Gio Urshela

3B Athletics

Age 35 R/R 6'0" / 215 lbs MLB HR -5% Svc 12.000 · Ctrl thru 2027

Overview

MLBExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2023	31	MLBLAA	228	.299/.333/.374	2	3	100	0.6
2024	32	MLBATL	461	.250/.289/.361	9	0	80	0.5
2025	33	AAA/INTL2 orgs	84	.351/.398/.468	1	0	123	—	.400/.438/.733
2025	33	MLBOAK	197	.238/.289/.326	0	0	64	-0.5
2026	34	No MLB games played
2027PROJ	35	MLBOAK	194	.252/.300/.373	3	2	82	0.0
2028PROJ	36	MLBOAK	144	.239/.285/.346	2	0	71	-0.8

Last 3 seasons WAR 0.6 · Next 2 projected WAR -0.8Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service12.000First FA2028

2027Ext / FA-deal$1M

Skills · percentileStatcast 2023-2025

xwOBA41

Bat Spd25

Avg EV20

Barrel%18

Speed10

CompsMike Matheny (age 35) · Raul Gonzalez (age 35) · Humberto Quintero (age 35)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 8182vR 83

AVG/OBP/SLG.252 / .300 / .373

PA194

HR3

K%20

BB%6

BABIP304

ISO128

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · Contract

ToolsStatcast %ile · 2023-2025

CONTACT

xAVG

590.259

POWER

Barrel%

184.0

Avg EV

2086.8

Bat Spd

2568.6

SPEED

Sprint

1024.2

Platoon Splits2024-2025 · 658 PA

vs LHP

vs RHP

Edge

154

504

—

wRC+

▶▶R

wOBA

230

297

▶▶R

ISO

059

118

▶▶R

BABIP

239

299

▶▶R

19.5%

16.3%

▶▶R

BB%

8.4%

4.4%

◀◀L

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

Status FA

MLB Debut 2015

Service 12.000 yrs.days

Team Control Through 2027

First FA Year 2028

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

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)
2009	17	ROK	AZL Indians	—	236	213	56	10	1	1	17	26	2	5	2	263	323	333	657	70	291	11	7	295	38	—	—	—	—	—	—
2011	19	A	Lake County Captains	—	529	505	120	24	2	9	14	69	4	3	0	238	264	347	610	109	258	13	3	269	42	—	—	—	—	—	—
2012	20	A+	Carolina Mudcats	—	475	438	122	30	1	14	16	61	7	1	1	279	315	447	762	169	291	13	3	327	76	—	—	—	—	—	—
2013	21	AA	Akron Aeros	—	466	445	120	23	2	8	14	48	1	1	1	270	293	384	678	115	286	10	3	298	69	—	—	—	—	—	—
2014	22	AAA	Columbus Clippers	—	430	395	109	27	6	13	30	51	3	0	2	276	332	473	805	197	289	12	7	352	86	—	—	—	—	—	—
2014	22	AA	Akron RubberDucks	—	98	90	27	9	0	5	6	16	1	1	1	300	351	567	917	267	314	16	6	394	112	—	—	—	—	—	—
2014	22	INTL	Aguilas del Zulia	—	118	108	43	2	3	3	5	13	2	0	1	398	435	556	990	157	421	11	4	426	175	—	—	—	—	—	—
2015	23	MLB	Cleveland Indians	—	288	267	60	8	1	6	18	58	2	0	1	225	279	330	608	105	266	20	6	275	72	-10	-0	+6	+1	+6	0.3
2015	23	AAA	Columbus Clippers	—	84	81	22	5	1	3	3	12	0	0	0	272	298	469	767	198	288	14	4	335	78	—	—	—	—	—	—
2016	24	AAA	Columbus Clippers	—	491	468	128	24	1	8	15	58	1	0	0	274	298	380	678	107	294	12	3	298	58	—	—	—	—	—	—
2016	24	INTL	Aguilas del Zulia	—	179	169	57	16	0	3	5	16	1	1	0	337	360	485	845	148	351	9	3	365	133	—	—	—	—	—	—
2017	25	MLB	Cleveland Indians	—	165	156	35	7	0	1	8	22	0	0	0	224	262	288	551	64	256	13	5	249	54	-9	+0	-2	+2	+4	-0.6
2017	25	AAA	Columbus Clippers	—	325	297	79	12	1	6	20	45	5	0	0	266	323	374	697	108	294	14	6	312	68	—	—	—	—	—	—
2018	26	MLB	Toronto Blue Jays	—	46	43	10	1	0	1	2	10	1	0	0	233	283	326	608	93	281	22	4	277	73	-1	+0	-2	+4	+1	0.2
2018	26	AAA	Scranton/Wilkes-Barre RailRiders	—	240	224	64	14	2	2	13	31	1	0	0	286	328	393	721	107	323	13	5	320	65	—	—	—	—	—	—
2018	26	INTL	Tigres del Licey	—	100	96	22	9	0	1	4	12	0	0	0	229	260	354	614	125	253	12	4	273	71	—	—	—	—	—	—
2019	27	MLB	New York Yankees	—	476	442	139	34	0	21	25	87	5	1	1	314	358	534	892	219	349	18	5	388	144	+25	-0	-4	+2	+10	3.3
2020	28	MLB	New York Yankees	—	174	151	45	11	0	6	18	25	1	1	0	298	376	490	867	192	315	14	10	375	138	+8	+0	-0	+1	+4	1.2
2021	29	MLB	New York Yankees	—	442	420	112	18	2	14	20	109	1	1	0	267	302	419	721	152	329	25	5	318	99	-0	+0	-1	+2	+10	1.0
2022	30	MLB	Minnesota Twins	—	551	501	143	27	3	13	41	96	2	1	0	285	342	429	771	144	326	17	7	340	114	+9	+0	-2	+2	+12	2.2
2023	31	MLB	Los Angeles Angels	—	228	214	64	8	1	2	10	36	1	3	2	299	333	374	707	75	346	16	4	315	100	+0	-0	-0	+1	+5	0.6
2024	32	MLB	Atlanta Braves	—	461	432	108	19	1	9	23	72	1	0	0	250	289	361	651	111	278	16	5	289	80	-11	+0	+4	+2	+10	0.5
2025	33	MLB	Athletics	—	197	181	43	14	1	0	13	40	0	0	1	238	289	326	615	88	303	20	7	274	64	-8	-0	-1	+1	+4	-0.5
2025	33	AAA	Las Vegas Aviators	—	16	14	7	2	0	1	2	4	0	0	0	500	562	857	1.420	357	667	25	12	604	178	—	—	—	—	—	—
2025	33	INTL	Leones del Escogido	—	68	63	20	4	0	0	3	12	1	0	0	317	358	381	739	63	385	18	4	330	110	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	3028	2807	759	147	9	73	178	555	14	7	5	270	317	407	724	137	311	18	6	320	103	+10	-1	-2	+17	+66	9.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2009	17	ROK MLE	AZL Indians	—	236	219	46	7	1	1	11	38	2	5	2	210	254	265	519	55	237	16	5	225	38	—	—	—	—	—	—
2011	19	A MLE	Lake County Captains	—	529	510	109	20	2	6	9	95	4	3	0	214	233	296	529	82	247	18	2	230	42	—	—	—	—	—	—
2012	20	A+ MLE	Carolina Mudcats	—	475	444	108	24	1	14	10	90	7	1	1	243	271	396	668	153	257	19	2	281	76	—	—	—	—	—	—
2013	21	AA MLE	Akron Aeros	—	466	449	114	21	2	7	10	60	1	1	1	254	272	356	628	102	274	13	2	270	69	—	—	—	—	—	—
2014	22	AAA MLE	Columbus Clippers	—	430	404	97	22	6	11	21	60	3	0	2	240	283	406	689	166	255	14	5	296	86	—	—	—	—	—	—
2014	22	AA MLE	Akron RubberDucks	—	98	92	25	8	0	5	4	20	1	1	1	272	309	522	831	250	279	20	4	334	112	—	—	—	—	—	—
2015	23	MLB MLE	Cleveland Indians	—	288	267	60	8	1	6	18	58	2	0	1	225	279	330	608	105	266	20	6	275	72	-10	-0	+6	+1	+6	0.3
2015	23	AAA MLE	Columbus Clippers	—	84	82	20	4	1	2	2	14	0	0	0	244	262	390	652	146	273	17	2	283	78	—	—	—	—	—	—
2016	24	AAA MLE	Columbus Clippers	—	491	473	114	19	1	6	10	72	1	0	0	241	258	323	582	82	265	15	2	254	58	—	—	—	—	—	—
2017	25	MLB MLE	Cleveland Indians	—	165	156	35	7	0	1	8	22	0	0	0	224	262	288	551	64	256	13	5	248	54	-9	+0	-2	+2	+4	-0.6
2017	25	AAA MLE	Columbus Clippers	—	325	305	75	10	1	4	12	55	5	0	0	246	286	325	610	79	281	17	4	269	68	—	—	—	—	—	—
2018	26	MLB MLE	Toronto Blue Jays	—	46	43	10	1	0	1	2	10	1	0	0	233	283	326	608	93	281	22	4	276	73	-1	+0	-2	+4	+1	0.2
2018	26	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	240	228	57	12	2	2	9	37	1	0	0	250	282	346	628	96	283	15	4	265	65	—	—	—	—	—	—
2019	27	MLB MLE	New York Yankees	—	476	443	138	34	0	20	24	87	5	1	1	312	354	524	878	212	349	18	5	381	144	+25	-0	-4	+2	+10	3.3
2020	28	MLB MLE	New York Yankees	—	174	151	45	11	0	6	18	25	1	1	0	298	376	490	867	192	315	14	10	371	138	+8	+0	-0	+1	+4	1.2
2021	29	MLB MLE	New York Yankees	—	442	420	111	18	2	13	20	109	1	1	0	264	299	410	709	145	329	25	5	315	99	-0	+0	-1	+2	+10	1.0
2022	30	MLB MLE	Minnesota Twins	—	551	503	143	27	3	13	39	96	2	1	0	284	338	427	766	143	326	17	7	337	114	+9	+0	-2	+2	+12	2.2
2023	31	MLB MLE	Los Angeles Angels	—	228	214	64	8	1	2	10	36	1	3	2	299	333	374	707	75	346	16	4	316	100	+0	-0	-0	+1	+5	0.6
2024	32	MLB MLE	Atlanta Braves	—	461	433	108	19	1	9	22	72	1	0	0	249	287	360	648	111	278	16	5	287	80	-11	+0	+4	+2	+10	0.5
2025	33	MLB MLE	Athletics	—	197	181	42	13	1	0	13	40	0	0	1	232	284	315	598	83	303	20	7	263	64	-8	-0	-1	+1	+4	-0.5
2025	33	AAA MLE	Las Vegas Aviators	—	16	15	6	2	0	1	1	5	0	0	0	400	438	733	1.171	333	519	31	6	432	178	—	—	—	—	—	—
2009	17	ROK MLE	AZL Indians	—	236	219	46	7	1	1	11	38	2	5	2	210	254	265	519	55	246	16	5	225	38	—	—	—	—	—	—
2009	17	ROK RAW	AZL Indians	—	236	213	56	10	1	1	17	26	2	5	2	263	323	333	657	70	291	11	7	295	38	—	—	—	—	—	—
2011	19	A MLE	Lake County Captains	—	529	510	109	20	2	6	9	95	4	3	0	214	233	296	529	82	249	18	2	230	42	—	—	—	—	—	—
2011	19	A RAW	Lake County Captains	—	529	505	120	24	2	9	14	69	4	3	0	238	264	347	610	109	258	13	3	269	42	—	—	—	—	—	—
2012	20	A+ MLE	Carolina Mudcats	—	475	444	108	24	1	14	10	90	7	1	1	243	271	396	668	153	270	19	2	281	76	—	—	—	—	—	—
2012	20	A+ RAW	Carolina Mudcats	—	475	438	122	30	1	14	16	61	7	1	1	279	315	447	762	169	291	13	3	327	76	—	—	—	—	—	—
2013	21	AA MLE	Akron Aeros	—	466	449	114	21	2	7	10	60	1	1	1	254	272	356	628	102	279	13	2	270	69	—	—	—	—	—	—
2013	21	AA RAW	Akron Aeros	—	466	445	120	23	2	8	14	48	1	1	1	270	293	384	678	115	286	10	3	298	69	—	—	—	—	—	—
2014	22	AAA MLE	3 teams	—	646	604	147	36	7	19	30	98	6	1	4	243	286	421	706	177	260	15	5	303	91	—	—	—	—	—	—
2014	22	AAA RAW	3 teams	—	646	593	179	38	9	21	41	80	6	1	4	302	353	503	856	201	318	12	6	372	91	—	—	—	—	—	—
2015	23	MLB MLE	2 teams	—	372	349	79	12	2	8	20	72	2	0	1	226	272	341	613	115	264	19	5	277	73	-12	-0	+6	+1	+8	0.3
2015	23	MLB RAW	2 teams	—	372	348	82	13	2	9	21	70	2	0	1	236	283	362	645	126	271	19	6	288	73	-12	-0	+6	+1	+8	0.3
2016	24	AAA MLE	2 teams	—	670	644	155	26	1	8	13	98	2	1	0	241	258	321	579	81	268	15	2	254	58	—	—	—	—	—	—
2016	24	AAA RAW	2 teams	—	670	637	185	40	1	11	20	74	2	1	0	290	314	408	722	118	310	11	3	316	58	—	—	—	—	—	—
2017	25	AAA MLE	2 teams	—	490	461	110	17	1	5	20	77	5	0	0	239	278	312	590	74	276	16	4	262	63	—	—	—	—	—	—
2017	25	AAA RAW	2 teams	—	490	453	114	19	1	7	28	67	5	0	0	252	302	344	647	93	281	14	6	291	63	—	—	—	—	—	—
2018	26	AAA MLE	3 teams	—	386	368	89	17	2	4	14	64	2	0	0	242	273	332	605	90	282	17	4	267	67	—	—	—	—	—	—
2018	26	AAA RAW	3 teams	—	386	363	96	24	2	4	19	53	2	0	0	264	305	375	679	110	300	14	5	303	67	—	—	—	—	—	—
2019	27	MLB MLE	New York Yankees	—	476	443	138	34	0	20	24	87	5	1	1	312	354	524	878	212	347	18	5	381	144	+25	-0	-4	+2	+10	3.3
2019	27	MLB RAW	New York Yankees	—	476	442	139	34	0	21	25	87	5	1	1	314	358	534	892	219	349	18	5	388	144	+25	-0	-4	+2	+10	3.3
2020	28	MLB MLE	New York Yankees	—	174	151	45	11	0	6	18	25	1	1	0	298	376	490	867	192	315	14	10	371	138	+8	+0	-0	+1	+4	1.2
2020	28	MLB RAW	New York Yankees	—	174	151	45	11	0	6	18	25	1	1	0	298	376	490	867	192	315	14	10	375	138	+8	+0	-0	+1	+4	1.2
2021	29	MLB MLE	New York Yankees	—	442	420	111	18	2	13	20	109	1	1	0	264	299	410	709	145	328	25	5	315	99	-0	+0	-1	+2	+10	1.0
2021	29	MLB RAW	New York Yankees	—	442	420	112	18	2	14	20	109	1	1	0	267	302	419	721	152	329	25	5	318	99	-0	+0	-1	+2	+10	1.0
2022	30	MLB MLE	Minnesota Twins	—	551	503	143	27	3	13	39	96	2	1	0	284	338	427	766	143	324	17	7	337	114	+9	+0	-2	+2	+12	2.2
2022	30	MLB RAW	Minnesota Twins	—	551	501	143	27	3	13	41	96	2	1	0	285	342	429	771	144	326	17	7	340	114	+9	+0	-2	+2	+12	2.2
2023	31	MLB MLE	Los Angeles Angels	—	228	214	64	8	1	2	10	36	1	3	2	299	333	374	707	75	346	16	4	316	100	+0	-0	-0	+1	+5	0.6
2023	31	MLB RAW	Los Angeles Angels	—	228	214	64	8	1	2	10	36	1	3	2	299	333	374	707	75	346	16	4	315	100	+0	-0	-0	+1	+5	0.6
2024	32	MLB MLE	Atlanta Braves	—	461	433	108	19	1	9	22	72	1	0	0	249	287	360	648	111	277	16	5	287	80	-11	+0	+4	+2	+10	0.5
2024	32	MLB RAW	Atlanta Braves	—	461	432	108	19	1	9	23	72	1	0	0	250	289	361	651	111	278	16	5	289	80	-11	+0	+4	+2	+10	0.5
2025	33	MLB MLE	3 teams	—	281	257	62	19	1	1	19	59	1	0	1	241	296	335	631	93	307	21	7	275	72	-9	-0	-1	+1	+6	-0.4
2025	33	MLB RAW	3 teams	—	281	258	70	20	1	1	18	56	1	0	1	271	321	368	690	97	340	20	6	306	72	-9	-0	-1	+1	+6	-0.4
2009	17	ROK MLE	AZL Indians	—	236	221	46	7	1	1	11	38	2	5	2	208	254	262	517	54	237	16	5	225	38	—	—	—	—	—	—
2011	19	A MLE	Lake County Captains	—	529	511	109	20	2	6	9	95	4	3	0	213	233	295	529	82	247	18	2	230	42	—	—	—	—	—	—
2012	20	A+ MLE	Carolina Mudcats	—	475	455	108	24	1	14	10	90	7	1	1	237	271	387	658	149	257	19	2	281	76	—	—	—	—	—	—
2013	21	AA MLE	Akron Aeros	—	466	452	114	21	2	7	10	60	1	1	1	252	272	354	626	102	274	13	2	270	69	—	—	—	—	—	—
2014	22	AAA MLE	3 teams	—	646	605	147	36	7	19	30	98	6	1	4	243	286	420	706	177	259	15	5	303	91	—	—	—	—	—	—
2015	23	MLB MLE	2 teams	—	372	347	79	12	2	8	20	72	2	0	1	228	272	343	615	115	268	19	5	277	73	—	—	—	—	—	—
2016	24	AAA MLE	2 teams	—	670	650	155	26	1	8	13	98	2	1	0	238	258	318	576	80	265	15	2	254	58	—	—	—	—	—	—
2017	25	AAA MLE	2 teams	—	490	462	110	17	1	5	20	77	5	0	0	238	278	312	589	74	272	16	4	262	63	—	—	—	—	—	—
2018	26	AAA MLE	3 teams	—	386	367	89	17	2	4	14	64	2	0	0	243	273	332	606	90	283	17	4	267	67	—	—	—	—	—	—
2019	27	MLB MLE	New York Yankees	—	476	444	138	34	0	20	24	87	5	1	1	311	354	523	876	212	349	18	5	381	144	—	—	—	—	—	—
2020	28	MLB MLE	New York Yankees	—	174	153	45	11	0	6	18	25	1	1	0	294	376	484	860	190	315	14	10	371	138	—	—	—	—	—	—
2021	29	MLB MLE	New York Yankees	—	442	418	111	18	2	13	20	109	1	1	0	266	299	411	711	146	329	25	5	315	99	—	—	—	—	—	—
2022	30	MLB MLE	Minnesota Twins	—	551	505	143	27	3	13	39	96	2	1	0	283	338	426	764	143	326	17	7	337	114	—	—	—	—	—	—
2023	31	MLB MLE	Los Angeles Angels	—	228	215	64	8	1	2	10	36	1	3	2	298	333	372	705	74	346	16	4	316	100	—	—	—	—	—	—
2024	32	MLB MLE	Atlanta Braves	—	461	435	108	19	1	9	22	72	1	0	0	248	287	359	646	110	278	16	5	287	80	—	—	—	—	—	—
2025	33	MLB MLE	3 teams	—	281	259	62	19	1	1	19	59	1	0	1	239	296	332	628	93	319	21	7	275	72	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	32	MLB MLE	Atlanta Braves	—	461	435	108	19	1	9	22	72	1	0	0	248	287	359	646	110	278	16	5	287	80	—	—	—	—	—	—
2025	33	MLB MLE	3 teams	—	281	259	62	19	1	1	19	59	1	0	1	239	296	332	628	93	319	21	7	275	72	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	35	MLB MLE	OAK	100%	303	281	68	16	1	4	18	61	1	2	1	244	292	359	651	115	293	20	6	290	82	-6	+0	-1	+1	+7	0.0
▸ 2027 — real world (MLB)
2027	35	MLB CTX	OAK	100%	194	179	46	12	1	3	12	39	1	2	1	252	300	373	673	121	304	20	6	299	82	-4	+0	-0	+1	+4	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	36	MLB MLE	OAK	100%	144	135	32	7	1	2	8	30	0	0	0	231	278	332	610	101	283	21	6	273	71	-5	+0	-7	+1	+3	-0.8
2028	36	MLB CTX	OAK	100%	144	135	33	8	1	2	8	30	0	0	0	239	285	346	631	107	293	21	6	282	71	-5	+0	-7	+1	+3	-0.8
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3172	2942	792	155	10	75	186	585	14	7	5	269	316	405	721	136	311	18	6	318	81	+5	-1	-9	+17	+69	8.3
/ 162G	—	A+C		—	650	603	162	32	2	15	38	120	3	1	1	269	315	403	718	134	311	18	6	318	81	+1	-0	-2	+3	+14	1.7
Career	—	MLE		—	7221	6783	1704	333	29	141	309	1245	44	21	14	251	288	371	659	120	286	17	4	288	81	+1	-1	-9	+18	+73	8.4
/ 162G	—	MLE		—	650	611	154	30	3	13	28	112	4	2	1	252	290	375	665	123	287	17	4	288	81	+0	-0	-2	+3	+14	1.6

How the minor-league lines were translated

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

2025 AAALas Vegas Aviators · 16 PAwOBA .587 → .432 (−155)K% 25.0% → 29.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷1.027	×1.200	—	—	29.22%
BB% (unintentional) /PA	12.50%	÷0.970	×0.690	—	×0.940	8.35%
HBP% /PA	0.00%	—	×0.940	—	×0.940	0.00%
Singles /BIP	40.00%	÷1.052	×0.930	—	×0.940	33.23%
Doubles /BIP	20.00%	÷0.988	×0.830	—	×0.940	15.79%
Triples /BIP	0.00%	÷1.000	×0.970	—	×0.940	0.00%
Home runs /BIP	10.00%	÷1.183	×0.700	—	×0.940	5.56%

Factors used: league row International League. Park (home-season share, regressed): HR 137, 1B 110, 2B 98, 3B 100, K 105, BB 94 — applied at half strength. Age: age 34 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (6.8 yr older than average).

Result: wOBA .587 → .432; ISO .357 → .232; BABIP .667 → .519. 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 · 240 PAwOBA .313 → .265 (−48)K% 12.9% → 15.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.92%	÷1.002	×1.200	—	—	15.48%
BB% (unintentional) /PA	5.42%	÷1.034	×0.690	—	×1.003	3.62%
HBP% /PA	0.42%	—	×0.940	—	×1.003	0.39%
Singles /BIP	23.83%	÷1.032	×0.930	×0.991	×1.003	21.35%
Doubles /BIP	7.25%	÷1.004	×0.830	×0.991	×1.003	5.96%
Triples /BIP	1.04%	÷1.130	×0.970	×0.991	×1.003	0.88%
Home runs /BIP	1.04%	÷1.046	×0.840	—	×1.003	0.83%

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 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 ×0.991.

Result: wOBA .313 → .265; ISO .107 → .088; BABIP .323 → .283. 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 AAAColumbus Clippers · 325 PAwOBA .305 → .269 (−35)K% 13.8% → 16.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.85%	÷0.989	×1.200	—	—	16.80%
BB% (unintentional) /PA	5.85%	÷1.089	×0.690	—	×1.018	3.77%
HBP% /PA	1.54%	—	×0.940	—	×1.018	1.47%
Singles /BIP	23.81%	÷0.945	×0.930	×0.987	×1.018	23.53%
Doubles /BIP	4.76%	÷1.018	×0.830	×0.987	×1.018	3.90%
Triples /BIP	0.40%	÷0.900	×0.970	×0.987	×1.018	0.43%
Home runs /BIP	2.38%	÷1.231	×0.840	—	×1.018	1.65%

Factors used: league row IL. Park (home-season share, regressed): HR 146, 1B 89, 2B 104, 3B 80, K 98, BB 118 — 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 ×0.987.

Result: wOBA .305 → .269; ISO .108 → .083; BABIP .294 → .281. 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 AAAColumbus Clippers · 491 PAwOBA .293 → .254 (−40)K% 11.8% → 14.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.81%	÷0.965	×1.200	—	—	14.68%
BB% (unintentional) /PA	3.05%	÷1.077	×0.690	—	×1.033	2.02%
HBP% /PA	0.20%	—	×0.940	—	×1.033	0.20%
Singles /BIP	23.17%	÷1.018	×0.930	×0.983	×1.033	21.51%
Doubles /BIP	5.85%	÷1.043	×0.830	×0.983	×1.033	4.73%
Triples /BIP	0.24%	÷0.901	×0.970	×0.983	×1.033	0.27%
Home runs /BIP	1.95%	÷1.113	×0.840	—	×1.033	1.52%

Factors used: league row IL. Park (home-season share, regressed): HR 123, 1B 104, 2B 109, 3B 80, K 93, 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 ×0.983.

Result: wOBA .293 → .254; ISO .107 → .086; BABIP .294 → .265. 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 AAAColumbus Clippers · 84 PAwOBA .325 → .283 (−43)K% 14.3% → 17.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.29%	÷1.009	×1.200	—	—	16.98%
BB% (unintentional) /PA	3.57%	÷1.068	×0.690	—	×1.048	2.42%
HBP% /PA	0.00%	—	×0.940	—	×1.048	0.00%
Singles /BIP	18.84%	÷1.005	×0.930	×1.013	×1.048	18.52%
Doubles /BIP	7.25%	÷1.019	×0.830	×1.013	×1.048	6.27%
Triples /BIP	1.45%	÷0.900	×0.970	×1.013	×1.048	1.66%
Home runs /BIP	4.35%	÷1.217	×0.840	—	×1.048	3.14%

Factors used: league row IL. Park (home-season share, regressed): HR 143, 1B 101, 2B 104, 3B 80, K 102, BB 114 — 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 ×1.013.

Result: wOBA .325 → .283; ISO .198 → .159; BABIP .288 → .273. 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 AAAColumbus Clippers · 430 PAwOBA .343 → .296 (−47)K% 11.9% → 14.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.86%	÷1.016	×1.200	—	—	14.00%
BB% (unintentional) /PA	6.74%	÷1.015	×0.690	—	×1.050	4.81%
HBP% /PA	0.70%	—	×0.940	—	×1.050	0.69%
Singles /BIP	18.31%	÷1.034	×0.930	×0.968	×1.050	16.76%
Doubles /BIP	7.85%	÷1.047	×0.830	×0.968	×1.050	6.33%
Triples /BIP	1.74%	÷1.007	×0.970	×0.968	×1.050	1.71%
Home runs /BIP	3.78%	÷1.028	×0.840	—	×1.050	3.24%

Factors used: league row IL. Park (home-season share, regressed): HR 106, 1B 107, 2B 109, 3B 102, K 103, BB 103 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.968.

Result: wOBA .343 → .296; ISO .197 → .171; BABIP .289 → .255. 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 AAAkron RubberDucks · 98 PAwOBA .384 → .334 (−49)K% 16.3% → 20.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.33%	÷0.965	×1.220	—	—	20.64%
BB% (unintentional) /PA	5.10%	÷1.008	×0.700	—	×1.027	3.64%
HBP% /PA	1.02%	—	×0.850	—	×1.027	0.89%
Singles /BIP	17.57%	÷1.064	×0.970	×0.974	×1.027	16.02%
Doubles /BIP	12.16%	÷0.992	×0.860	×0.974	×1.027	10.55%
Triples /BIP	0.00%	÷0.900	×0.950	×0.974	×1.027	0.00%
Home runs /BIP	6.76%	÷0.881	×0.780	—	×1.027	6.15%

Factors used: league row EL. Park (home-season share, regressed): HR 76, 1B 113, 2B 98, 3B 80, K 93, BB 102 — applied at half strength. Age: age 23 vs a level average of 24.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.974.

Result: wOBA .384 → .334; ISO .267 → .236; BABIP .314 → .279. 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 AAAkron Aeros · 466 PAwOBA .290 → .270 (−21)K% 10.3% → 12.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.30%	÷0.984	×1.220	—	—	12.77%
BB% (unintentional) /PA	3.00%	÷1.029	×0.700	—	×1.042	2.13%
HBP% /PA	0.21%	—	×0.850	—	×1.042	0.19%
Singles /BIP	21.91%	÷1.037	×0.970	×0.999	×1.042	21.34%
Doubles /BIP	5.79%	÷1.001	×0.860	×0.999	×1.042	5.19%
Triples /BIP	0.50%	÷1.049	×0.950	×0.999	×1.042	0.47%
Home runs /BIP	2.02%	÷0.879	×0.780	—	×1.042	1.86%

Factors used: league row EL. Park (home-season share, regressed): HR 76, 1B 107, 2B 100, 3B 110, K 97, BB 106 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.999.

Result: wOBA .290 → .270; ISO .115 → .104; BABIP .286 → .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).

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
#1Sean Berry'90-'00 * career totals — 10 seasons, 2,691 PA	4.1	2,691	81	47	261*	322*	441*	+4	-4	10.4	11.9
/162	664	20	12	+0.9	-0.9	2.6	pk7: 13
#2Aledmys Díazlast yr '23 career totals — 8 seasons, 2,509 PA	3.8	2,509	78	15	261	314	429	+10	+7	10.8	10.8
/162	664	21	4	+2.7	+1.8	2.9	pk7: 11
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 11 projected seasons	5.0	3,320	77	9	268	311	403	+9	+2	10.0	10.4
/162	664	15	2	+1.8	+0.5	2.0	pk7: 11
#3Danny Valencialast yr '18 career totals — 9 seasons, 3,222 PA	4.9	3,222	96	11	268	317	426	+1	-16	9.7	10.2
/162	664	20	2	+0.2	-3.2	2.0	pk7: 11
#4Lonnie Chisenhalllast yr '18 career totals — 8 seasons, 2,360 PA	3.6	2,360	64	20	268	320	427	-3	-9	8.0	7.9
/162	664	18	6	-0.8	-2.6	2.3	pk7: 8
#5Jeff Treadway'87-'95 * career totals — 9 seasons, 2,318 PA	3.5	2,318	28	14	280*	327*	411*	+8	+8	7.3	7.7
/162	664	8	4	+2.2	+2.2	2.1	pk7: 8
#6Bill Stein'72-'85 * career totals — 12 seasons, 3,067 PA	4.6	3,067	44	16	263*	314*	398*	-0	-9	5.2	5.2
/162	664	10	3	-0.0	-2.0	1.1	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
Gio Urshela (OGILVIE)	35	—	—	—	—	242/290/356	114	293	3	2	20%	6%	82	+0.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Mike Matheny 2006 · MLB	35	48→52	46→45	35→30	43	237/277/370	133	273	13	2	19%	5%	81	-0.1	234/282/372	138	269	14	5	19%	5%	83	+0.1	220/260/321	101	252	10	0	17%	4%	63	-0.4
✕Raul Gonzalez 2009 · AAA	35	51→58	41→45	37→50	48	245/296/347	102	279	9	5	16%	6%	82	-0.0	266/326/384	118	304	12	13	16%	7%	102	+1.5	293/358/411	118	331	12	16	15%	8%	116	+1.0
✕Humberto Quintero 2015 · MLB	35	47	44→45	41→40	38	233/263/350	118	284	11	5	22%	3%	70	-0.8	225/257/325	100	280	10	7	23%	3%	63	-1.4	220/242/296	76	267	11	3	22%	2%	47	-1.3
✕Dave Berg 2005 · MLB	34	51→56	44→45	38→40	46	251/296/365	114	286	12	3	17%	5%	86	+0.3	241/299/330	89	285	7	4	17%	7%	79	-0.2	248/310/317	69	295	3	1	16%	8%	81	-0.0
✕Issmael Salas 2017 · AAA	35	48	42→45	42→50	44	236/275/342	107	266	10	7	16%	4%	73	-0.6	233/279/343	110	256	11	6	14%	5%	75	-0.5	231/277/333	102	249	11	3	12%	5%	71	-0.5
✕Bobby Wilson 2017 · MLB	34	43→52	43→50	40	42	215/261/312	98	267	12	3	24%	6%	61	-1.5	196/250/316	120	245	15	3	26%	6%	59	-1.7	167/222/277	110	205	14	0	26%	6%	39	-1.1
✕Noe Mata 2009 · AAA	35	54→57	44→45	42→50	42	264/293/377	113	299	12	9	17%	3%	88	+0.4	221/253/313	92	270	9	8	21%	3%	58	-1.7	187/212/248	61	235	5	5	23%	2%	24	-1.5
✕Clint Barmes 2014 · MLB	35	44→54	44→55	40→50	42	222/265/332	110	262	12	3	21%	5%	68	-1.0	221/268/328	107	269	9	4	21%	5%	68	-1.0	212/261/306	94	262	6	1	21%	4%	60	-0.4
✕Hector Garanzuay 2016 · AAA	35	52→61	39→45	37→50	47	251/295/335	84	282	7	5	14%	5%	79	-0.2	238/289/331	93	273	8	7	16%	6%	76	-0.4	225/283/291	66	250	7	5	12%	7%	65	-0.4
✕Sergio Gastelum 2014 · AAA	35	53→63	39→40	38→50	47	251/305/341	90	288	6	4	15%	5%	84	+0.2	243/294/316	73	277	4	9	13%	5%	74	-0.5	238/290/292	53	270	2	7	12%	5%	65	-0.6
✕Adan Amezcua 2009 · AAA	35	51	41→45	41→45	48	247/303/348	101	282	8	7	16%	6%	85	+0.2	238/291/334	96	279	8	7	17%	6%	77	-0.3	244/310/369	125	285	12	4	18%	7%	91	+0.3
✕Jamie Burke 2008 · MLB	36	49→45	43→45	40→30	46	237/286/347	110	262	10	3	15%	5%	79	-0.2	225/275/317	92	264	8	5	17%	5%	68	-1.0	203/251/265	62	245	4	1	18%	5%	46	-0.6
✕Denny Hocking 2005 · MLB	35	47→57	40	38→45	50	227/286/320	93	267	7	4	18%	8%	72	-0.7	235/295/318	83	293	5	6	20%	8%	75	-0.5	242/300/293	51	310	0	2	20%	8%	70	-0.5
✕Lou Merloni 2007 · MLB	36	48→44	42→45	40	46	234/291/341	107	271	9	4	17%	6%	79	-0.2	215/270/303	88	250	7	5	16%	6%	63	-1.4	201/254/264	63	234	3	1	15%	6%	45	-2.0
✕Yorvit Torrealba 2013 · MLB	35	52→55	44→50	41→45	49	253/306/368	115	292	11	5	18%	7%	91	+0.7	235/291/334	99	270	9	6	16%	7%	78	-0.3	226/274/268	42	260	0	0	12%	6%	56	-0.6
✕Rolando Acosta 2017 · AAA	34	45→55	40→50	40→45	47	217/280/305	89	251	8	7	17%	6%	68	-1.0	215/269/303	88	257	8	7	19%	5%	63	-1.4	210/248/269	59	251	6	2	19%	3%	44	-0.8
✕Carlos Valencia 2014 · AAA	34	45→55	47→55	38→40	39	229/257/368	139	264	15	4	20%	3%	73	-0.6	206/239/320	114	240	14	4	21%	4%	55	-2.0	195/227/283	87	234	12	3	22%	4%	41	-1.6
✕John Flaherty 2003 · MLB	35	51→52	44→45	43→40	46	248/285/368	121	276	11	4	15%	5%	83	+0.1	237/276/388	151	265	16	5	18%	5%	84	+0.2	217/247/372	155	236	19	0	18%	3%	71	-0.2
✕Humberto Cota 2013 · AAA	34	52	43→50	38→30	50	254/318/362	108	310	11	4	21%	8%	94	+0.9	214/279/325	111	274	13	5	26%	7%	72	-0.7	186/255/292	106	235	14	1	26%	8%	55	-0.8
✕Ed Lucas 2016 · MLB	34	52→55	38→45	42→50	44	246/296/322	76	317	6	5	24%	6%	76	-0.4	207/260/298	91	278	7	6	27%	6%	57	-1.8	169/219/247	78	231	5	1	28%	6%	28	-2.6

Gio Urshela

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps