Willi Castro

2B Colorado Rockies

Age 30 S/R 6'0" / 209 lbs MLB HR +30%H +12% Svc 7.099 · Ctrl thru 2027

Overview

MLB40-MANExtFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	27	MLBMIN	635	.247/.333/.385	12	14	105	2.6
2025	28	MLBCHC	454	.226/.313/.366	11	10	93	0.1
2026	29	MLBCOL	477	.260/.333/.417	15	10	103	1.5
2027PROJ	30	MLBCOL	397	.249/.329/.403	11	9	97	0.8
2028PROJ	31	MLBCOL	379	.243/.323/.390	10	5	92	0.2

Last 3 seasons WAR 4.2 · Next 2 projected WAR 1.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service7.099First FA2028

2027Ext$6M

Skills · percentileStatcast 2024-2026

Speed66

xwOBA55

Bat Spd48

Barrel%42

Avg EV26

CompsSkye Bolt (age 30) · Abraham Almonte (age 30) · Cooper Hummel (age 29)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 9797vR 97

AVG/OBP/SLG.249 / .329 / .403

PA397

HR11

SB9

K%25

BB%9

BABIP315

ISO151

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

340.238

POWER

Barrel%

427.2

Avg EV

2687.3

Bat Spd

4871.2

SPEED

Sprint

6628.1

Platoon Splits2024-2026 · 1150 PA

vs LHP

vs RHP

Edge

276

874

—

wRC+

▶R

wOBA

311

314

—

ISO

164

128

◀◀L

BABIP

298

310

▶R

23.2%

24.9%

◀L

BB%

5.4%

9.3%

▶▶R

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

Status FA

MLB Debut 2019

Service 7.099 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$6M	+0.7	$3M	-$4M
Totals		$6M		$3M	-$4M

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)
2014	17	ROK	AZL Indians	—	170	155	37	5	3	2	6	33	4	9	4	239	285	348	633	110	292	19	4	276	30	—	—	—	—	—	—
2016	19	A	Lake County Captains	—	548	518	134	21	8	7	19	96	3	16	11	259	289	371	660	112	302	18	3	289	52	—	—	—	—	—	—
2017	20	A+	Lynchburg Hillcats	—	510	469	136	24	3	11	28	90	7	19	9	290	339	424	764	134	336	18	5	337	84	—	—	—	—	—	—
2017	20	INTL	Leones del Escogido	—	31	29	13	1	0	1	2	5	0	1	0	448	484	586	1.070	138	522	16	6	475	207	—	—	—	—	—	—
2018	21	AAA	Toledo Mud Hens	—	21	21	6	0	0	0	0	5	0	1	0	286	286	286	571		375	24	0	259	42	—	—	—	—	—	—
2018	21	AA	Erie SeaWolves	—	524	476	125	29	4	9	34	109	4	17	5	263	317	397	714	134	323	21	6	313	74	—	—	—	—	—	—
2018	21	INTL	Leones del Escogido	—	103	97	23	4	3	2	3	22	1	1	0	237	267	402	669	165	284	21	3	288	81	—	—	—	—	—	—
2019	22	MLB	Detroit Tigers	—	110	100	23	6	1	1	6	34	2	0	1	230	287	340	627	110	333	31	5	278	77	-3	-0	-1	+8	+2	0.6
2019	22	AAA	Toledo Mud Hens	—	525	465	140	28	8	11	37	110	14	17	4	301	370	467	837	166	369	21	7	366	104	—	—	—	—	—	—
2019	22	INTL	Leones del Escogido	—	94	86	19	2	0	0	6	17	0	1	0	221	272	244	516	23	268	18	6	236	46	—	—	—	—	—	—
2020	23	MLB	Detroit Tigers	—	140	129	45	4	2	6	7	38	1	0	1	349	387	550	937	202	448	27	5	402	164	+11	-0	-2	+2	+3	1.3
2021	24	MLB	Detroit Tigers	—	450	413	91	15	6	9	23	109	8	9	4	220	275	351	626	131	275	24	5	277	76	-13	+0	+1	+2	+10	-0.0
2021	24	AAA	Toledo Mud Hens	—	23	23	9	2	0	1	0	2	0	2	0	391	391	609	1.000	217	400	9	0	438	138	—	—	—	—	—	—
2021	24	INTL	Leones del Escogido	—	31	29	5	0	0	1	0	5	2	1	0	172	226	276	502	103	174	16	0	231	43	—	—	—	—	—	—
2022	25	MLB	Detroit Tigers	—	392	365	88	18	2	8	15	82	8	9	4	241	286	367	653	126	288	21	4	290	86	-7	+0	+0	-5	+8	-0.2
2022	25	AAA	Toledo Mud Hens	—	36	34	9	2	0	0	2	10	0	3	1	265	306	324	629	59	375	28	6	286	46	—	—	—	—	—	—
2023	26	MLB	Minnesota Twins	—	409	358	92	18	5	9	34	99	12	33	5	257	342	411	752	154	328	24	8	334	111	+5	+5	+2	-4	+9	1.7
2024	27	MLB	Minnesota Twins	—	635	558	138	31	5	12	51	150	21	14	9	247	333	385	719	138	315	24	8	323	105	+4	-1	+2	+7	+14	2.6
2025	28	MLB	Chicago Cubs	—	454	402	91	17	3	11	40	111	11	10	4	226	313	366	679	139	286	24	9	308	93	-4	+0	-7	+2	+10	0.1
2026	29	MLB	Colorado Rockies	—	477	427	111	20	1	15	41	129	6	10	6	260	333	417	750	157	336	27	9	334	103	+2	-0	+1	+2	+10	1.5
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	3067	2752	679	129	25	71	217	752	69	85	34	247	318	389	707	142	312	25	7	315	99	-2	+3	-3	+12	+66	7.9
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2014	17	ROK MLE	AZL Indians	—	170	157	31	4	2	2	4	48	4	9	4	197	236	287	523	89	252	28	2	213	30	—	—	—	—	—	—
2016	19	A MLE	Lake County Captains	—	548	524	119	18	7	4	13	127	3	16	11	227	250	311	561	84	284	23	2	245	52	—	—	—	—	—	—
2017	20	A+ MLE	Lynchburg Hillcats	—	510	480	125	18	2	11	17	122	7	19	9	260	296	375	671	115	321	24	3	292	84	—	—	—	—	—	—
2018	21	AAA MLE	Toledo Mud Hens	—	21	21	5	0	0	0	0	6	0	1	0	238	238	238	476		364	29	0	230	42	—	—	—	—	—	—
2018	21	AA MLE	Erie SeaWolves	—	524	486	120	27	4	7	24	133	4	17	5	247	288	362	650	115	316	25	5	277	74	—	—	—	—	—	—
2019	22	MLB MLE	Detroit Tigers	—	110	100	23	6	1	1	6	34	2	0	1	230	287	340	627	110	333	31	5	283	77	-3	-0	-1	+8	+2	0.6
2019	22	AAA MLE	Toledo Mud Hens	—	525	475	128	24	7	11	27	125	14	17	4	269	328	419	746	149	330	24	5	322	104	—	—	—	—	—	—
2020	23	MLB MLE	Detroit Tigers	—	140	129	45	4	2	6	7	38	1	0	1	349	387	550	937	202	448	27	5	410	164	+11	-0	-2	+2	+3	1.3
2021	24	MLB MLE	Detroit Tigers	—	450	414	92	15	6	9	22	109	8	9	4	222	275	353	627	130	275	24	5	280	76	-13	+0	+1	+2	+10	-0.0
2021	24	AAA MLE	Toledo Mud Hens	—	23	23	9	2	0	1	0	2	0	2	0	391	391	609	1.000	217	375	9	0	372	138	—	—	—	—	—	—
2022	25	MLB MLE	Detroit Tigers	—	392	365	89	18	2	8	15	82	8	9	4	244	289	370	659	126	288	21	4	295	86	-7	+0	+0	-5	+8	-0.2
2022	25	AAA MLE	Toledo Mud Hens	—	36	35	8	2	0	0	1	12	0	3	1	229	250	286	536	57	346	33	3	236	46	—	—	—	—	—	—
2023	26	MLB MLE	Minnesota Twins	—	409	359	92	18	5	9	33	99	12	33	5	256	339	409	749	153	328	24	8	332	111	+5	+5	+2	-4	+9	1.7
2024	27	MLB MLE	Minnesota Twins	—	635	558	138	31	5	12	51	150	21	14	9	247	333	385	719	138	315	24	8	323	105	+4	-1	+2	+7	+14	2.6
2025	28	MLB MLE	Chicago Cubs	—	454	403	91	17	3	11	39	111	11	10	4	226	311	365	676	139	286	24	9	305	93	-4	+0	-7	+2	+10	0.1
2026	29	MLB MLE	Colorado Rockies	—	477	427	106	19	1	13	41	129	6	10	6	248	323	389	712	141	336	27	9	321	103	+2	-0	+1	+2	+10	1.5
2014	17	ROK MLE	AZL Indians	—	170	157	31	4	2	2	4	48	4	9	4	197	236	287	523	89	271	28	2	213	30	—	—	—	—	—	—
2014	17	ROK RAW	AZL Indians	—	170	155	37	5	3	2	6	33	4	9	4	239	285	348	633	110	292	19	4	276	30	—	—	—	—	—	—
2016	19	A MLE	Lake County Captains	—	548	524	119	18	7	4	13	127	3	16	11	227	250	311	561	84	289	23	2	245	52	—	—	—	—	—	—
2016	19	A RAW	Lake County Captains	—	548	518	134	21	8	7	19	96	3	16	11	259	289	371	660	112	302	18	3	289	52	—	—	—	—	—	—
2017	20	A+ MLE	2 teams	—	541	510	133	19	2	12	18	129	7	20	9	261	295	376	672	116	324	24	3	292	84	—	—	—	—	—	—
2017	20	A+ RAW	2 teams	—	541	498	149	25	3	12	30	95	7	20	9	299	348	434	781	135	347	18	6	345	84	—	—	—	—	—	—
2018	21	AA MLE	3 teams	—	648	602	149	32	5	8	29	165	5	19	5	248	288	357	645	110	327	25	4	275	72	—	—	—	—	—	—
2018	21	AA RAW	3 teams	—	648	594	154	33	7	11	37	136	5	19	5	259	308	394	702	135	318	21	6	308	72	—	—	—	—	—	—
2019	22	AAA MLE	3 teams	—	729	662	173	34	9	14	38	182	16	18	5	261	317	403	720	142	335	25	5	315	99	—	—	—	—	—	—
2019	22	AAA RAW	3 teams	—	729	651	182	36	9	12	49	161	16	18	5	280	345	418	763	138	349	22	7	336	99	—	—	—	—	—	—
2020	23	MLB MLE	Detroit Tigers	—	140	129	45	4	2	6	7	38	1	0	1	349	387	550	937	202	448	27	5	410	164	+11	-0	-2	+2	+3	1.3
2020	23	MLB RAW	Detroit Tigers	—	140	129	45	4	2	6	7	38	1	0	1	349	387	550	937	202	448	27	5	402	164	+11	-0	-2	+2	+3	1.3
2021	24	MLB MLE	3 teams	—	504	465	107	18	6	11	23	119	10	12	4	230	281	366	647	135	284	24	5	285	79	-13	+1	+1	+2	+11	0.2
2021	24	MLB RAW	3 teams	—	504	465	105	17	6	11	23	116	10	12	4	226	277	359	636	133	276	23	5	282	79	-13	+1	+1	+2	+11	0.2
2022	25	MLB MLE	2 teams	—	428	400	97	20	2	8	16	94	8	12	5	242	285	362	648	120	296	22	4	290	82	-9	+0	+0	-5	+9	-0.4
2022	25	MLB RAW	2 teams	—	428	399	97	20	2	8	17	92	8	12	5	243	288	363	651	120	295	21	4	290	82	-9	+0	+0	-5	+9	-0.4
2023	26	MLB MLE	Minnesota Twins	—	409	359	92	18	5	9	33	99	12	33	5	256	339	409	749	153	327	24	8	332	111	+5	+5	+2	-4	+9	1.7
2023	26	MLB RAW	Minnesota Twins	—	409	358	92	18	5	9	34	99	12	33	5	257	342	411	752	154	328	24	8	334	111	+5	+5	+2	-4	+9	1.7
2024	27	MLB MLE	Minnesota Twins	—	635	558	138	31	5	12	51	150	21	14	9	247	333	385	719	138	315	24	8	323	105	+4	-1	+2	+7	+14	2.6
2024	27	MLB RAW	Minnesota Twins	—	635	558	138	31	5	12	51	150	21	14	9	247	333	385	719	138	315	24	8	323	105	+4	-1	+2	+7	+14	2.6
2025	28	MLB MLE	Chicago Cubs	—	454	403	91	17	3	11	39	111	11	10	4	226	311	365	676	139	285	24	9	305	93	-4	+0	-7	+2	+10	0.1
2025	28	MLB RAW	Chicago Cubs	—	454	402	91	17	3	11	40	111	11	10	4	226	313	366	679	139	286	24	9	308	93	-4	+0	-7	+2	+10	0.1
2026	29	MLB MLE	Colorado Rockies	—	477	427	106	19	1	13	41	129	6	10	6	248	323	389	712	141	323	27	9	321	103	+2	-0	+1	+2	+10	1.5
2026	29	MLB RAW	Colorado Rockies	—	477	427	111	20	1	15	41	129	6	10	6	260	333	417	750	157	336	27	9	334	103	+2	-0	+1	+2	+10	1.5
2014	17	ROK MLE	AZL Indians	—	170	160	31	4	2	2	4	48	4	9	4	194	236	281	518	87	252	28	2	213	30	—	—	—	—	—	—
2016	19	A MLE	Lake County Captains	—	548	527	119	18	7	4	13	127	3	16	11	226	250	309	559	83	284	23	2	245	52	—	—	—	—	—	—
2017	20	A+ MLE	2 teams	—	541	511	133	19	2	12	18	129	7	20	9	260	295	376	671	115	321	24	3	292	84	—	—	—	—	—	—
2018	21	AA MLE	3 teams	—	648	609	149	32	5	8	29	165	5	19	5	245	288	353	641	108	318	25	4	275	72	—	—	—	—	—	—
2019	22	AAA MLE	3 teams	—	729	669	173	34	9	14	38	182	16	18	5	259	317	399	716	141	331	25	5	315	99	—	—	—	—	—	—
2020	23	MLB MLE	Detroit Tigers	—	140	131	45	4	2	6	7	38	1	0	1	344	387	542	929	198	448	27	5	410	164	—	—	—	—	—	—
2021	24	MLB MLE	3 teams	—	504	466	107	18	6	11	23	119	10	12	4	230	281	365	646	135	280	24	5	285	79	—	—	—	—	—	—
2022	25	MLB MLE	2 teams	—	428	401	97	20	2	8	16	94	8	12	5	242	285	362	647	120	293	22	4	290	82	—	—	—	—	—	—
2023	26	MLB MLE	Minnesota Twins	—	409	361	92	18	5	9	33	99	12	33	5	255	339	407	746	152	328	24	8	332	111	—	—	—	—	—	—
2024	27	MLB MLE	Minnesota Twins	—	635	558	138	31	5	12	51	150	21	14	9	247	333	385	719	138	315	24	8	323	105	—	—	—	—	—	—
2025	28	MLB MLE	Chicago Cubs	—	454	401	91	17	3	11	39	111	11	10	4	227	311	367	678	140	286	24	9	305	93	—	—	—	—	—	—
2026	29	MLB MLE	Colorado Rockies	—	477	427	106	19	1	13	41	129	6	10	6	248	323	389	712	141	336	27	9	321	103	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	27	MLB MLE	Minnesota Twins	—	635	558	138	31	5	12	51	150	21	14	9	247	333	385	719	138	315	24	8	323	105	—	—	—	—	—	—
2025	28	MLB MLE	Chicago Cubs	—	454	401	91	17	3	11	39	111	11	10	4	227	311	367	678	140	286	24	9	305	93	—	—	—	—	—	—
2026	29	MLB MLE	Colorado Rockies	—	477	427	106	19	1	13	41	129	6	10	6	248	323	389	712	141	336	27	9	321	103	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	30	MLB MLE	COL	100%	481	428	101	19	2	12	41	122	9	11	3	237	318	374	692	137	300	25	9	311	97	-2	+1	-2	+2	+10	0.7
▸ 2027 — real world (MLB)
2027	30	MLB CTX	COL	100%	397	352	87	16	2	11	34	100	8	9	2	249	329	403	732	154	315	25	9	327	97	-2	+1	-2	+1	+9	0.8
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	31	MLB MLE	COL	100%	379	337	77	14	1	9	32	97	7	5	2	232	312	362	674	131	296	26	8	304	92	-4	+0	-4	+1	+8	0.2
2028	31	MLB CTX	COL	100%	379	337	82	15	2	10	32	97	7	5	2	243	323	390	712	146	310	26	8	319	92	-4	+0	-4	+1	+8	0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3446	3089	761	144	27	81	249	849	76	90	36	246	318	389	707	143	312	25	7	316	89	-6	+4	-7	+14	+75	8.0
/ 162G	—	A+C		—	650	583	143	27	5	15	47	160	14	17	7	245	317	386	703	141	311	25	7	316	89	-1	+1	-1	+3	+14	1.5
Career	—	MLE		—	6459	5885	1442	264	52	129	378	1588	119	187	72	245	304	373	677	128	312	25	6	299	89	-7	+5	-9	+15	+83	8.8
/ 162G	—	MLE		—	650	592	145	27	5	13	38	160	12	19	7	245	304	373	677	128	312	25	6	299	89	-1	+1	-2	+3	+14	1.5

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.

2022 AAAToledo Mud Hens · 36 PAwOBA .279 → .236 (−43)K% 27.8% → 33.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.78%	÷1.008	×1.200	—	—	33.08%
BB% (unintentional) /PA	5.56%	÷0.964	×0.690	—	×1.033	4.11%
HBP% /PA	0.00%	—	×0.940	—	×1.033	0.00%
Singles /BIP	29.17%	÷1.015	×0.930	—	×1.033	27.60%
Doubles /BIP	8.33%	÷1.015	×0.830	—	×1.033	7.04%
Triples /BIP	0.00%	÷1.150	×0.970	—	×1.033	0.00%
Home runs /BIP	0.00%	÷1.026	×0.700	—	×1.033	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 105, 1B 103, 2B 103, 3B 130, K 102, BB 93 — 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 .279 → .236; ISO .059 → .047; BABIP .375 → .346. 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 AAAToledo Mud Hens · 23 PAwOBA .425 → .372 (−53)K% 8.7% → 10.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.70%	÷1.000	×1.200	—	—	10.44%
BB% (unintentional) /PA	0.00%	÷1.038	×0.690	—	×1.048	0.00%
HBP% /PA	0.00%	—	×0.940	—	×1.048	0.00%
Singles /BIP	28.57%	÷0.991	×0.930	—	×1.048	28.10%
Doubles /BIP	9.52%	÷1.013	×0.830	—	×1.048	8.18%
Triples /BIP	0.00%	÷0.981	×0.920	—	×1.048	0.00%
Home runs /BIP	4.76%	÷1.052	×0.700	—	×1.048	3.32%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 110, 1B 98, 2B 103, 3B 96, K 100, BB 108 — applied at half strength. Age: age 24 vs a level average of 27.2 → +4.8% on BB/HBP/hit rates (3.2 yr younger than average).

Result: wOBA .425 → .372; ISO .217 → .162; BABIP .400 → .375. 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 AAAToledo Mud Hens · 525 PAwOBA .360 → .322 (−38)K% 21.0% → 23.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.95%	÷1.056	×1.200	—	—	23.82%
BB% (unintentional) /PA	7.05%	÷1.004	×0.690	—	×1.050	5.09%
HBP% /PA	2.67%	—	×0.940	—	×1.050	2.63%
Singles /BIP	26.20%	÷1.013	×0.930	×0.950	×1.050	23.99%
Doubles /BIP	7.89%	÷0.995	×0.830	×0.950	×1.050	6.56%
Triples /BIP	2.25%	÷1.096	×0.970	×0.950	×1.050	1.99%
Home runs /BIP	3.10%	÷0.888	×0.840	—	×1.050	3.08%

Factors used: league row IL. Park (home-season share, regressed): HR 78, 1B 103, 2B 99, 3B 119, K 111, BB 101 — applied at half strength. Age: age 22 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (5.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .360 → .322; ISO .166 → .153; BABIP .369 → .330. 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 AAErie SeaWolves · 524 PAwOBA .305 → .277 (−28)K% 20.8% → 25.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.80%	÷0.999	×1.220	—	—	25.41%
BB% (unintentional) /PA	6.30%	÷1.007	×0.700	—	×1.050	4.60%
HBP% /PA	0.76%	—	×0.850	—	×1.050	0.68%
Singles /BIP	22.62%	÷1.016	×0.970	×0.998	×1.050	22.62%
Doubles /BIP	7.90%	÷0.974	×0.860	×0.998	×1.050	7.31%
Triples /BIP	1.09%	÷0.901	×0.950	×0.998	×1.050	1.20%
Home runs /BIP	2.45%	÷1.112	×0.780	—	×1.050	1.81%

Factors used: league row EL. Park (home-season share, regressed): HR 122, 1B 103, 2B 95, 3B 80, K 100, BB 101 — applied at half strength. Age: age 21 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.998.

Result: wOBA .305 → .277; ISO .134 → .116; BABIP .323 → .316. 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 AAAToledo Mud Hens · 21 PAwOBA .251 → .230 (−21)K% 23.8% → 28.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.81%	÷1.011	×1.200	—	—	28.27%
BB% (unintentional) /PA	0.00%	÷0.980	×0.690	—	×1.050	0.00%
HBP% /PA	0.00%	—	×0.940	—	×1.050	0.00%
Singles /BIP	37.50%	÷1.005	×0.930	—	×1.050	36.43%
Doubles /BIP	0.00%	÷1.038	×0.830	—	×1.050	0.00%
Triples /BIP	0.00%	÷1.038	×0.970	—	×1.050	0.00%
Home runs /BIP	0.00%	÷0.893	×0.840	—	×1.050	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 79, 1B 101, 2B 108, 3B 108, K 102, BB 96 — applied at half strength. Age: age 21 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (6.2 yr younger than average).

Result: wOBA .251 → .230; ISO .000 → .000; BABIP .375 → .364. 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 A+Lynchburg Hillcats · 510 PAwOBA .330 → .292 (−37)K% 17.6% → 23.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.65%	÷1.048	×1.420	—	—	23.92%
BB% (unintentional) /PA	5.29%	÷1.008	×0.630	—	×1.042	3.45%
HBP% /PA	1.37%	—	×0.860	—	×1.042	1.23%
Singles /BIP	25.86%	÷0.978	×0.940	×0.996	×1.042	25.80%
Doubles /BIP	6.33%	÷1.084	×0.830	×0.996	×1.042	5.03%
Triples /BIP	0.79%	÷1.070	×0.800	×0.996	×1.042	0.61%
Home runs /BIP	2.90%	÷0.902	×0.900	—	×1.042	3.02%

Factors used: league row CAR. Park (home-season share, regressed): HR 80, 1B 96, 2B 117, 3B 114, K 110, BB 102 — 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 ×0.996.

Result: wOBA .330 → .292; ISO .134 → .119; BABIP .336 → .321. 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 ALake County Captains · 548 PAwOBA .283 → .245 (−38)K% 17.5% → 23.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.52%	÷1.033	×1.360	—	—	23.06%
BB% (unintentional) /PA	3.10%	÷0.986	×0.690	—	×1.045	2.27%
HBP% /PA	0.55%	—	×0.780	—	×1.045	0.45%
Singles /BIP	23.22%	÷1.001	×0.920	×0.994	×1.045	22.17%
Doubles /BIP	4.98%	÷0.973	×0.830	×0.994	×1.045	4.41%
Triples /BIP	1.90%	÷0.981	×0.910	×0.994	×1.045	1.83%
Home runs /BIP	1.66%	÷1.274	×0.800	—	×1.045	1.09%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 155, 1B 100, 2B 95, 3B 96, K 107, BB 97 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.994.

Result: wOBA .283 → .245; ISO .112 → .089; BABIP .302 → .284. 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 ROKAZL Indians · 170 PAwOBA .269 → .213 (−56)K% 19.4% → 28.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.41%	÷1.000	×1.440	—	—	27.95%
BB% (unintentional) /PA	3.53%	÷1.000	×0.620	—	×1.038	2.27%
HBP% /PA	2.35%	—	×0.720	—	×1.038	1.76%
Singles /BIP	22.13%	÷1.000	×0.820	×1.050	×1.038	19.77%
Doubles /BIP	4.10%	÷1.000	×0.720	×1.050	×1.038	3.21%
Triples /BIP	2.46%	÷1.000	×0.720	×1.050	×1.038	1.93%
Home runs /BIP	1.64%	÷1.000	×0.780	—	×1.038	1.33%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 17 vs a level average of 19.5 → +3.8% on BB/HBP/hit rates (2.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .269 → .213; ISO .110 → .082; BABIP .292 → .252. 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
#1Kolten Wonglast yr '23 career totals — 11 seasons, 4,283 PA	6.5	4,283	86	120	256	330	390	+15	+21	18.4	17.8
/162	664	13	19	+2.4	+3.2	2.8	pk7: 17
#2Adam Kennedy'99-'12 * career totals — 14 seasons, 6,054 PA	9.1	6,054	80	179	263*	319*	375*	+11	+3	13.1	13.2
/162	664	9	20	+1.2	+0.4	1.4	pk7: 13
#3Dick Green'63-'74 * career totals — 10 seasons, 4,462 PA	6.7	4,462	80	26	246*	308*	382*	+16	+18	11.8	12.8
/162	664	12	4	+2.4	+2.7	1.8	pk7: 14
#4Marwin Gonzalezlast yr '22 career totals — 11 seasons, 3,882 PA	5.8	3,882	107	44	252	310	399	-10	+17	10.9	10.9
/162	664	18	8	-1.6	+2.8	1.9	pk7: 11
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 10 projected seasons	5.8	3,843	90	99	245	314	386	+8	+0	10.3	10.2
/162	664	15	17	+1.4	+0.0	1.8	pk7: 10
#5Lenny Randle'71-'82 * career totals — 10 seasons, 4,427 PA	6.7	4,427	27	156	256*	323*	370*	+10	+7	8.7	9.8
/162	664	4	23	+1.5	+1.0	1.3	pk7: 11
#6Logan Forsythelast yr '19 career totals — 9 seasons, 3,502 PA	5.3	3,502	70	42	246	327	370	+5	-11	8.6	9.2
/162	664	13	8	+0.9	-2.2	1.6	pk7: 10

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
Willi Castro (OGILVIE)	30	—	—	—	—	235/315/371	136	300	10	9	25%	9%	97	+0.7	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Skye Bolt 2024 · MLB	30	48→40	45→50	52→50	45	235/301/358	123	313	12	11	28%	8%	87	+0.4	225/294/338	113	318	11	10	30%	8%	80	-0.2	194/271/275	81	289	7	4	32%	10%	57	-0.4
✕Abraham Almonte 2019 · MLB	30	46→55	45→55	52→55	50	227/295/358	132	278	11	12	22%	9%	84	+0.2	221/309/393	172	269	17	12	23%	11%	99	+1.2	220/317/396	176	267	19	11	24%	12%	100	+0.8
✕Cooper Hummel 2024 · MLB	29	46→50	45→50	55	53	221/318/357	136	301	10	19	28%	11%	94	+0.9	229/327/374	145	302	13	15	26%	11%	101	+1.4	226/332/378	152	291	15	13	25%	12%	102	+0.9
✕Niko Goodrum 2022 · MLB	30	45→52	48→55	53→55	46	220/295/366	145	309	16	19	32%	9%	87	+0.4	221/311/344	123	316	13	15	31%	11%	88	+0.4	219/316/327	108	312	11	14	30%	12%	83	+0.0
✕Phillip Ervin 2021 · MLB	29	48→51	47→50	49→55	48	237/313/384	147	298	14	13	24%	8%	98	+1.2	203/278/324	121	277	13	16	30%	9%	72	-0.7	155/232/248	93	213	12	21	32%	9%	34	-1.5
✕Bobby Scales 2008 · AAA	30	52→55	45→50	53→50	44	250/308/388	138	324	11	11	26%	7%	96	+1.0	245/314/373	128	312	12	10	24%	8%	95	+1.0	235/324/380	145	293	12	9	22%	10%	100	+0.6
✕Ryan Langerhans 2010 · MLB	30	47→41	47→50	48→50	51	232/313/378	146	297	14	13	26%	10%	96	+1.0	217/309/366	149	303	16	13	31%	11%	93	+0.8	195/296/338	143	283	16	12	34%	12%	80	-0.1
✕Ryan Roberts 2011 · MLB	30	47→52	45→50	52→55	51	230/299/358	127	277	12	16	21%	9%	86	+0.3	229/301/369	140	267	16	15	20%	9%	90	+0.6	227/300/361	134	261	16	13	19%	9%	88	+0.4
✕Tyler Saladino 2019 · MLB	30	45→47	43→45	51→55	46	222/286/329	107	283	11	16	25%	8%	75	-0.5	217/287/377	160	280	19	14	29%	8%	87	+0.4	194/268/371	176	242	23	14	30%	8%	76	-0.3
✕Brian Bogusevic 2015 · MLB	31	48→54	45	51→55	48	237/307/366	129	296	12	15	24%	8%	91	+0.7	247/293/372	125	306	14	16	23%	6%	87	+0.4	251/291/374	122	308	15	17	23%	5%	84	+0.1
✕Joe Borchard 2009 · MLB	30	46→43	51→55	46→45	47	235/299/393	159	290	19	9	26%	8%	95	+0.9	208/258/355	147	276	16	5	30%	6%	70	-0.8	194/242/338	144	257	16	1	31%	5%	58	-1.2
✕David Bote 2023 · MLB	30	43→50	48→50	49→45	43	219/287/358	139	283	15	8	28%	7%	82	+0.0	223/289/367	144	283	15	8	26%	7%	86	+0.3	212/283/357	146	264	15	6	25%	8%	79	-0.1
●Zach McKinstry 2024 · MLB	29	48→53	46→55	52→55	49	238/305/376	138	290	13	14	22%	8%	93	+0.8	235/306/375	140	287	11	18	21%	8%	93	+0.8	229/305/367	138	276	10	18	20%	9%	91	+0.5
✕Tyler Neslony 2024 · AAA	30	46→48	47→55	52→55	45	227/287/365	138	297	14	20	28%	8%	84	+0.1	215/267/320	105	287	9	17	27%	6%	65	-1.2	194/223/245	51	259	0	16	24%	3%	29	-0.9
✕Cole Gillespie 2014 · MLB	30	46→56	44→50	52→50	49	228/298/351	123	281	12	13	23%	8%	84	+0.2	244/302/357	113	292	9	12	19%	7%	87	+0.4	249/305/352	102	296	7	12	17%	7%	87	+0.2
✕Chad Huffman 2016 · AAA	31	47→52	48→50	50→45	48	237/307/381	145	297	16	9	25%	8%	95	+1.0	224/301/380	156	272	16	8	23%	8%	93	+0.8	214/294/368	154	261	17	5	24%	8%	85	+0.1
✕Rafael Ortega 2021 · MLB	30	45→55	49→55	52→55	49	230/292/383	153	269	16	16	21%	8%	90	+0.6	240/316/383	143	289	16	18	22%	10%	99	+1.2	228/314/353	125	275	14	21	21%	11%	91	+0.5
✕Mark Payton 2022 · MLB	30	48→51	47→55	48→50	46	238/290/381	143	281	14	10	21%	6%	88	+0.5	231/286/359	128	272	12	11	19%	7%	82	-0.0	231/288/355	124	272	11	10	19%	7%	79	-0.2
✕Jonathan Davis 2022 · MLB	30	40→50	44→45	52→55	48	198/301/313	115	267	11	19	28%	9%	79	-0.2	220/302/329	109	302	9	22	28%	9%	82	-0.0	216/296/320	104	303	8	22	29%	8%	75	-0.2
✕Andrew Beattie 2008 · AAA	30	44→51	47→45	46→50	47	223/290/358	135	284	15	10	27%	8%	83	+0.1	231/282/354	123	292	13	13	24%	7%	79	-0.2	235/280/345	110	294	10	14	23%	6%	74	-0.5

Willi Castro

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps