Jorge Soler

RF Los Angeles Angels

Age 35 R/R 6'3" / 235 lbs MLB K +5%HR +4% Svc 11.575 · Ctrl thru 2027

Overview

MLBExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	32	MLBATL	574	.241/.339/.442	21	1	119	1.3
2025	33	MLBLAA	315	.215/.295/.387	12	0	91	-0.4
2026	34	MLBLAA	361	.203/.294/.373	12	0	89	-0.2
2027PROJ	35	MLBLAA	237	.221/.311/.418	10	1	105	0.1
2028PROJ	36	MLBLAA	171	.208/.297/.389	7	1	93	-0.8

Last 3 seasons WAR 0.7 · Next 2 projected WAR -0.7Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service11.575First FA2028

2027Ext / FA-deal$1M

Skills · percentileStatcast 2024-2026

Barrel%77

Bat Spd77

xwOBA60

Avg EV59

Speed20

CompsMark Reynolds (age 35) · Miguel Olivo (age 35) · John Buck (age 34)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 107105vR 97

AVG/OBP/SLG.221 / .311 / .418

PA237

HR10

K%29

BB%10

BABIP274

ISO202

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

140.222

POWER

Barrel%

7712.2

Avg EV

5989.7

Bat Spd

7774.2

SPEED

Sprint

2026.0

Platoon Splits2024-2026 · 988 PA

vs LHP

vs RHP

Edge

235

753

—

wRC+

133

102

◀◀L

wOBA

364

319

◀L

ISO

215

187

◀L

BABIP

296

282

◀L

24.3%

28.0%

◀L

BB%

14.5%

9.8%

◀◀L

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

Status FA

MLB Debut 2014

Service 11.575 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$1M	+0.1	$0.4M	-$0.6M
Totals		$1M		$0.4M	-$0.6M

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)
2012	20	A	Peoria Chiefs	—	88	80	27	5	0	3	6	6	2	4	1	338	398	512	910	175	338	7	7	404	125	—	—	—	—	—	—
2012	20	ROK	AZL Cubs	—	61	54	13	2	0	2	6	13	1	8	0	241	328	389	717	148	282	21	10	325	36	—	—	—	—	—	—
2013	21	A+	Daytona Cubs	—	237	210	59	13	1	8	21	38	1	5	1	281	348	467	814	186	304	16	9	354	93	—	—	—	—	—	—
2013	21	INTL	Mesa Solar Sox	—	90	85	23	6	0	1	5	21	0	0	0	271	311	376	688	106	349	23	6	308	95	—	—	—	—	—	—
2014	22	MLB	Chicago Cubs	—	97	89	26	8	1	5	6	24	0	1	0	292	337	573	910	281	339	25	6	385	146	+5	+0	-2	-4	+2	0.2
2014	22	AAA	Iowa Cubs	—	127	110	31	11	1	8	17	26	0	0	1	282	378	618	996	336	303	20	13	427	113	—	—	—	—	—	—
2014	22	AA	Tennessee Smokies	—	79	65	27	9	1	6	12	15	0	0	0	415	506	862	1.368	446	457	19	15	557	214	—	—	—	—	—	—
2014	22	ROK	AZL Cubs	—	30	25	10	3	0	1	4	7	1	0	0	400	500	640	1.140	240	529	23	13	496	112	—	—	—	—	—	—
2015	23	MLB	Chicago Cubs	—	404	366	96	18	1	10	32	121	3	3	1	262	327	399	726	137	361	30	8	324	99	-1	+0	-9	-4	+9	-0.5
2015	23	AAA	Iowa Cubs	—	16	13	2	0	0	0	3	4	0	0	0	154	312	154	466		222	25	19	244	20	—	—	—	—	—	—
2016	24	MLB	Chicago Cubs	—	264	227	54	9	0	12	31	66	3	0	0	238	337	436	773	198	276	25	12	342	119	+6	+0	-4	-3	+6	0.4
2016	24	AA	Tennessee Smokies	—	42	30	5	0	0	0	11	11	0	0	0	167	390	167	557		250	26	26	290	47	—	—	—	—	—	—
2017	25	MLB	Kansas City Royals	—	110	97	14	5	0	2	12	36	1	0	0	144	245	258	503	113	203	33	11	237	44	-7	+0	-1	-5	+2	-1.1
2017	25	AAA	Omaha Storm Chasers	—	327	273	73	9	0	24	50	82	4	1	0	267	388	564	952	297	293	25	15	414	109	—	—	—	—	—	—
2018	26	MLB	Kansas City Royals	—	257	223	59	18	0	9	28	69	4	3	1	265	357	466	823	202	340	27	11	363	136	+11	+0	-7	-3	+6	0.7
2019	27	MLB	Kansas City Royals	—	679	589	156	33	1	48	73	178	10	3	1	265	354	569	923	304	294	26	11	396	161	+49	+0	-5	-7	+15	5.3
2020	28	MLB	Kansas City Royals	—	174	149	34	8	0	8	19	60	3	0	0	228	324	443	767	215	317	34	11	337	120	+4	+0	-0	-2	+4	0.6
2021	29	MLB	Atlanta Braves	—	602	516	115	27	0	27	67	142	6	0	0	223	315	432	747	209	250	24	11	328	108	+6	+0	-9	-6	+13	0.3
2022	30	MLB	Miami Marlins	—	306	270	56	13	0	13	31	90	3	0	2	207	295	400	695	193	256	29	10	310	102	+1	-1	-2	-3	+7	0.2
2023	31	MLB	Miami Marlins	—	580	504	126	24	0	36	66	141	6	1	0	250	344	512	856	262	272	24	11	372	144	+30	+0	-4	-6	+13	3.3
2024	32	MLB	Atlanta Braves	—	574	493	119	34	1	21	68	141	6	1	0	241	339	442	781	201	293	25	12	345	119	+13	+0	-7	-6	+12	1.3
2025	33	MLB	Los Angeles Angels	—	315	279	60	12	0	12	28	94	4	0	0	215	295	387	682	172	273	30	9	303	91	-3	+0	-4	-3	+7	-0.4
2026	34	MLB	Los Angeles Angels	—	361	316	64	16	1	12	35	118	6	0	0	203	294	373	668	171	274	33	10	298	89	-5	+0	-1	-4	+8	-0.2
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4723	4118	979	225	5	215	496	1280	55	12	5	238	326	451	778	214	287	27	11	342	117	+98	+0	-55	-57	+102	9.0
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	20	A MLE	Peoria Chiefs	—	88	83	26	4	0	3	3	8	2	4	1	313	352	470	822	157	319	9	3	353	125	—	—	—	—	—	—
2012	20	ROK MLE	AZL Cubs	—	61	56	9	1	0	1	4	19	1	8	0	161	230	232	462	71	222	31	7	222	36	—	—	—	—	—	—
2013	21	A+ MLE	Daytona Cubs	—	237	217	54	12	1	6	15	51	1	5	1	249	300	396	697	147	286	22	6	305	93	—	—	—	—	—	—
2014	22	MLB MLE	Chicago Cubs	—	97	89	26	8	1	5	6	24	0	1	0	292	337	573	910	281	339	25	6	384	146	+5	+0	-2	-4	+2	0.2
2014	22	AAA MLE	Iowa Cubs	—	127	118	28	9	1	7	9	34	0	0	1	237	291	508	800	271	261	27	7	335	113	—	—	—	—	—	—
2014	22	AA MLE	Tennessee Smokies	—	79	68	25	8	1	5	9	19	0	0	0	368	442	735	1.177	368	412	24	11	485	214	—	—	—	—	—	—
2014	22	ROK MLE	AZL Cubs	—	30	27	7	2	0	1	2	10	1	0	0	259	333	444	778	185	400	33	7	333	112	—	—	—	—	—	—
2015	23	MLB MLE	Chicago Cubs	—	404	371	95	17	1	10	27	121	3	3	1	256	312	388	700	132	361	30	7	314	99	-1	+0	-9	-4	+9	-0.5
2015	23	AAA MLE	Iowa Cubs	—	16	14	2	0	0	0	2	5	0	0	0	143	250	143	393		208	31	12	198	20	—	—	—	—	—	—
2016	24	MLB MLE	Chicago Cubs	—	264	227	54	9	0	12	31	66	3	0	0	238	337	436	773	198	276	25	12	344	119	+6	+0	-4	-3	+6	0.4
2016	24	AA MLE	Tennessee Smokies	—	42	33	5	0	0	0	8	14	0	0	0	152	317	152	469		231	33	19	238	47	—	—	—	—	—	—
2017	25	MLB MLE	Kansas City Royals	—	110	98	14	5	0	2	11	36	1	0	0	143	236	255	491	112	203	33	10	234	44	-7	+0	-1	-5	+2	-1.1
2017	25	AAA MLE	Omaha Storm Chasers	—	327	289	64	8	0	20	34	100	4	1	0	221	312	457	769	235	258	31	10	329	109	—	—	—	—	—	—
2018	26	MLB MLE	Kansas City Royals	—	257	223	60	18	0	10	28	69	4	3	1	269	361	484	845	215	340	27	11	370	136	+11	+0	-7	-3	+6	0.7
2019	27	MLB MLE	Kansas City Royals	—	679	595	161	33	1	52	70	178	10	3	1	271	357	592	949	321	294	26	10	406	161	+49	+0	-5	-7	+15	5.3
2020	28	MLB MLE	Kansas City Royals	—	174	151	35	8	0	9	19	60	3	0	0	232	329	464	793	232	317	34	11	346	120	+4	+0	-0	-2	+4	0.6
2021	29	MLB MLE	Atlanta Braves	—	602	524	115	27	0	27	67	142	6	0	0	219	315	426	740	206	250	24	11	328	108	+6	+0	-9	-6	+13	0.3
2022	30	MLB MLE	Miami Marlins	—	306	272	58	14	0	14	30	90	3	0	2	213	298	419	717	206	256	29	10	318	102	+1	-1	-2	-3	+7	0.2
2023	31	MLB MLE	Miami Marlins	—	580	508	131	26	0	38	62	141	6	1	0	258	345	533	879	276	272	24	11	381	144	+30	+0	-4	-6	+13	3.3
2024	32	MLB MLE	Atlanta Braves	—	574	496	119	34	1	21	68	141	6	1	0	240	339	440	778	200	293	25	12	345	119	+13	+0	-7	-6	+12	1.3
2025	33	MLB MLE	Los Angeles Angels	—	315	280	60	12	0	12	28	94	4	0	0	214	295	386	681	171	273	30	9	303	91	-3	+0	-4	-3	+7	-0.4
2026	34	MLB MLE	Los Angeles Angels	—	361	316	65	17	1	12	35	118	6	0	0	206	297	380	677	174	274	33	10	299	89	-5	+0	-1	-4	+8	-0.2
2012	20	A MLE	2 teams	—	149	140	36	6	0	4	6	27	3	12	1	257	302	386	688	129	294	18	4	299	89	—	—	—	—	—	—
2012	20	A RAW	2 teams	—	149	134	40	7	0	5	12	19	3	12	1	299	369	463	832	164	318	13	8	371	89	—	—	—	—	—	—
2013	21	A+ MLE	2 teams	—	327	301	75	16	1	9	21	70	1	5	1	249	300	399	699	150	292	21	6	305	93	—	—	—	—	—	—
2013	21	A+ RAW	2 teams	—	327	295	82	19	1	9	26	59	1	5	1	278	337	441	778	163	316	18	8	341	93	—	—	—	—	—	—
2014	22	AAA MLE	4 teams	—	333	302	85	26	3	18	26	86	1	1	1	281	340	566	907	285	332	26	8	385	146	—	—	—	—	—	—
2014	22	AAA RAW	4 teams	—	333	289	94	31	3	20	39	72	1	1	1	325	407	661	1.068	336	368	22	12	452	146	—	—	—	—	—	—
2015	23	MLB MLE	2 teams	—	420	385	97	17	1	10	29	126	3	3	1	252	309	379	689	127	345	30	7	310	96	-2	+0	-9	-4	+9	-0.6
2015	23	MLB RAW	2 teams	—	420	379	98	18	1	10	35	125	3	3	1	259	326	391	717	132	356	30	8	320	96	-2	+0	-9	-4	+9	-0.6
2016	24	MLB MLE	2 teams	—	306	260	59	9	0	12	39	80	3	0	0	227	334	400	734	173	273	26	13	329	109	+3	+0	-4	-3	+7	0.2
2016	24	MLB RAW	2 teams	—	306	257	59	9	0	12	42	77	3	0	0	230	344	405	749	175	273	25	14	335	109	+3	+0	-4	-3	+7	0.2
2017	25	AAA MLE	2 teams	—	437	387	78	13	0	22	45	136	5	1	0	202	293	406	699	204	245	31	10	305	93	—	—	—	—	—	—
2017	25	AAA RAW	2 teams	—	437	370	87	14	0	26	62	118	5	1	0	235	352	484	836	249	270	27	14	370	93	—	—	—	—	—	—
2018	26	MLB MLE	Kansas City Royals	—	257	223	60	18	0	10	28	69	4	3	1	269	361	484	845	215	342	27	11	370	136	+11	+0	-7	-3	+6	0.7
2018	26	MLB RAW	Kansas City Royals	—	257	223	59	18	0	9	28	69	4	3	1	265	357	466	823	202	340	27	11	363	136	+11	+0	-7	-3	+6	0.7
2019	27	MLB MLE	Kansas City Royals	—	679	595	161	33	1	52	70	178	10	3	1	271	357	592	949	321	295	26	10	406	161	+49	+0	-5	-7	+15	5.3
2019	27	MLB RAW	Kansas City Royals	—	679	589	156	33	1	48	73	178	10	3	1	265	354	569	923	304	294	26	11	396	161	+49	+0	-5	-7	+15	5.3
2020	28	MLB MLE	Kansas City Royals	—	174	151	35	8	0	9	19	60	3	0	0	232	329	464	793	232	313	34	11	346	120	+4	+0	-0	-2	+4	0.6
2020	28	MLB RAW	Kansas City Royals	—	174	149	34	8	0	8	19	60	3	0	0	228	324	443	767	215	317	34	11	337	120	+4	+0	-0	-2	+4	0.6
2021	29	MLB MLE	Atlanta Braves	—	602	524	115	27	0	27	67	142	6	0	0	219	315	426	740	206	244	24	11	328	108	+6	+0	-9	-6	+13	0.3
2021	29	MLB RAW	Atlanta Braves	—	602	516	115	27	0	27	67	142	6	0	0	223	315	432	747	209	250	24	11	328	108	+6	+0	-9	-6	+13	0.3
2022	30	MLB MLE	Miami Marlins	—	306	272	58	14	0	14	30	90	3	0	2	213	298	419	717	206	260	29	10	318	102	+1	-1	-2	-3	+7	0.2
2022	30	MLB RAW	Miami Marlins	—	306	270	56	13	0	13	31	90	3	0	2	207	295	400	695	193	256	29	10	310	102	+1	-1	-2	-3	+7	0.2
2023	31	MLB MLE	Miami Marlins	—	580	508	131	26	0	38	62	141	6	1	0	258	345	533	879	276	279	24	11	381	144	+30	+0	-4	-6	+13	3.3
2023	31	MLB RAW	Miami Marlins	—	580	504	126	24	0	36	66	141	6	1	0	250	344	512	856	262	272	24	11	372	144	+30	+0	-4	-6	+13	3.3
2024	32	MLB MLE	Atlanta Braves	—	574	496	119	34	1	21	68	141	6	1	0	240	339	440	778	200	290	25	12	345	119	+13	+0	-7	-6	+12	1.3
2024	32	MLB RAW	Atlanta Braves	—	574	493	119	34	1	21	68	141	6	1	0	241	339	442	781	201	293	25	12	345	119	+13	+0	-7	-6	+12	1.3
2025	33	MLB MLE	Los Angeles Angels	—	315	280	60	12	0	12	28	94	4	0	0	214	295	386	681	171	271	30	9	303	91	-3	+0	-4	-3	+7	-0.4
2025	33	MLB RAW	Los Angeles Angels	—	315	279	60	12	0	12	28	94	4	0	0	215	295	387	682	172	273	30	9	303	91	-3	+0	-4	-3	+7	-0.4
2026	34	MLB MLE	Los Angeles Angels	—	361	316	65	17	1	12	35	118	6	0	0	206	297	380	677	174	279	33	10	299	89	-5	+0	-1	-4	+8	-0.2
2026	34	MLB RAW	Los Angeles Angels	—	361	316	64	16	1	12	35	118	6	0	0	203	294	373	668	171	274	33	10	298	89	-5	+0	-1	-4	+8	-0.2
2012	20	A MLE	2 teams	—	149	139	36	6	0	4	6	27	3	12	1	259	302	388	691	129	279	18	4	299	89	—	—	—	—	—	—
2013	21	A+ MLE	2 teams	—	327	302	75	16	1	9	21	70	1	5	1	248	300	397	698	149	286	21	6	305	93	—	—	—	—	—	—
2014	22	AAA MLE	4 teams	—	333	303	85	26	3	18	26	86	1	1	1	281	340	564	905	284	332	26	8	385	146	—	—	—	—	—	—
2015	23	MLB MLE	2 teams	—	420	385	97	17	1	10	29	126	3	3	1	252	309	379	689	127	356	30	7	310	96	—	—	—	—	—	—
2016	24	MLB MLE	2 teams	—	306	261	59	9	0	12	39	80	3	0	0	226	334	398	733	172	270	26	13	329	109	—	—	—	—	—	—
2017	25	AAA MLE	2 teams	—	437	384	78	13	0	22	45	136	5	1	0	203	293	409	702	206	244	31	10	305	93	—	—	—	—	—	—
2018	26	MLB MLE	Kansas City Royals	—	257	223	60	18	0	10	28	69	4	3	1	269	361	484	845	215	340	27	11	370	136	—	—	—	—	—	—
2019	27	MLB MLE	Kansas City Royals	—	679	594	161	33	1	52	70	178	10	3	1	271	357	593	950	322	294	26	10	406	161	—	—	—	—	—	—
2020	28	MLB MLE	Kansas City Royals	—	174	150	35	8	0	9	19	60	3	0	0	233	329	467	796	233	317	34	11	346	120	—	—	—	—	—	—
2021	29	MLB MLE	Atlanta Braves	—	602	524	115	27	0	27	67	142	6	0	0	219	315	426	740	206	250	24	11	328	108	—	—	—	—	—	—
2022	30	MLB MLE	Miami Marlins	—	306	270	58	14	0	14	30	90	3	0	2	215	298	422	721	207	256	29	10	318	102	—	—	—	—	—	—
2023	31	MLB MLE	Miami Marlins	—	580	507	131	26	0	38	62	141	6	1	0	258	345	535	880	276	272	24	11	381	144	—	—	—	—	—	—
2024	32	MLB MLE	Atlanta Braves	—	574	495	119	34	1	21	68	141	6	1	0	240	339	440	779	200	293	25	12	345	119	—	—	—	—	—	—
2025	33	MLB MLE	Los Angeles Angels	—	315	280	60	12	0	12	28	94	4	0	0	214	295	386	681	171	273	30	9	303	91	—	—	—	—	—	—
2026	34	MLB MLE	Los Angeles Angels	—	361	317	65	17	1	12	35	118	6	0	0	205	297	379	675	174	274	33	10	299	89	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	32	MLB MLE	Atlanta Braves	—	574	495	119	34	1	21	68	141	6	1	0	240	339	440	779	200	293	25	12	345	119	—	—	—	—	—	—
2025	33	MLB MLE	Los Angeles Angels	—	315	280	60	12	0	12	28	94	4	0	0	214	295	386	681	171	273	30	9	303	91	—	—	—	—	—	—
2026	34	MLB MLE	Los Angeles Angels	—	361	317	65	17	1	12	35	118	6	0	0	205	297	379	675	174	274	33	10	299	89	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	35	MLB MLE	LAA	100%	349	306	68	16	1	14	35	100	5	2	1	222	312	418	730	196	277	29	10	324	105	+2	+0	-5	-4	+8	0.1
▸ 2027 — real world (MLB)
2027	35	MLB CTX	LAA	100%	237	208	46	10	1	10	24	68	3	1	0	221	311	418	729	197	274	29	10	323	105	+1	+0	-3	-3	+5	0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	36	MLB MLE	LAA	100%	171	150	31	7	0	6	17	50	2	1	0	209	298	389	687	180	264	29	10	306	93	-1	+0	-9	-2	+4	-0.8
2028	36	MLB CTX	LAA	100%	171	150	32	7	0	7	17	50	2	1	0	208	297	389	686	181	262	29	10	306	93	-1	+0	-9	-2	+4	-0.8
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	4894	4268	1011	232	5	222	513	1330	57	13	5	237	326	450	775	213	287	27	10	340	116	+97	+1	-64	-59	+106	8.2
/ 162G	—	A+C		—	650	567	134	31	1	29	68	177	8	2	1	236	326	448	774	212	287	27	10	340	116	+13	+0	-8	-8	+14	1.1
Career	—	MLE		—	6228	5498	1312	294	9	286	614	1676	69	32	8	239	323	451	774	213	287	27	10	339	116	+98	+1	-67	-62	+111	8.3
/ 162G	—	MLE		—	650	574	137	31	1	30	64	175	7	3	1	239	322	453	775	214	286	27	10	339	116	+12	+0	-8	-8	+14	1.1

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2017 AAAOmaha Storm Chasers · 327 PAwOBA .403 → .329 (−75)K% 25.1% → 30.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.08%	÷1.054	×1.290	—	—	30.68%
BB% (unintentional) /PA	15.29%	÷1.076	×0.710	—	×1.033	10.42%
HBP% /PA	1.22%	—	×0.980	—	×1.033	1.24%
Singles /BIP	20.94%	÷1.024	×0.900	×1.003	×1.033	19.07%
Doubles /BIP	4.71%	÷0.985	×0.810	×1.003	×1.033	4.02%
Triples /BIP	0.00%	÷0.914	×0.810	×1.003	×1.033	0.00%
Home runs /BIP	12.57%	÷0.956	×0.780	—	×1.033	10.59%

Factors used: league row PCL. Park (home-season share, regressed): HR 91, 1B 105, 2B 97, 3B 83, K 111, BB 115 — 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 ×1.003.

Result: wOBA .403 → .329; ISO .297 → .247; BABIP .293 → .258. 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 AATennessee Smokies · 42 PAwOBA .292 → .238 (−55)K% 26.2% → 32.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.19%	÷0.992	×1.220	—	—	32.23%
BB% (unintentional) /PA	26.19%	÷0.982	×0.680	—	×1.012	18.36%
HBP% /PA	0.00%	—	×0.840	—	×1.012	0.00%
Singles /BIP	26.32%	÷1.013	×0.920	—	×1.012	24.18%
Doubles /BIP	0.00%	÷0.918	×0.910	—	×1.012	0.00%
Triples /BIP	0.00%	÷0.900	×0.880	—	×1.012	0.00%
Home runs /BIP	0.00%	÷1.059	×0.800	—	×1.012	0.00%

Factors used: league row SL. Park (home-season share, regressed): HR 112, 1B 103, 2B 84, 3B 80, K 98, BB 96 — 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).

Result: wOBA .292 → .238; ISO .000 → .000; BABIP .250 → .231. 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 AAAIowa Cubs · 16 PAwOBA .239 → .198 (−41)K% 25.0% → 30.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷1.051	×1.290	—	—	30.68%
BB% (unintentional) /PA	18.75%	÷0.996	×0.710	—	×1.050	14.03%
HBP% /PA	0.00%	—	×0.980	—	×1.050	0.00%
Singles /BIP	22.22%	÷1.008	×0.900	—	×1.050	20.83%
Doubles /BIP	0.00%	÷0.984	×0.810	—	×1.050	0.00%
Triples /BIP	0.00%	÷0.948	×0.810	—	×1.050	0.00%
Home runs /BIP	0.00%	÷0.916	×0.780	—	×1.050	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 83, 1B 102, 2B 97, 3B 90, K 110, BB 99 — applied at half strength. Age: age 23 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (4.2 yr younger than average).

Result: wOBA .239 → .198; ISO .000 → .000; BABIP .222 → .208. 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 AAAIowa Cubs · 127 PAwOBA .411 → .335 (−76)K% 20.5% → 26.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.47%	÷0.996	×1.290	—	—	26.51%
BB% (unintentional) /PA	11.81%	÷1.249	×0.710	—	×1.050	7.05%
HBP% /PA	0.00%	—	×0.980	—	×1.050	0.00%
Singles /BIP	13.10%	÷1.021	×0.900	×1.036	×1.050	12.56%
Doubles /BIP	13.10%	÷1.111	×0.810	×1.036	×1.050	10.39%
Triples /BIP	1.19%	÷1.150	×0.810	×1.036	×1.050	0.91%
Home runs /BIP	9.52%	÷0.929	×0.780	—	×1.050	8.40%

Factors used: league row PCL. Park (home-season share, regressed): HR 86, 1B 104, 2B 122, 3B 130, K 99, BB 150 — 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 ×1.036.

Result: wOBA .411 → .335; ISO .336 → .287; BABIP .303 → .261. 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 AATennessee Smokies · 79 PAwOBA .555 → .485 (−71)K% 19.0% → 23.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.99%	÷0.980	×1.220	—	—	23.63%
BB% (unintentional) /PA	15.19%	÷0.948	×0.680	—	×1.042	11.35%
HBP% /PA	0.00%	—	×0.840	—	×1.042	0.00%
Singles /BIP	22.00%	÷0.958	×0.920	—	×1.042	22.01%
Doubles /BIP	18.00%	÷1.140	×0.910	—	×1.042	14.97%
Triples /BIP	2.00%	÷1.065	×0.880	—	×1.042	1.72%
Home runs /BIP	12.00%	÷1.009	×0.800	—	×1.042	9.92%

Factors used: league row SL. Park (home-season share, regressed): HR 102, 1B 92, 2B 128, 3B 113, K 96, BB 90 — 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).

Result: wOBA .555 → .485; ISO .446 → .381; BABIP .457 → .412. 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 ROKAZL Cubs · 30 PAwOBA .483 → .333 (−151)K% 23.3% → 33.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.33%	÷1.000	×1.440	—	—	33.60%
BB% (unintentional) /PA	13.33%	÷1.000	×0.620	—	×0.975	8.06%
HBP% /PA	3.33%	—	×0.720	—	×0.975	2.34%
Singles /BIP	33.33%	÷1.000	×0.820	—	×0.975	26.65%
Doubles /BIP	16.67%	÷1.000	×0.720	—	×0.975	11.70%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.975	0.00%
Home runs /BIP	5.56%	÷1.000	×0.780	—	×0.975	4.23%

Factors used: level-wide ROK 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 22 vs a level average of 19.5 → −2.5% on BB/HBP/hit rates (2.5 yr older than average).

Result: wOBA .483 → .333; ISO .240 → .164; BABIP .529 → .400. 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 A+Daytona Cubs · 237 PAwOBA .349 → .305 (−44)K% 16.0% → 21.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.03%	÷1.066	×1.420	—	—	21.37%
BB% (unintentional) /PA	8.44%	÷1.032	×0.750	—	×1.027	6.30%
HBP% /PA	0.42%	—	×0.930	—	×1.027	0.40%
Singles /BIP	21.51%	÷1.015	×0.920	×1.038	×1.027	20.80%
Doubles /BIP	7.56%	÷1.132	×0.960	×1.038	×1.027	6.83%
Triples /BIP	0.58%	÷0.900	×0.810	×1.038	×1.027	0.56%
Home runs /BIP	4.65%	÷1.144	×0.880	—	×1.027	3.67%

Factors used: league row FSL. Park (home-season share, regressed): HR 129, 1B 103, 2B 126, 3B 80, K 113, BB 106 — applied at half strength. Age: age 21 vs a level average of 22.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.038.

Result: wOBA .349 → .305; ISO .186 → .154; BABIP .304 → .286. 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).

2012 APeoria Chiefs · 88 PAwOBA .386 → .353 (−32)K% 6.8% → 9.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	6.82%	÷1.010	×1.360	—	—	9.18%
BB% (unintentional) /PA	4.55%	÷1.053	×0.690	—	×1.030	3.07%
HBP% /PA	2.27%	—	×0.780	—	×1.030	1.83%
Singles /BIP	25.68%	÷1.013	×0.920	×1.044	×1.030	25.08%
Doubles /BIP	6.76%	÷1.062	×0.830	×1.044	×1.030	5.68%
Triples /BIP	0.00%	÷1.146	×0.910	×1.044	×1.030	0.00%
Home runs /BIP	4.05%	÷0.952	×0.800	—	×1.030	3.51%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 90, 1B 103, 2B 112, 3B 129, K 102, BB 111 — 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 ×1.044.

Result: wOBA .386 → .353; ISO .175 → .153; BABIP .338 → .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).

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
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 15 projected seasons	7.7	5,131	231	14	236	322	448	-55	-76	18.5	17.6
/162	664	30	2	-7.1	-9.9	2.4	pk7: 17
#1Dan Ford'75-'85 * career totals — 11 seasons, 4,582 PA	6.9	4,582	121	61	266*	324*	459*	-36	-32	12.4	12.5
/162	664	18	9	-5.2	-4.7	1.8	pk7: 12
#2Matt Joycelast yr '21 career totals — 13 seasons, 4,318 PA	6.5	4,318	146	34	242	343	425	-46	-44	11.7	11.9
/162	664	22	5	-7.1	-6.7	1.8	pk7: 12
#3Candy Maldonado'81-'95 * career totals — 13 seasons, 4,590 PA	6.9	4,590	146	34	252*	320*	452*	-47	-24	10.6	11.0
/162	664	21	5	-6.8	-3.4	1.5	pk7: 11
#4Pete Incaviglia'86-'98 * career totals — 11 seasons, 4,677 PA	7.0	4,677	206	33	242*	307*	466*	-56	-19	9.9	10.5
/162	664	29	5	-8.0	-2.7	1.4	pk7: 11
#5Jonny Gomeslast yr '15 career totals — 11 seasons, 3,978 PA	6.0	3,978	162	50	243	335	438	-43	-67	8.3	9.2
/162	664	27	8	-7.1	-11.1	1.4	pk7: 10
#6Mitch Hanigerlast yr '24 career totals — 8 seasons, 3,089 PA	4.7	3,089	130	19	250	324	448	-31	-36	7.8	8.4
/162	664	28	4	-6.7	-7.8	1.7	pk7: 9

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
Jorge Soler (OGILVIE)	35	—	—	—	—	220/310/415	194	277	10	1	29%	10%	105	+0.7	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Mark Reynolds 2019 · MLB	35	49→56	56→65	43→50	50	251/329/439	189	316	25	3	28%	10%	116	+2.5	226/314/391	165	306	20	8	30%	11%	100	+1.3	159/283/285	126	237	13	7	35%	14%	69	-0.3
✕Miguel Olivo 2013 · MLB	35	43→50	53→60	40→50	37	231/260/394	163	280	22	8	27%	4%	80	-0.1	234/272/390	156	303	19	8	29%	4%	84	+0.1	216/254/339	124	304	13	8	32%	4%	62	-0.7
✕John Buck 2014 · MLB	34	42→52	51→60	43→30	48	221/293/376	155	261	21	3	24%	8%	89	+0.5	232/296/358	126	288	15	5	24%	7%	85	+0.2	229/290/300	70	298	6	0	24%	7%	68	-0.4
●Ruben Mateo 2013 · AAA	35	47→50	57→60	39→45	41	251/292/445	194	270	26	5	19%	4%	105	+1.7	244/304/428	184	272	24	3	20%	5%	105	+1.7	233/299/406	173	260	24	1	21%	5%	97	+0.7
✕Ryan Ludwick 2013 · MLB	35	49→55	55→65	37→45	50	253/322/439	186	290	23	2	21%	8%	114	+2.4	240/302/387	147	290	17	3	22%	8%	95	+0.9	227/287/337	110	283	11	0	23%	7%	76	-0.2
✕Marcus Thames 2010 · MLB	33	44→46	62→70	35→40	46	243/301/462	219	278	32	3	26%	8%	112	+2.2	247/309/428	181	296	25	4	25%	8%	107	+1.8	273/337/451	177	330	27	0	25%	8%	123	+1.3
✕Greg Norton 2007 · MLB	35	49	56→60	33→40	51	258/327/448	189	291	25	3	21%	9%	118	+2.6	250/339/395	145	302	16	5	21%	12%	110	+2.1	236/342/350	113	292	11	2	21%	14%	102	+0.5
●Robinson Chirinos 2017 · MLB	33	43→46	56→60	40→50	49	229/308/427	198	263	24	3	23%	8%	107	+1.8	236/339/446	210	295	26	4	28%	10%	122	+3.0	229/342/435	206	294	26	2	29%	11%	120	+1.8
✕Justin Upton 2022 · MLB	34	40→50	58→65	43→55	50	220/305/419	198	266	27	6	29%	10%	103	+1.6	218/300/381	163	297	20	8	32%	9%	93	+0.8	141/240/239	99	225	12	0	40%	9%	40	-0.6
✕Josh Willingham 2014 · MLB	35	44→53	58→65	45	56	236/344/446	210	280	26	4	25%	12%	124	+3.1	228/337/410	182	287	22	6	27%	12%	114	+2.3	208/330/391	183	260	24	3	28%	13%	107	+1.2
✕John Lindsey 2013 · AAA	36	45→51	57→60	43→30	41	241/302/437	196	290	25	2	27%	6%	107	+1.8	224/299/413	189	280	25	3	29%	7%	101	+1.4	204/288/394	190	253	27	0	30%	7%	90	+0.4
✕Olmedo Saenz 2006 · MLB	35	49	58→60	41→30	50	261/324/469	208	286	26	3	20%	8%	122	+2.9	255/329/459	204	289	25	4	21%	8%	122	+2.9	248/333/466	218	280	27	0	21%	9%	126	+0.9
✕José Hernández 2004 · MLB	35	50→60	51→55	41→45	43	249/307/405	157	338	19	4	31%	8%	101	+1.4	249/307/402	153	318	19	5	27%	8%	99	+1.3	254/309/406	152	311	20	4	24%	7%	102	+0.5
✕Chris Iannetta 2018 · MLB	35	44→54	55→60	43→45	54	231/325/416	186	282	23	2	26%	11%	110	+2.1	226/320/395	169	287	20	3	27%	11%	103	+1.6	206/309/357	151	264	17	0	27%	11%	94	+0.4
✕Nick Hundley 2019 · MLB	35	48→45	52→55	46→40	42	245/290/418	172	303	20	4	26%	6%	97	+1.1	226/277/380	154	301	18	7	30%	6%	84	+0.1	161/196/283	123	228	14	0	36%	3%	31	-0.8
✕Todd Frazier 2020 · MLB	34	44→52	55→60	42→50	52	235/322/420	185	268	24	6	22%	10%	110	+2.1	235/309/391	156	280	18	6	22%	8%	99	+1.2	243/309/394	151	308	14	3	24%	6%	99	+0.4
✕Eduardo Escobar 2023 · MLB	34	47→57	55→60	43→50	47	246/301/439	193	282	23	2	22%	7%	106	+1.8	237/290/391	154	292	17	6	24%	7%	91	+0.6	224/269/341	117	286	11	4	25%	6%	71	-0.4
✕Pat Burrell 2011 · MLB	34	46→54	57→65	40→30	57	242/335/443	201	281	25	2	24%	12%	120	+2.8	246/342/433	187	315	22	5	27%	12%	120	+2.8	233/356/416	183	323	21	0	31%	15%	122	+1.1
✕Eric Karros 2002 · MLB	34	46→55	54→55	43→40	51	241/310/419	177	267	23	5	20%	9%	105	+1.7	260/315/407	147	284	17	5	15%	7%	103	+1.6	265/317/401	137	285	15	3	13%	7%	104	+0.9
✕Shelley Duncan 2013 · MLB	33	41→44	54→60	40→45	51	221/297/399	178	253	23	4	23%	9%	96	+1.0	192/258/324	132	234	15	4	25%	8%	64	-1.3	155/214/261	106	191	12	0	26%	6%	32	-2.7

Jorge Soler

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps