Joey Bart

C Chicago White Sox

Age 30 R/R 6'2" / 242 lbs MLB HR +4% Svc 5.046 · Ctrl thru 2027

Overview

MLB40-MANArb-3FA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	27	MLBPIT	282	.265/.338/.462	13	0	130	2.1
2025	28	MLBPIT	332	.249/.355/.340	4	1	105	2.0
2026	29	MLBCWS	128	.214/.307/.357	4	0	90	0.5
2027PROJ	30	MLBCWS	173	.238/.334/.388	5	1	105	0.8
2028PROJ92% MLB	31	MLBCWS	146	.234/.329/.377	4	1	101	0.3

Last 3 seasons WAR 4.6 · Next 2 projected WAR 1.1Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service5.046First FA2028

2027Arb-3$4M

Skills · percentileStatcast 2024-2026

Bat Spd82

xwOBA61

Barrel%59

Avg EV33

Speed32

CompsMichael McKenry (age 30) · James McCann (age 30) · John Buck (age 30)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 110105vR 90

AVG/OBP/SLG.238 / .334 / .388

PA173

HR5

K%26

BB%10

BABIP302

ISO141

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · ContractCON 45 / POW 50

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT45

xAVG

210.228

POWER50

Barrel%

599.6

Avg EV

3387.8

Bat Spd

8274.8

EYE55

scouting grade only

SPEED45

Sprint

3226.6

Platoon Splits2024-2026 · 635 PA

vs LHP

vs RHP

Edge

160

475

—

wRC+

165

◀◀L

wOBA

413

304

◀◀L

ISO

209

119

◀◀L

BABIP

439

306

◀◀L

30.0%

26.5%

▶R

BB%

11.9%

9.3%

◀◀L

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

Status Arb-3

MLB Debut 2020

Service 5.046 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-3	$4M	+0.8	$3M	+$0.0M (cut)
Totals		$0.0M		$3M	+$0.0M

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)
2018	21	ROK	AZL Giants Orange	—	25	23	6	1	1	0	1	7	1	0	0	261	320	391	711	130	375	28	4	318	22	—	—	—	—	—	—
2019	22	AA	Richmond Flying Squirrels	—	87	79	25	4	1	4	7	21	0	0	2	316	372	544	916	228	382	24	8	396	120	—	—	—	—	—	—
2019	22	A+	San Jose Giants	—	251	234	62	10	2	12	14	50	3	5	2	265	315	479	793	214	291	20	6	348	70	—	—	—	—	—	—
2019	22	INTL	Scottsdale Scorpions	—	42	30	10	1	0	4	9	7	3	0	0	333	524	767	1.290	433	316	17	21	538	251	—	—	—	—	—	—
2020	23	MLB	San Francisco Giants	—	111	103	24	5	2	0	3	41	5	0	0	233	288	320	609	87	387	37	3	278	75	-3	+0	+3	+2	+2	0.4
2021	24	AAA	Sacramento River Cats	—	279	252	74	15	0	10	21	82	5	0	0	294	360	472	832	179	398	29	8	368	91	—	—	—	—	—	—
2022	25	MLB	San Francisco Giants	—	291	261	56	6	0	11	26	112	4	2	1	215	296	364	660	149	326	38	9	299	94	-2	+0	-1	+6	+6	0.9
2022	25	AAA	Sacramento River Cats	—	31	28	8	0	0	1	2	6	1	0	0	286	355	393	748	107	333	19	6	340	80	—	—	—	—	—	—
2023	26	MLB	San Francisco Giants	—	95	87	18	5	0	0	3	23	4	0	0	207	266	264	530	57	277	24	3	244	53	-5	+0	+3	+6	+2	0.6
2023	26	AAA	Sacramento River Cats	—	244	206	51	12	0	6	30	69	6	1	0	248	360	393	753	146	338	28	12	341	74	—	—	—	—	—	—
2024	27	MLB	Pittsburgh Pirates	—	282	253	67	11	0	13	22	73	6	0	0	265	338	462	801	198	321	26	8	354	130	+10	+0	-1	+5	+6	2.1
2024	27	AAA	Indianapolis Indians	—	20	17	6	1	0	0	3	3	0	0	0	353	450	412	862	59	429	15	15	395	105	—	—	—	—	—	—
2025	28	MLB	Pittsburgh Pirates	—	332	285	71	12	1	4	40	93	7	1	1	249	355	340	696	91	356	28	12	323	105	+2	-0	+4	+6	+7	2.0
2025	28	AAA	Indianapolis Indians	—	18	13	3	0	0	0	4	6	1	0	0	231	444	231	675		429	33	22	347	67	—	—	—	—	—	—
2026	29	MLB	Chicago White Sox	—	128	112	24	4	0	4	7	35	8	0	0	214	307	357	664	143	270	27	5	302	90	-2	+0	+1	+3	+3	0.5
2026	29	AAA	Indianapolis Indians	—	22	17	6	2	0	1	4	5	1	0	0	353	500	647	1.147	294	455	23	18	495	147	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1239	1101	260	43	3	32	101	377	34	3	2	236	320	368	687	132	328	30	8	312	97	-4	-0	+9	+28	+27	6.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2018	21	ROK MLE	AZL Giants Orange	—	25	23	5	1	1	0	1	10	1	0	0	217	280	348	628	130	288	40	4	200	22	—	—	—	—	—	—
2019	22	AA MLE	Richmond Flying Squirrels	—	87	82	24	4	1	4	4	26	0	0	2	293	326	512	838	220	367	30	5	345	120	—	—	—	—	—	—
2019	22	A+ MLE	San Jose Giants	—	251	237	49	7	1	11	11	69	3	5	2	207	251	384	635	177	243	27	4	271	70	—	—	—	—	—	—
2020	23	MLB MLE	San Francisco Giants	—	111	103	24	5	2	0	3	41	5	0	0	233	288	320	609	87	387	37	3	280	75	-3	+0	+3	+2	+2	0.4
2021	24	AAA MLE	Sacramento River Cats	—	279	257	65	14	0	7	16	95	5	0	0	253	309	389	698	136	365	34	6	302	91	—	—	—	—	—	—
2022	25	MLB MLE	San Francisco Giants	—	291	261	58	6	0	12	26	112	4	2	1	222	302	383	686	161	326	38	9	307	94	-2	+0	-1	+6	+6	0.9
2022	25	AAA MLE	Sacramento River Cats	—	31	29	8	0	0	1	1	7	1	0	0	276	323	379	702	103	322	23	3	287	80	—	—	—	—	—	—
2023	26	MLB MLE	San Francisco Giants	—	95	87	18	5	0	0	3	23	4	0	0	207	266	264	530	57	277	24	3	246	53	-5	+0	+3	+6	+2	0.6
2023	26	AAA MLE	Sacramento River Cats	—	244	215	45	10	0	4	21	76	6	1	0	209	298	312	609	102	298	31	9	277	74	—	—	—	—	—	—
2024	27	MLB MLE	Pittsburgh Pirates	—	282	253	68	11	0	14	22	73	6	0	0	269	342	478	820	209	321	26	8	360	130	+10	+0	-1	+5	+6	2.1
2024	27	AAA MLE	Indianapolis Indians	—	20	18	6	1	0	0	2	4	0	0	0	333	400	389	789	56	383	20	10	324	105	—	—	—	—	—	—
2025	28	MLB MLE	Pittsburgh Pirates	—	332	285	70	11	1	4	40	93	7	1	1	246	352	333	686	88	356	28	12	324	105	+2	-0	+4	+6	+7	2.0
2025	28	AAA MLE	Indianapolis Indians	—	18	15	3	0	0	0	2	7	1	0	0	200	333	200	533		388	39	11	267	67	—	—	—	—	—	—
2026	29	MLB MLE	Chicago White Sox	—	128	112	24	4	0	4	7	35	8	0	0	214	307	357	664	143	270	27	5	301	90	-2	+0	+1	+3	+3	0.5
2026	29	AAA MLE	Indianapolis Indians	—	22	18	6	2	0	1	3	6	1	0	0	333	455	611	1.066	278	382	27	14	385	147	—	—	—	—	—	—
2018	21	ROK MLE	AZL Giants Orange	—	25	23	5	1	1	0	1	10	1	0	0	217	280	348	628	130	385	40	4	200	22	—	—	—	—	—	—
2018	21	ROK RAW	AZL Giants Orange	—	25	23	6	1	1	0	1	7	1	0	0	261	320	391	711	130	375	28	4	318	22	—	—	—	—	—	—
2019	22	A+ MLE	3 teams	—	380	356	81	12	3	16	17	107	6	5	4	228	274	413	687	185	278	28	4	290	82	—	—	—	—	—	—
2019	22	A+ RAW	3 teams	—	380	343	97	15	3	20	30	78	6	5	4	283	351	519	870	236	313	21	8	380	82	—	—	—	—	—	—
2020	23	MLB MLE	San Francisco Giants	—	111	103	24	5	2	0	3	41	5	0	0	233	288	320	609	87	387	37	3	280	75	-3	+0	+3	+2	+2	0.4
2020	23	MLB RAW	San Francisco Giants	—	111	103	24	5	2	0	3	41	5	0	0	233	288	320	609	87	387	37	3	278	75	-3	+0	+3	+2	+2	0.4
2021	24	AAA MLE	Sacramento River Cats	—	279	257	65	14	0	7	16	95	5	0	0	253	309	389	698	136	372	34	6	302	91	—	—	—	—	—	—
2021	24	AAA RAW	Sacramento River Cats	—	279	252	74	15	0	10	21	82	5	0	0	294	360	472	832	179	398	29	8	368	91	—	—	—	—	—	—
2022	25	MLB MLE	2 teams	—	322	290	65	6	0	13	27	119	5	2	1	224	301	379	681	155	329	37	8	305	93	-3	+0	-1	+6	+7	0.9
2022	25	MLB RAW	2 teams	—	322	289	64	6	0	12	28	118	5	2	1	221	301	367	668	145	327	37	9	303	93	-3	+0	-1	+6	+7	0.9
2023	26	AAA MLE	2 teams	—	339	302	63	15	0	4	24	99	10	1	0	209	289	298	587	89	292	29	7	268	68	—	—	—	—	—	—
2023	26	AAA RAW	2 teams	—	339	293	69	17	0	6	33	92	10	1	0	235	333	355	688	119	318	27	10	314	68	—	—	—	—	—	—
2024	27	MLB MLE	2 teams	—	302	271	73	11	0	14	24	77	6	0	0	269	342	465	807	196	326	25	8	358	128	+10	+0	-1	+5	+7	2.2
2024	27	MLB RAW	2 teams	—	302	270	73	12	0	13	25	76	6	0	0	270	346	459	805	189	330	25	8	357	128	+10	+0	-1	+5	+7	2.2
2025	28	MLB MLE	2 teams	—	350	300	73	11	1	4	42	100	8	1	1	243	351	327	678	83	352	29	12	321	103	+1	-0	+4	+6	+8	2.0
2025	28	MLB RAW	2 teams	—	350	298	74	12	1	4	44	99	8	1	1	248	360	336	696	87	359	28	13	324	103	+1	-0	+4	+6	+8	2.0
2026	29	MLB MLE	2 teams	—	150	130	30	6	0	5	10	41	9	0	0	231	329	392	721	162	294	27	7	313	98	-0	+0	+1	+3	+3	0.7
2026	29	MLB RAW	2 teams	—	150	129	30	6	0	5	11	40	9	0	0	233	336	395	731	163	294	27	7	331	98	-0	+0	+1	+3	+3	0.7
2018	21	ROK MLE	AZL Giants Orange	—	25	23	5	1	1	0	1	10	1	0	0	217	280	348	628	130	288	40	4	200	22	—	—	—	—	—	—
2019	22	A+ MLE	3 teams	—	380	354	81	12	3	16	17	107	6	5	4	229	274	415	690	186	275	28	4	290	82	—	—	—	—	—	—
2020	23	MLB MLE	San Francisco Giants	—	111	102	24	5	2	0	3	41	5	0	0	235	288	324	612	88	387	37	3	280	75	—	—	—	—	—	—
2021	24	AAA MLE	Sacramento River Cats	—	279	256	65	14	0	7	16	95	5	0	0	254	309	391	700	137	365	34	6	302	91	—	—	—	—	—	—
2022	25	MLB MLE	2 teams	—	322	287	65	6	0	13	27	119	5	2	1	226	301	383	685	157	326	37	8	305	93	—	—	—	—	—	—
2023	26	AAA MLE	2 teams	—	339	302	63	15	0	4	24	99	10	1	0	209	289	298	587	89	292	29	7	268	68	—	—	—	—	—	—
2024	27	MLB MLE	2 teams	—	302	269	73	11	0	14	24	77	6	0	0	271	342	468	811	197	326	25	8	358	128	—	—	—	—	—	—
2025	28	MLB MLE	2 teams	—	350	297	73	11	1	4	42	100	8	1	1	246	351	330	681	84	358	29	12	321	103	—	—	—	—	—	—
2026	29	MLB MLE	2 teams	—	150	130	30	6	0	5	10	41	9	0	0	231	329	392	721	162	287	27	7	313	98	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	27	MLB MLE	2 teams	—	302	269	73	11	0	14	24	77	6	0	0	271	342	468	811	197	326	25	8	358	128	—	—	—	—	—	—
2025	28	MLB MLE	2 teams	—	350	297	73	11	1	4	42	100	8	1	1	246	351	330	681	84	358	29	12	321	103	—	—	—	—	—	—
2026	29	MLB MLE	2 teams	—	150	130	30	6	0	5	10	41	9	0	0	231	329	392	721	162	287	27	7	313	98	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	30	MLB MLE	CWS	100%	279	242	58	10	1	8	27	72	8	2	0	237	333	385	718	147	301	26	10	324	105	+2	+0	-1	+5	+6	0.8
▸ 2027 — real world (MLB)
2027	30	MLB CTX	CWS	100%	173	149	35	6	0	5	17	45	5	1	0	238	334	388	722	149	302	26	10	325	105	+1	+0	-1	+3	+4	0.8
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	31	MLB MLE	CWS	92%	159	138	31	5	0	4	15	42	5	1	0	233	328	373	702	141	297	26	9	317	101	+0	+0	-3	+3	+3	0.3
2028	31	MLB CTX	CWS	92%	146	127	29	5	0	4	14	38	4	1	0	234	329	377	705	143	298	26	10	319	101	+0	+0	-3	+3	+3	0.3
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1385	1228	289	48	3	36	115	415	38	4	2	235	320	367	687	132	324	30	8	313	94	-4	+0	+6	+31	+30	6.4
/ 162G	—	A+C		—	650	576	136	23	1	17	54	195	18	2	1	236	321	368	689	132	325	30	8	313	94	-2	+0	+3	+14	+14	3.0
Career	—	MLE		—	2590	2319	545	92	7	72	196	776	65	11	6	235	312	374	686	139	320	30	8	306	94	-3	+0	+5	+34	+34	7.2
/ 162G	—	MLE		—	650	582	137	23	2	18	49	195	16	3	2	235	312	375	686	139	321	30	8	306	94	-1	+0	+2	+14	+14	3.0

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.

2026 AAAIndianapolis Indians · 22 PAwOBA .483 → .385 (−98)K% 22.7% → 27.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.73%	÷1.000	×1.200	—	—	27.27%
BB% (unintentional) /PA	18.18%	÷1.000	×0.690	—	×0.972	12.19%
HBP% /PA	4.55%	—	×0.940	—	×0.972	4.15%
Singles /BIP	25.00%	÷1.000	×0.930	—	×0.972	22.60%
Doubles /BIP	16.67%	÷1.000	×0.830	—	×0.972	13.45%
Triples /BIP	0.00%	÷1.000	×0.970	—	×0.972	0.00%
Home runs /BIP	8.33%	÷1.000	×0.700	—	×0.972	5.67%

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 30 vs a level average of 27.2 → −2.8% on BB/HBP/hit rates (2.8 yr older than average).

Result: wOBA .483 → .385; ISO .294 → .222; BABIP .455 → .382. 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).

2025 AAAIndianapolis Indians · 18 PAwOBA .340 → .267 (−73)K% 33.3% → 41.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	33.33%	÷0.965	×1.200	—	—	41.46%
BB% (unintentional) /PA	22.22%	÷1.112	×0.690	—	×0.982	13.55%
HBP% /PA	5.56%	—	×0.940	—	×0.982	5.13%
Singles /BIP	42.86%	÷1.008	×0.930	—	×0.982	38.84%
Doubles /BIP	0.00%	÷0.995	×0.830	—	×0.982	0.00%
Triples /BIP	0.00%	÷1.150	×0.970	—	×0.982	0.00%
Home runs /BIP	0.00%	÷0.915	×0.700	—	×0.982	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 83, 1B 102, 2B 99, 3B 130, K 93, BB 122 — 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 .340 → .267; ISO .000 → .000; BABIP .429 → .388. 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 AAAIndianapolis Indians · 20 PAwOBA .386 → .324 (−61)K% 15.0% → 19.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.00%	÷0.948	×1.200	—	—	19.00%
BB% (unintentional) /PA	15.00%	÷0.977	×0.690	—	×0.992	10.51%
HBP% /PA	0.00%	—	×0.940	—	×0.992	0.00%
Singles /BIP	35.71%	÷1.009	×0.930	—	×0.992	32.67%
Doubles /BIP	7.14%	÷1.050	×0.830	—	×0.992	5.60%
Triples /BIP	0.00%	÷1.150	×0.970	—	×0.992	0.00%
Home runs /BIP	0.00%	÷0.909	×0.700	—	×0.992	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 82, 1B 102, 2B 110, 3B 130, K 90, BB 95 — 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).

Result: wOBA .386 → .324; ISO .059 → .046; BABIP .429 → .383. 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).

2023 AAASacramento River Cats · 244 PAwOBA .335 → .277 (−58)K% 28.3% → 31.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.28%	÷1.087	×1.200	—	—	31.22%
BB% (unintentional) /PA	12.30%	÷0.981	×0.690	—	×1.003	8.68%
HBP% /PA	2.46%	—	×0.940	—	×1.003	2.32%
Singles /BIP	24.09%	÷0.992	×0.930	×0.979	×1.003	22.17%
Doubles /BIP	8.76%	÷0.992	×0.830	×0.979	×1.003	7.20%
Triples /BIP	0.00%	÷0.956	×0.970	×0.979	×1.003	0.00%
Home runs /BIP	4.38%	÷1.057	×0.700	—	×1.003	2.91%

Factors used: league row International League. Park (home-season share, regressed): HR 111, 1B 98, 2B 98, 3B 91, K 117, BB 96 — 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 ×0.979.

Result: wOBA .335 → .277; ISO .146 → .109; BABIP .338 → .298. 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).

2022 AAASacramento River Cats · 31 PAwOBA .331 → .287 (−44)K% 19.4% → 23.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.35%	÷0.986	×1.200	—	—	23.55%
BB% (unintentional) /PA	6.45%	÷0.984	×0.690	—	×1.018	4.61%
HBP% /PA	3.23%	—	×0.940	—	×1.018	3.09%
Singles /BIP	31.82%	÷0.968	×0.930	—	×1.018	31.11%
Doubles /BIP	0.00%	÷0.967	×0.830	—	×1.018	0.00%
Triples /BIP	0.00%	÷0.900	×0.970	—	×1.018	0.00%
Home runs /BIP	4.55%	÷0.989	×0.700	—	×1.018	3.28%

Factors used: league row International League. Park (home-season share, regressed): HR 98, 1B 94, 2B 93, 3B 80, K 97, BB 97 — 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).

Result: wOBA .331 → .287; ISO .107 → .075; BABIP .333 → .322. 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 · 279 PAwOBA .359 → .302 (−58)K% 29.4% → 34.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	29.39%	÷1.034	×1.200	—	—	34.10%
BB% (unintentional) /PA	7.53%	÷0.956	×0.690	—	×1.033	5.61%
HBP% /PA	1.79%	—	×0.940	—	×1.033	1.74%
Singles /BIP	28.82%	÷1.049	×0.930	×1.015	×1.033	26.79%
Doubles /BIP	8.82%	÷0.916	×0.830	×1.015	×1.033	8.39%
Triples /BIP	0.00%	÷0.900	×0.920	×1.015	×1.033	0.00%
Home runs /BIP	5.88%	÷0.995	×0.700	—	×1.033	4.27%

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 ×1.015.

Result: wOBA .359 → .302; ISO .179 → .137; BABIP .398 → .365. 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 A+San Jose Giants · 251 PAwOBA .338 → .271 (−67)K% 19.9% → 27.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.92%	÷0.975	×1.340	—	—	27.38%
BB% (unintentional) /PA	5.58%	÷0.936	×0.710	—	×0.998	4.22%
HBP% /PA	1.20%	—	×0.790	—	×0.998	0.94%
Singles /BIP	20.65%	÷1.017	×0.910	×0.950	×0.998	17.52%
Doubles /BIP	5.43%	÷0.973	×0.820	×0.950	×0.998	4.34%
Triples /BIP	1.09%	÷0.903	×0.760	×0.950	×0.998	0.87%
Home runs /BIP	6.52%	÷0.947	×0.920	—	×0.998	6.32%

Factors used: league row CAL. Park (home-season share, regressed): HR 89, 1B 103, 2B 95, 3B 81, K 95, BB 87 — applied at half strength. Age: age 23 vs a level average of 22.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .338 → .271; ISO .214 → .181; BABIP .291 → .243. 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 AARichmond Flying Squirrels · 87 PAwOBA .386 → .345 (−41)K% 24.1% → 30.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.14%	÷0.975	×1.220	—	—	30.19%
BB% (unintentional) /PA	6.90%	÷1.011	×0.700	—	×1.027	4.90%
HBP% /PA	0.00%	—	×0.850	—	×1.027	0.00%
Singles /BIP	27.59%	÷1.020	×0.970	—	×1.027	26.93%
Doubles /BIP	6.90%	÷0.916	×0.860	—	×1.027	6.65%
Triples /BIP	1.72%	÷1.147	×0.950	—	×1.027	1.47%
Home runs /BIP	6.90%	÷0.890	×0.780	—	×1.027	6.21%

Factors used: league row EL. Park (home-season share, regressed): HR 78, 1B 104, 2B 83, 3B 129, K 95, 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).

Result: wOBA .386 → .345; ISO .228 → .202; BABIP .382 → .367. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Josh Bardlast yr '11 career totals — 9 seasons, 1,958 PA	2.9	1,958	38	1	252	318	381	+33	+24	10.4	10.4
/162	664	13	0	+11.1	+8.0	3.5	pk7: 11
#2Jim Essian'73-'84 * career totals — 9 seasons, 2,146 PA	3.2	2,146	33	9	239*	326*	368*	+34	-1	8.0	7.9
/162	664	10	3	+10.5	-0.4	2.5	pk7: 8
#3Curt Casalilast yr '24 career totals — 10 seasons, 1,566 PA	2.4	1,566	47	2	217	311	367	+28	+19	7.8	7.9
/162	664	20	1	+11.9	+7.9	3.3	pk7: 8
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 8 projected seasons	2.3	1,558	41	5	238	321	374	+28	+10	6.6	6.7
/162	664	18	2	+11.9	+4.2	2.8	pk7: 7
#4Devin Mesoracolast yr '18 career totals — 8 seasons, 1,574 PA	2.4	1,574	58	4	232	309	406	+28	-13	6.0	6.2
/162	664	24	2	+11.9	-5.3	2.5	pk7: 6
#5Jerry May'64-'73 * career totals — 7 seasons, 1,716 PA	2.6	1,716	15	1	236*	314*	355*	+31	+0	5.6	5.6
/162	664	6	0	+11.8	+0.0	2.2	pk7: 6
#6Lenny Webster'89-'00 * career totals — 9 seasons, 1,617 PA	2.4	1,617	33	1	244*	313*	372*	+28	+0	4.9	5.3
/162	664	14	0	+11.4	+0.0	2.0	pk7: 6

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
Joey Bart (OGILVIE)	30	45	50	45	55	235/331/381	146	301	5	1	26%	10%	105	+0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Michael McKenry 2015 · MLB	30	50→47	52→55	41→40	50	256/324/424	168	301	20	6	22%	8%	111	+2.1	219/310/363	144	287	14	6	27%	11%	93	+0.8	178/284/300	122	248	11	3	30%	12%	68	-0.4
✕James McCann 2020 · MLB	30	51→55	50	43→45	43	253/307/407	154	321	18	4	27%	6%	101	+1.4	246/306/395	149	319	18	5	28%	7%	98	+1.2	243/286/397	153	300	21	1	26%	5%	91	+0.3
●John Buck 2010 · MLB	30	45→53	53→60	39→30	47	232/299/414	182	279	20	3	25%	8%	100	+1.3	245/305/422	177	295	22	2	24%	7%	104	+1.6	236/304/405	169	281	22	0	24%	8%	101	+1.0
✕Welington Castillo 2017 · MLB	30	47→56	53→55	48→30	44	245/303/414	169	298	22	3	25%	7%	101	+1.4	250/301/422	172	311	23	3	27%	6%	103	+1.5	244/292/420	176	300	26	1	28%	6%	99	+0.6
✕Cameron Rupp 2018 · MLB	29	45→49	54→55	47→30	44	234/296/414	180	303	21	3	30%	8%	99	+1.2	200/270/360	160	289	20	3	36%	8%	77	-0.3	162/236/306	144	234	20	0	39%	8%	50	-1.1
✕Jarrod Saltalamacchia 2015 · MLB	30	48→54	52→60	42→40	48	238/314/413	175	323	20	3	31%	10%	105	+1.7	205/291/367	162	297	20	3	35%	11%	86	+0.3	167/258/318	152	242	20	0	38%	11%	64	-0.5
✕George Kottaras 2012 · MLB	29	48→54	51→55	43→30	53	241/318/414	173	288	18	4	23%	10%	106	+1.8	226/329/416	190	287	24	5	28%	13%	112	+2.2	190/315/383	193	236	27	1	31%	15%	100	+0.3
✕Matthew LeCroy 2007 · MLB	31	50	53→55	46→30	52	255/335/421	166	302	22	3	23%	10%	114	+2.4	204/270/312	108	246	11	5	21%	7%	65	-1.2	157/215/221	63	193	5	0	20%	5%	24	-2.1
✕Nick Hundley 2012 · MLB	28	52→45	50→55	42→40	47	258/319/426	168	322	16	4	24%	8%	109	+2.0	224/275/358	134	280	14	3	25%	6%	78	-0.3	259/299/420	161	312	16	3	22%	5%	102	+0.8
✕Devin Mesoraco 2017 · MLB	29	46→50	52→60	42→40	51	235/313/401	166	271	19	6	22%	9%	102	+1.5	220/303/375	155	253	19	5	21%	9%	93	+0.8	208/295/367	159	233	21	1	21%	9%	89	+0.2
✕P.J. Higgins 2023 · MLB	30	51→54	46→45	49→40	50	249/324/388	139	320	13	5	25%	9%	103	+1.5	227/282/338	111	299	10	3	26%	7%	75	-0.5	212/261/304	93	278	9	0	26%	5%	57	-1.4
✕John Hicks 2019 · MLB	29	51→52	49→55	43→50	41	254/298/402	148	325	17	6	27%	6%	97	+1.1	234/274/404	170	308	22	6	31%	5%	88	+0.4	211/245/385	174	278	23	9	33%	4%	71	-0.4
●Chris Iannetta 2013 · MLB	30	45→55	51→60	41→45	58	231/334/391	160	274	19	6	22%	12%	108	+1.9	231/343/379	148	295	16	4	25%	14%	108	+1.9	220/340/362	142	282	15	2	25%	14%	105	+1.0
✕Austin Nola 2020 · MLB	30	49→52	46→45	48→45	49	244/312/377	133	296	14	6	22%	8%	96	+1.0	257/328/392	135	300	13	5	18%	8%	105	+1.7	259/334/370	111	295	10	1	15%	8%	103	+0.7
✕Curt Casali 2020 · MLB	31	49	48→50	40→30	48	244/309/380	137	296	16	3	23%	8%	95	+1.0	230/320/392	162	298	19	5	28%	10%	103	+1.5	207/312/292	85	276	8	0	25%	11%	77	-0.1
✕Kelly Shoppach 2011 · MLB	31	45→50	54→60	46→30	47	226/328/412	186	314	22	3	33%	10%	111	+2.1	213/296/377	164	294	20	4	33%	8%	91	+0.7	197/276/352	155	274	19	1	34%	7%	79	-0.1
✕Josh Phegley 2017 · MLB	29	47→50	52→60	46→40	45	244/297/419	176	277	19	3	20%	6%	100	+1.3	224/282/372	148	263	15	3	21%	6%	84	+0.1	216/271/370	154	248	17	0	21%	5%	80	-0.1
✕Tim Beckham 2021 · MLB	31	46→55	55	39→50	43	238/296/424	186	300	22	5	28%	7%	101	+1.4	249/299/400	151	324	19	7	28%	6%	96	+1.0	255/299/384	129	337	17	4	28%	5%	89	+0.2
✕Omar Narváez 2021 · MLB	29	50→54	52→50	42→30	54	256/338/418	162	300	21	3	22%	10%	115	+2.4	240/317/367	127	286	13	2	20%	9%	95	+1.0	234/312/347	112	279	11	0	19%	9%	90	+0.3
✕Carson Kelly 2024 · MLB	30	45→52	46→55	49→40	51	224/301/355	130	269	14	5	22%	9%	87	+0.4	243/319/387	144	279	18	3	19%	9%	101	+1.4	248/328/392	144	277	19	1	18%	9%	106	+1.1

Joey Bart

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps