Thairo Estrada

2B Navegantes del Magallanes

Age 31 R/R 5'10" / 185 lbs INTL HR +30%H +12% Svc 8.000 · Ctrl thru 2027

Overview

INTLExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	28	AAASF	83	.333/.390/.493	3	1	114	—	.312/.354/.429
2024	28	MLBSF	381	.217/.248/.343	9	2	67	0.2
2025	29	MLBCOL	165	.253/.290/.370	3	1	75	-0.2
2026	30	INTLNavegantes de…	38	.333/.474/.533	0	1	190	—
2027PROJMLE	31	MLBCOL	334	.244/.282/.368	7	4	81	0.3
2028PROJ	32	MLBCOL	205	.249/.286/.380	5	1	75	-0.3

Last 3 seasons WAR -0.0 · Next 2 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service8.000First FA2028

2027Ext / FA-deal$2M

Skills · percentileStatcast 2023-2025

Speed58

Bat Spd54

xwOBA25

Barrel%22

Avg EV10

CompsJosh Wilson (age 31) · Jake Noll (age 29) · Seth Mejias-Brean (age 30)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 223 proj PA

wRC+†vL 8483vR 80

AVG/OBP/SLG.242 / .280 / .365

PA223

HR5

K%19

BB%4

ISO125

MLB%0%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · ContractCON 45 / POW 40

Toolsscout grade · Statcast %ile · 2023-2025

CONTACT45

xAVG

320.236

POWER40

Barrel%

224.5

Avg EV

1086.1

Bat Spd

5471.8

EYE35

scouting grade only

SPEED55

Sprint

5827.8

Platoon Splits2024-2025 · 546 PA

vs LHP

vs RHP

Edge

133

413

—

wRC+

▶▶R

wOBA

237

278

▶R

ISO

115

126

▶R

BABIP

202

277

▶▶R

17.3%

19.1%

◀L

BB%

5.3%

2.2%

◀◀L

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

Status FA

MLB Debut 2019

Service 8.000 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$2M	—	—	—
Totals		$2M		$0.0M	-$2M

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	17	ROK	GCL Yankees2	—	199	176	49	11	5	2	12	30	8	7	5	278	352	432	784	153	324	15	6	345	61	—	—	—	—	—	—
2014	18	ROK	GCL Yankees1	—	23	22	6	2	0	0	1	4	0	0	0	273	304	364	668	91	333	17	4	299	29	—	—	—	—	—	—
2016	20	A+	Tampa Yankees	—	351	315	92	15	1	3	29	46	3	7	5	292	357	375	732	83	332	13	8	329	91	—	—	—	—	—	—
2016	20	A	Charleston RiverDogs	—	148	140	40	3	1	5	8	21	0	11	3	286	324	429	753	143	307	14	5	335	82	—	—	—	—	—	—
2017	21	AA	Trenton Thunder	—	542	495	149	19	4	6	34	56	8	8	11	301	356	392	748	91	327	10	6	335	105	—	—	—	—	—	—
2017	21	INTL	Scottsdale Scorpions	—	84	79	27	2	1	1	3	19	2	3	1	342	381	430	811	89	441	23	4	365	133	—	—	—	—	—	—
2018	22	AAA	Scranton/Wilkes-Barre RailRiders	—	34	33	5	1	0	0	0	8	1	0	0	152	176	182	358	30	200	24	0	166	-17	—	—	—	—	—	—
2018	22	A+	Tampa Tarpons	—	47	45	10	2	0	0	0	9	1	0	0	222	239	267	506	44	270	19	0	224	22	—	—	—	—	—	—
2018	22	INTL	Glendale Desert Dogs	—	86	80	19	2	0	0	4	15	1	0	1	237	282	263	545	25	292	17	5	250	55	—	—	—	—	—	—
2019	23	MLB	New York Yankees	—	69	64	16	3	0	3	3	15	1	4	0	250	294	438	732	188	283	22	4	318	98	-0	+1	+1	+1	+1	0.4
2019	23	AAA	Scranton/Wilkes-Barre RailRiders	—	259	241	64	17	2	8	14	50	3	3	1	266	314	452	766	187	304	19	5	337	72	—	—	—	—	—	—
2020	24	MLB	New York Yankees	—	52	48	8	0	0	1	1	19	3	1	0	167	231	229	460	62	250	37	2	218	32	-4	+0	-0	+0	+1	-0.3
2021	25	MLB	San Francisco Giants	—	132	121	33	4	0	7	9	23	2	1	0	273	333	479	813	207	286	17	7	359	133	+5	+0	+3	+4	+3	1.5
2021	25	AAA	Sacramento River Cats	—	233	210	70	14	1	9	20	35	3	6	4	333	399	538	937	205	367	15	9	412	128	—	—	—	—	—	—
2022	26	MLB	San Francisco Giants	—	541	488	127	22	2	14	33	89	14	21	6	260	325	400	725	139	290	16	6	322	109	+6	+2	+2	+2	+12	2.3
2023	27	MLB	San Francisco Giants	—	530	495	134	26	2	14	22	120	11	23	7	271	316	416	732	145	331	23	4	325	110	+6	+2	+15	+2	+11	3.7
2024	28	MLB	San Francisco Giants	—	381	364	79	15	2	9	10	76	5	2	2	217	248	343	591	126	249	20	3	262	67	-15	-0	+7	+2	+8	0.2
2024	28	AAA	Sacramento River Cats	—	83	75	25	3	0	3	5	14	2	1	0	333	390	493	884	160	379	17	6	389	114	—	—	—	—	—	—
2025	29	MLB	Colorado Rockies	—	165	154	39	9	0	3	6	26	2	1	3	253	290	370	660	117	281	16	4	290	75	-5	-1	-1	+1	+4	-0.2
2025	29	AAA	Albuquerque Isotopes	—	24	23	7	1	0	0	1	5	0	0	0	304	333	348	681	43	389	21	4	309	48	—	—	—	—	—	—
2026	30	INTL	Navegantes del Magallanes	—	38	30	10	4	1	0	2	6	6	1	0	333	474	533	1.007	200	417	16	5	450	190	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1870	1734	436	79	6	51	84	368	38	53	18	251	301	392	693	141	290	20	4	308	94	-13	+3	+26	+11	+41	7.0
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2013	17	ROK MLE	GCL Yankees2	—	199	180	40	8	4	2	8	43	8	7	5	222	286	344	630	122	264	22	4	258	61	—	—	—	—	—	—
2014	18	ROK MLE	GCL Yankees1	—	23	22	4	1	0	0	1	6	0	0	0	182	217	227	445	45	268	26	4	211	29	—	—	—	—	—	—
2016	20	A+ MLE	Tampa Yankees	—	351	322	89	16	1	3	22	66	3	7	5	276	329	360	689	84	333	19	6	303	91	—	—	—	—	—	—
2016	20	A MLE	Charleston RiverDogs	—	148	143	37	2	1	5	5	28	0	11	3	259	284	392	675	133	292	19	3	289	82	—	—	—	—	—	—
2017	21	AA MLE	Trenton Thunder	—	542	504	155	19	4	5	25	68	8	8	11	308	350	391	741	83	340	13	5	324	105	—	—	—	—	—	—
2018	22	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	34	33	5	1	0	0	0	10	1	0	0	152	176	182	358	30	186	29	0	143	-17	—	—	—	—	—	—
2018	22	A+ MLE	Tampa Tarpons	—	47	45	9	2	0	0	0	13	1	0	0	200	217	244	462	44	259	28	0	201	22	—	—	—	—	—	—
2019	23	MLB MLE	New York Yankees	—	69	64	16	3	0	3	3	15	1	4	0	250	294	438	732	188	283	22	4	313	98	-0	+1	+1	+1	+1	0.4
2019	23	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	259	245	55	14	2	6	10	60	3	3	1	224	264	371	635	147	268	23	4	274	72	—	—	—	—	—	—
2020	24	MLB MLE	New York Yankees	—	52	48	8	0	0	1	1	19	3	1	0	167	231	229	460	62	250	37	2	215	32	-4	+0	-0	+0	+1	-0.3
2021	25	MLB MLE	San Francisco Giants	—	132	122	34	4	0	8	8	23	2	1	0	279	333	508	842	230	286	17	6	365	133	+5	+0	+3	+4	+3	1.5
2021	25	AAA MLE	Sacramento River Cats	—	233	215	66	14	1	7	15	41	3	6	4	307	361	479	840	172	351	18	6	357	128	—	—	—	—	—	—
2022	26	MLB MLE	San Francisco Giants	—	541	488	129	22	2	15	33	89	14	21	6	264	329	410	739	145	290	16	6	329	109	+6	+2	+2	+2	+12	2.3
2023	27	MLB MLE	San Francisco Giants	—	530	496	136	26	2	15	21	120	11	23	7	274	318	425	744	151	331	23	4	331	110	+6	+2	+15	+2	+11	3.7
2024	28	MLB MLE	San Francisco Giants	—	381	364	81	15	2	10	10	76	5	2	2	223	253	357	610	135	249	20	3	268	67	-15	-0	+7	+2	+8	0.2
2024	28	AAA MLE	Sacramento River Cats	—	83	77	24	3	0	2	3	16	2	1	0	312	354	429	782	117	362	19	4	336	114	—	—	—	—	—	—
2025	29	MLB MLE	Colorado Rockies	—	165	154	38	9	0	3	6	26	2	1	3	247	284	364	648	117	281	16	4	280	75	-5	-1	-1	+1	+4	-0.2
2025	29	AAA MLE	Albuquerque Isotopes	—	24	23	6	1	0	0	1	6	0	0	0	261	292	304	596	43	335	25	4	239	48	—	—	—	—	—	—
2013	17	ROK MLE	GCL Yankees2	—	199	180	40	8	4	2	8	43	8	7	5	222	286	344	630	122	279	22	4	258	61	—	—	—	—	—	—
2013	17	ROK RAW	GCL Yankees2	—	199	176	49	11	5	2	12	30	8	7	5	278	352	432	784	153	324	15	6	345	61	—	—	—	—	—	—
2014	18	ROK MLE	GCL Yankees1	—	23	22	4	1	0	0	1	6	0	0	0	182	217	227	445	45	250	26	4	211	29	—	—	—	—	—	—
2014	18	ROK RAW	GCL Yankees1	—	23	22	6	2	0	0	1	4	0	0	0	273	304	364	668	91	333	17	4	299	29	—	—	—	—	—	—
2016	20	A+ MLE	2 teams	—	499	464	126	18	2	8	28	94	3	18	8	272	317	371	688	99	324	19	6	299	88	—	—	—	—	—	—
2016	20	A+ RAW	2 teams	—	499	455	132	18	2	8	37	67	3	18	8	290	347	391	739	101	325	13	7	331	88	—	—	—	—	—	—
2017	21	AA MLE	2 teams	—	626	582	178	22	4	6	29	78	10	11	12	306	349	388	738	82	343	12	5	324	105	—	—	—	—	—	—
2017	21	AA RAW	2 teams	—	626	574	176	21	5	7	37	75	10	11	12	307	359	397	756	91	341	12	6	339	105	—	—	—	—	—	—
2018	22	INTL MLE	3 teams	—	167	162	27	6	0	0	0	46	3	0	1	167	182	204	386	37	231	28	0	177	6	—	—	—	—	—	—
2018	22	INTL RAW	3 teams	—	167	158	34	5	0	0	4	32	3	0	1	215	248	247	495	32	268	19	2	226	6	—	—	—	—	—	—
2019	23	AAA MLE	2 teams	—	328	309	71	17	2	9	13	75	4	7	1	230	270	385	655	155	274	23	4	282	77	—	—	—	—	—	—
2019	23	AAA RAW	2 teams	—	328	305	80	20	2	11	17	65	4	7	1	262	310	449	759	187	300	20	5	333	77	—	—	—	—	—	—
2020	24	MLB MLE	New York Yankees	—	52	48	8	0	0	1	1	19	3	1	0	167	231	229	460	62	250	37	2	215	32	-4	+0	-0	+0	+1	-0.3
2020	24	MLB RAW	New York Yankees	—	52	48	8	0	0	1	1	19	3	1	0	167	231	229	460	62	250	37	2	218	32	-4	+0	-0	+0	+1	-0.3
2021	25	AAA MLE	2 teams	—	365	337	99	18	1	14	23	64	5	7	4	294	348	478	826	184	328	18	6	360	130	—	—	—	—	—	—
2021	25	AAA RAW	2 teams	—	365	331	103	18	1	16	29	58	5	7	4	311	375	517	892	205	339	16	8	393	130	—	—	—	—	—	—
2022	26	MLB MLE	San Francisco Giants	—	541	488	129	22	2	15	33	89	14	21	6	264	329	410	739	145	293	16	6	329	109	+6	+2	+2	+2	+12	2.3
2022	26	MLB RAW	San Francisco Giants	—	541	488	127	22	2	14	33	89	14	21	6	260	325	400	725	139	290	16	6	322	109	+6	+2	+2	+2	+12	2.3
2023	27	MLB MLE	San Francisco Giants	—	530	496	136	26	2	15	21	120	11	23	7	274	318	425	744	151	333	23	4	331	110	+6	+2	+15	+2	+11	3.7
2023	27	MLB RAW	San Francisco Giants	—	530	495	134	26	2	14	22	120	11	23	7	271	316	416	732	145	331	23	4	325	110	+6	+2	+15	+2	+11	3.7
2024	28	MLB MLE	2 teams	—	464	441	104	17	2	12	13	92	7	3	2	236	269	365	634	129	271	20	3	280	76	-13	-0	+7	+2	+10	0.5
2024	28	MLB RAW	2 teams	—	464	439	104	18	2	12	15	90	7	3	2	237	273	369	642	132	271	19	3	285	76	-13	-0	+7	+2	+10	0.5
2025	29	MLB MLE	2 teams	—	189	177	43	9	0	3	7	32	2	1	3	243	280	345	624	102	276	17	4	274	72	-6	-1	-1	+1	+4	-0.3
2025	29	MLB RAW	2 teams	—	189	177	46	10	0	3	7	31	2	1	3	260	296	367	663	107	295	16	4	293	72	-6	-1	-1	+1	+4	-0.3
2026	30	INTL MLE	Navegantes del Magallanes	—	38	30	10	4	1	0	2	6	6	1	0	333	474	533	1.007	200	417	16	5	—	—	—	—	—	—	—	—
2026	30	INTL RAW	Navegantes del Magallanes	—	38	30	10	4	1	0	2	6	6	1	0	333	474	533	1.007	200	417	16	5	450	190	—	—	—	—	—	—
2013	17	ROK MLE	GCL Yankees2	—	199	181	40	8	4	2	8	43	8	7	5	221	286	343	628	122	264	22	4	258	61	—	—	—	—	—	—
2014	18	ROK MLE	GCL Yankees1	—	23	22	4	1	0	0	1	6	0	0	0	182	217	227	445	45	268	26	4	211	29	—	—	—	—	—	—
2016	20	A+ MLE	2 teams	—	499	465	126	18	2	8	28	94	3	18	8	271	317	370	687	99	321	19	6	299	88	—	—	—	—	—	—
2017	21	AA MLE	2 teams	—	626	582	178	22	4	6	29	78	10	11	12	306	349	388	738	82	340	12	5	324	105	—	—	—	—	—	—
2018	22	INTL MLE	3 teams	—	167	162	27	6	0	0	0	46	3	0	1	167	182	204	386	37	228	28	0	177	6	—	—	—	—	—	—
2019	23	AAA MLE	2 teams	—	328	308	71	17	2	9	13	75	4	7	1	231	270	386	656	156	271	23	4	282	77	—	—	—	—	—	—
2020	24	MLB MLE	New York Yankees	—	52	48	8	0	0	1	1	19	3	1	0	167	231	229	460	62	250	37	2	215	32	—	—	—	—	—	—
2021	25	AAA MLE	2 teams	—	365	334	99	18	1	14	23	64	5	7	4	296	348	482	830	186	327	18	6	360	130	—	—	—	—	—	—
2022	26	MLB MLE	San Francisco Giants	—	541	489	129	22	2	15	33	89	14	21	6	264	329	409	738	145	290	16	6	329	109	—	—	—	—	—	—
2023	27	MLB MLE	San Francisco Giants	—	530	493	136	26	2	15	21	120	11	23	7	276	318	428	746	152	331	23	4	331	110	—	—	—	—	—	—
2024	28	MLB MLE	2 teams	—	464	441	104	17	2	12	13	92	7	3	2	236	269	365	634	129	269	20	3	280	76	—	—	—	—	—	—
2025	29	MLB MLE	2 teams	—	189	178	43	9	0	3	7	32	2	1	3	242	280	343	622	101	288	17	4	274	72	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	28	MLB MLE	2 teams	—	464	441	104	17	2	12	13	92	7	3	2	236	269	365	634	129	269	20	3	280	76	—	—	—	—	—	—
2025	29	MLB MLE	2 teams	—	189	178	43	9	0	3	7	32	2	1	3	242	280	343	622	101	288	17	4	274	72	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	31	MLB MLE	COL	0%	334	314	76	14	1	7	13	65	4	4	1	244	282	368	650	125	283	19	4	288	81	-7	+0	+3	+1	+7	0.3
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	32	MLB MLE	COL	100%	205	194	46	8	1	4	7	41	2	1	0	238	275	355	630	117	278	20	3	280	75	-6	+0	-2	+1	+4	-0.3
2028	32	MLB CTX	COL	100%	205	194	49	9	1	5	7	41	2	1	0	249	286	380	665	130	290	20	3	294	75	-6	+0	-2	+1	+4	-0.3
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2075	1928	485	88	7	56	91	409	40	54	18	252	299	392	691	140	291	20	4	306	88	-19	+4	+24	+12	+45	6.7
/ 162G	—	A+C		—	650	604	153	28	2	18	29	128	13	17	6	253	302	396	698	142	292	20	4	306	88	-6	+1	+7	+4	+14	2.1
Career	—	MLE		—	4449	4140	1072	185	22	94	194	848	81	104	50	259	305	382	687	123	304	19	4	299	88	-24	+4	+26	+13	+50	7.0
/ 162G	—	MLE		—	650	605	157	27	3	14	28	124	12	15	7	260	305	383	689	124	304	19	4	299	88	-7	+1	+7	+4	+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.

2025 AAAAlbuquerque Isotopes · 24 PAwOBA .301 → .239 (−62)K% 20.8% → 26.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.83%	÷0.945	×1.200	—	—	26.46%
BB% (unintentional) /PA	4.17%	÷1.019	×0.690	—	×0.982	2.77%
HBP% /PA	0.00%	—	×0.940	—	×0.982	0.00%
Singles /BIP	33.33%	÷1.047	×0.930	—	×0.982	29.07%
Doubles /BIP	5.56%	÷1.029	×0.830	—	×0.982	4.40%
Triples /BIP	0.00%	÷1.028	×0.970	—	×0.982	0.00%
Home runs /BIP	0.00%	÷1.017	×0.700	—	×0.982	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 103, 1B 109, 2B 106, 3B 106, K 89, BB 104 — 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).

Result: wOBA .301 → .239; ISO .043 → .033; BABIP .389 → .335. 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).

2024 AAASacramento River Cats · 83 PAwOBA .378 → .336 (−41)K% 16.9% → 18.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.87%	÷1.081	×1.200	—	—	18.72%
BB% (unintentional) /PA	6.02%	÷1.032	×0.690	—	×0.992	4.00%
HBP% /PA	2.41%	—	×0.940	—	×0.992	2.25%
Singles /BIP	31.15%	÷0.976	×0.930	×1.050	×0.992	30.91%
Doubles /BIP	4.92%	÷1.052	×0.830	×1.050	×0.992	4.04%
Triples /BIP	0.00%	÷1.091	×0.970	×1.050	×0.992	0.00%
Home runs /BIP	4.92%	÷1.010	×0.700	—	×0.992	3.38%

Factors used: league row International League. Park (home-season share, regressed): HR 102, 1B 95, 2B 110, 3B 118, K 116, BB 106 — 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 ×1.050.

Result: wOBA .378 → .336; ISO .160 → .118; BABIP .379 → .362. 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).

2021 AAASacramento River Cats · 233 PAwOBA .401 → .357 (−44)K% 15.0% → 17.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.02%	÷1.034	×1.200	—	—	17.43%
BB% (unintentional) /PA	8.58%	÷0.956	×0.690	—	×1.033	6.40%
HBP% /PA	1.29%	—	×0.940	—	×1.033	1.25%
Singles /BIP	26.29%	÷1.049	×0.930	×1.050	×1.033	25.27%
Doubles /BIP	8.00%	÷0.916	×0.830	×1.050	×1.033	7.86%
Triples /BIP	0.57%	÷0.900	×0.920	×1.050	×1.033	0.63%
Home runs /BIP	5.14%	÷0.995	×0.700	—	×1.033	3.74%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 99, 1B 110, 2B 83, 3B 80, K 107, BB 91 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .401 → .357; ISO .205 → .169; BABIP .367 → .351. 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 · 259 PAwOBA .328 → .274 (−55)K% 19.3% → 23.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.31%	÷1.007	×1.200	—	—	23.01%
BB% (unintentional) /PA	5.41%	÷1.066	×0.690	—	×1.050	3.67%
HBP% /PA	1.16%	—	×0.940	—	×1.050	1.14%
Singles /BIP	19.37%	÷1.019	×0.930	×0.950	×1.050	17.63%
Doubles /BIP	8.90%	÷1.009	×0.830	×0.950	×1.050	7.30%
Triples /BIP	1.05%	÷0.938	×0.970	×0.950	×1.050	1.08%
Home runs /BIP	4.19%	÷1.087	×0.840	—	×1.050	3.40%

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 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 ×0.950.

Result: wOBA .328 → .274; ISO .187 → .152; BABIP .304 → .268. 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+Tampa Tarpons · 47 PAwOBA .223 → .201 (−22)K% 19.1% → 27.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.15%	÷1.004	×1.420	—	—	27.08%
BB% (unintentional) /PA	0.00%	÷1.015	×0.750	—	×1.012	0.00%
HBP% /PA	2.13%	—	×0.930	—	×1.012	2.00%
Singles /BIP	22.22%	÷1.003	×0.920	—	×1.012	20.64%
Doubles /BIP	5.56%	÷0.891	×0.960	—	×1.012	6.06%
Triples /BIP	0.00%	÷0.983	×0.810	—	×1.012	0.00%
Home runs /BIP	0.00%	÷1.205	×0.880	—	×1.012	0.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 141, 1B 101, 2B 78, 3B 97, K 101, BB 103 — applied at half strength. Age: age 22 vs a level average of 22.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average).

Result: wOBA .223 → .201; ISO .044 → .045; BABIP .270 → .259. 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 · 34 PAwOBA .161 → .143 (−19)K% 23.5% → 28.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.53%	÷1.002	×1.200	—	—	28.19%
BB% (unintentional) /PA	0.00%	÷1.034	×0.690	—	×1.050	0.00%
HBP% /PA	2.94%	—	×0.940	—	×1.050	2.90%
Singles /BIP	16.00%	÷1.032	×0.930	—	×1.050	15.14%
Doubles /BIP	4.00%	÷1.004	×0.830	—	×1.050	3.47%
Triples /BIP	0.00%	÷1.130	×0.970	—	×1.050	0.00%
Home runs /BIP	0.00%	÷1.046	×0.840	—	×1.050	0.00%

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 22 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (5.2 yr younger than average).

Result: wOBA .161 → .143; ISO .030 → .025; BABIP .200 → .186. 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 AATrenton Thunder · 542 PAwOBA .329 → .324 (−5)K% 10.3% → 12.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.33%	÷1.007	×1.220	—	—	12.52%
BB% (unintentional) /PA	6.27%	÷0.979	×0.700	—	×1.050	4.71%
HBP% /PA	1.48%	—	×0.850	—	×1.050	1.32%
Singles /BIP	27.33%	÷1.020	×0.970	×1.050	×1.050	28.66%
Doubles /BIP	4.33%	÷0.936	×0.860	×1.050	×1.050	4.38%
Triples /BIP	0.91%	÷1.150	×0.950	×1.050	×1.050	0.83%
Home runs /BIP	1.37%	÷0.960	×0.780	—	×1.050	1.17%

Factors used: league row EL. Park (home-season share, regressed): HR 92, 1B 104, 2B 87, 3B 130, K 101, BB 96 — 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 ×1.050.

Result: wOBA .329 → .324; ISO .091 → .085; BABIP .327 → .340. 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 A+Tampa Yankees · 351 PAwOBA .323 → .303 (−19)K% 13.1% → 18.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.11%	÷0.988	×1.420	—	—	18.83%
BB% (unintentional) /PA	8.26%	÷1.021	×0.750	—	×1.042	6.32%
HBP% /PA	0.85%	—	×0.930	—	×1.042	0.83%
Singles /BIP	27.14%	÷1.022	×0.920	×1.050	×1.042	26.73%
Doubles /BIP	5.58%	÷0.953	×0.960	×1.050	×1.042	6.15%
Triples /BIP	0.37%	÷1.032	×0.810	×1.050	×1.042	0.32%
Home runs /BIP	1.12%	÷0.862	×0.880	—	×1.042	1.19%

Factors used: league row FSL. Park (home-season share, regressed): HR 72, 1B 104, 2B 91, 3B 106, K 98, BB 104 — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .323 → .303; ISO .083 → .085; BABIP .332 → .333. 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
#1Kyle Farmerlast yr '25 career totals — 8 seasons, 2,367 PA	3.6	2,367	63	16	247	306	388	+17	+23	8.9	9.0
/162	664	18	4	+4.7	+6.4	2.5	pk7: 9
#2Mike Avileslast yr '17 career totals — 10 seasons, 3,234 PA	4.9	3,234	60	78	261	295	376	+13	+4	5.8	7.2
/162	664	12	16	+2.7	+0.8	1.2	pk7: 9
#3Rob Wilfong'77-'87 * career totals — 10 seasons, 3,014 PA	4.5	3,014	39	54	243*	302*	363*	+10	+49	6.8	6.7
/162	664	9	12	+2.2	+10.7	1.5	pk7: 7
#4Tim Hulett'83-'95 * career totals — 9 seasons, 2,316 PA	3.5	2,316	48	14	245*	295*	384*	+5	+31	5.0	5.8
/162	664	14	4	+1.5	+8.9	1.4	pk7: 7
#5Yolmer Sánchezlast yr '19 career totals — 6 seasons, 2,438 PA	3.7	2,438	31	30	244	299	357	+9	+26	5.4	5.4
/162	664	8	8	+2.4	+7.2	1.5	pk7: 5
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 9 projected seasons	3.5	2,298	60	56	251	294	388	+8	+37	4.9	5.2
/162	664	17	16	+2.4	+10.8	1.4	pk7: 5
#6Casey Candaele'86-'97 * career totals — 7 seasons, 2,132 PA	3.2	2,132	11	37	246*	305*	350*	+5	+26	4.2	4.6
/162	664	3	12	+1.5	+8.1	1.3	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
Thairo Estrada (OGILVIE)	31	45	40	55	35	242/280/365	124	283	5	3	19%	4%	81	-0.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Josh Wilson 2012 · MLB	31	48→50	41→45	50	42	231/279/335	104	280	7	8	20%	4%	74	-0.6	199/246/292	93	265	8	7	27%	5%	51	-2.3	197/242/267	70	274	6	7	29%	3%	42	-1.6
✕Jake Noll 2023 · MLB	29	47→51	45	52→45	41	231/272/361	129	273	12	7	20%	4%	77	-0.3	219/268/343	124	272	12	7	23%	5%	72	-0.7	191/239/301	110	238	11	0	24%	5%	48	-0.9
✕Seth Mejias-Brean 2021 · MLB	30	47→53	44→45	47→45	43	235/284/351	116	290	12	7	23%	6%	78	-0.3	219/276/341	122	288	13	13	27%	7%	74	-0.5	193/251/296	103	252	12	14	28%	6%	51	-0.9
✕Issmael Salas 2013 · AAA	31	50→48	47→45	47→50	46	248/298/386	139	282	15	8	18%	6%	93	+0.8	236/282/346	110	274	11	7	18%	5%	77	-0.3	237/282/342	105	262	10	5	14%	5%	76	-0.2
✕Adrián Sanchez 2022 · MLB	31	52→48	42→45	48→50	43	250/289/353	103	296	9	13	19%	5%	81	-0.1	224/267/327	103	282	7	10	22%	5%	67	-1.1	207/244/298	91	266	3	6	22%	5%	47	-1.1
✕Paul Leon 2019 · AAA	31	46→56	43→45	47→45	44	227/278/338	111	276	11	7	22%	6%	74	-0.6	231/269/337	106	283	12	6	22%	4%	70	-0.9	232/260/318	86	281	11	1	21%	3%	59	-1.1
✕Adonis García 2016 · MLB	31	51→54	45→50	48→50	41	255/281/379	124	285	13	9	16%	3%	84	+0.1	258/293/393	135	288	16	8	16%	4%	92	+0.7	244/284/367	123	276	15	9	17%	4%	83	+0.0
✕Jesús Sucre 2019 · MLB	31	46	43→40	48→40	44	229/269/331	103	258	12	6	17%	4%	69	-0.9	223/270/311	88	267	7	6	18%	5%	64	-1.3	217/258/270	53	269	0	0	18%	4%	47	-1.1
✕Austin Wynns 2022 · MLB	31	44→51	45	48→40	46	221/280/340	119	261	14	6	22%	7%	76	-0.4	238/302/348	110	299	11	5	23%	7%	85	+0.2	237/301/332	94	305	9	2	24%	7%	80	-0.1
✕Chris Heintz 2006 · MLB	31	51→52	44→40	48→40	42	252/286/370	118	304	11	4	21%	5%	84	+0.1	237/271/316	79	289	6	3	19%	4%	65	-1.2	231/264/288	57	280	3	1	18%	4%	54	-0.9
✕Mike Cervenak 2008 · AAA	31	49→58	45	50→40	41	243/274/366	122	271	13	4	16%	3%	78	-0.3	245/272/356	111	275	10	4	15%	3%	75	-0.5	256/299/370	115	282	13	3	14%	5%	87	+0.3
✕Jesus Alberto Vega 2013 · AAA	31	42	44→45	47→40	43	210/265/323	113	259	13	8	24%	6%	66	-1.1	215/266/326	111	284	12	7	28%	6%	67	-1.1	207/257/302	95	280	10	3	29%	5%	55	-0.8
✕Tim Federowicz 2019 · MLB	31	46→51	47→50	49→40	43	232/282/367	136	297	14	5	27%	6%	82	-0.0	205/258/332	127	273	15	6	29%	7%	65	-1.2	160/212/265	105	214	15	2	32%	6%	31	-1.5
✕Adeiny Hechavarría 2020 · MLB	31	49→59	47→50	48→50	44	247/289/382	136	284	14	8	19%	5%	88	+0.4	245/296/379	134	290	14	8	20%	6%	90	+0.6	170/215/310	140	204	18	0	27%	5%	43	-0.7
✕Charlie Culberson 2019 · MLB	30	48→54	46→45	47→50	41	238/278/366	128	297	13	9	24%	5%	80	-0.1	245/292/400	155	313	17	9	26%	6%	93	+0.8	244/286/380	136	314	13	10	26%	5%	86	+0.1
✕Joshua Rodriguez 2016 · AAA	31	45→53	44→50	48→50	45	224/285/345	121	285	12	9	25%	7%	78	-0.3	206/266/321	115	282	12	7	30%	7%	65	-1.2	208/267/328	119	277	15	4	29%	7%	65	-0.9
✕Roque Sanchez 2006 · AAA	31	51→53	45→40	53→45	44	247/275/376	129	258	12	7	11%	3%	81	-0.1	245/267/334	89	266	8	6	11%	2%	68	-1.0	258/281/334	76	293	4	1	13%	2%	69	-0.4
✕Luis Ordaz 2007 · AAA	31	52	42→40	51→50	45	250/281/358	109	272	9	8	13%	4%	78	-0.3	247/277/342	95	288	7	11	17%	3%	74	-0.6	255/280/337	82	298	6	10	16%	3%	73	-0.3
✕Humberto Quintero 2012 · MLB	32	47	41→45	48→40	38	232/259/326	94	282	9	4	21%	3%	63	-1.4	230/261/342	112	282	10	4	22%	3%	68	-1.0	229/256/341	112	282	9	1	22%	2%	65	-0.5
✕C.J. Hinojosa 2024 · AAA	30	46→56	43→45	48→45	43	227/266/338	111	269	11	8	20%	5%	69	-0.9	207/254/304	97	253	9	8	22%	5%	57	-1.8	184/232/257	74	225	7	4	21%	4%	35	-2.2

Thairo Estrada

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps