Jerar Encarnacion

RF San Francisco Giants

Age 29 R/R 6'4" / 265 lbs MLB HR -15%H -3% Svc 1.884 · Ctrl thru 2031

Overview

MLBPre-ArbFA 2032

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	26	AAA/INTL2 orgs	315	.322/.415/.537	14	4	142	—	.305/.372/.481
2024	26	MLBSF	119	.248/.280/.425	5	1	100	-0.3
2025	27	AAA/INTL2 orgs	152	.272/.344/.449	6	2	90	—	.227/.306/.364
2025	27	MLBSF	56	.200/.214/.364	2	1	62	-0.2
2026	28	MLBSF	35	.176/.200/.206	0	0	13	-0.4
2027PROJ	29	MLBSF	124	.250/.307/.420	4	2	108	0.3
2028PROJ82% MLB	30	MLBSF	147	.247/.303/.412	5	1	105	0.1
2029PROJ82% MLB	31	MLBSF	138	.243/.297/.401	5	0	101	-0.0

Last 3 seasons WAR -0.8 · Next 3 projected WAR 0.4Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2031Service1.884First FA2032

2027Pre-Arb$0.8M2028Pre-Arb$0.8M2029Arb-1$0.2M2030Ext$2M2031Ext$2M

Skills · percentileStatcast 2024-2026

Avg EV90

Bat Spd73

Barrel%70

xwOBA54

Speed33

CompsTim Beckham (age 29) · Trevor Plouffe (age 28) · Ty Wigginton (age 29)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 110108vR 101

AVG/OBP/SLG.250 / .307 / .420

PA124

HR4

K%26

BB%6

BABIP306

ISO149

MLB%100%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$2M ctrl surplus

Tools · Splits · ContractCON 55 / POW 55

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT55

xAVG

510.252

POWER55

Barrel%

7011.1

Avg EV

9092.6

Bat Spd

7373.8

EYE40

scouting grade only

SPEED40

Sprint

3326.7

Platoon Splits2024-2025 · 175 PA

vs LHP

vs RHP

Edge

105

—

wRC+

▶R

wOBA

277

295

▶R

ISO

119

209

▶▶R

BABIP

321

258

◀◀L

27.1%

28.6%

◀L

BB%

4.3%

2.9%

◀◀L

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

Status Pre-Arb

MLB Debut 2022

Service 1.884 yrs.days

Team Control Through 2031

First FA Year 2032

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+0.4	$2M	+$0.8M
2028	Pre-Arb	$0.8M	+0.1	$0.4M	+$0.0M (cut)
2029	Arb-1	$0.2M	—	—	—
2030	Ext	beyond projection horizon · no WAR estimate
2031	Ext	beyond projection horizon · no WAR estimate
Totals		$0.8M		$2M	+$0.8M

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)
2016	18	ROK	DSL Marlins	—	57	55	12	2	1	1	1	11	0	0	0	218	232	345	578	127	256	19	2	249	-13	—	—	—	—	—	—
2017	19	ROK	GCL Marlins	—	167	154	41	7	3	5	10	51	3	3	3	266	323	448	771	182	367	31	6	341	30	—	—	—	—	—	—
2018	20	A	Greensboro Grasshoppers	—	59	54	4	0	0	0	5	23	0	0	0	74	153	74	227		129	39	8	120	-57	—	—	—	—	—	—
2019	21	A+	Jupiter Hammerheads	—	272	253	64	10	1	6	17	71	0	3	2	253	300	372	672	119	326	26	6	299	44	—	—	—	—	—	—
2019	21	A	Clinton LumberKings	—	281	255	76	16	0	10	23	69	3	3	1	298	363	478	841	180	375	25	8	373	68	—	—	—	—	—	—
2019	21	INTL	Salt River Rafters	—	73	67	18	2	0	3	5	28	0	0	0	269	319	433	752	164	405	38	7	330	109	—	—	—	—	—	—
2021	23	AA	Pensacola Blue Wahoos	—	260	230	51	12	1	9	24	99	5	5	5	222	309	400	709	178	341	38	9	317	47	—	—	—	—	—	—
2022	24	MLB	Miami Marlins	—	81	77	14	3	0	3	3	32	0	2	0	182	212	338	550	156	256	40	4	240	55	-4	+0	+1	-7	+2	-0.8
2022	24	AAA	Jacksonville Jumbo Shrimp	—	297	264	70	12	0	14	29	87	0	0	1	265	338	470	808	205	335	29	10	352	72	—	—	—	—	—	—
2022	24	AA	Pensacola Blue Wahoos	—	136	120	43	3	0	8	13	35	2	4	2	358	430	583	1.013	225	449	26	10	441	120	—	—	—	—	—	—
2022	24	INTL	Aguilas Cibaenas	—	96	78	26	5	0	3	16	23	0	4	2	333	447	513	960	179	426	24	17	418	169	—	—	—	—	—	—
2023	25	AAA	Jacksonville Jumbo Shrimp	—	516	434	99	17	1	26	78	200	2	6	2	228	348	452	800	224	348	39	15	355	70	—	—	—	—	—	—
2023	25	INTL	Aguilas Cibaenas	—	109	100	23	4	1	3	9	29	0	3	0	230	294	380	674	150	294	27	8	301	90	—	—	—	—	—	—
2024	26	MLB	San Francisco Giants	—	119	113	28	5	0	5	5	34	0	1	0	248	280	425	704	177	307	29	4	308	100	+0	+0	-1	-5	+3	-0.3
2024	26	AAA	Sacramento River Cats	—	146	125	44	3	0	10	18	35	2	1	0	352	441	616	1.057	264	420	24	12	457	139	—	—	—	—	—	—
2024	26	INTL	Aguilas Cibaenas	—	169	145	43	9	2	4	20	31	3	3	2	297	393	469	862	172	351	18	12	382	145	—	—	—	—	—	—
2025	27	MLB	San Francisco Giants	—	56	55	11	3	0	2	1	15	0	1	0	200	214	364	578	164	237	27	2	253	62	-3	+0	+2	-2	+1	-0.2
2025	27	AAA	Sacramento River Cats	—	98	84	23	4	0	4	11	27	3	2	1	274	378	464	842	190	358	28	11	377	88	—	—	—	—	—	—
2025	27	INTL	Aguilas Cibaenas	—	54	52	14	2	0	2	1	12	0	0	0	269	283	423	706	154	308	22	2	305	93	—	—	—	—	—	—
2026	28	MLB	San Francisco Giants	—	35	34	6	1	0	0	1	8	0	0	0	176	200	206	406	29	231	23	3	186	13	-4	+0	-0	-0	+1	-0.4
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	291	279	59	12	0	10	10	89	0	4	0	211	239	362	601	151	269	31	3	263	64	-12	+1	+1	-14	+6	-1.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2016	18	ROK MLE	DSL Marlins	—	57	55	7	1	1	0	1	13	0	0	0	127	143	182	325	55	167	23	2	149	-13	—	—	—	—	—	—
2017	19	ROK MLE	GCL Marlins	—	167	158	26	4	2	3	6	73	3	3	3	165	210	272	482	108	284	44	4	212	30	—	—	—	—	—	—
2018	20	A MLE	Greensboro Grasshoppers	—	59	56	3	0	0	0	3	32	0	0	0	54	102	54	155		127	54	5	84	-57	—	—	—	—	—	—
2019	21	A+ MLE	Jupiter Hammerheads	—	272	258	51	9	1	6	12	100	0	3	2	198	233	310	543	112	284	37	4	233	44	—	—	—	—	—	—
2019	21	A MLE	Clinton LumberKings	—	281	263	59	12	0	7	15	92	3	3	1	224	274	350	624	125	310	33	5	268	68	—	—	—	—	—	—
2021	23	AA MLE	Pensacola Blue Wahoos	—	260	237	40	9	1	6	17	124	5	5	5	169	239	291	531	122	315	48	7	237	47	—	—	—	—	—	—
2022	24	MLB MLE	Miami Marlins	—	81	77	14	3	0	3	3	32	0	2	0	182	212	338	550	156	256	40	4	250	55	-4	+0	+1	-7	+2	-0.8
2022	24	AAA MLE	Jacksonville Jumbo Shrimp	—	297	273	58	11	0	9	20	108	0	0	1	212	266	352	618	139	302	36	7	275	72	—	—	—	—	—	—
2022	24	AA MLE	Pensacola Blue Wahoos	—	136	124	36	2	0	6	9	44	2	4	2	290	348	452	800	161	397	32	7	345	120	—	—	—	—	—	—
2023	25	AAA MLE	Jacksonville Jumbo Shrimp	—	516	458	86	15	1	18	54	231	2	6	2	188	276	343	619	155	317	45	10	272	70	—	—	—	—	—	—
2024	26	MLB MLE	San Francisco Giants	—	119	113	28	5	0	5	5	34	0	1	0	248	280	425	704	177	307	29	4	317	100	+0	+0	-1	-5	+3	-0.3
2024	26	AAA MLE	Sacramento River Cats	—	146	131	40	2	0	7	12	39	2	1	0	305	372	481	853	176	382	27	8	374	139	—	—	—	—	—	—
2025	27	MLB MLE	San Francisco Giants	—	56	55	11	3	0	2	1	15	0	1	0	200	214	364	578	164	237	27	2	260	62	-3	+0	+2	-2	+1	-0.2
2025	27	AAA MLE	Sacramento River Cats	—	98	88	20	3	0	3	7	32	3	2	1	227	306	364	670	136	324	33	7	299	88	—	—	—	—	—	—
2026	28	MLB MLE	San Francisco Giants	—	35	34	6	1	0	0	1	8	0	0	0	176	200	206	406	29	231	23	3	188	13	-4	+0	-0	-0	+1	-0.4
2016	18	ROK MLE	DSL Marlins	—	57	55	7	1	1	0	1	13	0	0	0	127	143	182	325	55	167	23	2	149	-13	—	—	—	—	—	—
2016	18	ROK RAW	DSL Marlins	—	57	55	12	2	1	1	1	11	0	0	0	218	232	345	578	127	256	19	2	249	-13	—	—	—	—	—	—
2017	19	ROK MLE	GCL Marlins	—	167	158	26	4	2	3	6	73	3	3	3	165	210	272	482	108	280	44	4	212	30	—	—	—	—	—	—
2017	19	ROK RAW	GCL Marlins	—	167	154	41	7	3	5	10	51	3	3	3	266	323	448	771	182	367	31	6	341	30	—	—	—	—	—	—
2018	20	A MLE	Greensboro Grasshoppers	—	59	56	3	0	0	0	3	32	0	0	0	54	102	54	155		125	54	5	84	-57	—	—	—	—	—	—
2018	20	A RAW	Greensboro Grasshoppers	—	59	54	4	0	0	0	5	23	0	0	0	74	153	74	227		129	39	8	120	-57	—	—	—	—	—	—
2019	21	A MLE	3 teams	—	626	589	122	23	1	14	31	218	3	6	3	207	250	321	571	114	300	35	5	251	56	—	—	—	—	—	—
2019	21	A RAW	3 teams	—	626	575	158	28	1	19	45	168	3	6	3	275	331	426	757	151	355	27	7	336	56	—	—	—	—	—	—
2021	23	AA MLE	Pensacola Blue Wahoos	—	260	237	40	9	1	6	17	124	5	5	5	169	239	291	531	122	315	48	7	237	47	—	—	—	—	—	—
2021	23	AA RAW	Pensacola Blue Wahoos	—	260	230	51	12	1	9	24	99	5	5	5	222	309	400	709	178	341	38	9	317	47	—	—	—	—	—	—
2022	24	AAA MLE	4 teams	—	610	562	130	20	0	22	38	219	2	10	5	231	282	384	667	153	328	36	6	290	82	—	—	—	—	—	—
2022	24	AAA RAW	4 teams	—	610	539	153	23	0	28	61	177	2	10	5	284	359	482	841	199	365	29	10	367	82	—	—	—	—	—	—
2023	25	AAA MLE	2 teams	—	625	556	103	18	1	21	65	279	2	9	2	185	273	335	607	149	318	45	10	272	70	—	—	—	—	—	—
2023	25	AAA RAW	2 teams	—	625	534	122	21	2	29	87	229	2	9	2	228	339	438	777	210	335	37	14	346	70	—	—	—	—	—	—
2024	26	INTL MLE	3 teams	—	434	398	113	12	0	21	28	119	5	5	2	284	339	472	811	188	352	27	6	348	122	—	—	—	—	—	—
2024	26	INTL RAW	3 teams	—	434	383	115	17	2	19	43	100	5	5	2	300	378	504	882	204	360	23	10	387	122	—	—	—	—	—	—
2025	27	AAA MLE	3 teams	—	208	193	43	9	0	7	11	64	3	3	1	223	275	378	654	155	293	31	5	285	79	—	—	—	—	—	—
2025	27	AAA RAW	3 teams	—	208	191	48	9	0	8	13	54	3	3	1	251	309	424	733	173	308	26	6	325	79	—	—	—	—	—	—
2026	28	MLB MLE	San Francisco Giants	—	35	34	6	1	0	0	1	8	0	0	0	176	200	206	406	29	231	23	3	188	13	-4	+0	-0	-0	+1	-0.4
2026	28	MLB RAW	San Francisco Giants	—	35	34	6	1	0	0	1	8	0	0	0	176	200	206	406	29	231	23	3	186	13	-4	+0	-0	-0	+1	-0.4
2016	18	ROK MLE	DSL Marlins	—	57	56	7	1	1	0	1	13	0	0	0	125	143	179	321	54	167	23	2	149	-13	—	—	—	—	—	—
2017	19	ROK MLE	GCL Marlins	—	167	156	26	4	2	3	6	73	3	3	3	167	210	276	485	109	284	44	4	212	30	—	—	—	—	—	—
2018	20	A MLE	Greensboro Grasshoppers	—	59	56	3	0	0	0	3	32	0	0	0	54	102	54	155		127	54	5	84	-57	—	—	—	—	—	—
2019	21	A MLE	3 teams	—	626	587	122	23	1	14	31	218	3	6	3	208	250	322	572	114	297	35	5	251	56	—	—	—	—	—	—
2021	23	AA MLE	Pensacola Blue Wahoos	—	260	236	40	9	1	6	17	124	5	5	5	169	239	292	532	123	315	48	7	237	47	—	—	—	—	—	—
2022	24	AAA MLE	4 teams	—	610	565	130	20	0	22	38	219	2	10	5	230	282	382	665	152	320	36	6	290	82	—	—	—	—	—	—
2023	25	AAA MLE	2 teams	—	625	553	103	18	1	21	65	279	2	9	2	186	273	336	609	150	317	45	10	272	70	—	—	—	—	—	—
2024	26	INTL MLE	3 teams	—	434	398	113	12	0	21	28	119	5	5	2	284	339	472	811	188	348	27	6	348	122	—	—	—	—	—	—
2025	27	AAA MLE	3 teams	—	208	192	43	9	0	7	11	64	3	3	1	224	275	380	656	156	292	31	5	285	79	—	—	—	—	—	—
2026	28	MLB MLE	San Francisco Giants	—	35	34	6	1	0	0	1	8	0	0	0	176	200	206	406	29	231	23	3	188	13	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	26	INTL MLE	3 teams	—	434	398	113	12	0	21	28	119	5	5	2	284	339	472	811	188	348	27	6	348	122	—	—	—	—	—	—
2025	27	AAA MLE	3 teams	—	208	192	43	9	0	7	11	64	3	3	1	224	275	380	656	156	292	31	5	285	79	—	—	—	—	—	—
2026	28	MLB MLE	San Francisco Giants	—	35	34	6	1	0	0	1	8	0	0	0	176	200	206	406	29	231	23	3	188	13	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	29	MLB MLE	SF	100%	200	183	47	8	1	8	13	51	2	3	1	256	312	435	746	179	310	26	6	328	108	+2	+0	+1	-2	+4	0.4
▸ 2027 — real world (MLB)
2027	29	MLB CTX	SF	100%	124	114	28	5	0	4	8	32	1	2	1	250	307	420	726	169	306	26	6	320	108	+1	+0	+0	-1	+3	0.3
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	30	MLB MLE	SF	82%	179	164	42	7	1	7	11	46	2	2	1	253	308	426	734	174	308	26	6	323	105	+1	+0	-1	-2	+4	0.2
2029	31	MLB MLE	SF	82%	168	154	37	6	0	6	10	44	2	1	0	248	302	416	718	168	304	26	6	317	101	+0	+0	-2	-2	+4	-0.0
2028	30	MLB CTX	SF	82%	147	135	33	6	0	5	9	38	2	1	1	247	303	412	714	164	303	26	6	315	105	+1	-0	-1	-2	+3	0.1
2029	31	MLB CTX	SF	82%	138	128	30	5	0	5	8	36	1	0	0	243	297	401	699	159	300	26	6	309	101	+0	+0	-2	-1	+3	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	576	542	122	23	0	20	27	163	3	5	1	225	266	378	644	153	281	28	5	288	73	-11	+1	-2	-17	+12	-1.7
/ 162G	—	A+C		—	650	612	138	26	0	23	30	184	3	6	1	225	265	381	646	155	280	28	5	288	73	-13	+1	-2	-19	+14	-2.0
Career	—	MLE		—	3552	3270	701	115	7	112	230	1271	28	46	23	214	272	357	628	142	309	36	6	277	73	-10	+1	-2	-19	+17	-1.4
/ 162G	—	MLE		—	650	598	127	21	1	20	42	233	5	8	4	212	270	351	621	139	307	36	6	277	73	-8	+1	-2	-16	+14	-1.2

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 AAASacramento River Cats · 98 PAwOBA .367 → .299 (−68)K% 27.6% → 32.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.55%	÷1.010	×1.200	—	—	32.72%
BB% (unintentional) /PA	11.22%	÷1.011	×0.690	—	×0.992	7.60%
HBP% /PA	3.06%	—	×0.940	—	×0.992	2.85%
Singles /BIP	26.32%	÷1.030	×0.930	×1.038	×0.992	24.47%
Doubles /BIP	7.02%	÷0.959	×0.830	×1.038	×0.992	6.25%
Triples /BIP	0.00%	÷0.900	×0.970	×1.038	×0.992	0.00%
Home runs /BIP	7.02%	÷0.938	×0.700	—	×0.992	5.20%

Factors used: league row International League. Park (home-season share, regressed): HR 88, 1B 106, 2B 92, 3B 80, K 102, BB 102 — applied at half strength. Age: age 28 vs a level average of 27.2 → −0.8% on BB/HBP/hit rates (0.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.038.

Result: wOBA .367 → .299; ISO .190 → .145; BABIP .358 → .324. 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 AAASacramento River Cats · 146 PAwOBA .448 → .374 (−73)K% 24.0% → 26.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.97%	÷1.081	×1.200	—	—	26.61%
BB% (unintentional) /PA	12.33%	÷1.032	×0.690	—	×1.003	8.27%
HBP% /PA	1.37%	—	×0.940	—	×1.003	1.29%
Singles /BIP	34.44%	÷0.976	×0.930	×1.004	×1.003	33.04%
Doubles /BIP	3.33%	÷1.052	×0.830	×1.004	×1.003	2.65%
Triples /BIP	0.00%	÷1.091	×0.970	×1.004	×1.003	0.00%
Home runs /BIP	11.11%	÷1.010	×0.700	—	×1.003	7.72%

Factors used: league row International League. Park (home-season share, regressed): HR 102, 1B 95, 2B 110, 3B 118, K 116, BB 106 — applied at half strength. Age: age 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.004.

Result: wOBA .448 → .374; ISO .264 → .192; BABIP .420 → .382. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2023 AAAJacksonville Jumbo Shrimp · 516 PAwOBA .347 → .272 (−74)K% 38.8% → 44.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	38.76%	÷1.040	×1.200	—	—	44.71%
BB% (unintentional) /PA	14.92%	÷1.008	×0.690	—	×1.018	10.40%
HBP% /PA	0.39%	—	×0.940	—	×1.018	0.37%
Singles /BIP	23.50%	÷1.016	×0.930	×1.030	×1.018	22.54%
Doubles /BIP	7.26%	÷0.955	×0.830	×1.030	×1.018	6.62%
Triples /BIP	0.43%	÷1.039	×0.970	×1.030	×1.018	0.42%
Home runs /BIP	11.11%	÷1.031	×0.700	—	×1.018	7.68%

Factors used: league row International League. Park (home-season share, regressed): HR 106, 1B 103, 2B 91, 3B 108, K 108, BB 102 — 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 ×1.030.

Result: wOBA .347 → .272; ISO .224 → .161; BABIP .348 → .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).

2022 AAAJacksonville Jumbo Shrimp · 297 PAwOBA .346 → .275 (−71)K% 29.3% → 36.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	29.29%	÷0.966	×1.200	—	—	36.40%
BB% (unintentional) /PA	9.43%	÷0.978	×0.690	—	×1.033	6.87%
HBP% /PA	0.00%	—	×0.940	—	×1.033	0.00%
Singles /BIP	24.86%	÷1.054	×0.930	×1.005	×1.033	22.77%
Doubles /BIP	6.78%	÷0.898	×0.830	×1.005	×1.033	6.51%
Triples /BIP	0.00%	÷0.930	×0.970	×1.005	×1.033	0.00%
Home runs /BIP	7.91%	÷1.032	×0.700	—	×1.033	5.54%

Factors used: league row International League. Park (home-season share, regressed): HR 106, 1B 111, 2B 80, 3B 86, K 93, BB 96 — 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 ×1.005.

Result: wOBA .346 → .275; ISO .205 → .148; BABIP .335 → .302. 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 AAPensacola Blue Wahoos · 136 PAwOBA .432 → .345 (−88)K% 25.7% → 32.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.74%	÷0.964	×1.220	—	—	32.56%
BB% (unintentional) /PA	9.56%	÷1.021	×0.680	—	×0.998	6.35%
HBP% /PA	1.47%	—	×0.840	—	×0.998	1.23%
Singles /BIP	37.65%	÷0.981	×0.920	×0.976	×0.998	34.40%
Doubles /BIP	3.53%	÷1.056	×0.910	×0.976	×0.998	2.96%
Triples /BIP	0.00%	÷1.150	×0.880	×0.976	×0.998	0.00%
Home runs /BIP	9.41%	÷1.048	×0.800	—	×0.998	7.17%

Factors used: league row SL. Park (home-season share, regressed): HR 110, 1B 96, 2B 111, 3B 130, K 93, BB 104 — applied at half strength. Age: age 25 vs a level average of 24.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.976.

Result: wOBA .432 → .345; ISO .225 → .166; BABIP .449 → .397. 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 AAPensacola Blue Wahoos · 260 PAwOBA .310 → .237 (−73)K% 38.1% → 47.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	38.08%	÷0.973	×1.220	—	—	47.76%
BB% (unintentional) /PA	9.23%	÷0.985	×0.690	—	×1.012	6.54%
HBP% /PA	1.92%	—	×0.850	—	×1.012	1.65%
Singles /BIP	22.14%	÷1.011	×0.940	×1.026	×1.012	21.38%
Doubles /BIP	9.16%	÷1.026	×0.870	×1.026	×1.012	8.06%
Triples /BIP	0.76%	÷1.150	×0.920	×1.026	×1.012	0.63%
Home runs /BIP	6.87%	÷1.011	×0.780	—	×1.012	5.37%

Factors used: level-wide AA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 102, 1B 102, 2B 105, 3B 130, K 95, BB 97 — applied at half strength. Age: age 24 vs a level average of 24.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.026.

Result: wOBA .310 → .237; ISO .178 → .127; BABIP .341 → .315. 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 AClinton LumberKings · 281 PAwOBA .361 → .268 (−92)K% 24.6% → 32.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.56%	÷1.019	×1.360	—	—	32.77%
BB% (unintentional) /PA	7.47%	÷0.972	×0.690	—	—	5.31%
HBP% /PA	1.07%	—	×0.780	—	—	0.83%
Singles /BIP	26.88%	÷1.019	×0.920	×0.950	—	23.05%
Doubles /BIP	8.60%	÷1.007	×0.830	×0.950	—	6.74%
Triples /BIP	0.00%	÷0.936	×0.910	×0.950	—	0.00%
Home runs /BIP	5.38%	÷1.085	×0.800	—	—	3.96%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 117, 1B 104, 2B 101, 3B 87, K 104, BB 94 — applied at half strength. Age: age 22 vs a level average of 22.0 → +0.0% on BB/HBP/hit rates (0.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .361 → .268; ISO .180 → .125; BABIP .375 → .310. 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+Jupiter Hammerheads · 272 PAwOBA .292 → .233 (−59)K% 26.1% → 36.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.10%	÷1.007	×1.420	—	—	36.82%
BB% (unintentional) /PA	5.88%	÷0.998	×0.750	—	×1.012	4.47%
HBP% /PA	0.00%	—	×0.930	—	×1.012	0.00%
Singles /BIP	25.82%	÷1.045	×0.920	×0.950	×1.012	21.86%
Doubles /BIP	5.49%	÷0.931	×0.960	×0.950	×1.012	5.45%
Triples /BIP	0.55%	÷1.120	×0.810	×0.950	×1.012	0.38%
Home runs /BIP	3.30%	÷0.803	×0.880	—	×1.012	3.66%

Factors used: league row FSL. Park (home-season share, regressed): HR 61, 1B 109, 2B 86, 3B 124, K 101, BB 100 — 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 .292 → .233; ISO .119 → .108; BABIP .326 → .284. 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
#1Chris Heiseylast yr '17 career totals — 8 seasons, 1,758 PA	2.6	1,758	62	25	238	296	413	-18	+3	3.0	3.2
/162	664	23	9	-6.7	+1.0	1.1	pk7: 4
#2Larry Stahl'64-'73 * career totals — 9 seasons, 1,889 PA	2.8	1,889	36	22	235*	297*	387*	-16	+11	2.4	2.9
/162	664	13	8	-5.5	+3.9	0.8	pk7: 4
#3Max Venable'79-'91 * career totals — 10 seasons, 1,560 PA	2.3	1,560	18	64	238*	301*	371*	-11	-1	0.9	1.9
/162	664	8	27	-4.6	-0.3	0.4	pk7: 3
#4Jake Cavelast yr '24 career totals — 7 seasons, 1,564 PA	2.4	1,564	45	13	236	292	400	-11	-6	1.3	1.3
/162	664	19	6	-4.5	-2.5	0.6	pk7: 1
#5Chad Pinderlast yr '22 career totals — 7 seasons, 1,740 PA	2.6	1,740	62	5	242	294	417	-17	-20	0.6	0.6
/162	664	24	2	-6.5	-7.6	0.2	pk7: 1
#6Dave McCarty'93-'05 * career totals — 9 seasons, 1,647 PA	2.5	1,647	36	9	233*	295*	365*	-26	+16	-1.1	0.5
/162	664	15	4	-10.5	+6.6	-0.4	pk7: 2
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	1.0	665	26	8	239	281	411	-7	+1	0.4	0.4
/162	664	26	8	-7.1	+1.1	0.4	pk7: 0

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
Jerar Encarnacion (OGILVIE)	29	55	55	40	40	254/309/431	177	310	5	2	26%	6%	108	+0.4	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Tim Beckham 2019 · MLB	29	49→55	50→55	41→50	43	245/299/396	151	314	18	5	27%	7%	95	+1.0	238/292/419	181	305	22	5	28%	7%	99	+1.2	248/297/425	177	324	22	3	30%	6%	101	+0.5
●Trevor Plouffe 2014 · MLB	28	47→54	53→60	41→45	47	246/306/417	171	281	21	4	21%	7%	103	+1.6	251/312/420	169	289	18	3	20%	8%	105	+1.7	250/312/422	172	284	18	2	19%	8%	107	+1.6
●Ty Wigginton 2007 · MLB	29	50→55	57→60	43→50	48	263/320/461	197	289	25	7	19%	7%	118	+2.7	273/329/464	191	300	24	5	18%	7%	122	+3.0	276/331/455	180	299	23	3	16%	6%	122	+2.4
✕Andrew Brown 2014 · MLB	29	46	54→55	46→40	44	236/298/420	184	304	21	5	29%	8%	101	+1.4	228/293/402	174	285	21	5	27%	7%	95	+0.9	212/278/382	171	257	23	2	27%	7%	83	+0.1
✕Welington Castillo 2016 · MLB	29	46→56	54→55	47→30	45	240/302/414	174	283	23	2	24%	7%	101	+1.4	253/305/422	169	313	23	3	26%	6%	104	+1.6	257/306/415	158	323	22	2	27%	6%	103	+0.9
✕Michael McKenry 2015 · MLB	30	50→47	52→55	41→40	50	256/324/424	168	301	20	6	22%	8%	111	+2.1	219/310/363	144	287	14	6	27%	11%	93	+0.8	178/284/300	122	248	11	3	30%	12%	68	-0.4
✕Austin Dean 2022 · MLB	28	46→56	51→55	41→45	45	233/297/403	170	304	19	7	29%	8%	97	+1.1	225/286/370	145	289	16	11	27%	6%	84	+0.2	218/275/362	143	275	16	12	26%	6%	75	-0.4
●Xavier Nady 2008 · MLB	29	53→59	55→60	44→45	44	272/322/455	183	305	23	5	20%	5%	118	+2.7	280/332/457	177	323	21	4	20%	6%	122	+2.9	274/325/427	153	320	18	2	20%	5%	113	+1.5
✕Renato Núñez 2021 · MLB	27	47→53	56→60	44→30	46	246/311/435	188	295	25	3	26%	8%	109	+2.0	234/304/429	195	287	26	5	28%	7%	106	+1.8	214/288/411	197	257	27	1	28%	6%	94	+0.6
✕Aledmys Díaz 2020 · MLB	29	49→57	52→55	43→45	50	251/306/420	169	262	20	6	14%	6%	104	+1.6	247/303/414	167	271	20	4	17%	6%	101	+1.4	236/287/371	135	270	15	1	18%	5%	86	+0.2
●Jonny Gomes 2011 · MLB	30	48→53	55→60	47→50	45	250/314/437	187	297	23	8	24%	7%	111	+2.1	243/335/434	191	302	25	8	27%	10%	118	+2.6	233/341/429	196	291	26	6	28%	12%	120	+1.7
✕Ryan McBroom 2021 · MLB	29	50→53	54→50	39→40	42	255/307/428	173	325	22	4	28%	6%	106	+1.8	220/278/397	177	268	24	6	27%	7%	88	+0.5	194/253/367	173	223	26	3	27%	6%	70	-0.7
✕Tyler Moore 2015 · MLB	28	45→48	52→65	42→40	46	234/300/399	165	295	20	3	28%	8%	97	+1.1	218/271/366	148	277	17	3	27%	6%	78	-0.3	207/249/358	151	259	17	0	27%	5%	68	-0.3
✕Cameron Rupp 2018 · MLB	29	45→49	54→55	47→30	44	234/296/414	180	303	21	3	30%	8%	99	+1.2	200/270/360	160	289	20	3	36%	8%	77	-0.3	162/236/306	144	234	20	0	39%	8%	50	-1.1
✕Yasmany Tomás 2018 · MLB	27	48→54	57→60	41→40	42	255/297/453	198	302	26	4	25%	6%	108	+1.9	218/249/388	170	290	22	4	32%	4%	75	-0.5	200/224/359	160	270	21	3	35%	3%	56	-1.2
✕Colin Moran 2021 · MLB	28	52→57	53→55	40→30	47	265/321/437	172	314	21	2	23%	7%	113	+2.3	235/304/380	145	297	18	3	26%	9%	94	+0.9	222/294/344	122	283	16	1	26%	9%	81	-0.0
✕John Hicks 2019 · MLB	29	51→52	49→55	43→50	41	254/298/402	148	325	17	6	27%	6%	97	+1.1	234/274/404	170	308	22	6	31%	5%	88	+0.4	211/245/385	174	278	23	9	33%	4%	71	-0.4
✕Devin Mesoraco 2016 · MLB	28	48→50	55→60	40	49	249/321/436	187	283	23	5	21%	8%	113	+2.3	222/305/375	153	258	18	5	21%	9%	93	+0.8	208/295/367	159	233	21	1	21%	9%	89	+0.2
✕John Buck 2011 · MLB	31	50→53	56→60	41→30	41	258/304/453	195	311	24	3	25%	5%	111	+2.1	232/301/396	164	277	21	2	24%	8%	97	+1.1	217/294/368	151	257	20	1	24%	9%	89	+0.4
●Nick Castellanos 2021 · MLB	29	52→61	59→65	40→45	45	271/325/497	226	319	26	3	24%	7%	129	+3.4	274/322/474	200	327	24	6	23%	6%	122	+3.0	275/321/465	190	333	23	7	24%	6%	120	+2.8

Jerar Encarnacion

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps