J.P. Crawford

SS Seattle Mariners

Age 32 L/R 6'0" / 202 lbs MLB K +7%HR -5% Svc 8.948 · Ctrl thru 2027

Overview

MLB40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	29	MLBSEA	451	.202/.304/.321	9	5	83	1.0
2025	30	MLBSEA	654	.265/.352/.370	12	8	108	2.4
2026	31	MLBSEA	489	.221/.337/.352	14	1	100	1.4
2027PROJ	32	MLBSEA	438	.238/.338/.356	10	4	102	1.0
2028PROJ	33	MLBSEA	496	.231/.330/.340	10	1	95	0.3
2029PROJ	34	MLBSEA	344	.222/.320/.321	7	0	87	-0.3

Last 3 seasons WAR 4.8 · Next 3 projected WAR 0.9Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service8.948First FA2028NTC

2027Ext / FA-deal$8M

Skills · percentileStatcast 2024-2026

xwOBA61

Bat Spd56

Barrel%31

Avg EV28

Speed23

Form.252/.346/.379 ▲ rolling true talent (60d window) · proj .240/.337/.361

CompsRamón Vázquez (age 32) · Ehire Adrianza (age 32) · Eric Sogard (age 32)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 89102vR 107

AVG/OBP/SLG.238 / .338 / .356

PA438

HR10

K%20

BB%12

BABIP280

ISO122

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Recent Form · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

420.245

POWER

Barrel%

315.7

Avg EV

2887.4

Bat Spd

5672.0

SPEED

Sprint

2326.2

Recent Formrolling true talent ⓘ

K%17%▲▲16% over 115 PA (60d) · proj 20%

BB%12%·11% over 115 PA (60d) · proj 12%

ISO.127·.135 over 96 AB (60d) · proj .121

HR/BB4.1%▲5.1% over 79 BBE (60d) · proj 3.5%

BABIP.282·.280 over 75 BIP (60d) · proj .283

SLASH.252/.346/.379▲proj .240/.337/.361

Platoon Splits2024-2026 · 1188 PA

vs LHP

vs RHP

Edge

379

809

—

wRC+

101

◀L

wOBA

318

305

◀L

ISO

125

102

◀◀L

BABIP

272

290

▶R

17.7%

21.3%

◀◀L

BB%

11.1%

12.1%

▶R

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

Status FA

MLB Debut 2017

Service 8.948 yrs.days

Team Control Through 2027

First FA Year 2028

NTC

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$8M	+1.1	$9M	+$0.6M
Totals		$8M		$9M	+$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)
2013	18	A	Lakewood BlueClaws	—	60	53	11	1	0	0	7	10	0	2	1	208	300	226	526	19	256	17	12	254	35	—	—	—	—	—	—
2013	18	ROK	GCL Phillies	—	168	142	49	8	3	1	25	25	0	12	5	345	443	465	908	120	414	15	15	405	97	—	—	—	—	—	—
2014	19	A+	Clearwater Threshers	—	271	236	65	7	0	8	28	37	2	10	7	275	357	407	764	131	292	14	10	339	98	—	—	—	—	—	—
2014	19	A	Lakewood BlueClaws	—	267	227	67	16	0	3	37	37	2	14	7	295	398	405	804	110	342	14	14	365	105	—	—	—	—	—	—
2015	20	AA	Reading Fightin Phils	—	405	351	93	21	7	5	49	45	1	7	2	265	357	407	764	142	289	11	12	340	91	—	—	—	—	—	—
2015	20	A+	Clearwater Threshers	—	95	79	31	1	0	1	14	9	1	5	2	392	489	443	932	51	435	9	15	422	141	—	—	—	—	—	—
2015	20	INTL	Glendale Desert Dogs	—	22	20	3	0	0	0	2	6	0	0	1	150	227	150	377		214	27	9	187	13	—	—	—	—	—	—
2016	21	AAA	Lehigh Valley IronPigs	—	385	336	82	11	1	4	42	59	1	7	4	244	330	318	648	74	284	15	11	296	60	—	—	—	—	—	—
2016	21	AA	Reading Fightin Phils	—	166	136	36	8	0	3	30	21	0	5	3	265	398	390	787	125	295	13	18	362	86	—	—	—	—	—	—
2017	22	MLB	Philadelphia Phillies	—	87	70	15	4	1	0	16	22	0	1	0	214	360	300	660	86	306	25	18	310	96	-0	+0	+4	+2	+2	0.8
2017	22	AAA	Lehigh Valley IronPigs	—	556	474	115	20	6	15	79	97	1	5	4	243	352	405	757	162	275	17	14	341	76	—	—	—	—	—	—
2018	23	MLB	Philadelphia Phillies	—	138	117	25	6	3	3	13	37	5	2	0	214	316	393	709	179	286	27	9	314	97	-0	+0	-2	+3	+3	0.3
2018	23	AAA	Lehigh Valley IronPigs	—	68	58	15	2	1	1	5	17	4	1	0	259	358	379	738	121	350	25	7	333	86	—	—	—	—	—	—
2018	23	A+	Clearwater Threshers	—	49	42	6	1	0	1	7	14	0	0	0	143	265	238	503	95	185	29	14	242	7	—	—	—	—	—	—
2019	24	MLB	Seattle Mariners	—	396	345	78	21	4	7	43	83	2	5	3	226	315	371	686	145	275	21	11	306	95	-2	-0	+2	+6	+9	1.4
2019	24	AAA	Tacoma Rainiers	—	138	116	37	7	0	3	19	25	2	3	0	319	423	457	880	138	382	18	14	394	103	—	—	—	—	—	—
2020	25	MLB	Seattle Mariners	—	232	204	52	7	2	2	23	39	3	6	3	255	339	338	677	83	303	17	10	309	97	-1	+0	+6	+2	+5	1.3
2021	26	MLB	Seattle Mariners	—	687	619	169	37	0	9	58	114	5	3	6	273	340	376	717	103	320	17	8	323	106	+5	-2	+5	+7	+15	3.0
2022	27	MLB	Seattle Mariners	—	603	518	126	24	3	6	68	80	10	3	2	243	342	336	678	93	275	13	11	310	98	-2	-0	-5	+6	+13	1.3
2023	28	MLB	Seattle Mariners	—	638	534	142	35	0	19	94	125	5	2	0	266	381	438	819	172	314	20	15	366	135	+27	+0	-3	+7	+14	4.5
2024	29	MLB	Seattle Mariners	—	451	392	79	16	2	9	52	102	6	5	0	202	304	321	626	120	248	23	12	289	83	-9	+1	+3	+5	+10	1.0
2025	30	MLB	Seattle Mariners	—	654	570	151	24	0	12	74	122	3	8	1	265	352	370	723	105	318	19	11	327	108	+6	+1	-5	+7	+14	2.4
2026	31	MLB	Seattle Mariners	—	489	412	91	12	0	14	64	97	8	1	3	221	337	352	689	131	253	20	13	315	100	-0	-1	-1	+5	+11	1.4
2026	31	AAA	Tacoma Rainiers	—	16	15	4	0	0	1	1	3	0	0	0	267	312	467	779	200	273	19	6	343	59	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4375	3781	928	186	15	81	505	821	47	36	18	245	341	367	708	121	292	19	12	321	103	+17	+0	+3	+51	+95	16.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2013	18	A MLE	Lakewood BlueClaws	—	60	55	11	1	0	0	5	13	0	2	1	200	267	218	485	18	260	22	8	220	35	—	—	—	—	—	—
2013	18	ROK MLE	GCL Phillies	—	168	151	41	6	2	1	16	36	0	12	5	272	341	358	699	86	353	21	10	311	97	—	—	—	—	—	—
2014	19	A+ MLE	Clearwater Threshers	—	271	241	63	7	0	7	23	51	2	10	7	261	331	378	708	116	294	19	8	313	98	—	—	—	—	—	—
2014	19	A MLE	Lakewood BlueClaws	—	267	237	67	15	0	3	27	49	2	14	7	283	361	384	745	101	339	18	10	324	105	—	—	—	—	—	—
2015	20	AA MLE	Reading Fightin Phils	—	405	366	92	20	6	4	34	52	1	7	2	251	317	372	688	120	276	13	8	302	91	—	—	—	—	—	—
2015	20	A+ MLE	Clearwater Threshers	—	95	81	29	1	0	1	12	14	1	5	2	358	447	407	854	49	417	15	13	376	141	—	—	—	—	—	—
2016	21	AAA MLE	Lehigh Valley IronPigs	—	385	349	79	10	1	4	29	70	1	7	4	226	288	295	583	69	264	18	8	257	60	—	—	—	—	—	—
2016	21	AA MLE	Reading Fightin Phils	—	166	145	34	7	0	2	21	27	0	5	3	234	331	324	655	90	274	16	13	295	86	—	—	—	—	—	—
2017	22	MLB MLE	Philadelphia Phillies	—	87	70	15	4	1	0	16	22	0	1	0	214	360	300	660	86	306	25	18	311	96	-0	+0	+4	+2	+2	0.8
2017	22	AAA MLE	Lehigh Valley IronPigs	—	556	497	105	18	6	13	56	121	1	5	4	211	292	350	643	139	249	22	10	281	76	—	—	—	—	—	—
2018	23	MLB MLE	Philadelphia Phillies	—	138	118	25	6	3	3	13	37	5	2	0	212	316	390	706	178	286	27	9	312	97	-0	+0	-2	+3	+3	0.3
2018	23	AAA MLE	Lehigh Valley IronPigs	—	68	59	14	2	1	1	4	21	4	1	0	237	328	356	684	119	341	31	6	295	86	—	—	—	—	—	—
2018	23	A+ MLE	Clearwater Threshers	—	49	44	5	1	0	1	5	20	0	0	0	114	204	205	409	91	176	41	10	178	7	—	—	—	—	—	—
2019	24	MLB MLE	Seattle Mariners	—	396	345	78	21	4	7	43	83	2	5	3	226	315	371	686	145	275	21	11	309	95	-2	-0	+2	+6	+9	1.4
2019	24	AAA MLE	Tacoma Rainiers	—	138	122	32	6	0	2	13	33	2	3	0	262	343	361	704	98	337	24	9	320	103	—	—	—	—	—	—
2020	25	MLB MLE	Seattle Mariners	—	232	204	52	7	2	2	23	39	3	6	3	255	339	338	677	83	303	17	10	311	97	-1	+0	+6	+2	+5	1.3
2021	26	MLB MLE	Seattle Mariners	—	687	620	171	38	0	9	57	114	5	3	6	276	342	381	722	105	320	17	8	324	106	+5	-2	+5	+7	+15	3.0
2022	27	MLB MLE	Seattle Mariners	—	603	518	126	24	3	6	68	80	10	3	2	243	342	336	678	93	275	13	11	313	98	-2	-0	-5	+6	+13	1.3
2023	28	MLB MLE	Seattle Mariners	—	638	535	143	36	0	19	93	125	5	2	0	267	381	441	822	174	314	20	15	368	135	+27	+0	-3	+7	+14	4.5
2024	29	MLB MLE	Seattle Mariners	—	451	392	79	16	2	9	52	102	6	5	0	202	304	321	626	120	248	23	12	291	83	-9	+1	+3	+5	+10	1.0
2025	30	MLB MLE	Seattle Mariners	—	654	571	152	24	0	12	73	122	3	8	1	266	352	371	724	105	318	19	11	328	108	+6	+1	-5	+7	+14	2.4
2026	31	MLB MLE	Seattle Mariners	—	489	413	91	12	0	14	63	97	8	1	3	220	335	351	686	131	253	20	13	316	100	-0	-1	-1	+5	+11	1.4
2026	31	AAA MLE	Tacoma Rainiers	—	16	15	4	0	0	1	1	4	0	0	0	267	312	467	779	200	237	25	6	255	59	—	—	—	—	—	—
2013	18	ROK MLE	2 teams	—	228	206	52	7	2	1	21	49	0	14	6	252	322	320	642	68	327	21	9	287	80	—	—	—	—	—	—
2013	18	ROK RAW	2 teams	—	228	195	60	9	3	1	32	35	0	14	6	308	405	400	805	92	371	15	14	366	80	—	—	—	—	—	—
2014	19	A+ MLE	2 teams	—	538	478	130	22	0	10	50	100	4	24	14	272	346	381	727	109	323	19	9	318	102	—	—	—	—	—	—
2014	19	A+ RAW	2 teams	—	538	463	132	23	0	11	65	74	4	24	14	285	378	406	784	121	317	14	12	352	102	—	—	—	—	—	—
2015	20	AA MLE	3 teams	—	522	468	126	22	6	5	47	68	2	12	5	269	338	374	712	105	304	13	9	316	100	—	—	—	—	—	—
2015	20	AA RAW	3 teams	—	522	450	127	22	7	6	65	60	2	12	5	282	375	402	777	120	313	11	12	349	100	—	—	—	—	—	—
2016	21	AAA MLE	2 teams	—	551	493	113	17	1	6	51	97	1	12	7	229	303	304	607	75	273	18	9	268	68	—	—	—	—	—	—
2016	21	AAA RAW	2 teams	—	551	472	118	19	1	7	72	80	1	12	7	250	350	339	689	89	287	15	13	316	68	—	—	—	—	—	—
2017	22	AAA MLE	2 teams	—	643	567	120	22	7	13	72	143	1	6	4	212	302	344	645	132	259	22	11	285	79	—	—	—	—	—	—
2017	22	AAA RAW	2 teams	—	643	544	130	24	7	15	95	119	1	6	4	239	353	392	745	153	279	19	15	336	79	—	—	—	—	—	—
2018	23	MLB MLE	3 teams	—	255	221	43	9	4	4	22	78	9	3	0	195	294	326	619	131	281	31	9	281	77	-7	+1	-2	+3	+6	-0.1
2018	23	MLB RAW	3 teams	—	255	217	46	9	4	5	25	68	9	3	0	212	317	359	677	147	285	27	10	305	77	-7	+1	-2	+3	+6	-0.1
2019	24	MLB MLE	2 teams	—	534	467	112	27	4	10	56	116	4	8	3	240	326	379	705	139	296	22	10	312	97	-2	+0	+2	+6	+12	1.8
2019	24	MLB RAW	2 teams	—	534	461	115	28	4	10	62	108	4	8	3	249	343	393	736	143	303	20	12	329	97	-2	+0	+2	+6	+12	1.8
2020	25	MLB MLE	Seattle Mariners	—	232	204	52	7	2	2	23	39	3	6	3	255	339	338	677	83	303	17	10	311	97	-1	+0	+6	+2	+5	1.3
2020	25	MLB RAW	Seattle Mariners	—	232	204	52	7	2	2	23	39	3	6	3	255	339	338	677	83	303	17	10	309	97	-1	+0	+6	+2	+5	1.3
2021	26	MLB MLE	Seattle Mariners	—	687	620	171	38	0	9	57	114	5	3	6	276	342	381	722	105	323	17	8	324	106	+5	-2	+5	+7	+15	3.0
2021	26	MLB RAW	Seattle Mariners	—	687	619	169	37	0	9	58	114	5	3	6	273	340	376	717	103	320	17	8	323	106	+5	-2	+5	+7	+15	3.0
2022	27	MLB MLE	Seattle Mariners	—	603	518	126	24	3	6	68	80	10	3	2	243	342	336	678	93	275	13	11	313	98	-2	-0	-5	+6	+13	1.3
2022	27	MLB RAW	Seattle Mariners	—	603	518	126	24	3	6	68	80	10	3	2	243	342	336	678	93	275	13	11	310	98	-2	-0	-5	+6	+13	1.3
2023	28	MLB MLE	Seattle Mariners	—	638	535	143	36	0	19	93	125	5	2	0	267	381	441	822	174	316	20	15	368	135	+27	+0	-3	+7	+14	4.5
2023	28	MLB RAW	Seattle Mariners	—	638	534	142	35	0	19	94	125	5	2	0	266	381	438	819	172	314	20	15	366	135	+27	+0	-3	+7	+14	4.5
2024	29	MLB MLE	Seattle Mariners	—	451	392	79	16	2	9	52	102	6	5	0	202	304	321	626	120	248	23	12	291	83	-9	+1	+3	+5	+10	1.0
2024	29	MLB RAW	Seattle Mariners	—	451	392	79	16	2	9	52	102	6	5	0	202	304	321	626	120	248	23	12	289	83	-9	+1	+3	+5	+10	1.0
2025	30	MLB MLE	Seattle Mariners	—	654	571	152	24	0	12	73	122	3	8	1	266	352	371	724	105	320	19	11	328	108	+6	+1	-5	+7	+14	2.4
2025	30	MLB RAW	Seattle Mariners	—	654	570	151	24	0	12	74	122	3	8	1	265	352	370	723	105	318	19	11	327	108	+6	+1	-5	+7	+14	2.4
2026	31	MLB MLE	2 teams	—	505	428	95	12	0	15	64	101	8	1	3	222	334	355	689	133	254	20	13	314	99	-1	-1	-1	+5	+11	1.3
2026	31	MLB RAW	2 teams	—	505	427	95	12	0	15	65	100	8	1	3	222	336	356	692	133	254	20	13	316	99	-1	-1	-1	+5	+11	1.3
2013	18	ROK MLE	2 teams	—	228	205	52	7	2	1	21	49	0	14	6	254	322	322	644	68	329	21	9	287	80	—	—	—	—	—	—
2014	19	A+ MLE	2 teams	—	538	479	130	22	0	10	50	100	4	24	14	271	346	380	726	109	316	19	9	318	102	—	—	—	—	—	—
2015	20	AA MLE	3 teams	—	522	468	126	22	6	5	47	68	2	12	5	269	338	374	712	105	303	13	9	316	100	—	—	—	—	—	—
2016	21	AAA MLE	2 teams	—	551	494	113	17	1	6	51	97	1	12	7	229	303	304	606	75	267	18	9	268	68	—	—	—	—	—	—
2017	22	AAA MLE	2 teams	—	643	565	120	22	7	13	72	143	1	6	4	212	302	345	647	133	257	22	11	285	79	—	—	—	—	—	—
2018	23	MLB MLE	3 teams	—	255	222	43	9	4	4	22	78	9	3	0	194	294	324	618	131	279	31	9	281	77	—	—	—	—	—	—
2019	24	MLB MLE	2 teams	—	534	469	112	27	4	10	56	116	4	8	3	239	326	377	704	139	291	22	10	312	97	—	—	—	—	—	—
2020	25	MLB MLE	Seattle Mariners	—	232	204	52	7	2	2	23	39	3	6	3	255	339	338	677	83	303	17	10	311	97	—	—	—	—	—	—
2021	26	MLB MLE	Seattle Mariners	—	687	620	171	38	0	9	57	114	5	3	6	276	342	381	722	105	320	17	8	324	106	—	—	—	—	—	—
2022	27	MLB MLE	Seattle Mariners	—	603	520	126	24	3	6	68	80	10	3	2	242	342	335	677	92	275	13	11	313	98	—	—	—	—	—	—
2023	28	MLB MLE	Seattle Mariners	—	638	535	143	36	0	19	93	125	5	2	0	267	381	441	822	174	314	20	15	368	135	—	—	—	—	—	—
2024	29	MLB MLE	Seattle Mariners	—	451	390	79	16	2	9	52	102	6	5	0	203	304	323	628	121	248	23	12	291	83	—	—	—	—	—	—
2025	30	MLB MLE	Seattle Mariners	—	654	573	152	24	0	12	73	122	3	8	1	265	352	370	722	105	318	19	11	328	108	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	505	428	95	12	0	15	64	101	8	1	3	222	334	355	689	133	253	20	13	314	99	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	29	MLB MLE	Seattle Mariners	—	451	390	79	16	2	9	52	102	6	5	0	203	304	323	628	121	248	23	12	291	83	—	—	—	—	—	—
2025	30	MLB MLE	Seattle Mariners	—	654	573	152	24	0	12	73	122	3	8	1	265	352	370	722	105	318	19	11	328	108	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	505	428	95	12	0	15	64	101	8	1	3	222	334	355	689	133	253	20	13	314	99	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	32	MLB MLE	SEA	100%	514	442	107	17	1	12	61	101	6	4	1	240	340	361	701	121	283	20	12	319	102	+1	+0	-7	+6	+11	1.1
▸ 2027 — real world (MLB)
2027	32	MLB CTX	SEA	100%	438	378	90	14	1	10	52	86	5	4	1	238	338	356	694	119	280	20	12	316	102	+1	+0	-6	+5	+9	1.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	33	MLB MLE	SEA	100%	496	430	100	15	0	11	58	101	5	1	1	233	332	345	676	112	277	20	12	309	95	-3	-0	-11	+5	+11	0.3
2029	34	MLB MLE	SEA	100%	344	298	66	9	0	7	40	72	3	0	0	224	322	325	647	102	270	21	12	297	87	-5	+0	-9	+4	+7	-0.3
2028	33	MLB CTX	SEA	100%	496	430	98	15	0	10	58	101	5	1	1	231	330	340	670	110	275	20	12	307	95	-3	-0	-11	+5	+11	0.3
2029	34	MLB CTX	SEA	100%	344	298	66	9	0	7	40	72	3	0	0	222	320	321	641	99	268	21	12	295	87	-5	+0	-9	+4	+7	-0.3
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	5215	4509	1092	210	15	98	603	994	55	37	19	242	339	361	699	118	289	19	12	318	97	+9	-0	-17	+60	+113	16.8
/ 162G	—	A+C		—	650	562	136	26	2	12	75	124	7	5	2	242	339	359	698	117	289	19	12	318	97	+1	-0	-2	+7	+14	2.1
Career	—	MLE		—	8319	7274	1771	321	32	149	899	1593	74	112	56	243	333	358	691	114	291	19	11	311	97	+10	+0	-23	+65	+122	17.8
/ 162G	—	MLE		—	650	568	139	25	3	12	70	124	6	9	4	245	334	363	697	118	292	19	11	311	97	+1	+0	-3	+7	+14	2.0

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.

2026 AAATacoma Rainiers · 16 PAwOBA .333 → .255 (−78)K% 18.8% → 22.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.75%	÷1.000	×1.200	—	—	22.50%
BB% (unintentional) /PA	6.25%	÷1.000	×0.690	—	×0.962	4.15%
HBP% /PA	0.00%	—	×0.940	—	×0.962	0.00%
Singles /BIP	25.00%	÷1.000	×0.930	—	×0.962	22.37%
Doubles /BIP	0.00%	÷1.000	×0.830	—	×0.962	0.00%
Triples /BIP	0.00%	÷1.000	×0.970	—	×0.962	0.00%
Home runs /BIP	8.33%	÷1.000	×0.700	—	×0.962	5.61%

Factors used: league row International League. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 31 vs a level average of 27.2 → −3.8% on BB/HBP/hit rates (3.8 yr older than average).

Result: wOBA .333 → .255; ISO .200 → .132; BABIP .273 → .237. 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 AAATacoma Rainiers · 138 PAwOBA .385 → .320 (−65)K% 18.1% → 23.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.12%	÷0.990	×1.290	—	—	23.60%
BB% (unintentional) /PA	13.04%	÷1.039	×0.710	—	×1.048	9.34%
HBP% /PA	1.45%	—	×0.980	—	×1.048	1.49%
Singles /BIP	29.67%	÷0.985	×0.900	×0.950	×1.048	26.99%
Doubles /BIP	7.69%	÷0.998	×0.810	×0.950	×1.048	6.21%
Triples /BIP	0.00%	÷1.073	×0.810	×0.950	×1.048	0.00%
Home runs /BIP	3.30%	÷1.049	×0.780	—	×1.048	2.57%

Factors used: league row PCL. Park (home-season share, regressed): HR 110, 1B 97, 2B 100, 3B 115, K 98, BB 108 — applied at half strength. Age: age 24 vs a level average of 27.2 → +4.8% on BB/HBP/hit rates (3.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .385 → .320; ISO .138 → .109; BABIP .382 → .337. 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 AAALehigh Valley IronPigs · 68 PAwOBA .325 → .295 (−29)K% 25.0% → 31.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷0.962	×1.200	—	—	31.18%
BB% (unintentional) /PA	7.35%	÷0.932	×0.690	—	×1.050	5.72%
HBP% /PA	5.88%	—	×0.940	—	×1.050	5.81%
Singles /BIP	26.83%	÷1.000	×0.930	—	×1.050	26.20%
Doubles /BIP	4.88%	÷0.971	×0.830	—	×1.050	4.38%
Triples /BIP	2.44%	÷0.900	×0.970	—	×1.050	2.76%
Home runs /BIP	2.44%	÷0.954	×0.840	—	×1.050	2.25%

Factors used: league row IL. Park (home-season share, regressed): HR 91, 1B 100, 2B 94, 3B 80, K 92, BB 86 — 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 .325 → .295; ISO .121 → .112; BABIP .350 → .341. 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 A+Clearwater Threshers · 49 PAwOBA .237 → .178 (−59)K% 28.6% → 40.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.57%	÷0.995	×1.420	—	—	40.77%
BB% (unintentional) /PA	14.29%	÷1.005	×0.750	—	×0.998	10.64%
HBP% /PA	0.00%	—	×0.930	—	×0.998	0.00%
Singles /BIP	14.29%	÷0.950	×0.920	—	×0.998	13.81%
Doubles /BIP	3.57%	÷1.028	×0.960	—	×0.998	3.33%
Triples /BIP	0.00%	÷1.000	×0.810	—	×0.998	0.00%
Home runs /BIP	3.57%	÷1.197	×0.880	—	×0.998	2.62%

Factors used: league row FSL. Park (home-season share, regressed): HR 139, 1B 90, 2B 106, 3B 100, K 99, BB 101 — applied at half strength. Age: age 23 vs a level average of 22.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average).

Result: wOBA .237 → .178; ISO .095 → .063; BABIP .185 → .176. 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 AAALehigh Valley IronPigs · 556 PAwOBA .332 → .281 (−52)K% 17.4% → 21.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.45%	÷0.961	×1.200	—	—	21.78%
BB% (unintentional) /PA	14.03%	÷1.014	×0.690	—	×1.050	10.02%
HBP% /PA	0.18%	—	×0.940	—	×1.050	0.18%
Singles /BIP	19.63%	÷1.055	×0.930	×0.986	×1.050	17.91%
Doubles /BIP	5.31%	÷0.969	×0.830	×0.986	×1.050	4.70%
Triples /BIP	1.59%	÷1.047	×0.970	×0.986	×1.050	1.53%
Home runs /BIP	3.98%	÷1.043	×0.840	—	×1.050	3.36%

Factors used: league row IL. Park (home-season share, regressed): HR 109, 1B 111, 2B 94, 3B 109, K 92, BB 103 — 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 ×0.986.

Result: wOBA .332 → .281; ISO .162 → .142; BABIP .275 → .249. 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 AAALehigh Valley IronPigs · 385 PAwOBA .290 → .257 (−33)K% 15.3% → 18.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.32%	÷1.018	×1.200	—	—	18.07%
BB% (unintentional) /PA	10.91%	÷1.035	×0.690	—	×1.050	7.64%
HBP% /PA	0.26%	—	×0.940	—	×1.050	0.26%
Singles /BIP	23.83%	÷1.028	×0.930	×0.994	×1.050	22.49%
Doubles /BIP	3.97%	÷1.018	×0.830	×0.994	×1.050	3.38%
Triples /BIP	0.36%	÷1.107	×0.970	×0.994	×1.050	0.33%
Home runs /BIP	1.44%	÷0.942	×0.840	—	×1.050	1.35%

Factors used: league row IL. Park (home-season share, regressed): HR 88, 1B 106, 2B 104, 3B 121, K 104, BB 107 — 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 ×0.994.

Result: wOBA .290 → .257; ISO .074 → .069; BABIP .284 → .264. 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 AAReading Fightin Phils · 166 PAwOBA .353 → .295 (−58)K% 12.7% → 16.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.65%	÷0.936	×1.220	—	—	16.49%
BB% (unintentional) /PA	18.07%	÷1.042	×0.700	—	×1.050	12.75%
HBP% /PA	0.00%	—	×0.850	—	×1.050	0.00%
Singles /BIP	21.74%	÷1.002	×0.970	×0.950	×1.050	21.00%
Doubles /BIP	6.96%	÷0.998	×0.860	×0.950	×1.050	5.98%
Triples /BIP	0.00%	÷1.150	×0.950	×0.950	×1.050	0.00%
Home runs /BIP	2.61%	÷1.273	×0.780	—	×1.050	1.68%

Factors used: league row EL. Park (home-season share, regressed): HR 155, 1B 100, 2B 100, 3B 130, K 87, BB 108 — 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 ×0.950.

Result: wOBA .353 → .295; ISO .125 → .095; BABIP .295 → .274. 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 AAReading Fightin Phils · 405 PAwOBA .333 → .302 (−31)K% 11.1% → 12.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.11%	÷1.060	×1.220	—	—	12.79%
BB% (unintentional) /PA	11.60%	÷1.029	×0.700	—	×1.050	8.29%
HBP% /PA	0.25%	—	×0.850	—	×1.050	0.22%
Singles /BIP	19.61%	÷0.995	×0.970	×0.962	×1.050	19.30%
Doubles /BIP	6.86%	÷0.949	×0.860	×0.962	×1.050	6.28%
Triples /BIP	2.29%	÷1.150	×0.950	×0.962	×1.050	1.91%
Home runs /BIP	1.63%	÷1.021	×0.780	—	×1.050	1.31%

Factors used: league row EL. Park (home-season share, regressed): HR 104, 1B 99, 2B 90, 3B 130, K 112, BB 106 — 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 ×0.962.

Result: wOBA .333 → .302; ISO .142 → .127; BABIP .289 → .276. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Stephen Drewlast yr '17 career totals — 12 seasons, 4,917 PA	7.4	4,917	123	41	252	318	423	+48	+35	26.3	25.1
/162	664	17	6	+6.5	+4.7	3.5	pk7: 24
#2Jed Lowrielast yr '22 career totals — 13 seasons, 5,188 PA	7.8	5,188	121	8	257	330	407	+31	+28	25.3	24.5
/162	664	15	1	+4.0	+3.5	3.2	pk7: 24
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 13 projected seasons	8.5	5,653	109	41	243	336	363	+58	+23	22.1	20.0
/162	664	13	5	+6.8	+2.7	2.6	pk7: 18
#3Scott Fletcher'81-'95 * career totals — 13 seasons, 5,976 PA	9.0	5,976	34	99	258*	330*	357*	+42	+40	17.2	18.2
/162	664	4	11	+4.6	+4.5	1.9	pk7: 19
#4Kolten Wonglast yr '23 career totals — 11 seasons, 4,283 PA	6.5	4,283	86	120	256	330	390	+15	+21	18.4	17.8
/162	664	13	19	+2.4	+3.2	2.8	pk7: 17
#5Wayne Garrett'69-'78 * career totals — 10 seasons, 3,913 PA	5.9	3,913	61	38	236*	346*	370*	+15	+13	15.2	16.0
/162	664	10	6	+2.5	+2.2	2.6	pk7: 17
#6Spike Owen'83-'95 * career totals — 13 seasons, 5,615 PA	8.5	5,615	46	82	242*	322*	356*	+55	+30	15.6	15.3
/162	664	5	10	+6.5	+3.6	1.8	pk7: 15

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
J.P. Crawford (OGILVIE)	32	—	—	—	—	238/337/358	120	283	10	4	20%	12%	102	+1.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Ramón Vázquez 2009 · MLB	32	50→58	45	46→50	53	245/317/375	130	295	11	4	21%	10%	97	+1.1	232/301/322	90	288	6	4	20%	9%	78	-0.3	218/286/271	53	274	2	2	20%	8%	59	-0.6
✕Ehire Adrianza 2022 · MLB	32	49→52	46→50	47→50	53	240/320/379	139	285	13	4	20%	10%	99	+1.3	227/302/344	117	279	11	8	21%	9%	84	+0.2	208/291/271	63	269	5	7	23%	9%	63	-0.4
●Eric Sogard 2018 · MLB	32	54→57	41→45	48→55	59	259/344/366	107	290	8	11	14%	11%	105	+1.7	240/315/358	118	276	11	10	16%	9%	92	+0.7	259/317/384	125	290	12	8	15%	7%	100	+0.6
✕Eddie Taubensee 2001 · MLB	32	52	46→45	47→30	50	256/314/382	126	285	14	4	16%	7%	97	+1.1	249/311/384	135	280	15	6	17%	8%	97	+1.1	246/305/356	110	271	14	0	15%	7%	88	+0.1
✕John Baker 2012 · MLB	31	50→59	43→45	49→45	53	241/323/364	123	302	10	4	22%	10%	97	+1.1	212/283/284	72	281	5	5	24%	9%	63	-1.3	193/263/235	42	263	3	2	26%	8%	45	-1.0
✕Daniel Descalso 2019 · MLB	32	46→56	51→50	48→45	58	232/334/401	168	284	17	4	24%	13%	109	+2.0	201/297/334	133	273	14	6	29%	12%	81	-0.1	159/261/244	85	219	9	5	30%	12%	48	-0.9
✕Mitch Maier 2013 · MLB	31	48→56	44→50	52→50	52	233/310/352	118	296	11	9	24%	10%	89	+0.5	228/298/350	122	308	13	9	28%	9%	84	+0.1	259/340/362	102	329	10	11	22%	11%	97	+0.3
✕David Freitas 2022 · MLB	33	49→59	46→45	47→40	51	243/313/370	127	289	14	7	21%	9%	95	+0.9	217/275/333	116	267	12	7	23%	7%	72	-0.7	204/257/306	102	247	11	0	22%	6%	58	-0.4
✕Brock Holt 2020 · MLB	32	54→64	43→45	45→50	53	259/340/373	114	320	10	8	21%	10%	105	+1.7	235/309/340	105	292	8	9	21%	9%	86	+0.3	208/282/290	81	262	3	10	20%	9%	64	-0.4
✕Austin Wynns 2023 · MLB	32	51	45	48→40	50	251/319/369	117	301	13	5	21%	8%	97	+1.1	234/291/359	125	301	13	5	26%	7%	84	+0.1	220/267/354	134	290	15	1	29%	5%	74	-0.1
✕Tucker Barnhart 2023 · MLB	32	49→53	41→45	45→40	47	233/301/329	96	303	8	2	25%	8%	80	-0.1	208/284/288	80	284	6	5	27%	9%	65	-1.2	176/261/232	56	247	3	3	27%	9%	44	-0.7
✕Ryan Flaherty 2018 · MLB	32	47	44→55	49→45	51	230/309/347	117	289	12	5	24%	9%	88	+0.5	220/283/343	123	286	14	7	27%	8%	77	-0.3	206/265/331	125	269	15	5	28%	7%	68	-0.6
✕Kevin Plawecki 2023 · MLB	32	51→59	41→45	47→30	50	246/311/346	100	286	9	4	17%	7%	88	+0.4	226/285/335	109	270	11	3	20%	7%	76	-0.4	215/272/316	101	256	10	0	20%	7%	63	-0.6
✕Brian Schneider 2010 · MLB	33	48→53	44→50	46→30	56	233/304/348	115	250	12	2	13%	9%	86	+0.3	222/293/340	118	258	12	4	18%	8%	80	-0.1	203/275/305	101	244	10	0	20%	8%	66	-0.3
✕Jack Hannahan 2012 · MLB	32	45→55	45	47→45	51	225/300/353	128	281	13	5	24%	9%	86	+0.3	232/304/338	106	293	9	4	22%	9%	84	+0.1	231/309/318	87	291	6	0	21%	9%	81	-0.0
✕Keith Osik 2002 · MLB	33	50	46→40	52→50	56	244/331/375	131	267	14	9	15%	9%	103	+1.5	225/302/328	103	266	10	5	18%	9%	81	-0.1	220/303/299	78	265	6	0	18%	10%	75	-0.2
✕Omar Narváez 2024 · MLB	32	47→54	43→50	46→30	53	229/305/342	113	270	11	3	19%	9%	85	+0.2	203/283/298	95	244	9	3	20%	9%	68	-1.0	182/268/253	72	219	7	0	20%	9%	50	-1.0
✕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
✕Phil Gosselin 2021 · MLB	32	48→58	45	45	48	238/301/368	130	295	12	5	23%	8%	89	+0.5	242/295/356	114	307	11	8	24%	6%	84	+0.1	242/292/343	101	307	9	7	23%	6%	80	-0.1
✕A.J. Ellis 2013 · MLB	32	52→54	44→45	41→40	57	254/348/376	122	301	12	2	19%	11%	109	+2.0	232/325/351	119	271	12	2	18%	11%	95	+1.0	219/320/329	110	252	11	0	17%	12%	91	+0.4

J.P. Crawford

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps