Chris Taylor

LF Salt Lake Bees

Age 36 R/R 6'0" / 196 lbs AAA K +5%HR +4% Svc 13.000 · Ctrl thru 2027

Overview

AAAExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	33	MLBLAD	246	.202/.300/.300	4	5	78	-0.7
2025	34	MLBLAA	125	.186/.258/.301	2	2	60	-0.6
2026	35	AAALAA	132	.255/.388/.321	0	3	63	—	.212/.310/.265
2027PROJ10% MLB	36	MLBLAA	9	.229/.312/.339	0	0	88	-0.0
2028PROJ	37	MLBLAA	80	.218/.299/.313	1	1	77	-0.8

Last 3 seasons WAR -1.3 · Next 2 projected WAR -0.8Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service13.000First FA2028

2027Ext / FA-deal$1M

Skills · percentileStatcast 2023-2025

Speed58

Barrel%52

xwOBA42

Bat Spd36

Avg EV10

CompsCurt Casali (age 35) · Drew Butera (age 36) · Daniel Hinojosa (age 35)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 8888vR 85

AVG/OBP/SLG.229 / .312 / .339

PA9

HR0

K%33

BB%11

BABIP315

ISO84

MLB%10%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · Contract

ToolsStatcast %ile · 2023-2025

CONTACT

xAVG

100.216

POWER

Barrel%

528.4

Avg EV

1086.1

Bat Spd

3669.8

SPEED

Sprint

5827.8

Platoon Splits2024-2025 · 371 PA

vs LHP

vs RHP

Edge

134

237

—

wRC+

▶▶R

wOBA

225

290

▶▶R

ISO

061

129

▶▶R

BABIP

242

308

▶▶R

31.3%

32.1%

—

BB%

11.2%

7.6%

◀◀L

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

Status FA

MLB Debut 2014

Service 13.000 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$1M	+0.0	$0.0M	-$1.0M
Totals		$1M		$0.0M	-$1.0M

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	21	A	Clinton LumberKings	—	53	46	14	0	0	0	2	4	3	4	1	304	373	304	677		333	8	4	307	76	—	—	—	—	—	—
2013	22	AA	Jackson Generals	—	300	256	75	12	4	1	40	55	2	18	3	293	393	383	775	90	368	18	13	353	85	—	—	—	—	—	—
2013	22	A+	High Desert Mavericks	—	319	269	90	16	7	7	44	62	2	20	2	335	432	524	956	190	407	19	14	417	107	—	—	—	—	—	—
2013	22	INTL	Peoria Javelinas	—	76	68	20	4	1	1	6	15	0	5	2	294	351	426	778	132	365	20	8	338	115	—	—	—	—	—	—
2014	23	MLB	Seattle Mariners	—	151	136	39	8	0	0	11	39	2	5	2	287	349	346	695	59	398	26	7	314	100	+0	+0	+2	+5	+3	1.1
2014	23	AAA	Tacoma Rainiers	—	346	302	99	22	7	5	35	74	3	14	6	328	403	497	900	169	412	21	10	391	116	—	—	—	—	—	—
2015	24	MLB	Seattle Mariners	—	102	94	16	3	1	0	6	31	0	3	2	170	220	223	443	53	254	30	6	201	23	-9	-0	+2	+5	+2	-0.0
2015	24	AAA	Tacoma Rainiers	—	396	343	103	20	6	4	50	61	2	16	8	300	392	429	821	128	355	15	13	369	98	—	—	—	—	—	—
2016	25	MLB	Los Angeles Dodgers	—	65	61	13	2	2	1	4	15	0	0	0	213	262	361	622	148	267	23	6	276	74	-2	+0	+1	+4	+1	0.5
2016	25	AAA	Oklahoma City Dodgers	—	344	304	98	25	6	3	35	65	3	17	5	322	398	474	871	151	401	19	10	385	95	—	—	—	—	—	—
2017	26	MLB	Los Angeles Dodgers	—	568	514	148	34	5	21	50	142	3	17	4	288	354	496	851	208	361	25	9	374	144	+30	+2	+1	-7	+12	3.9
2017	26	AAA	Oklahoma City Dodgers	—	49	43	10	2	2	1	5	5	1	1	2	233	327	442	768	209	243	10	10	339	65	—	—	—	—	—	—
2018	27	MLB	Los Angeles Dodgers	—	604	536	136	35	8	17	55	178	9	9	6	254	333	444	777	190	345	29	9	343	125	+18	-1	+4	+6	+13	4.2
2019	28	MLB	Los Angeles Dodgers	—	414	366	96	29	4	12	37	115	4	8	0	262	337	462	798	199	344	28	9	347	124	+12	+2	+0	-5	+9	1.9
2019	28	A+	Rancho Cucamonga Quakes	—	15	14	6	0	0	1	1	2	0	0	0	429	467	643	1.110	214	455	13	7	487	143	—	—	—	—	—	—
2020	29	MLB	Los Angeles Dodgers	—	214	185	50	10	2	8	26	55	2	3	2	270	366	476	842	205	344	26	12	371	143	+11	-0	+3	+2	+5	2.1
2021	30	MLB	Los Angeles Dodgers	—	582	507	129	25	4	20	63	167	8	13	1	254	346	438	784	183	337	29	11	348	124	+17	+2	-5	+2	+13	3.0
2022	31	MLB	Los Angeles Dodgers	—	454	402	89	25	3	10	44	160	5	10	1	221	306	373	679	152	336	35	10	305	96	-2	+2	+1	-5	+10	0.6
2023	32	MLB	Los Angeles Dodgers	—	384	338	80	15	1	15	41	125	4	16	3	237	326	420	746	183	327	33	11	333	112	+6	+2	-2	-4	+8	1.0
2024	33	MLB	Los Angeles Dodgers	—	246	213	43	7	1	4	28	76	2	5	1	202	300	300	601	99	289	31	11	276	78	-7	+1	-4	-3	+5	-0.7
2025	34	MLB	Los Angeles Angels	—	125	113	21	7	0	2	5	42	6	2	2	186	258	301	559	115	271	34	4	255	60	-6	-0	-1	-2	+3	-0.6
2025	34	AAA	Salt Lake Bees	—	20	19	4	0	0	0	1	6	0	0	0	211	250	211	461		308	30	5	216	-6	—	—	—	—	—	—
2026	35	AAA	Salt Lake Bees	—	132	106	27	7	0	0	20	35	3	3	1	255	388	321	708	66	370	27	15	328	63	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	3909	3465	860	200	31	110	370	1145	45	91	24	248	329	419	748	171	336	29	9	332	111	+49	+9	+3	+2	+85	15.0
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	21	A MLE	Clinton LumberKings	—	53	47	14	0	0	0	1	6	3	4	1	298	353	298	651		317	11	2	280	76	—	—	—	—	—	—
2013	22	AA MLE	Jackson Generals	—	300	269	69	11	3	1	27	68	2	18	3	257	329	331	660	74	334	23	9	294	85	—	—	—	—	—	—
2013	22	A+ MLE	High Desert Mavericks	—	319	283	76	13	5	5	30	86	2	20	2	269	343	403	746	134	356	27	9	326	107	—	—	—	—	—	—
2014	23	MLB MLE	Seattle Mariners	—	151	136	39	8	0	0	11	39	2	5	2	287	349	346	695	59	398	26	7	316	100	+0	+0	+2	+5	+3	1.1
2014	23	AAA MLE	Tacoma Rainiers	—	346	313	91	20	6	4	24	94	3	14	6	291	347	431	778	141	385	27	7	339	116	—	—	—	—	—	—
2015	24	MLB MLE	Seattle Mariners	—	102	94	16	3	1	0	6	31	0	3	2	170	220	223	443	53	254	30	6	203	23	-9	-0	+2	+5	+2	-0.0
2015	24	AAA MLE	Tacoma Rainiers	—	396	358	96	18	6	3	35	75	2	16	8	268	337	377	714	109	329	19	9	313	98	—	—	—	—	—	—
2016	25	MLB MLE	Los Angeles Dodgers	—	65	62	13	2	2	1	3	15	0	0	0	210	246	355	601	145	267	23	5	278	74	-2	+0	+1	+4	+1	0.5
2016	25	AAA MLE	Oklahoma City Dodgers	—	344	315	83	21	4	2	24	86	3	17	5	263	322	375	696	111	354	25	7	308	95	—	—	—	—	—	—
2017	26	MLB MLE	Los Angeles Dodgers	—	568	514	151	36	6	20	50	142	3	17	4	294	360	504	864	210	361	25	9	382	144	+30	+2	+1	-7	+12	3.9
2017	26	AAA MLE	Oklahoma City Dodgers	—	49	45	9	2	1	1	3	6	1	1	2	200	265	356	621	156	204	12	6	264	65	—	—	—	—	—	—
2018	27	MLB MLE	Los Angeles Dodgers	—	604	536	140	37	10	16	55	178	9	9	6	261	340	457	797	196	345	29	9	353	125	+18	-1	+4	+6	+13	4.2
2019	28	MLB MLE	Los Angeles Dodgers	—	414	369	100	31	5	12	34	115	4	8	0	271	339	480	819	209	344	28	8	351	124	+12	+2	+0	-5	+9	1.9
2019	28	A+ MLE	Rancho Cucamonga Quakes	—	15	14	5	0	0	1	1	3	0	0	0	357	400	571	971	214	369	20	7	380	143	—	—	—	—	—	—
2020	29	MLB MLE	Los Angeles Dodgers	—	214	185	51	11	2	8	26	55	2	3	2	276	371	486	857	211	344	26	12	380	143	+11	-0	+3	+2	+5	2.1
2021	30	MLB MLE	Los Angeles Dodgers	—	582	509	131	26	5	19	61	167	8	13	1	257	346	440	786	183	337	29	10	352	124	+17	+2	-5	+2	+13	3.0
2022	31	MLB MLE	Los Angeles Dodgers	—	454	404	92	26	4	10	42	160	5	10	1	228	308	386	694	158	336	35	9	310	96	-2	+2	+1	-5	+10	0.6
2023	32	MLB MLE	Los Angeles Dodgers	—	384	340	80	16	1	14	39	125	4	16	3	235	321	412	733	176	327	33	10	334	112	+6	+2	-2	-4	+8	1.0
2024	33	MLB MLE	Los Angeles Dodgers	—	246	213	43	7	1	4	28	76	2	5	1	202	300	300	601	99	289	31	11	283	78	-7	+1	-4	-3	+5	-0.7
2025	34	MLB MLE	Los Angeles Angels	—	125	113	21	7	0	2	5	42	6	2	2	186	258	301	559	115	271	34	4	258	60	-6	-0	-1	-2	+3	-0.6
2025	34	AAA MLE	Salt Lake Bees	—	20	19	3	0	0	0	1	7	0	0	0	158	200	158	358		257	35	5	159	-6	—	—	—	—	—	—
2026	35	AAA MLE	Salt Lake Bees	—	132	113	24	6	0	0	13	42	3	3	1	212	310	265	576	53	313	32	10	261	63	—	—	—	—	—	—
2012	21	A MLE	Clinton LumberKings	—	53	47	14	0	0	0	1	6	3	4	1	298	353	298	651		341	11	2	280	76	—	—	—	—	—	—
2012	21	A RAW	Clinton LumberKings	—	53	46	14	0	0	0	2	4	3	4	1	304	373	304	677		333	8	4	307	76	—	—	—	—	—	—
2013	22	A+ MLE	3 teams	—	695	619	162	27	9	6	64	173	4	43	7	262	335	363	698	102	351	25	9	310	96	—	—	—	—	—	—
2013	22	A+ RAW	3 teams	—	695	593	185	32	12	9	90	132	4	43	7	312	406	452	858	140	385	19	13	380	96	—	—	—	—	—	—
2014	23	AAA MLE	2 teams	—	497	449	130	28	6	4	35	133	5	19	8	290	348	405	753	116	396	27	7	332	111	—	—	—	—	—	—
2014	23	AAA RAW	2 teams	—	497	438	138	30	7	5	46	113	5	19	8	315	387	450	836	135	408	23	9	368	111	—	—	—	—	—	—
2015	24	AAA MLE	2 teams	—	498	452	113	22	7	3	41	106	2	19	10	250	315	350	665	100	320	21	8	290	83	—	—	—	—	—	—
2015	24	AAA RAW	2 teams	—	498	437	119	23	7	4	56	92	2	19	10	272	358	384	742	112	336	18	11	335	83	—	—	—	—	—	—
2016	25	AAA MLE	2 teams	—	409	377	97	23	7	3	27	101	3	17	5	257	312	379	691	122	343	25	7	303	91	—	—	—	—	—	—
2016	25	AAA RAW	2 teams	—	409	365	111	27	8	4	39	80	3	17	5	304	376	455	831	151	379	20	10	368	91	—	—	—	—	—	—
2017	26	MLB MLE	2 teams	—	617	559	160	38	7	21	53	148	4	18	6	286	352	492	844	206	355	24	9	372	138	+28	+1	+1	-7	+13	3.8
2017	26	MLB RAW	2 teams	—	617	557	158	36	7	22	55	147	4	18	6	284	352	492	844	208	350	24	9	371	138	+28	+1	+1	-7	+13	3.8
2018	27	MLB MLE	Los Angeles Dodgers	—	604	536	140	37	10	16	55	178	9	9	6	261	340	457	797	196	358	29	9	353	125	+18	-1	+4	+6	+13	4.2
2018	27	MLB RAW	Los Angeles Dodgers	—	604	536	136	35	8	17	55	178	9	9	6	254	333	444	777	190	345	29	9	343	125	+18	-1	+4	+6	+13	4.2
2019	28	MLB MLE	2 teams	—	429	383	103	31	5	12	35	118	4	8	0	269	336	470	806	201	353	28	8	352	124	+12	+2	+0	-5	+9	2.0
2019	28	MLB RAW	2 teams	—	429	380	102	29	4	13	38	117	4	8	0	268	341	468	810	200	349	27	9	352	124	+12	+2	+0	-5	+9	2.0
2020	29	MLB MLE	Los Angeles Dodgers	—	214	185	51	11	2	8	26	55	2	3	2	276	371	486	857	211	352	26	12	380	143	+11	-0	+3	+2	+5	2.1
2020	29	MLB RAW	Los Angeles Dodgers	—	214	185	50	10	2	8	26	55	2	3	2	270	366	476	842	205	344	26	12	371	143	+11	-0	+3	+2	+5	2.1
2021	30	MLB MLE	Los Angeles Dodgers	—	582	509	131	26	5	19	61	167	8	13	1	257	346	440	786	183	344	29	10	352	124	+17	+2	-5	+2	+13	3.0
2021	30	MLB RAW	Los Angeles Dodgers	—	582	507	129	25	4	20	63	167	8	13	1	254	346	438	784	183	337	29	11	348	124	+17	+2	-5	+2	+13	3.0
2022	31	MLB MLE	Los Angeles Dodgers	—	454	404	92	26	4	10	42	160	5	10	1	228	308	386	694	158	346	35	9	310	96	-2	+2	+1	-5	+10	0.6
2022	31	MLB RAW	Los Angeles Dodgers	—	454	402	89	25	3	10	44	160	5	10	1	221	306	373	679	152	336	35	10	305	96	-2	+2	+1	-5	+10	0.6
2023	32	MLB MLE	Los Angeles Dodgers	—	384	340	80	16	1	14	39	125	4	16	3	235	321	412	733	176	327	33	10	334	112	+6	+2	-2	-4	+8	1.0
2023	32	MLB RAW	Los Angeles Dodgers	—	384	338	80	15	1	15	41	125	4	16	3	237	326	420	746	183	327	33	11	333	112	+6	+2	-2	-4	+8	1.0
2024	33	MLB MLE	Los Angeles Dodgers	—	246	213	43	7	1	4	28	76	2	5	1	202	300	300	601	99	289	31	11	283	78	-7	+1	-4	-3	+5	-0.7
2024	33	MLB RAW	Los Angeles Dodgers	—	246	213	43	7	1	4	28	76	2	5	1	202	300	300	601	99	289	31	11	276	78	-7	+1	-4	-3	+5	-0.7
2025	34	MLB MLE	2 teams	—	145	132	24	7	0	2	6	49	6	2	2	182	250	280	530	98	268	34	4	244	51	-8	-0	-1	-2	+3	-0.8
2025	34	MLB RAW	2 teams	—	145	132	25	7	0	2	6	48	6	2	2	189	257	288	545	98	277	33	4	250	51	-8	-0	-1	-2	+3	-0.8
2026	35	AAA MLE	Salt Lake Bees	—	132	113	24	6	0	0	13	42	3	3	1	212	310	265	576	53	329	32	10	261	63	—	—	—	—	—	—
2026	35	AAA RAW	Salt Lake Bees	—	132	106	27	7	0	0	20	35	3	3	1	255	388	321	708	66	370	27	15	328	63	—	—	—	—	—	—
2012	21	A MLE	Clinton LumberKings	—	53	49	14	0	0	0	1	6	3	4	1	286	353	286	639		317	11	2	280	76	—	—	—	—	—	—
2013	22	A+ MLE	3 teams	—	695	622	162	27	9	6	64	173	4	43	7	260	335	362	697	101	345	25	9	310	96	—	—	—	—	—	—
2014	23	AAA MLE	2 teams	—	497	454	130	28	6	4	35	133	5	19	8	286	348	401	749	115	389	27	7	332	111	—	—	—	—	—	—
2015	24	AAA MLE	2 teams	—	498	452	113	22	7	3	41	106	2	19	10	250	315	350	665	100	314	21	8	290	83	—	—	—	—	—	—
2016	25	AAA MLE	2 teams	—	409	376	97	23	7	3	27	101	3	17	5	258	312	380	692	122	340	25	7	303	91	—	—	—	—	—	—
2017	26	MLB MLE	2 teams	—	617	555	160	38	7	21	53	148	4	18	6	288	352	495	848	207	348	24	9	372	138	—	—	—	—	—	—
2018	27	MLB MLE	Los Angeles Dodgers	—	604	535	140	37	10	16	55	178	9	9	6	262	340	458	798	196	345	29	9	353	125	—	—	—	—	—	—
2019	28	MLB MLE	2 teams	—	429	387	103	31	5	12	35	118	4	8	0	266	336	465	802	199	345	28	8	352	124	—	—	—	—	—	—
2020	29	MLB MLE	Los Angeles Dodgers	—	214	184	51	11	2	8	26	55	2	3	2	277	371	489	860	212	344	26	12	380	143	—	—	—	—	—	—
2021	30	MLB MLE	Los Angeles Dodgers	—	582	508	131	26	5	19	61	167	8	13	1	258	346	441	787	183	337	29	10	352	124	—	—	—	—	—	—
2022	31	MLB MLE	Los Angeles Dodgers	—	454	404	92	26	4	10	42	160	5	10	1	228	308	386	694	158	336	35	9	310	96	—	—	—	—	—	—
2023	32	MLB MLE	Los Angeles Dodgers	—	384	338	80	16	1	14	39	125	4	16	3	237	321	414	735	178	327	33	10	334	112	—	—	—	—	—	—
2024	33	MLB MLE	Los Angeles Dodgers	—	246	214	43	7	1	4	28	76	2	5	1	201	300	299	599	98	289	31	11	283	78	—	—	—	—	—	—
2025	34	MLB MLE	2 teams	—	145	132	24	7	0	2	6	49	6	2	2	182	250	280	530	98	269	34	4	244	51	—	—	—	—	—	—
2026	35	AAA MLE	Salt Lake Bees	—	132	115	24	6	0	0	13	42	3	3	1	209	310	261	571	52	313	32	10	261	63	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	33	MLB MLE	Los Angeles Dodgers	—	246	214	43	7	1	4	28	76	2	5	1	201	300	299	599	98	289	31	11	283	78	—	—	—	—	—	—
2025	34	MLB MLE	2 teams	—	145	132	24	7	0	2	6	49	6	2	2	182	250	280	530	98	269	34	4	244	51	—	—	—	—	—	—
2026	35	AAA MLE	Salt Lake Bees	—	132	115	24	6	0	0	13	42	3	3	1	209	310	261	571	52	313	32	10	261	63	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	36	MLB MLE	LAA	10%	150	133	30	6	1	2	13	43	3	3	1	231	314	341	655	110	318	29	9	298	88	-2	+0	+0	-2	+3	0.1
▸ 2027 — real world (MLB)
2027	36	MLB CTX	LAA	10%	9	8	1	0	0	0	1	3	0	0	0	229	312	339	651	109	315	33	11	296	88	-0	+0	+0	-0	+0	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	37	MLB MLE	LAA	100%	80	71	15	3	0	1	7	23	2	1	0	219	301	316	617	97	307	29	9	282	77	-2	+0	-7	-1	+2	-0.8
2028	37	MLB CTX	LAA	100%	80	71	15	3	0	1	7	23	2	1	0	218	299	313	613	96	305	29	9	281	77	-2	+0	-7	-1	+2	-0.8
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3989	3536	875	203	31	111	377	1168	47	92	24	247	328	417	745	169	335	29	9	331	107	+47	+9	-4	+1	+86	14.2
/ 162G	—	A+C		—	650	576	142	33	5	18	61	190	8	15	4	247	327	415	742	168	334	29	9	331	107	+8	+1	-1	+0	+14	2.3
Career	—	MLE		—	6132	5472	1397	312	64	124	541	1687	68	192	54	255	330	404	734	148	344	28	9	327	107	+46	+9	-4	-0	+88	14.2
/ 162G	—	MLE		—	650	580	148	33	7	13	57	179	7	20	6	255	329	403	733	148	344	28	9	327	107	+7	+1	-1	-0	+14	2.3

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 AAASalt Lake Bees · 132 PAwOBA .325 → .261 (−64)K% 26.5% → 31.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.52%	÷1.000	×1.200	—	—	31.82%
BB% (unintentional) /PA	15.15%	÷1.000	×0.690	—	×0.940	9.83%
HBP% /PA	2.27%	—	×0.940	—	×0.940	2.01%
Singles /BIP	28.17%	÷1.000	×0.930	×0.994	×0.940	24.49%
Doubles /BIP	9.86%	÷1.000	×0.830	×0.994	×0.940	7.65%
Triples /BIP	0.00%	÷1.000	×0.970	×0.994	×0.940	0.00%
Home runs /BIP	0.00%	÷1.000	×0.700	—	×0.940	0.00%

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 36 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (8.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.994.

Result: wOBA .325 → .261; ISO .066 → .054; BABIP .370 → .313. 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).

2025 AAASalt Lake Bees · 20 PAwOBA .210 → .159 (−52)K% 30.0% → 36.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.00%	÷0.978	×1.200	—	—	36.81%
BB% (unintentional) /PA	5.00%	÷0.964	×0.690	—	×0.940	3.36%
HBP% /PA	0.00%	—	×0.940	—	×0.940	0.00%
Singles /BIP	30.77%	÷1.046	×0.930	—	×0.940	25.73%
Doubles /BIP	0.00%	÷1.005	×0.830	—	×0.940	0.00%
Triples /BIP	0.00%	÷1.079	×0.970	—	×0.940	0.00%
Home runs /BIP	0.00%	÷0.989	×0.700	—	×0.940	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 98, 1B 109, 2B 101, 3B 116, K 96, BB 93 — applied at half strength. Age: age 35 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (7.8 yr older than average).

Result: wOBA .210 → .159; ISO .000 → .000; BABIP .308 → .257. 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+Rancho Cucamonga Quakes · 15 PAwOBA .473 → .380 (−93)K% 13.3% → 18.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.33%	÷0.991	×1.340	—	—	18.03%
BB% (unintentional) /PA	6.67%	÷0.948	×0.710	—	×0.940	4.70%
HBP% /PA	0.00%	—	×0.790	—	×0.940	0.00%
Singles /BIP	41.67%	÷1.043	×0.910	—	×0.940	34.16%
Doubles /BIP	0.00%	÷0.935	×0.820	—	×0.940	0.00%
Triples /BIP	0.00%	÷1.049	×0.760	—	×0.940	0.00%
Home runs /BIP	8.33%	÷0.969	×0.920	—	×0.940	7.44%

Factors used: league row CAL. Park (home-season share, regressed): HR 94, 1B 109, 2B 87, 3B 110, K 98, BB 90 — applied at half strength. Age: age 29 vs a level average of 22.8 → −6.0% on BB/HBP/hit rates (6.2 yr older than average).

Result: wOBA .473 → .380; ISO .214 → .185; BABIP .455 → .369. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2017 AAAOklahoma City Dodgers · 49 PAwOBA .331 → .264 (−66)K% 10.2% → 13.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.20%	÷1.000	×1.290	—	—	13.17%
BB% (unintentional) /PA	10.20%	÷1.017	×0.710	—	×1.003	7.14%
HBP% /PA	2.04%	—	×0.980	—	×1.003	2.01%
Singles /BIP	13.16%	÷0.978	×0.900	—	×1.003	12.15%
Doubles /BIP	5.26%	÷1.038	×0.810	—	×1.003	4.12%
Triples /BIP	5.26%	÷1.150	×0.810	—	×1.003	3.72%
Home runs /BIP	2.63%	÷0.989	×0.780	—	×1.003	2.08%

Factors used: league row PCL. Park (home-season share, regressed): HR 98, 1B 96, 2B 108, 3B 130, K 100, BB 103 — applied at half strength. Age: age 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average).

Result: wOBA .331 → .264; ISO .209 → .158; BABIP .243 → .204. 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 AAAOklahoma City Dodgers · 344 PAwOBA .377 → .308 (−69)K% 18.9% → 25.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.90%	÷0.972	×1.290	—	—	25.07%
BB% (unintentional) /PA	10.17%	÷1.059	×0.710	—	×1.018	6.95%
HBP% /PA	0.87%	—	×0.980	—	×1.018	0.87%
Singles /BIP	26.78%	÷1.017	×0.900	×1.010	×1.018	24.37%
Doubles /BIP	10.46%	÷0.975	×0.810	×1.010	×1.018	8.94%
Triples /BIP	2.51%	÷1.104	×0.810	×1.010	×1.018	1.89%
Home runs /BIP	1.26%	÷0.947	×0.780	—	×1.018	1.05%

Factors used: league row PCL. Park (home-season share, regressed): HR 89, 1B 103, 2B 95, 3B 121, K 94, BB 112 — 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 ×1.010.

Result: wOBA .377 → .308; ISO .151 → .121; BABIP .401 → .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).

2015 AAATacoma Rainiers · 396 PAwOBA .361 → .313 (−48)K% 15.4% → 18.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.40%	÷1.049	×1.290	—	—	18.94%
BB% (unintentional) /PA	12.63%	÷1.046	×0.710	—	×1.033	8.85%
HBP% /PA	0.51%	—	×0.980	—	×1.033	0.51%
Singles /BIP	25.89%	÷0.995	×0.900	×0.999	×1.033	24.16%
Doubles /BIP	7.09%	÷0.910	×0.810	×0.999	×1.033	6.51%
Triples /BIP	2.13%	÷0.900	×0.810	×0.999	×1.033	1.98%
Home runs /BIP	1.42%	÷1.127	×0.780	—	×1.033	1.01%

Factors used: league row PCL. Park (home-season share, regressed): HR 125, 1B 99, 2B 82, 3B 80, K 110, BB 109 — 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 ×0.999.

Result: wOBA .361 → .313; ISO .128 → .112; BABIP .355 → .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).

2014 AAATacoma Rainiers · 346 PAwOBA .386 → .339 (−47)K% 21.4% → 27.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.39%	÷1.017	×1.290	—	—	27.13%
BB% (unintentional) /PA	9.83%	÷1.052	×0.710	—	×1.048	6.95%
HBP% /PA	0.87%	—	×0.980	—	×1.048	0.89%
Singles /BIP	28.51%	÷1.016	×0.900	×1.020	×1.048	27.01%
Doubles /BIP	9.65%	÷0.937	×0.810	×1.020	×1.048	8.92%
Triples /BIP	3.07%	÷0.971	×0.810	×1.020	×1.048	2.74%
Home runs /BIP	2.19%	÷0.963	×0.780	—	×1.048	1.86%

Factors used: league row PCL. Park (home-season share, regressed): HR 93, 1B 103, 2B 87, 3B 94, K 103, BB 110 — 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 ×1.020.

Result: wOBA .386 → .339; ISO .169 → .149; BABIP .412 → .385. 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+High Desert Mavericks · 319 PAwOBA .411 → .326 (−85)K% 19.4% → 27.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.44%	÷0.960	×1.340	—	—	27.14%
BB% (unintentional) /PA	13.79%	÷1.037	×0.710	—	×0.998	9.42%
HBP% /PA	0.63%	—	×0.790	—	×0.998	0.49%
Singles /BIP	28.99%	÷1.038	×0.910	×1.037	×0.998	26.31%
Doubles /BIP	7.73%	÷0.990	×0.820	×1.037	×0.998	6.62%
Triples /BIP	3.38%	÷1.083	×0.760	×1.037	×0.998	2.46%
Home runs /BIP	3.38%	÷1.251	×0.920	—	×0.998	2.48%

Factors used: league row CAL. Park (home-season share, regressed): HR 150, 1B 108, 2B 98, 3B 117, K 92, BB 107 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.037.

Result: wOBA .411 → .326; ISO .190 → .142; BABIP .407 → .356. 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
#1Austin Kearnslast yr '12 career totals — 11 seasons, 4,148 PA	6.2	4,148	121	33	254	351	415	-42	-4	15.7	15.9
/162	664	19	5	-6.8	-0.6	2.5	pk7: 16
#2Josh Reddicklast yr '21 career totals — 13 seasons, 4,879 PA	7.3	4,879	146	61	262	321	426	-52	-8	13.1	13.0
/162	664	20	8	-7.1	-1.1	1.8	pk7: 13
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 13 projected seasons	6.0	3,998	111	92	249	326	419	-43	+4	12.2	12.9
/162	664	18	15	-7.1	+0.6	2.0	pk7: 14
#3John Lowenstein'70-'85 * career totals — 14 seasons, 3,988 PA	6.0	3,988	116	128	252*	339*	439*	-40	-8	12.3	12.7
/162	664	19	21	-6.7	-1.3	2.0	pk7: 13
#4Michael Tucker'95-'06 * career totals — 12 seasons, 4,686 PA	7.1	4,686	125	114	246*	326*	410*	-44	+9	9.4	9.1
/162	664	18	16	-6.3	+1.3	1.3	pk7: 9
#5Rob Mackowiaklast yr '08 career totals — 8 seasons, 2,618 PA	3.9	2,618	64	49	259	332	405	-11	-3	8.7	8.9
/162	664	16	12	-2.7	-0.8	2.2	pk7: 9
#6Jeffrey Hammonds'93-'05 * career totals — 12 seasons, 3,404 PA	5.1	3,404	110	67	260*	323*	434*	-25	+1	8.6	8.7
/162	664	21	13	-4.8	+0.2	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
Chris Taylor (OGILVIE)	36	—	—	—	—	229/311/338	109	318	1	2	29%	9%	88	+0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Curt Casali 2024 · MLB	35	43	43→50	47→30	51	211/304/320	109	285	11	4	28%	10%	81	-0.1	233/322/344	111	290	10	6	22%	10%	93	+0.8	235/335/321	87	290	7	0	19%	11%	92	+0.3
✕Drew Butera 2020 · MLB	36	42	44→40	49→40	47	209/277/326	117	269	11	5	26%	8%	71	-0.8	190/259/298	108	261	11	8	30%	7%	58	-1.7	137/214/222	85	196	9	7	34%	6%	23	-2.0
✕Daniel Hinojosa 2019 · AAA	35	46	39→40	49→55	43	218/276/297	79	299	6	11	28%	7%	63	-1.3	207/259/340	133	322	16	10	39%	6%	68	-1.0	127/163/250	124	192	20	5	47%	4%	9	-1.0
✕Royce Clayton 2006 · MLB	36	54→57	40→45	50	49	259/313/359	100	311	6	11	18%	7%	91	+0.6	246/297/339	93	307	5	12	20%	6%	80	-0.1	240/289/322	82	302	2	13	20%	6%	74	-0.3
✕Curtis Pride 2005 · MLB	36	48	45	51→55	43	238/292/367	129	300	12	12	24%	6%	86	+0.3	232/305/361	129	313	12	18	27%	9%	89	+0.5	222/299/340	118	307	10	21	29%	9%	81	-0.0
✕Ryan Hanigan 2017 · MLB	36	44→54	41→40	47→40	51	215/296/310	96	260	9	4	21%	9%	75	-0.5	219/284/309	90	283	9	5	24%	7%	70	-0.9	229/291/287	58	311	6	0	26%	7%	72	-0.2
✕Matt Treanor 2012 · MLB	36	44	41→40	39→40	56	214/313/306	93	254	10	6	19%	11%	81	-0.1	219/309/339	120	270	12	8	22%	10%	86	+0.3	170/266/275	105	214	9	5	24%	10%	59	-0.3
✕Anthony Recker 2018 · MLB	34	40→48	45→50	49→45	43	203/272/329	126	276	13	5	30%	7%	70	-0.8	209/270/358	149	284	17	6	31%	7%	76	-0.4	182/243/344	162	237	21	0	32%	7%	60	-0.8
✕Mike Benjamin 2002 · MLB	36	51	44→45	47→50	46	249/300/374	125	293	9	12	18%	6%	90	+0.6	213/273/318	105	267	9	8	23%	7%	68	-1.0	148/200/180	33	198	0	0	24%	5%	8	-1.2
✕Charlie Culberson 2023 · MLB	34	49→54	45	47→50	43	240/287/367	127	300	12	13	24%	6%	84	+0.1	222/270/335	113	309	12	12	30%	6%	70	-0.8	164/189/198	34	266	4	14	39%	3%	8	-1.0
✕Vinny Rottino 2016 · AAA	36	44→54	42→45	49→55	45	218/276/317	99	276	10	5	24%	7%	68	-1.0	209/276/303	94	272	9	6	25%	7%	65	-1.2	173/252/229	57	227	6	0	25%	8%	38	-1.4
✕Robinson Cancel 2012 · AAA	36	49	39→45	49→50	46	233/284/320	87	285	6	14	20%	6%	72	-0.7	242/290/355	113	285	12	16	19%	6%	82	-0.0	255/302/364	110	293	13	17	17%	6%	85	+0.1
✕Jolbert Cabrera 2009 · MLB	36	48	44→45	49→50	41	234/280/363	129	279	10	8	20%	4%	80	-0.1	244/284/369	125	293	11	11	20%	4%	83	+0.1	250/285/374	124	296	12	9	19%	3%	83	+0.1
✕Jesus Alberto Vega 2019 · AAA	37	42	43→45	48→40	40	210/261/320	110	280	11	7	29%	5%	63	-1.3	204/254/326	122	300	14	9	35%	6%	62	-1.4	156/198/251	95	230	14	3	38%	4%	21	-1.4
✕Tom Prince 2001 · MLB	36	49	46→50	50→45	51	239/315/373	135	292	12	8	22%	9%	97	+1.1	230/306/381	151	259	17	8	19%	8%	95	+1.0	217/295/364	147	239	18	7	18%	7%	88	+0.1
✕A.J. Ellis 2017 · MLB	36	45→54	43→45	45→40	59	221/314/334	112	252	11	5	17%	11%	87	+0.4	239/326/368	129	280	13	5	19%	10%	99	+1.3	241/338/360	119	287	13	0	19%	11%	103	+0.4
✕Angel Berroa 2013 · AAA	36	45→55	44→50	50	40	225/264/347	121	273	11	11	22%	4%	70	-0.8	243/287/381	138	289	15	6	21%	4%	87	+0.4	243/286/379	136	286	15	4	21%	4%	84	+0.1
✕Yuniesky Betancourt 2017 · AAA	35	46→56	43→50	50	45	225/277/338	113	267	11	12	20%	6%	74	-0.6	224/259/306	82	249	7	7	13%	4%	58	-1.7	224/242/258	35	243	2	0	9%	2%	39	-1.1
✕Humberto Cota 2015 · AAA	36	41	45→50	47→30	44	210/269/324	114	261	14	5	26%	6%	68	-1.0	203/271/321	118	264	14	4	27%	8%	68	-1.0	184/259/289	106	240	13	0	28%	9%	56	-0.7
✕Miguel Ojeda 2011 · AAA	36	47→45	46→45	43→45	51	235/298/365	131	265	14	8	18%	8%	88	+0.4	228/284/331	103	275	10	7	20%	7%	74	-0.5	225/281/317	91	274	8	6	20%	6%	68	-0.7

Chris Taylor

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps