaukee Brewers	—	555	494	131	34	1	24	56	156	0	5	4	265	338	484	821	219	331	28	10	360	130	—	—	—	—	—	—
2022	26	MLB MLE	Milwaukee Brewers	—	617	565	135	33	0	30	46	166	1	8	3	239	297	457	754	218	278	27	7	328	108	—	—	—	—	—	—
2023	27	MLB MLE	Milwaukee Brewers	—	638	557	121	31	2	23	70	165	6	5	3	217	312	404	716	187	259	26	11	318	102	—	—	—	—	—	—
2024	28	MLB MLE	Milwaukee Brewers	—	688	611	153	35	0	30	71	173	1	21	4	250	328	455	783	205	297	25	10	347	121	—	—	—	—	—	—
2025	29	MLB MLE	San Francisco Giants	—	686	598	136	22	2	32	78	179	5	12	4	227	323	431	755	204	263	26	11	335	113	—	—	—	—	—	—
2026	30	MLB MLE	San Francisco Giants	—	505	461	110	25	1	23	37	139	2	5	2	239	296	447	742	208	281	28	7	323	105	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	28	MLB MLE	Milwaukee Brewers	—	688	611	153	35	0	30	71	173	1	21	4	250	328	455	783	205	297	25	10	347	121	—	—	—	—	—	—
2025	29	MLB MLE	San Francisco Giants	—	686	598	136	22	2	32	78	179	5	12	4	227	323	431	755	204	263	26	11	335	113	—	—	—	—	—	—
2026	30	MLB MLE	San Francisco Giants	—	505	461	110	25	1	23	37	139	2	5	2	239	296	447	742	208	281	28	7	323	105	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	31	MLB MLE	SF	100%	558	497	119	24	1	25	53	146	3	10	2	240	317	444	761	204	285	26	9	334	112	+8	+1	-2	+6	+12	2.4
▸ 2027 — real world (MLB)
2027	31	MLB CTX	SF	100%	489	438	102	21	1	20	46	128	2	9	2	234	312	427	739	193	281	26	9	326	112	+7	+1	-1	+5	+11	2.3
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	32	MLB MLE	SF	100%	614	548	129	25	1	27	58	164	3	6	2	234	310	430	741	196	281	27	9	326	107	+5	+0	-5	+7	+13	2.0
2029	33	MLB MLE	SF	100%	516	461	105	20	1	21	48	141	2	1	1	227	302	413	715	186	274	27	9	316	100	-0	-0	-6	+6	+11	1.1
2030	34	MLB MLE	SF	100%	408	367	80	15	1	16	37	114	1	1	1	218	291	392	683	175	266	28	9	303	91	-4	-0	-6	+4	+9	0.3
2028	32	MLB CTX	SF	100%	614	548	125	25	1	25	58	164	3	6	2	229	305	414	719	185	276	27	9	318	107	+5	+0	-5	+7	+13	2.0
2029	33	MLB CTX	SF	100%	516	461	103	20	1	20	48	141	2	1	1	222	297	397	694	176	270	27	9	308	100	-0	-0	-6	+6	+11	1.1
2030	34	MLB CTX	SF	100%	408	367	79	15	1	15	37	114	1	1	1	212	287	377	664	165	262	28	9	296	91	-4	-0	-6	+4	+9	0.3
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	6339	5659	1347	279	11	261	608	1719	25	76	32	238	315	430	744	192	292	27	10	328	102	+71	+2	+19	+71	+137	30.7
/ 162G	—	A+C		—	650	580	139	29	1	27	62	176	3	8	3	240	316	433	749	193	294	27	10	328	102	+7	+0	+2	+7	+14	3.2
Career	—	MLE		—	9525	8522	2032	419	49	319	878	2643	45	137	67	238	313	411	724	173	305	28	9	319	102	+79	+3	+18	+76	+148	33.0
/ 162G	—	MLE		—	650	582	139	29	3	22	60	180	3	9	5	239	313	412	726	174	305	28	9	319	102	+7	+0	+2	+7	+14	3.1

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.

2018 AAADurham Bulls · 278 PAwOBA .335 → .294 (−41)K% 23.7% → 27.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.74%	÷1.032	×1.200	—	—	27.60%
BB% (unintentional) /PA	8.99%	÷0.986	×0.690	—	×1.050	6.61%
HBP% /PA	0.36%	—	×0.940	—	×1.050	0.36%
Singles /BIP	29.05%	÷1.052	×0.930	×0.976	×1.050	26.32%
Doubles /BIP	5.03%	÷1.091	×0.830	×0.976	×1.050	3.92%
Triples /BIP	2.79%	÷0.993	×0.970	×0.976	×1.050	2.80%
Home runs /BIP	2.23%	÷0.970	×0.840	—	×1.050	2.03%

Factors used: league row IL. Park (home-season share, regressed): HR 94, 1B 110, 2B 118, 3B 99, K 106, BB 97 — 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 ×0.976.

Result: wOBA .335 → .294; ISO .127 → .116; BABIP .367 → .328. 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 AAADurham Bulls · 578 PAwOBA .341 → .298 (−43)K% 22.8% → 26.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.84%	÷1.027	×1.200	—	—	26.68%
BB% (unintentional) /PA	11.25%	÷0.993	×0.690	—	×1.050	8.21%
HBP% /PA	0.52%	—	×0.940	—	×1.050	0.51%
Singles /BIP	25.40%	÷1.025	×0.930	×0.999	×1.050	24.18%
Doubles /BIP	8.02%	÷1.008	×0.830	×0.999	×1.050	6.93%
Triples /BIP	1.34%	÷1.022	×0.970	×0.999	×1.050	1.33%
Home runs /BIP	2.67%	÷1.049	×0.840	—	×1.050	2.25%

Factors used: league row IL. Park (home-season share, regressed): HR 110, 1B 105, 2B 102, 3B 104, K 105, BB 99 — 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 ×0.999.

Result: wOBA .341 → .298; ISO .138 → .121; BABIP .354 → .329. 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 AAMontgomery Biscuits · 568 PAwOBA .351 → .309 (−42)K% 21.3% → 26.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.30%	÷0.982	×1.220	—	—	26.47%
BB% (unintentional) /PA	12.85%	÷0.980	×0.680	—	×1.050	9.37%
HBP% /PA	0.70%	—	×0.840	—	×1.050	0.62%
Singles /BIP	23.29%	÷0.982	×0.920	×1.013	×1.050	23.20%
Doubles /BIP	8.49%	÷1.040	×0.910	×1.013	×1.050	7.90%
Triples /BIP	1.64%	÷0.994	×0.880	×1.013	×1.050	1.55%
Home runs /BIP	3.01%	÷1.081	×0.800	—	×1.050	2.34%

Factors used: league row SL. Park (home-season share, regressed): HR 116, 1B 96, 2B 108, 3B 99, K 96, BB 96 — 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 ×1.013.

Result: wOBA .351 → .309; ISO .156 → .134; BABIP .342 → .332. 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+Charlotte Stone Crabs · 456 PAwOBA .320 → .270 (−50)K% 27.0% → 39.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.97%	÷0.979	×1.420	—	—	39.13%
BB% (unintentional) /PA	11.62%	÷0.994	×0.750	—	×1.042	9.13%
HBP% /PA	0.00%	—	×0.930	—	×1.042	0.00%
Singles /BIP	24.91%	÷0.976	×0.920	×1.017	×1.042	24.90%
Doubles /BIP	8.79%	÷0.978	×0.960	×1.017	×1.042	9.15%
Triples /BIP	2.20%	÷1.150	×0.810	×1.017	×1.042	1.64%
Home runs /BIP	1.47%	÷0.822	×0.880	—	×1.042	1.64%

Factors used: league row FSL. Park (home-season share, regressed): HR 64, 1B 95, 2B 96, 3B 130, K 96, BB 99 — 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 ×1.017.

Result: wOBA .320 → .270; ISO .121 → .103; BABIP .356 → .354. 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 ABowling Green Hot Rods · 514 PAwOBA .337 → .292 (−45)K% 24.5% → 33.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.51%	÷0.991	×1.360	—	—	33.64%
BB% (unintentional) /PA	10.31%	÷1.073	×0.690	—	×1.045	6.93%
HBP% /PA	0.78%	—	×0.780	—	×1.045	0.63%
Singles /BIP	25.00%	÷0.976	×0.920	×1.024	×1.045	25.22%
Doubles /BIP	5.86%	÷0.946	×0.830	×1.024	×1.045	5.51%
Triples /BIP	4.32%	÷0.920	×0.910	×1.024	×1.045	4.57%
Home runs /BIP	2.47%	÷0.966	×0.800	—	×1.045	2.14%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 93, 1B 95, 2B 89, 3B 84, K 98, BB 115 — 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 ×1.024.

Result: wOBA .337 → .292; ISO .158 → .141; BABIP .358 → .358. 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).

2013 DSLDSL Tigers · 267 PAwOBA .360 → .257 (−103)K% 16.5% → 20.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.48%	÷1.000	×1.220	—	—	20.10%
BB% (unintentional) /PA	20.97%	÷1.000	×0.700	—	×1.008	14.79%
HBP% /PA	2.25%	—	×0.700	—	×1.008	1.58%
Singles /BIP	19.87%	÷1.000	×0.680	×1.037	×1.008	14.12%
Doubles /BIP	7.69%	÷1.000	×0.600	×1.037	×1.008	4.82%
Triples /BIP	3.21%	÷1.000	×0.600	×1.037	×1.008	2.01%
Home runs /BIP	0.64%	÷1.000	×0.470	—	×1.008	0.30%

Factors used: level-wide DSL 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 18 vs a level average of 18.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.037.

Result: wOBA .360 → .257; ISO .125 → .083; BABIP .304 → .207. 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
#1Jhonny Peraltalast yr '17 career totals — 14 seasons, 7,291 PA	11.0	7,291	202	17	267	329	423	+66	+63	42.9	37.5
/162	664	18	2	+6.1	+5.8	3.9	pk7: 32
#2Kyle Seagerlast yr '21 career totals — 11 seasons, 6,204 PA	9.3	6,204	242	55	251	321	442	+22	+55	35.4	32.4
/162	664	26	6	+2.4	+5.8	3.8	pk7: 29
#3Roy Smalley'75-'87 * career totals — 13 seasons, 6,594 PA	9.9	6,594	163	27	253*	344*	418*	+20	+50	33.1	30.5
/162	664	16	3	+2.0	+5.1	3.3	pk7: 28
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 13 projected seasons	10.3	6,828	287	85	240	313	436	+70	+76	33.7	28.5
/162	664	28	8	+6.8	+7.4	3.3	pk7: 23
#4Jose Valentin'92-'07 * career totals — 15 seasons, 6,317 PA	9.5	6,317	249	136	233*	309*	433*	+53	+78	31.1	27.3
/162	664	26	14	+5.6	+8.2	3.3	pk7: 24
#5Doug Rader'67-'77 * career totals — 11 seasons, 5,832 PA	8.8	5,832	155	37	249*	320*	439*	+12	+51	29.6	26.6
/162	664	18	4	+1.4	+5.8	3.4	pk7: 24
#6Todd Frazierlast yr '20 career totals — 10 seasons, 4,909 PA	7.4	4,909	218	73	242	319	448	+18	+35	27.6	26.2
/162	664	29	10	+2.4	+4.7	3.7	pk7: 25

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
Willy Adames (OGILVIE)	31	—	—	—	—	238/314/440	202	285	22	9	26%	9%	112	+1.8	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Brad Miller 2021 · MLB	31	46→56	59→60	47→50	50	242/325/458	215	300	27	6	28%	10%	120	+2.8	225/306/402	177	286	23	7	29%	10%	100	+1.3	210/293/370	160	265	22	6	29%	10%	88	+0.2
●Joe Dillon 2007 · MLB	31	51→52	55	52→45	50	263/337/446	183	291	23	12	19%	8%	122	+2.9	242/314/396	154	267	16	8	16%	8%	101	+1.4	234/311/377	143	257	15	7	15%	9%	96	+0.6
✕Adolis García 2024 · MLB	31	45→49	60	51→50	46	244/309/464	220	296	29	14	28%	8%	116	+2.5	226/287/403	177	280	22	12	27%	7%	93	+0.8	215/273/372	157	269	20	11	27%	6%	81	-0.0
✕Tyrone Taylor 2024 · MLB	30	45→54	57→60	55	42	241/293/448	207	278	24	13	24%	5%	106	+1.8	244/295/404	160	296	15	16	22%	5%	95	+1.0	248/299/400	152	299	13	17	21%	5%	97	+0.6
●Brian Dozier 2019 · MLB	32	46→56	58→65	50	54	245/326/452	207	270	25	13	20%	10%	118	+2.7	238/326/419	181	275	22	8	22%	11%	111	+2.1	235/335/426	190	268	25	4	22%	12%	117	+2.1
●Todd Frazier 2017 · MLB	31	43→52	61→60	46→50	49	240/306/459	219	261	31	13	22%	8%	114	+2.3	226/319/425	199	254	26	8	23%	10%	110	+2.1	224/324/411	187	254	25	5	22%	11%	110	+1.8
✕Brandon Dixon 2023 · AAA	31	48	67→60	55	44	265/322/528	263	314	36	16	28%	7%	135	+3.9	228/286/395	167	325	21	13	35%	6%	91	+0.7	203/263/342	139	302	19	12	37%	6%	68	-0.6
✕Eric Hinske 2009 · MLB	31	46→55	57→60	50	54	243/324/449	206	276	24	11	22%	10%	117	+2.6	245/325/438	193	290	23	6	23%	10%	115	+2.4	241/323/429	188	290	23	1	25%	10%	113	+1.0
●Preston Wilson 2005 · MLB	31	50→52	58→60	46→55	49	262/327/469	206	300	26	12	22%	8%	123	+3.0	259/314/441	182	312	22	10	24%	7%	112	+2.2	259/314/441	182	313	23	10	24%	6%	112	+2.1
✕Welington Castillo 2018 · MLB	31	50→56	55	47→30	43	259/310/438	179	315	25	3	26%	6%	109	+2.0	241/294/413	172	302	23	4	27%	6%	97	+1.1	221/273/386	165	275	22	1	28%	6%	84	+0.1
✕Ramon Castro 2008 · MLB	32	48	59→55	47→40	47	257/319/462	206	304	27	4	25%	8%	118	+2.7	249/310/452	203	282	28	4	22%	8%	113	+2.3	239/300/438	199	261	29	1	22%	8%	107	+0.5
✕Miguel Sanó 2024 · MLB	31	41→51	58→70	48→45	48	221/304/424	203	292	27	7	33%	10%	105	+1.7	227/303/364	137	334	16	7	34%	8%	90	+0.6	203/284/307	103	325	13	0	38%	8%	69	-0.2
✕Miguel Olivo 2010 · MLB	32	46→50	58→60	51→50	37	248/283/456	207	302	27	9	28%	4%	104	+1.6	239/274/413	174	299	22	9	28%	4%	90	+0.6	231/261/390	160	285	21	8	27%	4%	81	-0.1
✕Jung Ho Kang 2018 · MLB	31	48→58	60	44→45	49	258/340/473	215	289	28	7	22%	8%	129	+3.4	237/306/442	205	280	27	6	25%	8%	109	+2.0	198/252/428	230	235	32	0	32%	6%	86	+0.1
✕Jedd Gyorko 2019 · MLB	30	50→53	56→60	48→45	54	261/336/454	193	294	25	5	21%	10%	122	+3.0	243/320/416	173	290	23	7	24%	10%	108	+1.9	211/293/375	164	248	26	5	26%	10%	90	+0.1
✕Seth Brown 2023 · MLB	31	41→48	63→65	51→50	47	234/299/470	235	269	32	11	27%	8%	114	+2.3	239/298/433	194	289	26	8	26%	7%	104	+1.6	238/295/419	181	289	25	5	27%	7%	100	+0.8
✕Colby Rasmus 2018 · MLB	31	42→52	59→65	48→50	45	230/295/433	203	289	28	6	31%	9%	103	+1.5	226/286/392	166	300	20	8	30%	7%	90	+0.6	168/225/279	110	236	12	0	33%	6%	40	-0.5
●AJ Pollock 2020 · MLB	32	49→59	57→65	53→55	47	256/317/459	203	285	25	14	20%	7%	117	+2.6	269/320/482	213	300	28	9	20%	6%	124	+3.1	267/316/467	200	296	25	7	19%	6%	120	+1.8
✕Sean Rodríguez 2017 · MLB	32	48→51	58→60	45→50	43	253/314/456	204	314	26	6	28%	7%	116	+2.5	217/304/387	170	293	22	6	32%	10%	96	+1.0	178/283/327	149	245	20	4	34%	11%	76	-0.1
✕Gary Sánchez 2024 · MLB	31	38→48	57→65	48→45	48	210/294/404	194	251	26	3	28%	9%	97	+1.1	227/316/417	190	271	26	3	26%	10%	107	+1.9	221/325/412	190	258	26	0	25%	11%	110	+0.8

Willy Adames

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps