Connor Joe

1B Tacoma Rainiers

Age 34 R/R 5'11" / 205 lbs AAA K +7%HR -5% Svc 3.753 · Ctrl thru 2029

Overview

AAAArb-1FA 2030

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	31	MLBPIT	416	.228/.321/.368	9	2	97	-0.3
2025	32	AAACIN	205	.225/.346/.306	0	5	50	—	.186/.273/.251
2025	32	MLBCIN	80	.186/.269/.243	0	2	45	-1.0
2026	33	AAASEA	366	.261/.359/.433	11	6	65	—	.203/.273/.315
2026	33	MLBSEA	45	.179/.289/.308	1	2	75	-0.8
2027PROJ10% MLB	34	MLBSEA	26	.212/.292/.329	0	0	78	-0.1
2028PROJ	35	MLBSEA	196	.200/.279/.304	3	1	68	-1.2

Last 3 seasons WAR -2.1 · Next 2 projected WAR -1.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2029Service3.753First FA2030

2027Arb-1$0.3M2028Arb-2$0.4M2029Ext$0.7M

Skills · percentileStatcast 2024-2026

Bat Spd56

Speed40

xwOBA29

Barrel%26

Avg EV16

CompsIldelfonso Lara (age 34) · Fernando Rios (age 34) · Paulo Orlando (age 33)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 8078vR 71

AVG/OBP/SLG.212 / .292 / .329

PA26

HR0

K%23

BB%8

BABIP263

ISO42

MLB%10%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$1M ctrl surplus

Tools · Splits · ContractCON 40 / POW 40

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT40

xAVG

100.209

POWER40

Barrel%

265.2

Avg EV

1686.5

Bat Spd

5671.9

EYE60

scouting grade only

SPEED50

Sprint

4027.0

Platoon Splits2024-2025 · 496 PA

vs LHP

vs RHP

Edge

210

286

—

wRC+

—

wOBA

297

295

—

ISO

123

129

▶R

BABIP

266

280

▶R

20.5%

23.8%

◀L

BB%

11.0%

9.4%

◀L

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

Status Arb-1

MLB Debut 2019

Service 3.753 yrs.days

Team Control Through 2029

First FA Year 2030

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-1	$0.3M	—	—	—
2028	Arb-2	$0.4M	—	—	—
2029	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$-5M	+$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.

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)
2015	22	A	West Virginia Power	—	357	290	71	12	1	1	50	34	8	0	4	245	371	303	674	59	270	10	14	312	60	—	—	—	—	—	—
2016	23	A+	Bradenton Marauders	—	443	390	108	26	2	5	45	84	2	2	4	277	354	392	746	115	337	19	10	334	70	—	—	—	—	—	—
2016	23	INTL	Surprise Saguaros	—	62	49	10	1	0	2	11	11	2	3	0	204	371	347	718	143	222	18	18	338	115	—	—	—	—	—	—
2017	24	AA	Mississippi Braves	—	343	294	65	12	4	5	40	58	4	2	5	221	322	340	663	119	256	17	12	300	55	—	—	—	—	—	—
2018	25	AAA	Oklahoma City Dodgers	—	188	160	47	10	2	6	22	31	3	2	0	294	389	494	883	200	328	16	12	385	100	—	—	—	—	—	—
2018	25	AA	Tulsa Drillers	—	248	204	62	16	1	11	38	57	5	1	2	304	423	554	977	250	375	23	15	427	104	—	—	—	—	—	—
2019	26	MLB	San Francisco Giants	—	16	15	1	0	0	0	1	5	0	0	0	67	125	67	192		100	31	6	100	-45	-3	+0	+0	-5	+0	-0.7
2019	26	AAA	Oklahoma City Dodgers	—	446	360	108	26	1	15	72	81	10	1	2	300	430	503	933	203	347	18	16	411	99	—	—	—	—	—	—
2021	28	MLB	Colorado Rockies	—	211	179	51	9	0	8	26	41	3	0	0	285	385	469	854	184	323	19	12	376	132	+8	+0	-1	-3	+5	0.8
2021	28	AAA	Albuquerque Isotopes	—	110	92	30	7	0	9	15	22	1	1	0	326	426	696	1.122	370	333	20	14	469	109	—	—	—	—	—	—
2022	29	MLB	Colorado Rockies	—	467	404	96	20	4	7	55	97	7	6	2	238	339	359	698	121	296	21	12	319	94	-3	+0	-4	-5	+10	-0.2
2023	30	MLB	Pittsburgh Pirates	—	472	413	102	31	4	11	50	110	8	3	5	247	340	421	761	174	311	23	11	340	117	+10	-1	-1	-5	+10	1.3
2024	31	MLB	Pittsburgh Pirates	—	416	364	83	22	1	9	44	91	6	2	2	228	321	368	689	140	278	22	11	312	97	-1	-0	-3	-7	+9	-0.3
2025	32	MLB	Cincinnati Reds	—	80	70	13	4	0	0	7	20	1	2	2	186	269	243	512	57	250	25	9	236	45	-5	-0	-3	-3	+2	-1.0
2025	32	AAA	Louisville Bats	—	205	173	39	10	2	0	29	36	3	5	3	225	346	306	653	81	285	18	14	307	50	—	—	—	—	—	—
2026	33	MLB	Seattle Mariners	—	45	39	7	2	0	1	6	15	0	2	0	179	289	308	597	128	261	33	13	277	75	-1	+0	-1	-7	+1	-0.8
2026	33	AAA	Tacoma Rainiers	—	366	314	82	21	0	11	45	71	3	6	6	261	359	433	792	172	301	19	12	352	65	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1707	1484	353	88	9	36	189	379	25	15	11	238	334	382	716	144	294	22	11	323	105	+10	-1	-12	-36	+37	-0.3
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2015	22	A MLE	West Virginia Power	—	357	308	66	10	1	1	32	45	8	0	4	214	305	263	568	49	238	13	9	257	60	—	—	—	—	—	—
2016	23	A+ MLE	Bradenton Marauders	—	443	403	93	22	2	4	33	120	2	2	4	231	292	325	617	94	305	27	7	271	70	—	—	—	—	—	—
2017	24	AA MLE	Mississippi Braves	—	343	309	60	12	3	4	25	73	4	2	5	194	263	291	555	97	232	21	7	250	55	—	—	—	—	—	—
2018	25	AAA MLE	Oklahoma City Dodgers	—	188	166	42	8	2	5	16	41	3	2	0	253	330	416	745	163	295	22	9	316	100	—	—	—	—	—	—
2018	25	AA MLE	Tulsa Drillers	—	248	217	52	13	1	8	26	72	5	1	2	240	335	419	754	180	318	29	10	322	104	—	—	—	—	—	—
2019	26	MLB MLE	San Francisco Giants	—	16	15	1	0	0	0	1	5	0	0	0	67	125	67	192		100	31	6	101	-45	-3	+0	+0	-5	+0	-0.7
2019	26	AAA MLE	Oklahoma City Dodgers	—	446	380	87	20	1	11	52	103	10	1	2	229	337	374	711	145	274	23	12	314	99	—	—	—	—	—	—
2021	28	MLB MLE	Colorado Rockies	—	211	179	49	9	0	7	26	41	3	0	0	274	375	441	816	168	323	19	12	363	132	+8	+0	-1	-3	+5	0.8
2021	28	AAA MLE	Albuquerque Isotopes	—	110	97	23	6	0	5	10	28	1	1	0	237	315	454	768	216	254	25	9	330	109	—	—	—	—	—	—
2022	29	MLB MLE	Colorado Rockies	—	467	404	91	19	3	6	55	97	7	6	2	225	328	332	660	106	296	21	12	308	94	-3	+0	-4	-5	+10	-0.2
2023	30	MLB MLE	Pittsburgh Pirates	—	472	413	102	30	4	12	50	110	8	3	5	247	340	426	766	179	311	23	11	341	117	+10	-1	-1	-5	+10	1.3
2024	31	MLB MLE	Pittsburgh Pirates	—	416	365	83	21	1	10	43	91	6	2	2	227	319	373	691	145	278	22	10	312	97	-1	-0	-3	-7	+9	-0.3
2025	32	MLB MLE	Cincinnati Reds	—	80	70	13	4	0	0	7	20	1	2	2	186	269	243	512	57	250	25	9	235	45	-5	-0	-3	-3	+2	-1.0
2025	32	AAA MLE	Louisville Bats	—	205	183	34	8	2	0	19	44	3	5	3	186	273	251	525	66	246	21	9	242	50	—	—	—	—	—	—
2026	33	MLB MLE	Seattle Mariners	—	45	39	7	2	0	1	6	15	0	2	0	179	289	308	597	128	261	33	13	279	75	-1	+0	-1	-7	+1	-0.8
2026	33	AAA MLE	Tacoma Rainiers	—	366	330	67	16	0	7	29	85	3	6	6	203	273	315	589	112	244	23	8	264	65	—	—	—	—	—	—
2015	22	A MLE	West Virginia Power	—	357	308	66	10	1	1	32	45	8	0	4	214	305	263	568	49	244	13	9	257	60	—	—	—	—	—	—
2015	22	A RAW	West Virginia Power	—	357	290	71	12	1	1	50	34	8	0	4	245	371	303	674	59	270	10	14	312	60	—	—	—	—	—	—
2016	23	A+ MLE	2 teams	—	505	458	105	25	2	4	38	136	4	5	4	229	294	319	613	90	313	27	8	271	70	—	—	—	—	—	—
2016	23	A+ RAW	2 teams	—	505	439	118	27	2	7	56	95	4	5	4	269	356	387	743	118	325	19	11	334	70	—	—	—	—	—	—
2017	24	AA MLE	Mississippi Braves	—	343	309	60	12	3	4	25	73	4	2	5	194	263	291	555	97	238	21	7	250	55	—	—	—	—	—	—
2017	24	AA RAW	Mississippi Braves	—	343	294	65	12	4	5	40	58	4	2	5	221	322	340	663	119	256	17	12	300	55	—	—	—	—	—	—
2018	25	AA MLE	2 teams	—	436	384	93	21	3	12	41	113	8	3	2	242	328	406	734	164	310	26	9	319	102	—	—	—	—	—	—
2018	25	AA RAW	2 teams	—	436	364	109	26	3	17	60	88	8	3	2	299	409	527	936	228	352	20	14	409	102	—	—	—	—	—	—
2019	26	AAA MLE	2 teams	—	462	395	88	20	1	11	53	108	10	1	2	223	330	362	692	139	275	23	11	307	94	—	—	—	—	—	—
2019	26	AAA RAW	2 teams	—	462	375	109	26	1	15	73	86	10	1	2	291	419	485	905	195	338	19	16	401	94	—	—	—	—	—	—
2021	28	MLB MLE	2 teams	—	321	276	70	14	0	12	36	69	4	1	0	254	348	435	783	181	290	21	11	351	124	+9	+0	-1	-3	+7	1.2
2021	28	MLB RAW	2 teams	—	321	271	81	16	0	17	41	63	4	1	0	299	399	546	945	247	327	20	13	408	124	+9	+0	-1	-3	+7	1.2
2022	29	MLB MLE	Colorado Rockies	—	467	404	91	19	3	6	55	97	7	6	2	225	328	332	660	106	281	21	12	308	94	-3	+0	-4	-5	+10	-0.2
2022	29	MLB RAW	Colorado Rockies	—	467	404	96	20	4	7	55	97	7	6	2	238	339	359	698	121	296	21	12	319	94	-3	+0	-4	-5	+10	-0.2
2023	30	MLB MLE	Pittsburgh Pirates	—	472	413	102	30	4	12	50	110	8	3	5	247	340	426	766	179	308	23	11	341	117	+10	-1	-1	-5	+10	1.3
2023	30	MLB RAW	Pittsburgh Pirates	—	472	413	102	31	4	11	50	110	8	3	5	247	340	421	761	174	311	23	11	340	117	+10	-1	-1	-5	+10	1.3
2024	31	MLB MLE	Pittsburgh Pirates	—	416	365	83	21	1	10	43	91	6	2	2	227	319	373	691	145	274	22	10	312	97	-1	-0	-3	-7	+9	-0.3
2024	31	MLB RAW	Pittsburgh Pirates	—	416	364	83	22	1	9	44	91	6	2	2	228	321	368	689	140	278	22	11	312	97	-1	-0	-3	-7	+9	-0.3
2025	32	AAA MLE	2 teams	—	285	253	47	12	2	0	26	64	4	7	5	186	272	249	521	63	246	22	9	240	49	—	—	—	—	—	—
2025	32	AAA RAW	2 teams	—	285	243	52	14	2	0	36	56	4	7	5	214	325	288	613	74	275	20	13	287	49	—	—	—	—	—	—
2026	33	AAA MLE	2 teams	—	411	369	74	18	0	8	35	100	3	8	6	201	275	314	590	114	249	24	9	266	66	—	—	—	—	—	—
2026	33	AAA RAW	2 teams	—	411	353	89	23	0	12	51	86	3	8	6	252	351	419	771	167	297	21	12	343	66	—	—	—	—	—	—
2015	22	A MLE	West Virginia Power	—	357	314	66	10	1	1	32	45	8	0	4	210	305	258	563	48	238	13	9	257	60	—	—	—	—	—	—
2016	23	A+ MLE	2 teams	—	505	458	105	25	2	4	38	136	4	5	4	229	294	319	613	90	305	27	8	271	70	—	—	—	—	—	—
2017	24	AA MLE	Mississippi Braves	—	343	311	60	12	3	4	25	73	4	2	5	193	263	289	553	96	232	21	7	250	55	—	—	—	—	—	—
2018	25	AA MLE	2 teams	—	436	384	93	21	3	12	41	113	8	3	2	242	328	406	734	164	308	26	9	319	102	—	—	—	—	—	—
2019	26	AAA MLE	2 teams	—	462	396	88	20	1	11	53	108	10	1	2	222	330	361	691	139	268	23	11	307	94	—	—	—	—	—	—
2021	28	MLB MLE	2 teams	—	321	278	70	14	0	12	36	69	4	1	0	252	348	432	780	180	300	21	11	351	124	—	—	—	—	—	—
2022	29	MLB MLE	Colorado Rockies	—	467	402	91	19	3	6	55	97	7	6	2	226	328	333	662	107	296	21	12	308	94	—	—	—	—	—	—
2023	30	MLB MLE	Pittsburgh Pirates	—	472	411	102	30	4	12	50	110	8	3	5	248	340	428	768	180	311	23	11	341	117	—	—	—	—	—	—
2024	31	MLB MLE	Pittsburgh Pirates	—	416	364	83	21	1	10	43	91	6	2	2	228	319	374	692	146	278	22	10	312	97	—	—	—	—	—	—
2025	32	AAA MLE	2 teams	—	285	253	47	12	2	0	26	64	4	7	5	186	272	249	521	63	247	22	9	240	49	—	—	—	—	—	—
2026	33	AAA MLE	2 teams	—	411	370	74	18	0	8	35	100	3	8	6	200	275	314	589	114	246	24	9	266	66	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	31	MLB MLE	Pittsburgh Pirates	—	416	364	83	21	1	10	43	91	6	2	2	228	319	374	692	146	278	22	10	312	97	—	—	—	—	—	—
2025	32	AAA MLE	2 teams	—	285	253	47	12	2	0	26	64	4	7	5	186	272	249	521	63	247	22	9	240	49	—	—	—	—	—	—
2026	33	AAA MLE	2 teams	—	411	370	74	18	0	8	35	100	3	8	6	200	275	314	589	114	246	24	9	266	66	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	34	MLB MLE	SEA	10%	366	326	71	17	1	7	33	84	4	6	2	214	294	333	627	119	266	23	9	284	78	-9	+0	+1	-7	+8	-0.5
▸ 2027 — real world (MLB)
2027	34	MLB CTX	SEA	10%	26	24	4	1	0	0	2	6	0	0	0	212	292	329	621	116	263	23	8	282	78	-1	+0	+0	-0	+1	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	35	MLB MLE	SEA	100%	196	175	36	8	1	3	17	47	2	1	1	202	281	308	589	106	254	24	9	268	68	-8	-0	-5	-4	+4	-1.2
2028	35	MLB CTX	SEA	100%	196	175	36	8	1	3	17	47	2	1	1	200	279	304	583	104	252	24	9	266	68	-8	-0	-5	-4	+4	-1.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1903	1659	389	96	10	39	206	426	27	16	12	234	329	375	704	140	291	22	11	317	85	+2	-2	-17	-40	+41	-1.5
/ 162G	—	A+C		—	650	567	132	33	3	13	70	146	9	5	4	233	326	370	696	138	290	22	11	317	85	+1	-1	-6	-14	+14	-0.5
Career	—	MLE		—	4926	4337	965	222	22	88	474	1112	70	43	39	223	309	345	654	122	276	23	10	293	85	-4	-1	-16	-44	+47	-2.0
/ 162G	—	MLE		—	650	572	128	29	3	12	63	147	9	6	5	224	311	348	658	124	278	23	10	293	85	-1	-0	-5	-13	+14	-0.6

How the minor-league lines were translated

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

2026 AAATacoma Rainiers · 366 PAwOBA .345 → .264 (−82)K% 19.4% → 23.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.40%	÷1.000	×1.200	—	—	23.28%
BB% (unintentional) /PA	12.02%	÷1.000	×0.690	—	×0.940	7.80%
HBP% /PA	0.82%	—	×0.940	—	×0.940	0.72%
Singles /BIP	20.58%	÷1.000	×0.930	×0.971	×0.940	17.47%
Doubles /BIP	8.64%	÷1.000	×0.830	×0.971	×0.940	6.55%
Triples /BIP	0.00%	÷1.000	×0.970	×0.971	×0.940	0.00%
Home runs /BIP	4.53%	÷1.000	×0.700	—	×0.940	2.98%

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 34 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (6.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.971.

Result: wOBA .345 → .264; ISO .172 → .123; BABIP .301 → .244. 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 AAALouisville Bats · 205 PAwOBA .300 → .242 (−58)K% 17.6% → 21.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.56%	÷0.975	×1.200	—	—	21.61%
BB% (unintentional) /PA	14.15%	÷1.002	×0.690	—	×0.942	9.18%
HBP% /PA	1.46%	—	×0.940	—	×0.942	1.30%
Singles /BIP	19.71%	÷1.049	×0.930	×1.040	×0.942	17.11%
Doubles /BIP	7.30%	÷0.992	×0.830	×1.040	×0.942	5.98%
Triples /BIP	1.46%	÷0.900	×0.970	×1.040	×0.942	1.54%
Home runs /BIP	0.00%	÷0.901	×0.700	—	×0.942	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 80, 1B 110, 2B 98, 3B 80, K 95, BB 100 — applied at half strength. Age: age 33 vs a level average of 27.2 → −5.8% on BB/HBP/hit rates (5.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.040.

Result: wOBA .300 → .242; ISO .081 → .073; BABIP .285 → .246. 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 AAAAlbuquerque Isotopes · 110 PAwOBA .464 → .330 (−134)K% 20.0% → 25.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.00%	÷0.958	×1.200	—	—	25.05%
BB% (unintentional) /PA	13.64%	÷1.032	×0.690	—	×0.982	8.95%
HBP% /PA	0.91%	—	×0.940	—	×0.982	0.84%
Singles /BIP	20.00%	÷1.110	×0.930	×0.978	×0.982	16.10%
Doubles /BIP	10.00%	÷0.988	×0.830	×0.978	×0.982	8.07%
Triples /BIP	0.00%	÷1.150	×0.920	×0.978	×0.982	0.00%
Home runs /BIP	12.86%	÷1.172	×0.700	—	×0.982	7.54%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 134, 1B 122, 2B 98, 3B 130, K 92, BB 106 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.978.

Result: wOBA .464 → .330; ISO .370 → .239; BABIP .333 → .254. 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 · 446 PAwOBA .405 → .314 (−91)K% 18.2% → 23.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.16%	÷1.014	×1.290	—	—	23.10%
BB% (unintentional) /PA	16.14%	÷0.993	×0.710	—	×1.003	11.58%
HBP% /PA	2.24%	—	×0.980	—	×1.003	2.20%
Singles /BIP	23.66%	÷1.048	×0.900	×0.950	×1.003	19.37%
Doubles /BIP	9.32%	÷1.012	×0.810	×0.950	×1.003	7.11%
Triples /BIP	0.36%	÷1.045	×0.810	×0.950	×1.003	0.26%
Home runs /BIP	5.38%	÷1.073	×0.780	—	×1.003	3.92%

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 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 ×0.950.

Result: wOBA .405 → .314; ISO .203 → .152; BABIP .347 → .274. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2018 AATulsa Drillers · 248 PAwOBA .416 → .322 (−94)K% 23.0% → 29.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.98%	÷0.964	×1.220	—	—	29.10%
BB% (unintentional) /PA	15.32%	÷1.033	×0.700	—	×0.988	10.26%
HBP% /PA	2.02%	—	×0.870	—	×0.988	1.73%
Singles /BIP	23.13%	÷0.987	×0.920	×0.968	×0.988	20.63%
Doubles /BIP	10.88%	÷0.991	×0.840	×0.968	×0.988	8.82%
Triples /BIP	0.68%	÷0.907	×0.940	×0.968	×0.988	0.67%
Home runs /BIP	7.48%	÷1.147	×0.800	—	×0.988	5.16%

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 26 vs a level average of 24.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.968.

Result: wOBA .416 → .322; ISO .250 → .184; BABIP .375 → .318. 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 · 188 PAwOBA .379 → .316 (−62)K% 16.5% → 21.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.49%	÷0.970	×1.290	—	—	21.94%
BB% (unintentional) /PA	11.70%	÷1.021	×0.710	—	×1.018	8.28%
HBP% /PA	1.60%	—	×0.980	—	×1.018	1.59%
Singles /BIP	22.48%	÷0.992	×0.900	×1.022	×1.018	21.22%
Doubles /BIP	7.75%	÷1.029	×0.810	×1.022	×1.018	6.35%
Triples /BIP	1.55%	÷1.020	×0.810	×1.022	×1.018	1.28%
Home runs /BIP	4.65%	÷1.020	×0.780	—	×1.018	3.62%

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 26 vs a level average of 27.2 → +1.8% on BB/HBP/hit rates (1.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.022.

Result: wOBA .379 → .316; ISO .200 → .158; BABIP .328 → .295. 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 AAMississippi Braves · 343 PAwOBA .292 → .250 (−42)K% 16.9% → 21.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.91%	÷0.970	×1.220	—	—	21.26%
BB% (unintentional) /PA	10.79%	÷0.989	×0.680	—	×0.998	7.40%
HBP% /PA	1.17%	—	×0.840	—	×0.998	0.98%
Singles /BIP	18.64%	÷1.026	×0.920	×1.009	×0.998	16.85%
Doubles /BIP	5.08%	÷0.951	×0.910	×1.009	×0.998	4.90%
Triples /BIP	1.69%	÷1.146	×0.880	×1.009	×0.998	1.31%
Home runs /BIP	2.12%	÷0.925	×0.800	—	×0.998	1.83%

Factors used: league row SL. Park (home-season share, regressed): HR 85, 1B 105, 2B 90, 3B 129, K 94, BB 98 — applied at half strength. Age: age 25 vs a level average of 24.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.009.

Result: wOBA .292 → .250; ISO .119 → .107; BABIP .256 → .232. 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+Bradenton Marauders · 443 PAwOBA .329 → .271 (−58)K% 19.0% → 27.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.96%	÷0.996	×1.420	—	—	27.03%
BB% (unintentional) /PA	10.16%	÷1.009	×0.750	—	×0.988	7.46%
HBP% /PA	0.45%	—	×0.930	—	×0.988	0.41%
Singles /BIP	24.51%	÷0.999	×0.920	×1.004	×0.988	22.39%
Doubles /BIP	8.50%	÷1.059	×0.960	×1.004	×0.988	7.64%
Triples /BIP	0.65%	÷0.900	×0.810	×1.004	×0.988	0.58%
Home runs /BIP	1.63%	÷1.098	×0.880	—	×0.988	1.29%

Factors used: league row FSL. Park (home-season share, regressed): HR 120, 1B 100, 2B 112, 3B 80, K 99, BB 102 — applied at half strength. Age: age 24 vs a level average of 22.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.004.

Result: wOBA .329 → .271; ISO .115 → .094; BABIP .337 → .305. 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
#1Daric Bartonlast yr '14 career totals — 8 seasons, 2,085 PA	3.1	2,085	30	13	247	356	365	-37	-10	3.0	3.4
/162	664	10	4	-11.9	-3.1	0.9	pk7: 4
#2Jerry Turner'74-'83 * career totals — 7 seasons, 1,931 PA	2.9	1,931	45	45	251*	316*	413*	-22	-11	3.0	3.4
/162	664	15	15	-7.7	-3.7	1.0	pk7: 4
#3Dan Johnson'05-'15 * career totals — 5 seasons, 1,625 PA	2.4	1,625	57	1	226*	330*	401*	-30	-3	2.2	2.8
/162	664	23	0	-12.2	-1.2	0.9	pk7: 3
#4Norm Miller'65-'74 * career totals — 6 seasons, 1,561 PA	2.4	1,561	24	16	238*	325*	391*	-14	-3	2.4	2.7
/162	664	10	7	-6.1	-1.3	1.0	pk7: 3
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	2.8	1,868	39	15	238	329	381	-33	-14	1.8	2.2
/162	664	14	5	-11.9	-5.0	0.6	pk7: 3
#5Travis Sniderlast yr '15 career totals — 8 seasons, 1,971 PA	3.0	1,971	54	22	244	311	399	-21	-17	1.4	1.8
/162	664	18	7	-7.1	-5.8	0.5	pk7: 2
#6Pete LaCock'72-'80 * career totals — 7 seasons, 1,945 PA	2.9	1,945	27	8	251*	322*	392*	-33	-4	-0.4	0.2
/162	664	9	3	-11.2	-1.2	-0.1	pk7: 1

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
Connor Joe (OGILVIE)	34	40	40	50	60	212/292/330	118	266	5	4	23%	9%	78	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Ildelfonso Lara 2009 · AAA	34	48→51	42→45	50→45	47	233/291/341	108	288	9	6	22%	7%	79	-0.2	229/288/340	111	296	11	8	25%	7%	78	-0.3	227/285/319	92	295	10	5	25%	6%	70	-0.4
✕Fernando Rios 2013 · AAA	34	47	41→40	49→50	47	230/283/323	93	269	9	10	18%	6%	72	-0.7	225/277/321	96	263	9	10	17%	6%	69	-0.9	215/256/250	35	242	3	4	12%	4%	43	-0.6
✕Paulo Orlando 2019 · MLB	33	46→56	43→45	48→55	39	228/265/337	110	283	10	8	24%	4%	68	-1.0	201/251/327	126	259	13	9	27%	4%	62	-1.4	170/222/294	124	221	13	8	29%	3%	42	-1.8
●Reynaldo Rodriguez 2019 · AAA	33	43→45	44→55	50	45	213/275/324	111	279	12	15	28%	8%	70	-0.9	267/311/489	222	299	31	13	22%	5%	122	+2.9	288/324/555	267	305	41	11	20%	4%	144	+2.0
✕Vinny Rottino 2015 · MLB	35	46→56	46→45	51→55	46	231/281/359	129	264	13	16	18%	6%	80	-0.2	210/273/303	93	271	9	4	24%	7%	64	-1.3	198/264/276	78	255	8	1	24%	7%	53	-1.4
✕Issmael Salas 2016 · AAA	34	49→48	41→45	45→50	45	238/282/335	98	270	9	7	16%	5%	74	-0.5	233/279/341	108	260	10	6	15%	5%	75	-0.5	230/272/335	105	252	11	3	13%	4%	69	-0.6
✕Nick Ahmed 2024 · MLB	34	44→54	43→55	49→55	44	218/268/334	116	271	11	11	24%	6%	69	-0.9	228/278/333	105	286	10	9	23%	6%	72	-0.7	225/266/292	66	287	5	5	22%	5%	58	-0.7
✕Pedro Diaz 2013 · AAA	34	43→47	42→45	47→45	42	214/259/319	105	267	10	6	24%	5%	62	-1.4	221/247/341	120	270	14	4	24%	3%	62	-1.4	221/241/338	117	262	15	0	22%	2%	58	-0.7
✕Shawn Wooten 2007 · MLB	35	42	43→45	47→30	41	210/254/317	107	250	12	3	22%	4%	60	-1.6	201/252/285	84	249	8	5	22%	6%	52	-2.2	175/230/219	43	218	4	0	20%	5%	27	-1.2
✕Brendan Ryan 2015 · MLB	33	41→51	38→40	43→55	47	197/261/276	79	246	6	8	22%	7%	53	-2.1	202/255/279	77	271	5	8	26%	6%	51	-2.2	190/243/253	63	256	3	7	25%	6%	39	-1.4
✕Ryan Roberts 2015 · MLB	34	44→52	44→50	41→55	46	219/271/332	113	265	11	7	22%	7%	70	-0.9	224/276/353	129	256	14	4	18%	6%	76	-0.4	221/271/348	127	243	14	0	16%	6%	72	-0.6
✕Nick Green 2013 · MLB	34	42→46	46→50	42→45	41	215/261/349	134	257	14	5	23%	4%	70	-0.8	201/249/317	116	260	13	6	27%	5%	59	-1.7	161/207/246	84	213	10	1	29%	4%	24	-2.9
✕Mike Rivera 2011 · MLB	34	42	41→55	45	47	204/282/308	105	271	8	6	27%	8%	70	-0.9	201/264/306	105	273	11	6	29%	6%	61	-1.5	183/239/271	88	249	11	3	30%	5%	42	-0.9
✕Jantzen Witte 2024 · AAA	34	42→52	47→45	44→45	42	217/269/353	136	280	15	8	28%	6%	74	-0.5	214/273/354	140	279	16	8	28%	7%	76	-0.4	187/251/323	136	227	18	0	26%	8%	59	-0.5
✕Jeff Mathis 2016 · MLB	33	40→48	43→50	48→45	43	203/258/315	113	271	11	4	29%	7%	61	-1.5	218/271/325	107	298	9	4	28%	6%	68	-1.0	209/264/294	85	295	6	1	29%	7%	59	-0.5
✕Pete Kozma 2021 · MLB	33	43→47	43→45	50	46	211/265/327	116	247	10	8	19%	6%	66	-1.1	201/248/289	88	257	6	8	24%	5%	51	-2.2	182/225/251	69	236	3	6	23%	4%	30	-3.1
✕Joshua Rodriguez 2019 · AAA	34	40→50	44→50	47→50	41	200/255/309	109	280	12	6	32%	7%	59	-1.7	236/290/379	143	302	17	6	27%	7%	88	+0.4	239/293/382	143	298	19	3	26%	7%	86	+0.3
✕Doug Bernier 2014 · MLB	34	47→52	37→40	47→45	44	221/282/302	81	300	4	8	26%	7%	67	-1.1	225/278/310	85	286	7	7	22%	6%	67	-1.1	221/273/300	79	278	7	6	22%	6%	60	-1.1
✕Collin Cowgill 2019 · AAA	33	38→48	45→50	45→55	42	198/254/318	120	257	13	8	28%	6%	61	-1.5	202/270/344	142	274	17	12	31%	7%	74	-0.6	160/241/300	140	214	18	15	34%	7%	50	-1.1
✕Trinidad Robles 2008 · AAA	35	46	42→40	46→45	46	227/280/332	105	272	10	10	20%	6%	73	-0.6	209/264/288	79	260	6	7	21%	6%	57	-1.8	208/262/234	26	270	0	0	21%	5%	41	-1.2

Connor Joe

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps