Kyle Higashioka

C Texas Rangers

Age 37 R/R 6'1" / 202 lbs MLB HR +15%BB +5% Svc 8.029 · Ctrl thru 2027

Overview

MLB40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	34	MLBSD	263	.220/.264/.476	17	2	102	1.8
2025	35	MLBTEX	327	.241/.292/.403	11	3	91	1.5
2026	36	AAATEX	52	.239/.327/.413	2	1	52	—	.188/.250/.292
2026	36	MLBTEX	186	.218/.306/.370	7	0	89	0.5
2027PROJ	37	MLBTEX	138	.217/.284/.397	6	1	87	0.3
2028PROJ	38	MLBTEX	80	.206/.272/.370	3	0	76	-0.7

Last 3 seasons WAR 3.7 · Next 2 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service8.029First FA2028Options2

2027Ext / FA-deal$1M

Skills · percentileStatcast 2024-2026

Barrel%58

Bat Spd47

Avg EV43

xwOBA40

Speed10

CompsJohn Flaherty (age 37) · Miguel Olivo (age 36) · Martín Maldonado (age 37)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 8987vR 80

AVG/OBP/SLG.217 / .284 / .397

PA138

HR6

K%23

BB%8

BABIP243

ISO184

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · ContractCON 45 / POW 50

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT45

xAVG

170.224

POWER50

Barrel%

589.4

Avg EV

4388.6

Bat Spd

4771.1

EYE50

scouting grade only

SPEED35

Sprint

1024.6

Platoon Splits2024-2026 · 623 PA

vs LHP

vs RHP

Edge

195

428

—

wRC+

▶R

wOBA

307

313

—

ISO

221

191

◀L

BABIP

243

267

▶R

24.1%

24.8%

—

BB%

4.1%

7.5%

▶▶R

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

Status FA

MLB Debut 2017

Service 8.029 yrs.days

Team Control Through 2027

First FA Year 2028

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$1M	+0.2	$0.8M	-$0.5M
Totals		$1M		$0.8M	-$0.5M

Options · projected decision
2027	MUTUAL OPT	$1.3M / $0.0M buyout	DECLINE
2028	MUTUAL OPT	$7.0M / $1.0M buyout	DECLINE

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. Catcher framing: only 2027 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run 1-3 WAR low.

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)
2008	18	ROK	GCL Yankees	—	50	46	12	1	0	1	2	8	1	0	0	261	306	348	654	87	289	16	4	291	37	—	—	—	—	—	—
2010	20	A	Charleston RiverDogs	—	359	320	72	18	0	6	31	64	5	0	2	225	303	338	641	113	263	18	9	291	45	—	—	—	—	—	—
2011	21	A+	Tampa Yankees	—	180	164	39	10	0	4	14	22	1	1	0	238	302	372	674	134	252	12	8	302	65	—	—	—	—	—	—
2011	21	A	Charleston RiverDogs	—	144	130	29	6	0	4	9	19	2	0	0	223	284	362	645	138	229	13	6	285	39	—	—	—	—	—	—
2012	22	AA	Trenton Thunder	—	26	23	2	0	0	0	2	8	0	0	0	87	160	87	247		125	31	8	123	-37	—	—	—	—	—	—
2012	22	A+	Tampa Yankees	—	139	124	23	5	0	6	10	34	0	1	1	185	244	371	615	185	198	24	7	264	26	—	—	—	—	—	—
2013	23	AA	Trenton Thunder	—	26	25	8	3	0	1	0	5	0	0	0	320	320	560	880	240	368	19	0	367	91	—	—	—	—	—	—
2014	24	A+	Tampa Yankees	—	31	26	6	3	0	1	4	4	0	0	0	231	333	462	795	231	227	13	13	340	93	—	—	—	—	—	—
2014	24	ROK	GCL Yankees1	—	27	23	5	1	0	0	3	7	0	0	0	217	308	261	569	43	294	26	11	259	7	—	—	—	—	—	—
2014	24	INTL	Scottsdale Scorpions	—	25	22	9	3	0	1	3	2	0	1	1	409	480	682	1.162	273	421	8	12	502	226	—	—	—	—	—	—
2015	25	AAA	Scranton/Wilkes-Barre RailRiders	—	17	17	3	1	0	0	0	4	0	0	0	176	176	235	412	59	231	24	0	182	-8	—	—	—	—	—	—
2015	25	A+	Tampa Yankees	—	331	307	78	18	2	5	22	49	1	0	0	254	306	375	681	121	287	15	7	305	46	—	—	—	—	—	—
2016	26	AAA	Scranton/Wilkes-Barre RailRiders	—	160	148	37	9	0	10	12	31	0	0	1	250	306	514	820	264	252	19	8	356	77	—	—	—	—	—	—
2016	26	AA	Trenton Thunder	—	256	222	65	15	0	11	26	42	0	0	1	293	367	509	876	216	305	16	10	373	101	—	—	—	—	—	—
2017	27	MLB	New York Yankees	—	20	18	0	0	0	0	2	6	0	0	0		100		100			30	10	70	-67	-4	+0	+1	+1	+0	-0.1
2017	27	AAA	Scranton/Wilkes-Barre RailRiders	—	57	53	14	4	0	2	4	7	0	0	0	264	316	453	769	189	273	12	7	339	63	—	—	—	—	—	—
2018	28	MLB	New York Yankees	—	79	72	12	2	0	3	6	16	1	0	0	167	241	319	560	153	170	20	8	254	55	-4	+0	+4	+5	+2	0.7
2018	28	AAA	Scranton/Wilkes-Barre RailRiders	—	211	188	38	10	1	5	17	44	3	2	0	202	278	346	623	144	234	21	8	279	32	—	—	—	—	—	—
2019	29	MLB	New York Yankees	—	57	56	12	5	0	3	0	26	0	0	0	214	214	464	679	250	321	46	0	286	76	-2	+0	+3	+6	+1	0.9
2019	29	AAA	Scranton/Wilkes-Barre RailRiders	—	270	241	67	13	0	20	24	53	3	0	0	278	351	581	932	303	276	20	9	400	91	—	—	—	—	—	—
2020	30	MLB	New York Yankees	—	48	48	12	1	0	4	0	11	0	0	0	250	250	521	771	271	242	23	0	332	104	+0	+0	+3	+1	+1	0.5
2021	31	MLB	New York Yankees	—	211	193	35	10	0	10	17	59	0	0	0	181	248	389	636	207	200	28	8	280	72	-7	+0	+8	+4	+5	0.9
2022	32	MLB	New York Yankees	—	248	229	52	7	0	10	12	52	1	0	1	227	269	389	657	162	246	21	5	285	75	-7	-0	+13	+4	+5	1.6
2023	33	MLB	New York Yankees	—	260	242	57	13	0	10	14	74	0	0	0	236	277	413	691	178	292	28	5	300	86	-4	+0	+10	+5	+6	1.7
2024	34	MLB	San Diego Padres	—	263	246	54	10	1	17	15	74	0	2	0	220	264	476	740	256	237	28	6	319	102	+1	+0	+6	+5	+6	1.8
2025	35	MLB	Texas Rangers	—	327	303	73	14	1	11	20	72	2	3	1	241	292	403	695	162	279	22	6	307	91	-3	+0	+5	+6	+7	1.5
2026	36	MLB	Texas Rangers	—	186	165	36	4	0	7	19	47	2	0	0	218	306	370	676	152	261	25	10	307	89	-2	+0	-1	+4	+4	0.5
2026	36	AAA	Round Rock Express	—	52	46	11	2	0	2	6	9	0	1	0	239	327	413	740	174	257	17	12	332	52	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1699	1572	343	66	2	75	105	437	6	5	2	218	270	406	676	188	250	26	6	296	86	-28	+0	+53	+41	+37	10.5
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2008	18	ROK MLE	GCL Yankees	—	50	47	10	1	0	1	1	12	1	0	0	213	245	298	543	85	238	24	2	223	37	—	—	—	—	—	—
2010	20	A MLE	Charleston RiverDogs	—	359	329	62	15	0	5	22	81	5	0	2	188	250	280	530	91	229	23	6	234	45	—	—	—	—	—	—
2011	21	A+ MLE	Tampa Yankees	—	180	167	35	9	0	4	11	30	1	1	0	210	263	335	598	126	235	17	6	265	65	—	—	—	—	—	—
2011	21	A MLE	Charleston RiverDogs	—	144	134	25	5	0	3	5	26	2	0	0	187	227	291	518	104	201	18	3	226	39	—	—	—	—	—	—
2012	22	AA MLE	Trenton Thunder	—	26	23	2	0	0	0	2	10	0	0	0	87	160	87	247		129	38	8	113	-37	—	—	—	—	—	—
2012	22	A+ MLE	Tampa Yankees	—	139	128	19	4	0	5	7	49	0	1	1	148	193	297	489	148	170	35	5	207	26	—	—	—	—	—	—
2013	23	AA MLE	Trenton Thunder	—	26	25	7	2	0	1	0	6	0	0	0	280	280	480	760	200	323	23	0	303	91	—	—	—	—	—	—
2014	24	A+ MLE	Tampa Yankees	—	31	27	6	3	0	1	3	6	0	0	0	222	300	444	744	222	210	19	10	306	93	—	—	—	—	—	—
2014	24	ROK MLE	GCL Yankees1	—	27	24	4	1	0	0	2	10	0	0	0	167	231	208	439	42	224	37	7	179	7	—	—	—	—	—	—
2015	25	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	17	17	3	1	0	0	0	5	0	0	0	176	176	235	412	59	219	29	0	157	-8	—	—	—	—	—	—
2015	25	A+ MLE	Tampa Yankees	—	331	313	62	15	1	5	16	69	1	0	0	198	239	300	540	102	236	21	5	236	46	—	—	—	—	—	—
2016	26	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	160	153	31	7	0	8	7	37	0	0	1	203	237	405	643	203	214	23	4	282	77	—	—	—	—	—	—
2016	26	AA MLE	Trenton Thunder	—	256	231	60	13	0	9	17	51	0	0	1	260	310	433	743	173	272	20	7	317	101	—	—	—	—	—	—
2017	27	MLB MLE	New York Yankees	—	20	18	0	0	0	0	2	6	0	0	0		100		100			30	10	70	-67	-4	+0	+1	+1	+0	-0.1
2017	27	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	57	54	11	3	0	1	3	8	0	0	0	204	246	315	560	111	237	14	5	262	63	—	—	—	—	—	—
2018	28	MLB MLE	New York Yankees	—	79	72	12	2	0	3	6	16	1	0	0	167	241	319	560	153	170	20	8	249	55	-4	+0	+4	+5	+2	0.7
2018	28	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	211	195	32	8	1	4	11	53	3	2	0	164	220	277	497	113	192	25	5	216	32	—	—	—	—	—	—
2019	29	MLB MLE	New York Yankees	—	57	56	12	5	0	3	0	26	0	0	0	214	214	464	679	250	321	46	0	280	76	-2	+0	+3	+6	+1	0.9
2019	29	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	270	250	54	10	0	15	15	63	3	0	0	216	269	436	705	220	223	23	6	303	91	—	—	—	—	—	—
2020	30	MLB MLE	New York Yankees	—	48	48	12	1	0	4	0	11	0	0	0	250	250	521	771	271	242	23	0	322	104	+0	+0	+3	+1	+1	0.5
2021	31	MLB MLE	New York Yankees	—	211	193	34	10	0	9	17	59	0	0	0	176	243	368	611	192	200	28	8	275	72	-7	+0	+8	+4	+5	0.9
2022	32	MLB MLE	New York Yankees	—	248	229	51	7	0	9	12	52	1	0	1	223	264	371	636	148	246	21	5	280	75	-7	-0	+13	+4	+5	1.6
2023	33	MLB MLE	New York Yankees	—	260	242	56	13	0	9	14	74	0	0	0	231	273	397	670	165	292	28	5	296	86	-4	+0	+10	+5	+6	1.7
2024	34	MLB MLE	San Diego Padres	—	263	246	55	11	1	17	15	74	0	2	0	224	268	484	752	260	237	28	6	320	102	+1	+0	+6	+5	+6	1.8
2025	35	MLB MLE	Texas Rangers	—	327	303	73	15	1	10	20	72	2	3	1	241	292	396	688	155	279	22	6	303	91	-3	+0	+5	+6	+7	1.5
2026	36	MLB MLE	Texas Rangers	—	186	165	36	4	0	7	19	47	2	0	0	218	306	370	676	152	261	25	10	300	89	-2	+0	-1	+4	+4	0.5
2026	36	AAA MLE	Round Rock Express	—	52	48	9	2	0	1	4	11	0	1	0	188	250	292	542	104	215	21	8	245	52	—	—	—	—	—	—
2008	18	ROK MLE	GCL Yankees	—	50	47	10	1	0	1	1	12	1	0	0	213	245	298	543	85	257	24	2	223	37	—	—	—	—	—	—
2008	18	ROK RAW	GCL Yankees	—	50	46	12	1	0	1	2	8	1	0	0	261	306	348	654	87	289	16	4	291	37	—	—	—	—	—	—
2010	20	A MLE	Charleston RiverDogs	—	359	329	62	15	0	5	22	81	5	0	2	188	250	280	530	91	234	23	6	234	45	—	—	—	—	—	—
2010	20	A RAW	Charleston RiverDogs	—	359	320	72	18	0	6	31	64	5	0	2	225	303	338	641	113	263	18	9	291	45	—	—	—	—	—	—
2011	21	A+ MLE	2 teams	—	324	301	61	14	0	7	16	56	3	1	0	203	250	319	569	116	224	17	5	248	54	—	—	—	—	—	—
2011	21	A+ RAW	2 teams	—	324	294	68	16	0	8	23	41	3	1	0	231	294	367	661	136	242	13	7	294	54	—	—	—	—	—	—
2012	22	A+ MLE	2 teams	—	165	152	21	4	0	5	8	59	0	1	1	138	181	263	444	125	176	36	5	192	16	—	—	—	—	—	—
2012	22	A+ RAW	2 teams	—	165	147	25	5	0	6	12	42	0	1	1	170	231	327	558	156	186	25	7	242	16	—	—	—	—	—	—
2013	23	AA MLE	Trenton Thunder	—	26	25	7	2	0	1	0	6	0	0	0	280	280	480	760	200	333	23	0	303	91	—	—	—	—	—	—
2013	23	AA RAW	Trenton Thunder	—	26	25	8	3	0	1	0	5	0	0	0	320	320	560	880	240	368	19	0	367	91	—	—	—	—	—	—
2014	24	A+ MLE	3 teams	—	83	74	13	5	0	1	7	23	0	1	1	176	247	284	531	108	231	28	8	247	53	—	—	—	—	—	—
2014	24	A+ RAW	3 teams	—	83	71	20	7	0	2	10	13	0	1	1	282	370	465	835	183	310	16	12	362	53	—	—	—	—	—	—
2015	25	A+ MLE	2 teams	—	348	330	65	16	1	5	16	73	1	0	0	197	236	297	533	100	237	21	5	232	43	—	—	—	—	—	—
2015	25	A+ RAW	2 teams	—	348	324	81	19	2	5	22	53	1	0	0	250	300	367	667	117	285	15	6	299	43	—	—	—	—	—	—
2016	26	AA MLE	2 teams	—	416	384	91	20	0	17	24	89	0	0	2	237	282	422	704	185	259	21	6	304	92	—	—	—	—	—	—
2016	26	AA RAW	2 teams	—	416	370	102	24	0	21	38	73	0	0	2	276	343	511	854	235	285	18	9	367	92	—	—	—	—	—	—
2017	27	AAA MLE	2 teams	—	77	72	11	3	0	1	5	14	0	0	0	153	208	236	444	83	175	18	6	212	30	—	—	—	—	—	—
2017	27	AAA RAW	2 teams	—	77	71	14	4	0	2	6	13	0	0	0	197	260	338	598	141	214	17	8	269	30	—	—	—	—	—	—
2018	28	AAA MLE	2 teams	—	290	267	44	10	1	7	17	69	4	2	0	165	226	288	514	124	192	24	6	225	39	—	—	—	—	—	—
2018	28	AAA RAW	2 teams	—	290	260	50	12	1	8	23	60	4	2	0	192	267	338	606	146	216	21	8	272	39	—	—	—	—	—	—
2019	29	AAA MLE	2 teams	—	327	306	66	15	0	18	15	89	3	0	0	216	259	441	700	225	238	27	5	299	89	—	—	—	—	—	—
2019	29	AAA RAW	2 teams	—	327	297	79	18	0	23	24	79	3	0	0	266	327	559	886	293	283	24	7	380	89	—	—	—	—	—	—
2020	30	MLB MLE	New York Yankees	—	48	48	12	1	0	4	0	11	0	0	0	250	250	521	771	271	242	23	0	322	104	+0	+0	+3	+1	+1	0.5
2020	30	MLB RAW	New York Yankees	—	48	48	12	1	0	4	0	11	0	0	0	250	250	521	771	271	242	23	0	332	104	+0	+0	+3	+1	+1	0.5
2021	31	MLB MLE	New York Yankees	—	211	193	34	10	0	9	17	59	0	0	0	176	243	368	611	192	198	28	8	275	72	-7	+0	+8	+4	+5	0.9
2021	31	MLB RAW	New York Yankees	—	211	193	35	10	0	10	17	59	0	0	0	181	248	389	636	207	200	28	8	280	72	-7	+0	+8	+4	+5	0.9
2022	32	MLB MLE	New York Yankees	—	248	229	51	7	0	9	12	52	1	0	1	223	264	371	636	148	244	21	5	280	75	-7	-0	+13	+4	+5	1.6
2022	32	MLB RAW	New York Yankees	—	248	229	52	7	0	10	12	52	1	0	1	227	269	389	657	162	246	21	5	285	75	-7	-0	+13	+4	+5	1.6
2023	33	MLB MLE	New York Yankees	—	260	242	56	13	0	9	14	74	0	0	0	231	273	397	670	165	290	28	5	296	86	-4	+0	+10	+5	+6	1.7
2023	33	MLB RAW	New York Yankees	—	260	242	57	13	0	10	14	74	0	0	0	236	277	413	691	178	292	28	5	300	86	-4	+0	+10	+5	+6	1.7
2024	34	MLB MLE	San Diego Padres	—	263	246	55	11	1	17	15	74	0	2	0	224	268	484	752	260	244	28	6	320	102	+1	+0	+6	+5	+6	1.8
2024	34	MLB RAW	San Diego Padres	—	263	246	54	10	1	17	15	74	0	2	0	220	264	476	740	256	237	28	6	319	102	+1	+0	+6	+5	+6	1.8
2025	35	MLB MLE	Texas Rangers	—	327	303	73	15	1	10	20	72	2	3	1	241	292	396	688	155	283	22	6	303	91	-3	+0	+5	+6	+7	1.5
2025	35	MLB RAW	Texas Rangers	—	327	303	73	14	1	11	20	72	2	3	1	241	292	403	695	162	279	22	6	307	91	-3	+0	+5	+6	+7	1.5
2026	36	MLB MLE	2 teams	—	238	213	45	6	0	8	23	58	2	1	0	211	294	352	646	141	252	24	10	288	81	-5	+0	-1	+4	+5	0.3
2026	36	MLB RAW	2 teams	—	238	211	47	6	0	9	25	56	2	1	0	223	311	379	690	156	260	24	11	312	81	-5	+0	-1	+4	+5	0.3
2008	18	ROK MLE	GCL Yankees	—	50	48	10	1	0	1	1	12	1	0	0	208	245	292	537	83	238	24	2	223	37	—	—	—	—	—	—
2010	20	A MLE	Charleston RiverDogs	—	359	329	62	15	0	5	22	81	5	0	2	188	250	280	530	91	229	23	6	234	45	—	—	—	—	—	—
2011	21	A+ MLE	2 teams	—	324	302	61	14	0	7	16	56	3	1	0	202	250	318	568	116	220	17	5	248	54	—	—	—	—	—	—
2012	22	A+ MLE	2 teams	—	165	156	21	4	0	5	8	59	0	1	1	135	181	256	438	122	164	36	5	192	16	—	—	—	—	—	—
2013	23	AA MLE	Trenton Thunder	—	26	26	7	2	0	1	0	6	0	0	0	269	280	462	742	192	323	23	0	303	91	—	—	—	—	—	—
2014	24	A+ MLE	3 teams	—	83	76	13	5	0	1	7	23	0	1	1	171	247	276	523	105	217	28	8	247	53	—	—	—	—	—	—
2015	25	A+ MLE	2 teams	—	348	328	65	16	1	5	16	73	1	0	0	198	236	299	535	101	235	21	5	232	43	—	—	—	—	—	—
2016	26	AA MLE	2 teams	—	416	389	91	20	0	17	24	89	0	0	2	234	282	416	698	183	250	21	6	304	92	—	—	—	—	—	—
2017	27	AAA MLE	2 teams	—	77	72	11	3	0	1	5	14	0	0	0	153	208	236	444	83	175	18	6	212	30	—	—	—	—	—	—
2018	28	AAA MLE	2 teams	—	290	267	44	10	1	7	17	69	4	2	0	165	226	288	514	124	186	24	6	225	39	—	—	—	—	—	—
2019	29	AAA MLE	2 teams	—	327	306	66	15	0	18	15	89	3	0	0	216	259	441	700	225	240	27	5	299	89	—	—	—	—	—	—
2020	30	MLB MLE	New York Yankees	—	48	48	12	1	0	4	0	11	0	0	0	250	250	521	771	271	242	23	0	322	104	—	—	—	—	—	—
2021	31	MLB MLE	New York Yankees	—	211	192	34	10	0	9	17	59	0	0	0	177	243	370	613	193	200	28	8	275	72	—	—	—	—	—	—
2022	32	MLB MLE	New York Yankees	—	248	233	51	7	0	9	12	52	1	0	1	219	264	365	629	146	246	21	5	280	75	—	—	—	—	—	—
2023	33	MLB MLE	New York Yankees	—	260	244	56	13	0	9	14	74	0	0	0	230	273	393	667	164	292	28	5	296	86	—	—	—	—	—	—
2024	34	MLB MLE	San Diego Padres	—	263	246	55	11	1	17	15	74	0	2	0	224	268	484	752	260	237	28	6	320	102	—	—	—	—	—	—
2025	35	MLB MLE	Texas Rangers	—	327	302	73	15	1	10	20	72	2	3	1	242	292	397	690	156	279	22	6	303	91	—	—	—	—	—	—
2026	36	MLB MLE	2 teams	—	238	211	45	6	0	8	23	58	2	1	0	213	294	355	650	142	251	24	10	288	81	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	34	MLB MLE	San Diego Padres	—	263	246	55	11	1	17	15	74	0	2	0	224	268	484	752	260	237	28	6	320	102	—	—	—	—	—	—
2025	35	MLB MLE	Texas Rangers	—	327	302	73	15	1	10	20	72	2	3	1	242	292	397	690	156	279	22	6	303	91	—	—	—	—	—	—
2026	36	MLB MLE	2 teams	—	238	211	45	6	0	8	23	58	2	1	0	213	294	355	650	142	251	24	10	288	81	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	37	MLB MLE	TEX	100%	223	202	44	8	1	9	17	52	2	2	1	215	282	387	669	172	243	23	8	297	87	-3	+0	-1	+4	+5	0.2
▸ 2027 — real world (MLB)
2027	37	MLB CTX	TEX	100%	138	125	27	5	0	6	11	32	1	1	0	217	284	397	682	180	243	23	8	301	87	-2	+0	-0	+2	+3	0.3
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	38	MLB MLE	TEX	100%	80	73	15	3	0	3	6	19	1	0	0	204	270	360	630	156	233	24	8	281	76	-2	+0	-8	+1	+2	-0.7
2028	38	MLB CTX	TEX	100%	80	73	14	2	0	3	6	19	1	0	0	206	272	370	642	164	233	24	8	285	76	-2	+0	-8	+1	+2	-0.7
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1779	1645	357	68	2	78	111	456	7	5	2	217	269	403	672	186	248	26	6	295	69	-30	+0	+45	+42	+39	9.8
/ 162G	—	A+C		—	650	601	130	25	1	28	41	167	3	2	1	216	270	401	671	185	249	26	6	295	69	-11	+0	+16	+15	+14	3.6
Career	—	MLE		—	4278	3959	818	176	4	142	249	1022	24	12	8	207	258	361	618	154	239	24	6	270	69	-32	+0	+44	+45	+42	10.1
/ 162G	—	MLE		—	650	602	125	27	1	22	38	155	4	2	1	208	260	365	625	158	240	24	6	270	69	-11	+0	+15	+15	+14	3.4

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 AAARound Rock Express · 52 PAwOBA .323 → .245 (−78)K% 17.3% → 20.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.31%	÷1.000	×1.200	—	—	20.77%
BB% (unintentional) /PA	11.54%	÷1.000	×0.690	—	×0.940	7.48%
HBP% /PA	0.00%	—	×0.940	—	×0.940	0.00%
Singles /BIP	18.92%	÷1.000	×0.930	—	×0.940	16.54%
Doubles /BIP	5.41%	÷1.000	×0.830	—	×0.940	4.22%
Triples /BIP	0.00%	÷1.000	×0.970	—	×0.940	0.00%
Home runs /BIP	5.41%	÷1.000	×0.700	—	×0.940	3.56%

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).

Result: wOBA .323 → .245; ISO .174 → .121; BABIP .257 → .215. 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 AAAScranton/Wilkes-Barre RailRiders · 270 PAwOBA .390 → .303 (−87)K% 19.6% → 23.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.63%	÷1.007	×1.200	—	—	23.40%
BB% (unintentional) /PA	8.52%	÷1.066	×0.690	—	×0.982	5.42%
HBP% /PA	1.11%	—	×0.940	—	×0.982	1.03%
Singles /BIP	18.09%	÷1.019	×0.930	×0.950	×0.982	15.39%
Doubles /BIP	6.91%	÷1.009	×0.830	×0.950	×0.982	5.30%
Triples /BIP	0.00%	÷0.938	×0.970	×0.950	×0.982	0.00%
Home runs /BIP	10.64%	÷1.087	×0.840	—	×0.982	8.07%

Factors used: league row IL. Park (home-season share, regressed): HR 117, 1B 104, 2B 102, 3B 88, K 101, BB 113 — applied at half strength. Age: age 29 vs a level average of 27.2 → −1.8% on BB/HBP/hit rates (1.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .390 → .303; ISO .303 → .232; BABIP .276 → .223. 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 AAAScranton/Wilkes-Barre RailRiders · 211 PAwOBA .274 → .216 (−58)K% 20.9% → 25.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.85%	÷1.002	×1.200	—	—	24.98%
BB% (unintentional) /PA	8.06%	÷1.034	×0.690	—	×0.992	5.33%
HBP% /PA	1.42%	—	×0.940	—	×0.992	1.33%
Singles /BIP	15.28%	÷1.032	×0.930	×0.950	×0.992	12.98%
Doubles /BIP	6.94%	÷1.004	×0.830	×0.950	×0.992	5.41%
Triples /BIP	0.69%	÷1.130	×0.970	×0.950	×0.992	0.56%
Home runs /BIP	3.47%	÷1.046	×0.840	—	×0.992	2.77%

Factors used: league row IL. Park (home-season share, regressed): HR 109, 1B 106, 2B 101, 3B 126, K 100, BB 107 — 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 ×0.950.

Result: wOBA .274 → .216; ISO .144 → .114; BABIP .234 → .192. 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 AAAScranton/Wilkes-Barre RailRiders · 57 PAwOBA .330 → .262 (−67)K% 12.3% → 14.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.28%	÷0.995	×1.200	—	—	14.81%
BB% (unintentional) /PA	7.02%	÷1.105	×0.690	—	×1.003	4.40%
HBP% /PA	0.00%	—	×0.940	—	×1.003	0.00%
Singles /BIP	17.39%	÷0.980	×0.930	×0.950	×1.003	15.73%
Doubles /BIP	8.70%	÷0.951	×0.830	×0.950	×1.003	7.23%
Triples /BIP	0.00%	÷1.150	×0.970	×0.950	×1.003	0.00%
Home runs /BIP	4.35%	÷1.247	×0.840	—	×1.003	2.94%

Factors used: league row IL. Park (home-season share, regressed): HR 149, 1B 96, 2B 90, 3B 130, K 99, BB 121 — 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 ×0.950.

Result: wOBA .330 → .262; ISO .189 → .139; 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).

2016 AATrenton Thunder · 256 PAwOBA .375 → .317 (−58)K% 16.4% → 20.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.41%	÷0.997	×1.220	—	—	20.08%
BB% (unintentional) /PA	10.16%	÷1.061	×0.700	—	×0.988	6.62%
HBP% /PA	0.00%	—	×0.850	—	×0.988	0.00%
Singles /BIP	21.67%	÷0.981	×0.970	×0.950	×0.988	20.11%
Doubles /BIP	8.33%	÷0.962	×0.860	×0.950	×0.988	6.99%
Triples /BIP	0.00%	÷1.039	×0.950	×0.950	×0.988	0.00%
Home runs /BIP	6.11%	÷1.015	×0.780	—	×0.988	4.64%

Factors used: league row EL. Park (home-season share, regressed): HR 103, 1B 96, 2B 92, 3B 108, K 99, BB 112 — applied at half strength. Age: age 26 vs a level average of 24.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .375 → .317; ISO .216 → .177; BABIP .305 → .272. 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 AAAScranton/Wilkes-Barre RailRiders · 160 PAwOBA .342 → .282 (−60)K% 19.4% → 23.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.38%	÷0.994	×1.200	—	—	23.38%
BB% (unintentional) /PA	6.25%	÷0.977	×0.690	—	×1.018	4.49%
HBP% /PA	0.00%	—	×0.940	—	×1.018	0.00%
Singles /BIP	15.38%	÷0.991	×0.930	×0.950	×1.018	13.97%
Doubles /BIP	7.69%	÷1.059	×0.830	×0.950	×1.018	5.83%
Triples /BIP	0.00%	÷0.900	×0.970	×0.950	×1.018	0.00%
Home runs /BIP	8.55%	÷0.996	×0.840	—	×1.018	7.34%

Factors used: league row IL. Park (home-season share, regressed): HR 99, 1B 98, 2B 112, 3B 80, K 99, BB 95 — 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 ×0.950.

Result: wOBA .342 → .282; ISO .264 → .217; BABIP .252 → .214. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2015 A+Tampa Yankees · 331 PAwOBA .297 → .236 (−61)K% 14.8% → 20.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.80%	÷1.016	×1.420	—	—	20.69%
BB% (unintentional) /PA	6.65%	÷1.015	×0.750	—	×0.978	4.80%
HBP% /PA	0.30%	—	×0.930	—	×0.978	0.27%
Singles /BIP	20.54%	÷1.046	×0.920	×0.950	×0.978	16.79%
Doubles /BIP	6.98%	÷1.044	×0.960	×0.950	×0.978	5.96%
Triples /BIP	0.78%	÷1.150	×0.810	×0.950	×0.978	0.51%
Home runs /BIP	1.94%	÷0.832	×0.880	—	×0.978	2.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 66, 1B 109, 2B 109, 3B 130, K 103, BB 103 — applied at half strength. Age: age 25 vs a level average of 22.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .297 → .236; ISO .121 → .104; BABIP .287 → .236. 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 AAAScranton/Wilkes-Barre RailRiders · 17 PAwOBA .177 → .157 (−20)K% 23.5% → 28.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.53%	÷0.991	×1.200	—	—	28.50%
BB% (unintentional) /PA	0.00%	÷1.139	×0.690	—	×1.033	0.00%
HBP% /PA	0.00%	—	×0.940	—	×1.033	0.00%
Singles /BIP	15.38%	÷1.011	×0.930	—	×1.033	14.62%
Doubles /BIP	7.69%	÷0.903	×0.830	—	×1.033	7.30%
Triples /BIP	0.00%	÷1.150	×0.970	—	×1.033	0.00%
Home runs /BIP	0.00%	÷0.878	×0.840	—	×1.033	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 76, 1B 102, 2B 81, 3B 130, K 98, BB 128 — 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).

Result: wOBA .177 → .157; ISO .059 → .052; BABIP .231 → .219. 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
#1Rod Barajaslast yr '12 career totals — 12 seasons, 3,753 PA	5.7	3,753	134	2	235	284	407	+60	+30	15.8	16.0
/162	664	24	0	+10.7	+5.3	2.8	pk7: 16
#2René Riveralast yr '21 career totals — 10 seasons, 1,602 PA	2.4	1,602	42	1	221	273	354	+29	+90	11.7	11.8
/162	664	17	0	+11.9	+37.2	4.9	pk7: 12
#3Ron Karkovice'86-'97 * career totals — 12 seasons, 2,948 PA	4.4	2,948	96	24	215*	282*	390*	+52	+0	7.6	8.1
/162	664	22	5	+11.7	+0.1	1.7	pk7: 9
#4Curt Casalilast yr '24 career totals — 10 seasons, 1,566 PA	2.4	1,566	47	2	217	311	367	+28	+19	7.8	7.9
/162	664	20	1	+11.9	+7.9	3.3	pk7: 8
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 10 projected seasons	2.8	1,849	79	6	219	270	405	+30	+53	5.5	5.4
/162	664	28	2	+10.6	+18.9	2.0	pk7: 5
#5Barry Foote'73-'82 * career totals — 9 seasons, 2,300 PA	3.5	2,300	57	10	225*	274*	401*	+40	-0	4.0	4.9
/162	664	16	3	+11.6	-0.1	1.2	pk7: 6
#6Chris Widger'95-'06 * career totals — 8 seasons, 1,998 PA	3.0	1,998	55	10	227*	283*	381*	+33	-0	3.6	4.1
/162	664	18	3	+11.1	-0.2	1.2	pk7: 5

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
Kyle Higashioka (OGILVIE)	37	45	50	35	50	213/280/383	170	243	5	1	23%	8%	87	+0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕John Flaherty 2005 · MLB	37	48→52	52→45	38→40	43	248/284/415	167	272	19	5	18%	4%	94	+0.9	220/270/362	142	251	16	7	19%	6%	77	-0.3	160/203/244	84	184	9	0	19%	4%	24	-1.0
✕Miguel Olivo 2014 · MLB	36	42→50	54→60	39→50	38	227/259/398	170	272	24	7	27%	4%	81	-0.1	230/270/370	140	313	16	8	31%	5%	78	-0.3	216/254/339	124	304	13	8	32%	4%	62	-0.7
✕Martín Maldonado 2024 · MLB	37	34→44	52→50	45→40	43	191/261/348	157	245	22	2	32%	8%	71	-0.8	196/252/337	141	269	18	4	33%	6%	64	-1.3	159/206/272	113	220	15	0	35%	5%	33	-0.9
✕A.J. Ellis 2018 · MLB	37	45→54	48→45	45→40	54	228/311/370	143	252	17	5	18%	9%	95	+0.9	247/334/371	124	299	12	6	20%	11%	103	+1.5	266/370/339	73	343	3	0	20%	14%	109	+0.6
✕Sal Fasano 2008 · MLB	36	42	52→55	44→40	37	220/278/379	159	274	21	4	28%	4%	85	+0.2	203/259/316	113	281	12	6	31%	4%	62	-1.4	175/227/258	82	257	7	4	33%	3%	35	-1.1
✕Rod Barajas 2012 · MLB	36	43→47	56→60	46→30	43	232/274/418	186	243	26	2	18%	4%	92	+0.7	225/287/386	161	250	21	4	20%	7%	89	+0.5	202/270/342	140	220	20	0	19%	7%	74	-0.3
✕Adam Rosales 2019 · MLB	36	39→49	50→55	42→45	41	206/258/357	151	260	18	5	28%	6%	72	-0.7	198/246/318	120	268	14	6	31%	5%	57	-1.8	161/200/243	83	229	11	2	34%	4%	20	-2.2
✕Robinson Chirinos 2021 · MLB	37	44→46	53→60	43→50	50	226/326/403	178	292	21	4	29%	10%	108	+1.9	217/302/373	156	293	18	5	30%	9%	92	+0.7	192/283/338	146	265	17	2	32%	9%	78	-0.1
✕Mike DiFelice 2006 · MLB	37	40	48→50	42→30	45	210/270/351	141	249	16	5	23%	7%	74	-0.5	214/272/317	103	279	10	4	26%	6%	67	-1.1	208/260/284	76	277	6	0	26%	5%	54	-0.8
✕José Hernández 2006 · MLB	37	47→57	50→55	41→45	45	242/299/391	150	302	19	5	26%	7%	95	+0.9	234/289/361	127	295	14	6	25%	7%	84	+0.1	230/285/340	110	295	11	6	25%	6%	75	-0.3
✕Vance Wilson 2009 · MLB	36	49	50	43→40	44	248/299/406	157	286	18	9	21%	6%	98	+1.2	232/292/386	154	280	19	6	24%	6%	91	+0.7	213/266/351	138	253	20	0	24%	4%	71	-0.3
✕Kelly Stinnett 2006 · MLB	36	47	50	46→40	44	240/301/390	150	294	19	4	25%	7%	95	+1.0	212/264/329	117	271	14	5	26%	6%	67	-1.1	177/219/253	76	229	9	0	27%	5%	31	-1.0
✕Eliezer Alfonzo 2016 · AAA	37	44→54	50→55	44→40	36	230/265/372	142	284	19	5	27%	3%	77	-0.3	254/287/418	164	304	22	7	24%	4%	97	+1.1	269/293/443	174	312	26	3	23%	2%	104	+1.0
✕Ernie Young 2006 · MLB	37	45→50	50→45	44→40	46	229/310/376	147	301	20	8	30%	8%	95	+1.0	220/290/352	132	283	16	5	27%	7%	82	+0.0	208/278/329	121	264	15	1	26%	7%	70	-0.6
✕Cody Ransom 2013 · MLB	37	41→39	54→55	46→50	44	218/288/397	179	295	22	7	33%	8%	92	+0.7	210/282/385	175	288	21	6	33%	9%	87	+0.4	172/236/335	164	217	21	1	32%	8%	59	-0.5
✕Brooks Conrad 2015 · MLB	35	39→43	55	38→50	41	212/266/391	180	271	24	3	32%	7%	82	+0.0	190/250/311	121	256	13	6	30%	6%	57	-1.8	137/201/214	77	188	7	3	30%	6%	15	-2.5
✕Doug Mirabelli 2007 · MLB	36	44	53→50	48→30	46	228/304/398	170	292	21	5	29%	8%	99	+1.2	228/300/390	162	298	20	7	29%	8%	95	+1.0	200/276/357	157	261	24	0	32%	9%	79	-0.0
✕Alex Gonzalez 2013 · MLB	36	47→54	51→55	44→40	43	245/284/408	162	276	20	4	20%	5%	93	+0.8	222/272/344	122	261	13	7	20%	6%	73	-0.6	178/206/231	53	222	5	0	22%	3%	21	-0.9
✕Jonathan Aceves 2015 · AAA	37	40	47→50	46→30	43	208/258/334	126	250	16	4	24%	6%	66	-1.1	227/290/339	112	274	12	4	21%	7%	79	-0.2	228/295/332	104	273	11	1	20%	7%	78	-0.2
✕Erik Kratz 2016 · MLB	36	41→44	51→60	45	46	218/270/380	162	243	19	4	21%	6%	81	-0.1	201/253/323	122	246	14	6	24%	5%	61	-1.5	213/269/346	133	243	17	4	20%	5%	72	-0.3

Kyle Higashioka

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps