Will Smith

C Los Angeles Dodgers

Age 32 R/R 5'10" / 195 lbs MLB HR +8%BB -8% Svc 7.523 · Ctrl thru 2033

Overview

MLB40-MANExtFA 2034

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	29	MLBLAD	544	.248/.332/.433	20	1	112	3.2
2025	30	MLBLAD	436	.296/.408/.497	17	2	159	5.0
2026	31	MLBLAD	276	.260/.360/.426	10	0	125	2.2
2027PROJ	32	MLBLAD	275	.261/.360/.446	11	1	129	2.0
2028PROJ	33	MLBLAD	211	.253/.351/.427	8	1	122	0.9

Last 3 seasons WAR 10.4 · Next 2 projected WAR 2.8Projected rows: MLB playing time only, park and league context applied.

ContractCONFIRMED

Control thru2033Service7.523First FA2034

2027Ext$14M2028Ext$14M2029Ext$14M2030Ext$14M2031Ext$14M2032Ext$14M2033Ext$14M

Skills · percentileStatcast 2024-2026

xwOBA90

Barrel%73

Avg EV63

Speed43

Bat Spd33

Form.274/.376/.478 ▲▲ rolling true talent (60d window) · proj .263/.360/.447

CompsZack Cozart (age 32) · Wilson Ramos (age 32) · Asdrúbal Cabrera (age 32)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 130129vR 123

AVG/OBP/SLG.261 / .360 / .446

PA275

HR11

K%19

BB%12

BABIP287

ISO181

MLB%100%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$5M ctrl surplus

Tools · Recent Form · Splits · ContractCON 55 / POW 55

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT55

xAVG

580.258

POWER55

Barrel%

7311.6

Avg EV

6390.0

Bat Spd

3369.5

EYE60

scouting grade only

SPEED50

Sprint

4327.2

Recent Formrolling true talent ⓘ

K%16%▲▲15% over 75 PA (60d) · proj 18%

BB%13%▲15% over 75 PA (60d) · proj 12%

ISO.204▲.258 over 62 AB (60d) · proj .183

HR/BB6.2%▲7.7% over 52 BBE (60d) · proj 5.5%

BABIP.293·.292 over 48 BIP (60d) · proj .293

SLASH.274/.376/.478▲▲proj .263/.360/.447

Platoon Splits2024-2026 · 1050 PA

vs LHP

vs RHP

Edge

267

783

—

wRC+

136

125

◀L

wOBA

370

353

◀L

ISO

231

177

◀◀L

BABIP

281

312

▶R

18.4%

19.8%

◀L

BB%

12.0%

10.5%

◀L

Contract CONFIRMED · hand-curated extension

Status FA

MLB Debut 2019

Service 7.523 yrs.days

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$14M	+2.0	$16M	+$2M
2028	Ext	$14M	+0.9	$3M	-$9M
2029	Ext	beyond projection horizon · no WAR estimate
2030	Ext	beyond projection horizon · no WAR estimate
2031	Ext	beyond projection horizon · no WAR estimate
2032	Ext	beyond projection horizon · no WAR estimate
2033	Ext	beyond projection horizon · no WAR estimate
Totals		$28M		$19M	-$7M

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)
2016	21	A+	Rancho Cucamonga Quakes	—	115	97	21	4	0	2	14	31	3	1	0	216	333	320	653	103	292	27	12	303	43	—	—	—	—	—	—
2016	21	A	Great Lakes Loons	—	97	82	21	1	0	1	11	18	4	2	1	256	371	305	676	49	317	19	11	321	64	—	—	—	—	—	—
2016	21	ROK	Ogden Raptors	—	33	28	9	0	0	1	4	1	0	0	0	321	406	429	835	107	296	3	12	367	85	—	—	—	—	—	—
2017	22	A+	Rancho Cucamonga Quakes	—	305	250	58	15	3	11	37	71	13	6	2	232	360	448	808	216	273	23	12	356	68	—	—	—	—	—	—
2017	22	INTL	Glendale Desert Dogs	—	73	62	23	4	1	2	10	18	0	0	0	371	458	565	1.023	194	488	25	14	443	186	—	—	—	—	—	—
2018	23	AAA	Oklahoma City Dodgers	—	98	87	12	4	0	1	7	37	1	1	0	138	211	218	429	80	216	38	7	196	-17	—	—	—	—	—	—
2018	23	AA	Tulsa Drillers	—	307	265	70	14	0	19	36	75	4	4	0	264	361	532	893	268	295	24	12	388	85	—	—	—	—	—	—
2019	24	MLB	Los Angeles Dodgers	—	196	170	43	9	0	15	18	52	5	2	0	253	342	571	913	318	264	27	9	389	147	+11	+0	+4	+8	+4	2.9
2019	24	AAA	Oklahoma City Dodgers	—	270	224	60	11	2	20	40	49	3	1	0	268	386	603	988	335	253	18	15	420	107	—	—	—	—	—	—
2020	25	MLB	Los Angeles Dodgers	—	137	114	33	9	0	8	20	22	2	0	0	289	404	579	983	289	294	16	15	424	173	+12	+0	-4	+2	+3	1.4
2021	26	MLB	Los Angeles Dodgers	—	501	414	107	19	2	25	58	101	18	3	0	258	373	495	869	237	274	20	12	376	140	+24	+1	+12	+9	+11	5.7
2022	27	MLB	Los Angeles Dodgers	—	578	508	132	26	3	24	56	96	10	1	0	260	345	465	810	205	276	17	10	357	128	+19	+0	+8	+10	+13	5.1
2023	28	MLB	Los Angeles Dodgers	—	554	464	121	21	2	19	63	89	15	3	0	261	367	438	805	177	277	16	11	354	128	+18	+1	+10	+10	+12	5.2
2024	29	MLB	Los Angeles Dodgers	—	544	476	118	24	2	20	51	105	9	1	1	248	332	433	765	185	273	19	9	336	112	+8	-0	+3	+10	+12	3.2
2025	30	MLB	Los Angeles Dodgers	—	436	362	107	20	1	17	64	89	5	2	3	296	408	497	906	202	345	20	15	398	159	+30	-1	+2	+8	+9	5.0
2026	31	MLB	Los Angeles Dodgers	—	276	235	61	9	0	10	34	45	3	0	0	260	360	426	786	166	277	16	12	349	125	+8	+0	+2	+5	+6	2.2
2026	31	AAA	Oklahoma City Comets	—	16	16	4	2	0	1	0	4	0	0	0	250	250	562	812	312	273	25	0	347	49	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	3222	2743	722	137	10	138	364	599	67	12	4	263	363	471	835	208	284	19	11	366	134	+129	+1	+38	+63	+70	30.6
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2016	21	A+ MLE	Rancho Cucamonga Quakes	—	115	101	17	3	0	2	10	42	3	1	0	168	263	257	521	89	253	37	9	232	43	—	—	—	—	—	—
2016	21	A MLE	Great Lakes Loons	—	97	85	19	1	0	1	8	25	4	2	1	224	320	271	590	47	301	26	8	263	64	—	—	—	—	—	—
2016	21	ROK MLE	Ogden Raptors	—	33	30	8	0	0	1	2	1	0	0	0	267	312	367	679	100	238	3	6	294	85	—	—	—	—	—	—
2017	22	A+ MLE	Rancho Cucamonga Quakes	—	305	263	47	11	2	9	24	96	13	6	2	179	280	338	618	160	220	31	8	268	68	—	—	—	—	—	—
2018	23	AAA MLE	Oklahoma City Dodgers	—	98	89	9	3	0	1	5	49	1	1	0	101	158	169	326	67	184	50	5	143	-17	—	—	—	—	—	—
2018	23	AA MLE	Tulsa Drillers	—	307	276	57	11	0	13	25	95	4	4	0	207	282	388	670	181	259	31	8	294	85	—	—	—	—	—	—
2019	24	MLB MLE	Los Angeles Dodgers	—	196	171	43	10	0	14	17	52	5	2	0	251	337	556	892	304	264	27	9	386	147	+11	+0	+4	+8	+4	2.9
2019	24	AAA MLE	Oklahoma City Dodgers	—	270	235	49	9	2	15	29	62	3	1	0	209	303	455	759	247	205	23	11	326	107	—	—	—	—	—	—
2020	25	MLB MLE	Los Angeles Dodgers	—	137	115	34	10	0	8	19	22	2	0	0	296	404	591	996	296	294	16	14	424	173	+12	+0	-4	+2	+3	1.4
2021	26	MLB MLE	Los Angeles Dodgers	—	501	418	108	20	2	24	54	101	18	3	0	258	367	488	855	230	274	20	11	375	140	+24	+1	+12	+9	+11	5.7
2022	27	MLB MLE	Los Angeles Dodgers	—	578	512	135	28	4	23	52	96	10	1	0	264	343	469	812	205	276	17	9	357	128	+19	+0	+8	+10	+13	5.1
2023	28	MLB MLE	Los Angeles Dodgers	—	554	466	122	22	2	18	61	89	15	3	0	262	365	433	799	172	277	16	11	357	128	+18	+1	+10	+10	+12	5.2
2024	29	MLB MLE	Los Angeles Dodgers	—	544	482	119	25	2	19	45	105	9	1	1	247	323	425	748	178	273	19	8	334	112	+8	-0	+3	+10	+12	3.2
2025	30	MLB MLE	Los Angeles Dodgers	—	436	363	108	21	1	16	63	89	5	2	3	298	408	493	901	196	345	20	14	403	159	+30	-1	+2	+8	+9	5.0
2026	31	MLB MLE	Los Angeles Dodgers	—	276	235	62	10	0	10	34	45	3	0	0	264	364	434	798	170	277	16	12	353	125	+8	+0	+2	+5	+6	2.2
2026	31	AAA MLE	Oklahoma City Comets	—	16	16	3	1	0	1	0	5	0	0	0	188	188	438	625	250	220	31	0	241	49	—	—	—	—	—	—
2016	21	A+ MLE	3 teams	—	245	216	43	4	0	3	20	69	7	3	1	199	288	259	547	60	274	28	8	253	57	—	—	—	—	—	—
2016	21	A+ RAW	3 teams	—	245	207	51	5	0	4	29	50	7	3	1	246	358	329	687	82	303	20	12	319	57	—	—	—	—	—	—
2017	22	A+ MLE	2 teams	—	378	329	56	13	2	11	30	119	13	6	2	170	266	322	588	152	221	31	8	268	68	—	—	—	—	—	—
2017	22	A+ RAW	2 teams	—	378	312	81	19	4	13	47	89	13	6	2	260	379	471	850	212	316	24	12	373	68	—	—	—	—	—	—
2018	23	AA MLE	2 teams	—	405	365	67	14	0	14	30	144	5	5	0	184	255	337	592	153	251	36	7	257	60	—	—	—	—	—	—
2018	23	AA RAW	2 teams	—	405	352	82	18	0	20	43	112	5	5	0	233	325	455	780	222	277	28	11	341	60	—	—	—	—	—	—
2019	24	AAA MLE	2 teams	—	466	406	92	18	2	30	46	114	8	3	0	227	317	502	820	276	231	24	10	351	124	—	—	—	—	—	—
2019	24	AAA RAW	2 teams	—	466	394	103	20	2	35	58	101	8	3	0	261	367	589	956	327	258	22	12	407	124	—	—	—	—	—	—
2020	25	MLB MLE	Los Angeles Dodgers	—	137	115	34	10	0	8	19	22	2	0	0	296	404	591	996	296	302	16	14	424	173	+12	+0	-4	+2	+3	1.4
2020	25	MLB RAW	Los Angeles Dodgers	—	137	114	33	9	0	8	20	22	2	0	0	289	404	579	983	289	294	16	15	424	173	+12	+0	-4	+2	+3	1.4
2021	26	MLB MLE	Los Angeles Dodgers	—	501	418	108	20	2	24	54	101	18	3	0	258	367	488	855	230	276	20	11	375	140	+24	+1	+12	+9	+11	5.7
2021	26	MLB RAW	Los Angeles Dodgers	—	501	414	107	19	2	25	58	101	18	3	0	258	373	495	869	237	274	20	12	376	140	+24	+1	+12	+9	+11	5.7
2022	27	MLB MLE	Los Angeles Dodgers	—	578	512	135	28	4	23	52	96	10	1	0	264	343	469	812	205	282	17	9	357	128	+19	+0	+8	+10	+13	5.1
2022	27	MLB RAW	Los Angeles Dodgers	—	578	508	132	26	3	24	56	96	10	1	0	260	345	465	810	205	276	17	10	357	128	+19	+0	+8	+10	+13	5.1
2023	28	MLB MLE	Los Angeles Dodgers	—	554	466	122	22	2	18	61	89	15	3	0	262	365	433	799	172	280	16	11	357	128	+18	+1	+10	+10	+12	5.2
2023	28	MLB RAW	Los Angeles Dodgers	—	554	464	121	21	2	19	63	89	15	3	0	261	367	438	805	177	277	16	11	354	128	+18	+1	+10	+10	+12	5.2
2024	29	MLB MLE	Los Angeles Dodgers	—	544	482	119	25	2	19	45	105	9	1	1	247	323	425	748	178	273	19	8	334	112	+8	-0	+3	+10	+12	3.2
2024	29	MLB RAW	Los Angeles Dodgers	—	544	476	118	24	2	20	51	105	9	1	1	248	332	433	765	185	273	19	9	336	112	+8	-0	+3	+10	+12	3.2
2025	30	MLB MLE	Los Angeles Dodgers	—	436	363	108	21	1	16	63	89	5	2	3	298	408	493	901	196	350	20	14	403	159	+30	-1	+2	+8	+9	5.0
2025	30	MLB RAW	Los Angeles Dodgers	—	436	362	107	20	1	17	64	89	5	2	3	296	408	497	906	202	345	20	15	398	159	+30	-1	+2	+8	+9	5.0
2026	31	MLB MLE	2 teams	—	292	251	64	11	0	10	34	50	3	0	0	255	351	418	769	163	277	17	12	347	121	+7	+0	+2	+5	+6	2.1
2026	31	MLB RAW	2 teams	—	292	251	65	11	0	11	34	49	3	0	0	259	354	434	788	175	277	17	12	349	121	+7	+0	+2	+5	+6	2.1
2016	21	A+ MLE	3 teams	—	245	216	43	4	0	3	20	69	7	3	1	199	288	259	547	60	270	28	8	253	57	—	—	—	—	—	—
2017	22	A+ MLE	2 teams	—	378	332	56	13	2	11	30	119	13	6	2	169	266	319	585	151	220	31	8	268	68	—	—	—	—	—	—
2018	23	AA MLE	2 teams	—	405	367	67	14	0	14	30	144	5	5	0	183	255	335	590	153	241	36	7	257	60	—	—	—	—	—	—
2019	24	AAA MLE	2 teams	—	466	409	92	18	2	30	46	114	8	3	0	225	317	499	816	274	230	24	10	351	124	—	—	—	—	—	—
2020	25	MLB MLE	Los Angeles Dodgers	—	137	115	34	10	0	8	19	22	2	0	0	296	404	591	996	296	294	16	14	424	173	—	—	—	—	—	—
2021	26	MLB MLE	Los Angeles Dodgers	—	501	424	108	20	2	24	54	101	18	3	0	255	367	481	848	226	274	20	11	375	140	—	—	—	—	—	—
2022	27	MLB MLE	Los Angeles Dodgers	—	578	511	135	28	4	23	52	96	10	1	0	264	343	470	813	205	276	17	9	357	128	—	—	—	—	—	—
2023	28	MLB MLE	Los Angeles Dodgers	—	554	473	122	22	2	18	61	89	15	3	0	258	365	427	792	169	277	16	11	357	128	—	—	—	—	—	—
2024	29	MLB MLE	Los Angeles Dodgers	—	544	485	119	25	2	19	45	105	9	1	1	245	323	423	745	177	273	19	8	334	112	—	—	—	—	—	—
2025	30	MLB MLE	Los Angeles Dodgers	—	436	365	108	21	1	16	63	89	5	2	3	296	408	490	899	195	345	20	14	403	159	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	292	253	64	11	0	10	34	50	3	0	0	253	351	415	766	162	274	17	12	347	121	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	29	MLB MLE	Los Angeles Dodgers	—	544	485	119	25	2	19	45	105	9	1	1	245	323	423	745	177	273	19	8	334	112	—	—	—	—	—	—
2025	30	MLB MLE	Los Angeles Dodgers	—	436	365	108	21	1	16	63	89	5	2	3	296	408	490	899	195	345	20	14	403	159	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	292	253	64	11	0	10	34	50	3	0	0	253	351	415	766	162	274	17	12	347	121	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	32	MLB MLE	LAD	100%	383	330	86	15	1	14	46	71	4	2	1	264	362	447	809	183	293	19	12	359	129	+13	+0	-2	+7	+8	2.0
▸ 2027 — real world (MLB)
2027	32	MLB CTX	LAD	100%	275	237	61	10	0	11	33	51	3	1	0	261	360	446	806	185	287	19	12	358	129	+10	+0	-1	+5	+6	2.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	33	MLB MLE	LAD	100%	211	182	47	8	0	8	25	40	2	1	0	255	353	427	781	172	286	19	12	348	122	+5	+0	-5	+4	+5	0.9
2028	33	MLB CTX	LAD	100%	211	182	45	7	0	8	25	40	2	1	0	253	351	427	778	174	281	19	12	347	122	+5	+0	-5	+4	+5	0.9
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3433	2925	767	144	10	146	389	639	69	13	4	262	362	468	830	206	284	19	11	364	117	+134	+1	+33	+66	+74	31.5
/ 162G	—	A+C		—	650	554	145	27	2	28	74	121	13	2	1	262	362	469	831	208	283	19	11	364	117	+25	+0	+6	+13	+14	6.0
Career	—	MLE		—	5022	4342	1057	205	16	194	512	1089	100	29	7	243	337	432	769	189	276	22	10	341	117	+144	+1	+32	+71	+80	33.5
/ 162G	—	MLE		—	650	562	137	27	2	25	66	141	13	4	1	244	337	432	769	189	277	22	10	341	117	+25	+0	+6	+13	+14	5.9

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 AAAOklahoma City Comets · 16 PAwOBA .336 → .241 (−95)K% 25.0% → 30.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷1.000	×1.200	—	—	30.00%
BB% (unintentional) /PA	0.00%	÷1.000	×0.690	—	×0.962	0.00%
HBP% /PA	0.00%	—	×0.940	—	×0.962	0.00%
Singles /BIP	8.33%	÷1.000	×0.930	—	×0.962	7.46%
Doubles /BIP	16.67%	÷1.000	×0.830	—	×0.962	13.31%
Triples /BIP	0.00%	÷1.000	×0.970	—	×0.962	0.00%
Home runs /BIP	8.33%	÷1.000	×0.700	—	×0.962	5.61%

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 31 vs a level average of 27.2 → −3.8% on BB/HBP/hit rates (3.8 yr older than average).

Result: wOBA .336 → .241; ISO .312 → .211; BABIP .273 → .220. 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 AAAOklahoma City Dodgers · 270 PAwOBA .413 → .326 (−87)K% 18.1% → 23.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.15%	÷1.014	×1.290	—	—	23.09%
BB% (unintentional) /PA	14.44%	÷0.993	×0.710	—	×1.048	10.82%
HBP% /PA	1.11%	—	×0.980	—	×1.048	1.14%
Singles /BIP	15.43%	÷1.048	×0.900	×0.950	×1.048	13.20%
Doubles /BIP	6.29%	÷1.012	×0.810	×0.950	×1.048	5.01%
Triples /BIP	1.14%	÷1.045	×0.810	×0.950	×1.048	0.88%
Home runs /BIP	11.43%	÷1.073	×0.780	—	×1.048	8.71%

Factors used: league row PCL. Park (home-season share, regressed): HR 115, 1B 110, 2B 102, 3B 109, K 103, BB 99 — 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 ×0.950.

Result: wOBA .413 → .326; ISO .335 → .258; BABIP .253 → .205. 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 AATulsa Drillers · 307 PAwOBA .380 → .294 (−86)K% 24.4% → 30.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.43%	÷0.964	×1.220	—	—	30.93%
BB% (unintentional) /PA	11.73%	÷1.033	×0.700	—	×1.027	8.16%
HBP% /PA	1.30%	—	×0.870	—	×1.027	1.16%
Singles /BIP	19.47%	÷0.987	×0.920	×0.969	×1.027	18.08%
Doubles /BIP	7.37%	÷0.991	×0.840	×0.969	×1.027	6.22%
Triples /BIP	0.00%	÷0.907	×0.940	×0.969	×1.027	0.00%
Home runs /BIP	10.00%	÷1.147	×0.800	—	×1.027	7.16%

Factors used: league row TL. Park (home-season share, regressed): HR 129, 1B 97, 2B 98, 3B 81, K 93, BB 107 — 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 ×0.969.

Result: wOBA .380 → .294; ISO .268 → .192; BABIP .295 → .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 AAAOklahoma City Dodgers · 98 PAwOBA .195 → .143 (−52)K% 37.8% → 50.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	37.76%	÷0.970	×1.290	—	—	50.24%
BB% (unintentional) /PA	7.14%	÷1.021	×0.710	—	×1.050	5.21%
HBP% /PA	1.02%	—	×0.980	—	×1.050	1.05%
Singles /BIP	14.00%	÷0.992	×0.900	×0.950	×1.050	12.67%
Doubles /BIP	8.00%	÷1.029	×0.810	×0.950	×1.050	6.28%
Triples /BIP	0.00%	÷1.020	×0.810	×0.950	×1.050	0.00%
Home runs /BIP	2.00%	÷1.020	×0.780	—	×1.050	1.61%

Factors used: league row PCL. Park (home-season share, regressed): HR 104, 1B 98, 2B 106, 3B 104, K 94, BB 104 — 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 .195 → .143; ISO .080 → .054; BABIP .216 → .184. 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+Rancho Cucamonga Quakes · 305 PAwOBA .352 → .268 (−84)K% 23.3% → 31.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.28%	÷0.990	×1.340	—	—	31.52%
BB% (unintentional) /PA	12.13%	÷1.099	×0.710	—	×1.012	7.93%
HBP% /PA	4.26%	—	×0.790	—	×1.012	3.41%
Singles /BIP	16.20%	÷1.006	×0.910	×0.950	×1.012	14.09%
Doubles /BIP	8.38%	÷1.064	×0.820	×0.950	×1.012	6.21%
Triples /BIP	1.68%	÷1.150	×0.760	×0.950	×1.012	1.06%
Home runs /BIP	6.15%	÷1.085	×0.920	—	×1.012	5.27%

Factors used: league row CAL. Park (home-season share, regressed): HR 117, 1B 101, 2B 113, 3B 130, K 98, BB 120 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .352 → .268; ISO .216 → .168; BABIP .273 → .220. 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+Rancho Cucamonga Quakes · 115 PAwOBA .298 → .232 (−67)K% 27.0% → 36.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.96%	÷0.979	×1.340	—	—	36.89%
BB% (unintentional) /PA	12.17%	÷1.046	×0.710	—	×1.027	8.49%
HBP% /PA	2.61%	—	×0.790	—	×1.027	2.12%
Singles /BIP	22.73%	÷1.043	×0.910	×0.970	×1.027	19.76%
Doubles /BIP	6.06%	÷0.938	×0.820	×0.970	×1.027	5.28%
Triples /BIP	0.00%	÷1.142	×0.760	×0.970	×1.027	0.00%
Home runs /BIP	3.03%	÷1.003	×0.920	—	×1.027	2.85%

Factors used: league row CAL. Park (home-season share, regressed): HR 101, 1B 109, 2B 88, 3B 128, K 96, BB 109 — applied at half strength. Age: age 21 vs a level average of 22.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.970.

Result: wOBA .298 → .232; ISO .103 → .086; BABIP .292 → .253. 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 AGreat Lakes Loons · 97 PAwOBA .314 → .263 (−51)K% 18.6% → 25.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.56%	÷0.990	×1.360	—	—	25.48%
BB% (unintentional) /PA	11.34%	÷1.011	×0.690	—	×1.015	7.85%
HBP% /PA	4.12%	—	×0.780	—	×1.015	3.26%
Singles /BIP	29.69%	÷0.977	×0.920	×0.998	×1.015	28.30%
Doubles /BIP	1.56%	÷0.961	×0.830	×0.998	×1.015	1.37%
Triples /BIP	0.00%	÷0.900	×0.910	×0.998	×1.015	0.00%
Home runs /BIP	1.56%	÷0.960	×0.800	—	×1.015	1.32%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 92, 1B 95, 2B 92, 3B 80, K 98, BB 102 — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.998.

Result: wOBA .314 → .263; ISO .049 → .040; BABIP .317 → .301. 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 ROKOgden Raptors · 33 PAwOBA .369 → .294 (−75)K% 3.0% → 4.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	3.03%	÷1.000	×1.440	—	—	4.36%
BB% (unintentional) /PA	12.12%	÷1.000	×0.610	—	×0.985	7.28%
HBP% /PA	0.00%	—	×0.720	—	×0.985	0.00%
Singles /BIP	29.63%	÷1.000	×0.820	—	×0.985	23.93%
Doubles /BIP	0.00%	÷1.000	×0.720	—	×0.985	0.00%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.985	0.00%
Home runs /BIP	3.70%	÷1.000	×0.750	—	×0.985	2.74%

Factors used: league row PIO. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 21 vs a level average of 19.5 → −1.5% on BB/HBP/hit rates (1.5 yr older than average).

Result: wOBA .369 → .294; ISO .107 → .085; BABIP .296 → .238. 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
#1Jorge Posada'96-'11 * career totals — 15 seasons, 7,150 PA	10.8	7,150	275	20	263*	364*	464*	+91	+0	55.1	47.1
/162	664	26	2	+8.4	+0.0	5.1	pk7: 39
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 10 projected seasons	5.6	3,708	156	14	262	358	466	+66	+48	31.1	28.5
/162	664	28	3	+11.9	+8.5	5.6	pk7: 26
#2Matt Wieterslast yr '19 career totals — 11 seasons, 4,387 PA	6.6	4,387	146	9	250	313	411	+78	+81	30.0	28.4
/162	664	22	1	+11.9	+12.2	4.5	pk7: 27
#3Tom Haller'61-'72 * career totals — 12 seasons, 4,519 PA	6.8	4,519	134	14	256*	344*	450*	+79	-1	30.9	27.5
/162	664	20	2	+11.6	-0.1	4.5	pk7: 24
#4Wilson Ramoslast yr '21 career totals — 12 seasons, 3,786 PA	5.7	3,786	136	1	271	318	432	+68	+61	28.0	26.7
/162	664	24	0	+11.9	+10.7	4.9	pk7: 25
#5Geovany Sotolast yr '16 career totals — 10 seasons, 2,801 PA	4.2	2,801	105	3	247	332	438	+50	+74	26.0	25.0
/162	664	25	1	+11.9	+17.5	6.2	pk7: 24
#6Chris Hoiles'89-'98 * career totals — 9 seasons, 3,338 PA	5.0	3,338	151	5	253*	354*	468*	+50	-0	25.1	24.7
/162	664	30	1	+9.9	-0.1	5.0	pk7: 24

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
Will Smith (OGILVIE)	32	55	55	50	60	261/359/443	181	293	10	1	18%	12%	129	+1.6	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Zack Cozart 2018 · MLB	32	52→56	56→60	50	56	269/342/471	202	288	22	5	16%	10%	128	+3.3	231/305/381	150	258	15	5	16%	8%	95	+0.9	188/263/293	105	214	8	0	16%	7%	59	-0.5
✕Wilson Ramos 2020 · MLB	32	57→61	50→55	47→30	50	285/337/436	151	312	19	2	16%	7%	118	+2.7	255/306/414	159	284	21	4	18%	6%	102	+1.5	232/275/395	164	253	24	0	20%	5%	86	+0.1
●Asdrúbal Cabrera 2018 · MLB	32	56→63	52→60	45→50	50	280/339/452	172	312	19	5	17%	8%	123	+3.0	262/327/444	182	299	21	4	19%	9%	117	+2.6	254/322/441	187	289	22	2	20%	9%	115	+1.8
✕Neil Walker 2018 · MLB	32	53→57	53→55	42→45	54	269/343/443	173	299	21	3	18%	9%	122	+3.0	248/327/394	146	296	16	4	21%	10%	105	+1.7	240/324/375	134	290	14	2	21%	10%	101	+0.9
✕Danny Valencia 2017 · MLB	32	55→59	54→60	41→40	47	282/336/464	182	330	23	3	22%	7%	124	+3.1	260/319/418	158	312	19	4	22%	8%	107	+1.9	253/312/400	147	304	18	2	22%	8%	102	+0.9
✕Anthony Rendon 2022 · MLB	32	53→59	55→65	47→50	61	272/365/471	199	289	22	4	15%	12%	137	+4.0	237/335/363	126	272	12	8	16%	11%	101	+1.4	224/331/314	90	263	7	10	16%	12%	90	+0.2
✕Charles Johnson 2003 · MLB	32	48→56	55→60	46→30	49	250/315/438	189	298	22	2	24%	8%	111	+2.1	233/322/423	190	273	22	4	23%	11%	111	+2.1	228/329/434	206	259	26	2	23%	12%	116	+1.6
✕John Jaso 2015 · MLB	31	54→57	49→50	51→45	58	265/354/422	157	301	15	6	17%	11%	121	+2.9	259/345/421	162	303	15	4	19%	11%	118	+2.6	252/346/417	166	295	15	1	19%	11%	118	+1.4
●Dexter Fowler 2018 · MLB	32	52→62	53→55	53→55	58	261/359/452	191	311	19	12	22%	12%	130	+3.5	232/330/402	170	280	20	9	23%	12%	109	+2.0	217/320/372	156	262	20	8	24%	12%	101	+0.8
✕Preston Wilson 2006 · MLB	32	50→52	58→60	42→55	47	262/325/467	205	308	25	8	24%	8%	122	+2.9	254/305/418	164	308	20	12	23%	6%	103	+1.5	260/302/418	158	312	19	13	23%	5%	102	+1.3
✕Aaron Hicks 2021 · MLB	31	46→56	55→60	48→55	64	237/352/429	192	273	22	9	21%	15%	122	+3.0	226/330/361	135	280	15	10	23%	13%	99	+1.3	221/326/330	109	278	13	11	23%	13%	92	+0.4
●Mitch Garver 2023 · MLB	32	43→46	57→70	42→40	52	231/320/426	195	284	25	5	28%	11%	111	+2.1	226/323/414	188	279	25	3	27%	12%	109	+2.0	212/315/390	178	262	24	2	28%	12%	101	+0.9
●Josh Willingham 2011 · MLB	32	50→53	57→65	50→45	60	260/366/465	206	293	23	8	20%	12%	136	+3.9	249/348/473	224	290	29	5	24%	11%	131	+3.6	238/343/462	224	279	29	3	25%	11%	128	+3.1
★Miguel Tejada 2006 · MLB	32	57→64	57→60	50→45	49	295/338/501	207	297	24	5	11%	5%	135	+3.8	300/342/464	164	314	19	5	11%	5%	127	+3.3	298/339/444	146	312	17	5	11%	5%	121	+3.1
●Marlon Byrd 2010 · MLB	32	57→63	51→60	47→50	48	283/338/457	174	317	17	8	17%	6%	124	+3.1	273/324/410	137	311	13	6	16%	5%	107	+1.9	265/308/466	201	329	25	2	27%	5%	117	+2.5
✕Troy Tulowitzki 2017 · MLB	32	51→57	55→65	46→50	50	267/329/449	182	296	24	3	19%	8%	119	+2.7	249/308/407	158	277	20	5	18%	7%	101	+1.4	244/296/372	128	269	17	0	16%	6%	88	+0.2
✕Curt Casali 2021 · MLB	32	48	54→50	46→30	51	245/328/422	177	300	22	6	25%	10%	112	+2.2	219/313/359	140	293	16	4	28%	11%	93	+0.8	207/312/292	85	276	8	0	25%	11%	77	-0.1
●Brian Dozier 2019 · MLB	32	46→56	58→65	50	54	245/326/452	207	270	25	13	20%	10%	118	+2.7	238/326/419	181	275	22	8	22%	11%	111	+2.1	235/335/426	190	268	25	4	22%	12%	117	+2.1
✕Mendy López 2007 · MLB	33	52→54	58→55	45→30	54	269/351/469	201	315	26	5	23%	11%	132	+3.6	249/320/423	174	300	21	3	23%	9%	109	+2.0	241/312/403	162	289	19	0	23%	9%	101	+0.8
✕Mike Lieberthal 2005 · MLB	33	56→63	50→55	42→30	51	282/344/444	161	298	17	2	12%	7%	123	+3.0	259/313/416	157	265	18	3	10%	5%	105	+1.7	255/306/418	163	252	19	0	8%	4%	104	+0.9

Will Smith

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps