Greg Allen

CF Iowa Cubs

Age 34 S/R 5'10" / 187 lbs AAA HR -8% Svc 10.000 · Ctrl thru 2027

Overview

AAAExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2023	30	AAAMIL	203	.242/.387/.366	3	26	82	—	.213/.332/.308
2023	30	MLBNYY	28	.217/.333/.478	1	3	116	-0.1
2024	31	AAA/INTL2 orgs	308	.226/.354/.363	5	15	76	—	.194/.286/.296
2025	32	AAACHC	231	.270/.355/.440	6	11	72	—	.227/.298/.348
2026	33	No MLB games played
2027PROJ10% MLB	34	MLBCHC	17	.222/.287/.352	0	0	79	0.0
2028PROJ6% MLB	35	MLBCHC	8	.212/.275/.329	0	0	70	-0.0

Last 3 seasons WAR -0.1 · Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service10.000First FA2028

2027Ext / FA-deal$1M

Skills · percentileStatcast 2022-2025

Bat Spd42

Speed40

Avg EV34

Barrel%10

xwOBA10

CompsRamiro Pena (age 34) · Andrew Romine (age 35) · Tim Torres (age 33)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†79

AVG/OBP/SLG.222 / .287 / .352

PA17

HR0

K%24

BB%6

BABIP281

ISO62

MLB%10%

Value2027 · WAR

trajectory · projected WAR by year

Tools · ContractCON 50 / POW 50

Toolsscout grade · Statcast %ile · 2022-2025

CONTACT50

xAVG

100.161

POWER50

Barrel%

101.9

Avg EV

3487.9

Bat Spd

4270.5

EYE35

scouting grade only

SPEED55

Sprint

4027.0

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

Status FA

MLB Debut 2017

Service 10.000 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$1M	+0.0	$0.0M	-$1.0M
Totals		$1M		$0.0M	-$1.0M

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+	Lynchburg Hillcats	—	16	13	2	1	0	0	2	3	1	3	0	154	312	231	543	77	200	19	12	270	26	—	—	—	—	—	—
2015	22	A	Lake County Captains	—	564	479	131	27	2	7	53	57	20	43	16	273	370	382	752	109	297	10	9	337	78	—	—	—	—	—	—
2016	23	AA	Akron RubberDucks	—	174	145	42	7	3	3	19	27	8	7	6	290	401	441	843	152	336	16	11	376	103	—	—	—	—	—	—
2016	23	A+	Lynchburg Hillcats	—	432	346	103	16	4	4	58	51	19	38	7	298	426	402	827	104	338	12	13	373	103	—	—	—	—	—	—
2016	23	INTL	Mesa Solar Sox	—	96	78	21	3	1	3	10	17	4	12	2	269	380	449	829	179	310	18	10	357	128	—	—	—	—	—	—
2017	24	MLB	Cleveland Indians	—	39	35	8	1	0	1	2	8	1	1	0	229	289	343	632	114	259	21	5	280	75	-1	+0	+1	+1	+1	0.2
2017	24	AA	Akron RubberDucks	—	303	258	68	16	1	2	22	55	13	21	2	264	352	357	708	93	319	18	7	315	77	—	—	—	—	—	—
2017	24	ROK	AZL Indians	—	17	15	5	0	0	0	0	1	1	3	0	333	375	333	708		333	6	0	309	62	—	—	—	—	—	—
2018	25	MLB	Cleveland Indians	—	291	265	68	11	3	2	14	58	7	21	4	257	311	343	655	87	320	20	5	292	84	-6	+3	+1	+2	+6	0.6
2018	25	AAA	Columbus Clippers	—	205	171	51	13	0	2	19	44	9	12	6	298	397	409	806	111	389	21	9	358	112	—	—	—	—	—	—
2019	26	MLB	Cleveland Indians	—	256	231	53	9	3	4	11	53	9	8	2	229	291	346	637	117	280	21	4	283	78	-7	+1	+3	-5	+6	-0.3
2019	26	AAA	Columbus Clippers	—	226	198	53	9	3	5	20	44	8	10	5	268	358	419	778	152	322	19	9	351	84	—	—	—	—	—	—
2020	27	MLB	San Diego Padres	—	32	26	4	1	0	1	3	10	2	2	0	154	290	308	598	154	188	31	9	273	72	-1	+0	-0	-0	+1	-0.0
2021	28	MLB	New York Yankees	—	48	37	10	4	1	0	5	13	5	5	0	270	426	432	858	162	400	27	10	384	147	+3	+1	+0	-3	+1	0.2
2021	28	AAA	Scranton/Wilkes-Barre RailRiders	—	263	215	70	13	1	5	26	45	19	26	2	326	442	465	907	140	394	17	10	407	116	—	—	—	—	—	—
2022	29	MLB	Pittsburgh Pirates	—	134	118	22	4	0	2	10	42	2	8	2	186	262	271	533	85	267	31	7	240	50	-8	+1	+2	-2	+3	-0.4
2022	29	AAA	Indianapolis Indians	—	16	14	6	2	0	1	0	3	2	0	0	429	500	786	1.286	357	500	19	0	552	172	—	—	—	—	—	—
2023	30	MLB	New York Yankees	—	28	23	5	1	1	1	2	10	2	3	1	217	333	478	812	261	333	36	7	345	116	+1	+0	-0	-2	+1	-0.1
2023	30	AAA	Nashville Sounds	—	203	161	39	9	1	3	25	39	13	26	2	242	387	366	753	124	295	19	12	345	82	—	—	—	—	—	—
2024	31	AAA	Scranton/Wilkes-Barre RailRiders	—	218	178	40	9	3	3	23	47	9	13	2	225	343	360	702	135	282	22	11	312	60	—	—	—	—	—	—
2024	31	INTL	Yaquis de Obregon	—	90	70	16	4	0	2	14	13	3	2	2	229	379	371	751	143	250	14	16	337	114	—	—	—	—	—	—
2025	32	AAA	Iowa Cubs	—	231	200	54	14	1	6	15	52	12	11	3	270	355	440	795	170	336	23	6	352	72	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	828	735	170	31	8	11	47	194	28	48	9	231	302	340	643	109	297	23	6	287	80	-19	+6	+7	-10	+18	0.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2015	22	A+ MLE	Lynchburg Hillcats	—	16	14	2	1	0	0	1	4	1	3	0	143	250	214	464	71	177	25	6	206	26	—	—	—	—	—	—
2015	22	A MLE	Lake County Captains	—	564	496	123	26	2	5	36	77	20	43	16	248	324	339	663	91	270	14	6	284	78	—	—	—	—	—	—
2016	23	AA MLE	Akron RubberDucks	—	174	150	39	6	2	3	14	33	8	7	6	260	355	387	741	127	303	19	8	321	103	—	—	—	—	—	—
2016	23	A+ MLE	Lynchburg Hillcats	—	432	368	101	14	3	4	36	76	19	38	7	274	369	361	730	87	323	18	8	320	103	—	—	—	—	—	—
2017	24	MLB MLE	Cleveland Indians	—	39	35	8	1	0	1	2	8	1	1	0	229	289	343	632	114	259	21	5	279	75	-1	+0	+1	+1	+1	0.2
2017	24	AA MLE	Akron RubberDucks	—	303	265	66	13	1	2	15	68	13	21	2	249	321	328	649	79	302	22	5	282	77	—	—	—	—	—	—
2017	24	ROK MLE	AZL Indians	—	17	15	4	0	0	0	0	1	1	3	0	267	312	267	579		262	6	0	260	62	—	—	—	—	—	—
2018	25	MLB MLE	Cleveland Indians	—	291	266	69	11	4	2	13	58	7	21	4	259	311	353	665	94	320	20	4	292	84	-6	+3	+1	+2	+6	0.6
2018	25	AAA MLE	Columbus Clippers	—	205	177	53	13	0	2	13	52	9	12	6	299	377	407	784	107	388	25	6	334	112	—	—	—	—	—	—
2019	26	MLB MLE	Cleveland Indians	—	256	232	54	9	4	4	10	53	9	8	2	233	291	358	649	125	280	21	4	283	78	-7	+1	+3	-5	+6	-0.3
2019	26	AAA MLE	Columbus Clippers	—	226	206	47	7	3	4	12	53	8	10	5	228	296	350	646	121	293	23	5	292	84	—	—	—	—	—	—
2020	27	MLB MLE	San Diego Padres	—	32	26	4	1	0	1	3	10	2	2	0	154	290	308	598	154	188	31	9	275	72	-1	+0	-0	-0	+1	-0.0
2021	28	MLB MLE	New York Yankees	—	48	37	10	4	1	0	5	13	5	5	0	270	426	432	858	162	400	27	10	385	147	+3	+1	+0	-3	+1	0.2
2021	28	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	263	223	64	12	1	3	18	54	19	26	2	287	388	390	779	103	354	21	7	339	116	—	—	—	—	—	—
2022	29	MLB MLE	Pittsburgh Pirates	—	134	118	22	4	0	2	10	42	2	8	2	186	262	271	533	85	267	31	7	242	50	-8	+1	+2	-2	+3	-0.4
2022	29	AAA MLE	Indianapolis Indians	—	16	14	5	2	0	1	0	4	2	0	0	357	438	714	1.152	357	408	25	0	422	172	—	—	—	—	—	—
2023	30	MLB MLE	New York Yankees	—	28	23	5	1	1	1	2	10	2	3	1	217	333	478	812	261	333	36	7	340	116	+1	+0	-0	-2	+1	-0.1
2023	30	AAA MLE	Nashville Sounds	—	203	169	36	8	1	2	17	48	13	26	2	213	332	308	639	95	266	24	8	290	82	—	—	—	—	—	—
2024	31	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	218	186	36	7	3	2	15	57	9	13	2	194	286	296	581	102	246	26	7	257	60	—	—	—	—	—	—
2025	32	AAA MLE	Iowa Cubs	—	231	207	47	11	1	4	9	63	12	11	3	227	298	348	646	121	290	27	4	274	72	—	—	—	—	—	—
2015	22	A MLE	2 teams	—	580	510	123	26	2	5	37	81	21	46	16	241	319	329	648	88	277	14	6	282	77	—	—	—	—	—	—
2015	22	A RAW	2 teams	—	580	492	133	28	2	7	55	60	21	46	16	270	368	378	746	108	295	10	9	335	77	—	—	—	—	—	—
2016	23	A+ MLE	3 teams	—	702	599	163	23	7	8	57	126	31	57	15	272	365	374	739	102	331	18	8	320	103	—	—	—	—	—	—
2016	23	A+ RAW	3 teams	—	702	569	166	26	8	10	87	95	31	57	15	292	413	418	832	127	334	14	12	372	103	—	—	—	—	—	—
2017	24	AA MLE	3 teams	—	359	315	79	14	1	3	17	77	15	25	2	251	320	330	650	79	313	21	5	281	76	—	—	—	—	—	—
2017	24	AA RAW	3 teams	—	359	308	81	17	1	3	24	64	15	25	2	263	346	354	700	91	313	18	7	311	76	—	—	—	—	—	—
2018	25	MLB MLE	2 teams	—	496	443	121	23	4	4	26	110	16	33	10	273	336	370	706	97	353	22	5	309	95	-3	+3	+1	+2	+11	1.4
2018	25	MLB RAW	2 teams	—	496	436	119	24	3	4	33	102	16	33	10	273	346	369	716	96	346	21	7	319	95	-3	+3	+1	+2	+11	1.4
2019	26	MLB MLE	2 teams	—	482	438	101	16	7	8	22	106	17	18	7	231	294	354	647	123	286	22	5	287	80	-11	+1	+3	-5	+10	-0.2
2019	26	MLB RAW	2 teams	—	482	429	106	18	6	9	31	97	17	18	7	247	323	380	703	133	299	20	6	315	80	-11	+1	+3	-5	+10	-0.2
2020	27	MLB MLE	San Diego Padres	—	32	26	4	1	0	1	3	10	2	2	0	154	290	308	598	154	188	31	9	275	72	-1	+0	-0	-0	+1	-0.0
2020	27	MLB RAW	San Diego Padres	—	32	26	4	1	0	1	3	10	2	2	0	154	290	308	598	154	188	31	9	273	72	-1	+0	-0	-0	+1	-0.0
2021	28	AAA MLE	2 teams	—	311	260	74	16	2	3	23	67	24	31	2	285	394	396	790	112	372	22	7	346	120	—	—	—	—	—	—
2021	28	AAA RAW	2 teams	—	311	252	80	17	2	5	31	58	24	31	2	317	440	460	900	143	395	19	10	403	120	—	—	—	—	—	—
2022	29	MLB MLE	2 teams	—	150	132	26	5	0	3	10	46	4	8	2	197	274	303	577	106	274	31	7	261	63	-7	+1	+2	-2	+3	-0.2
2022	29	MLB RAW	2 teams	—	150	132	28	6	0	3	10	45	4	8	2	212	288	326	613	114	294	30	7	274	63	-7	+1	+2	-2	+3	-0.2
2023	30	AAA MLE	2 teams	—	231	192	41	9	2	3	19	58	15	29	3	214	332	328	660	115	284	25	8	296	87	—	—	—	—	—	—
2023	30	AAA RAW	2 teams	—	231	184	44	10	2	4	27	49	15	29	3	239	381	380	761	141	299	21	12	345	87	—	—	—	—	—	—
2024	31	AAA MLE	2 teams	—	308	264	52	10	5	3	21	80	12	15	4	197	286	307	593	110	265	26	7	257	60	—	—	—	—	—	—
2024	31	AAA RAW	2 teams	—	308	248	56	13	3	5	37	60	12	15	4	226	354	363	716	137	273	19	12	319	60	—	—	—	—	—	—
2025	32	AAA MLE	Iowa Cubs	—	231	207	47	11	1	4	9	63	12	11	3	227	298	348	646	121	305	27	4	274	72	—	—	—	—	—	—
2025	32	AAA RAW	Iowa Cubs	—	231	200	54	14	1	6	15	52	12	11	3	270	355	440	795	170	336	23	6	352	72	—	—	—	—	—	—
2015	22	A MLE	2 teams	—	580	517	123	26	2	5	37	81	21	46	16	238	319	325	644	87	267	14	6	282	77	—	—	—	—	—	—
2016	23	A+ MLE	3 teams	—	702	608	163	23	7	8	57	126	31	57	15	268	365	368	734	100	317	18	8	320	103	—	—	—	—	—	—
2017	24	AA MLE	3 teams	—	359	324	79	14	1	3	17	77	15	25	2	244	320	321	641	77	295	21	5	281	76	—	—	—	—	—	—
2018	25	MLB MLE	2 teams	—	496	451	121	23	4	4	26	110	16	33	10	268	336	364	700	95	348	22	5	309	95	—	—	—	—	—	—
2019	26	MLB MLE	2 teams	—	482	440	101	16	7	8	22	106	17	18	7	230	294	352	646	123	286	22	5	287	80	—	—	—	—	—	—
2020	27	MLB MLE	San Diego Padres	—	32	27	4	1	0	1	3	10	2	2	0	148	290	296	587	148	188	31	9	275	72	—	—	—	—	—	—
2021	28	AAA MLE	2 teams	—	311	261	74	16	2	3	23	67	24	31	2	284	394	395	789	111	361	22	7	346	120	—	—	—	—	—	—
2022	29	MLB MLE	2 teams	—	150	135	26	5	0	3	10	46	4	8	2	193	274	296	570	104	282	31	7	261	63	—	—	—	—	—	—
2023	30	AAA MLE	2 teams	—	231	195	41	9	2	3	19	58	15	29	3	210	332	323	655	113	274	25	8	296	87	—	—	—	—	—	—
2024	31	AAA MLE	2 teams	—	308	272	52	10	5	3	21	80	12	15	4	191	286	298	584	107	246	26	7	257	60	—	—	—	—	—	—
2025	32	AAA MLE	Iowa Cubs	—	231	208	47	11	1	4	9	63	12	11	3	226	298	346	644	120	290	27	4	274	72	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	31	AAA MLE	2 teams	—	308	272	52	10	5	3	21	80	12	15	4	191	286	298	584	107	246	26	7	257	60	—	—	—	—	—	—
2025	32	AAA MLE	Iowa Cubs	—	231	208	47	11	1	4	9	63	12	11	3	226	298	346	644	120	290	27	4	274	72	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	34	MLB MLE	CHC	10%	279	254	56	11	2	6	16	70	7	8	2	221	286	350	635	129	277	25	6	285	79	-7	+1	+0	+1	+6	0.1
▸ 2027 — real world (MLB)
2027	34	MLB CTX	CHC	10%	17	16	3	1	0	0	1	4	0	0	0	222	287	352	639	130	281	24	6	287	79	-0	+0	+0	+0	+0	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	35	MLB MLE	CHC	6%	138	126	27	5	1	3	7	36	4	2	1	210	274	327	601	117	268	26	5	271	70	-5	+0	-6	+0	+3	-0.7
2028	35	MLB CTX	CHC	6%	8	8	1	0	0	0	0	2	0	0	0	212	275	329	605	118	271	25	0	273	70	-0	+0	-0	+0	+0	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	836	743	171	31	8	11	47	196	28	48	9	230	301	338	639	108	295	23	6	287	85	-20	+6	+7	-10	+18	0.2
/ 162G	—	A+C		—	650	578	133	24	6	9	37	152	22	37	7	230	302	339	641	109	294	23	6	287	85	-15	+5	+5	-8	+14	0.1
Career	—	MLE		—	4193	3668	893	166	33	52	261	903	178	282	66	243	324	349	674	106	307	22	6	294	85	-29	+7	+2	-9	+25	-0.4
/ 162G	—	MLE		—	650	569	139	26	5	8	40	140	28	44	10	244	325	350	675	105	308	22	6	294	85	-16	+4	+1	-5	+14	-0.2

How the minor-league lines were translated

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

2025 AAAIowa Cubs · 231 PAwOBA .342 → .274 (−68)K% 22.5% → 27.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.51%	÷0.989	×1.200	—	—	27.32%
BB% (unintentional) /PA	6.06%	÷1.005	×0.690	—	×0.952	3.96%
HBP% /PA	5.19%	—	×0.940	—	×0.952	4.65%
Singles /BIP	22.30%	÷0.949	×0.930	×0.992	×0.952	20.64%
Doubles /BIP	9.46%	÷1.033	×0.830	×0.992	×0.952	7.18%
Triples /BIP	0.68%	÷0.939	×0.970	×0.992	×0.952	0.66%
Home runs /BIP	4.05%	÷1.125	×0.700	—	×0.952	2.40%

Factors used: league row International League. Park (home-season share, regressed): HR 125, 1B 90, 2B 107, 3B 88, K 98, BB 101 — applied at half strength. Age: age 32 vs a level average of 27.2 → −4.8% on BB/HBP/hit rates (4.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.992.

Result: wOBA .342 → .274; ISO .170 → .116; BABIP .336 → .290. 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 AAAScranton/Wilkes-Barre RailRiders · 218 PAwOBA .308 → .257 (−51)K% 21.6% → 26.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.56%	÷0.990	×1.200	—	—	26.12%
BB% (unintentional) /PA	10.55%	÷1.011	×0.690	—	×0.962	6.93%
HBP% /PA	4.13%	—	×0.940	—	×0.962	3.73%
Singles /BIP	19.08%	÷0.976	×0.930	×0.992	×0.962	17.35%
Doubles /BIP	6.87%	÷1.072	×0.830	×0.992	×0.962	5.08%
Triples /BIP	2.29%	÷0.900	×0.970	×0.992	×0.962	2.36%
Home runs /BIP	2.29%	÷1.045	×0.700	—	×0.962	1.48%

Factors used: league row International League. Park (home-season share, regressed): HR 109, 1B 95, 2B 114, 3B 80, K 98, BB 102 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.992.

Result: wOBA .308 → .257; ISO .135 → .110; BABIP .282 → .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).

2023 AAANashville Sounds · 203 PAwOBA .342 → .290 (−51)K% 19.2% → 23.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.21%	÷0.978	×1.200	—	—	23.58%
BB% (unintentional) /PA	12.32%	÷0.995	×0.690	—	×0.972	8.30%
HBP% /PA	6.40%	—	×0.940	—	×0.972	5.85%
Singles /BIP	21.31%	÷0.953	×0.930	×0.981	×0.972	19.84%
Doubles /BIP	7.38%	÷0.971	×0.830	×0.981	×0.972	6.01%
Triples /BIP	0.82%	÷0.900	×0.970	×0.981	×0.972	0.84%
Home runs /BIP	2.46%	÷0.905	×0.700	—	×0.972	1.85%

Factors used: league row International League. Park (home-season share, regressed): HR 81, 1B 91, 2B 94, 3B 80, K 96, BB 99 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.981.

Result: wOBA .342 → .290; ISO .124 → .104; BABIP .295 → .266. 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 AAAIndianapolis Indians · 16 PAwOBA .536 → .422 (−114)K% 18.8% → 22.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.75%	÷0.982	×1.200	—	—	22.92%
BB% (unintentional) /PA	0.00%	÷1.058	×0.690	—	×0.982	0.00%
HBP% /PA	12.50%	—	×0.940	—	×0.982	11.54%
Singles /BIP	27.27%	÷1.087	×0.930	—	×0.982	22.92%
Doubles /BIP	18.18%	÷0.964	×0.830	—	×0.982	15.38%
Triples /BIP	0.00%	÷0.942	×0.970	—	×0.982	0.00%
Home runs /BIP	9.09%	÷1.013	×0.700	—	×0.982	6.17%

Factors used: league row International League. Park (home-season share, regressed): HR 103, 1B 117, 2B 93, 3B 88, K 96, BB 112 — 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 .536 → .422; ISO .357 → .254; BABIP .500 → .408. 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 AAAScranton/Wilkes-Barre RailRiders · 263 PAwOBA .396 → .339 (−56)K% 17.1% → 20.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.11%	÷0.993	×1.200	—	—	20.67%
BB% (unintentional) /PA	9.51%	÷0.973	×0.690	—	×0.992	6.68%
HBP% /PA	7.22%	—	×0.940	—	×0.992	6.74%
Singles /BIP	30.00%	÷0.974	×0.930	×0.971	×0.992	27.60%
Doubles /BIP	7.65%	÷0.915	×0.830	×0.971	×0.992	6.68%
Triples /BIP	0.59%	÷1.150	×0.920	×0.971	×0.992	0.45%
Home runs /BIP	2.94%	÷1.149	×0.700	—	×0.992	1.78%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 130, 1B 95, 2B 83, 3B 130, K 99, 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.971.

Result: wOBA .396 → .339; ISO .140 → .104; BABIP .394 → .354. 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 AAAColumbus Clippers · 226 PAwOBA .340 → .292 (−48)K% 19.5% → 23.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.47%	÷0.993	×1.200	—	—	23.53%
BB% (unintentional) /PA	8.41%	÷1.089	×0.690	—	×1.018	5.42%
HBP% /PA	3.54%	—	×0.940	—	×1.018	3.39%
Singles /BIP	23.38%	÷0.970	×0.930	×0.950	×1.018	21.69%
Doubles /BIP	5.84%	÷0.995	×0.830	×0.950	×1.018	4.72%
Triples /BIP	1.95%	÷0.900	×0.970	×0.950	×1.018	2.03%
Home runs /BIP	3.25%	÷0.985	×0.840	—	×1.018	2.82%

Factors used: league row IL. Park (home-season share, regressed): HR 97, 1B 94, 2B 99, 3B 80, K 99, BB 118 — 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 ×0.950.

Result: wOBA .340 → .292; ISO .152 → .133; BABIP .322 → .293. 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 AAAColumbus Clippers · 205 PAwOBA .349 → .334 (−15)K% 21.5% → 25.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.46%	÷1.017	×1.200	—	—	25.33%
BB% (unintentional) /PA	8.78%	÷0.972	×0.690	—	×1.033	6.44%
HBP% /PA	4.39%	—	×0.940	—	×1.033	4.26%
Singles /BIP	28.35%	÷0.974	×0.930	×1.042	×1.033	29.13%
Doubles /BIP	10.24%	÷0.958	×0.830	×1.042	×1.033	9.54%
Triples /BIP	0.00%	÷0.900	×0.970	×1.042	×1.033	0.00%
Home runs /BIP	1.57%	÷1.135	×0.840	—	×1.033	1.20%

Factors used: league row IL. Park (home-season share, regressed): HR 127, 1B 95, 2B 92, 3B 80, K 103, BB 94 — 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 ×1.042.

Result: wOBA .349 → .334; ISO .111 → .101; BABIP .389 → .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).

2017 AAAkron RubberDucks · 303 PAwOBA .314 → .282 (−32)K% 18.2% → 22.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.15%	÷0.990	×1.220	—	—	22.37%
BB% (unintentional) /PA	7.26%	÷1.052	×0.700	—	×1.012	4.89%
HBP% /PA	4.29%	—	×0.850	—	×1.012	3.69%
Singles /BIP	24.14%	÷0.978	×0.970	×0.994	×1.012	24.09%
Doubles /BIP	7.88%	÷1.072	×0.860	×0.994	×1.012	6.36%
Triples /BIP	0.49%	÷1.150	×0.950	×0.994	×1.012	0.41%
Home runs /BIP	0.99%	÷1.008	×0.780	—	×1.012	0.77%

Factors used: league row EL. Park (home-season share, regressed): HR 102, 1B 96, 2B 114, 3B 130, K 98, BB 110 — applied at half strength. Age: age 24 vs a level average of 24.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.994.

Result: wOBA .314 → .282; ISO .093 → .077; BABIP .319 → .302. 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
#1Garrett Hampsonlast yr '25 career totals — 7 seasons, 1,805 PA	2.7	1,805	29	65	234	296	352	+10	+10	3.9	3.9
/162	664	11	24	+3.6	+3.7	1.4	pk7: 4
#2Luis Matos'00-'06 * career totals — 6 seasons, 1,773 PA	2.7	1,773	30	72	245*	304*	365*	+1	+10	3.2	3.2
/162	664	11	27	+0.3	+3.9	1.2	pk7: 3
#3Chuck Carr'90-'97 * career totals — 6 seasons, 1,914 PA	2.9	1,914	13	144	242*	306*	331*	+6	+20	2.6	2.6
/162	664	5	50	+2.1	+7.1	0.9	pk7: 3
#4Travis Jankowskilast yr '25 career totals — 9 seasons, 1,718 PA	2.6	1,718	11	100	238	321	309	-9	+11	2.1	2.5
/162	664	4	39	-3.6	+4.2	0.8	pk7: 3
#5Milt Cuyler'90-'98 * career totals — 7 seasons, 1,567 PA	2.4	1,567	10	77	233*	299*	338*	+1	+4	0.6	0.9
/162	664	4	33	+0.6	+1.9	0.3	pk7: 1
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 3 projected seasons	1.1	706	9	38	230	288	328	+2	+2	0.6	0.6
/162	664	8	35	+2.3	+2.2	0.6	pk7: 1
#6Herm Winningham'84-'92 * career totals — 8 seasons, 2,069 PA	3.1	2,069	19	105	238*	296*	357*	+1	-3	-0.5	0.2
/162	664	6	34	+0.3	-1.1	-0.2	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
Greg Allen (OGILVIE)	34	50	50	55	35	219/283/347	128	277	4	5	25%	6%	79	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Ramiro Pena 2019 · MLB	34	49→55	44→45	46→50	45	241/290/362	121	284	12	11	20%	6%	84	+0.1	249/285/378	129	272	14	9	14%	4%	85	+0.2	261/288/382	121	281	13	7	12%	3%	86	+0.2
✕Andrew Romine 2021 · MLB	35	46→55	42→40	55	43	225/272/327	102	272	10	19	21%	5%	69	-0.9	231/281/321	90	298	8	9	24%	6%	70	-0.8	235/280/294	59	309	3	3	24%	5%	61	-0.8
✕Tim Torres 2017 · AAA	33	51→49	44→45	55	45	246/304/370	124	320	11	20	26%	7%	91	+0.6	242/309/370	128	322	13	18	27%	9%	93	+0.8	238/321/351	114	321	12	20	28%	11%	96	+0.3
✕Charlie Culberson 2022 · MLB	33	49→54	47→45	53→50	44	241/292/382	142	301	13	13	24%	6%	89	+0.5	226/271/339	113	305	11	12	28%	6%	71	-0.8	206/235/275	69	295	7	12	32%	4%	43	-0.5
✕Wilson Batista 2015 · AAA	34	50→47	45	49→50	44	248/298/375	128	296	12	11	21%	6%	90	+0.6	239/292/353	114	289	11	14	20%	6%	82	+0.0	239/290/327	88	284	8	16	18%	6%	74	-0.2
✕Kristopher Negrón 2019 · MLB	33	44→49	45	54→55	39	217/273/341	124	302	13	16	32%	6%	73	-0.6	227/287/352	125	328	14	14	33%	7%	81	-0.1	227/288/343	116	327	14	14	33%	7%	78	-0.2
✕Hernán Pérez 2024 · MLB	33	45→55	45→50	54→55	42	226/273/344	118	287	13	21	26%	6%	73	-0.6	206/254/330	124	263	14	13	27%	6%	63	-1.3	165/208/277	113	202	13	9	26%	5%	32	-1.8
✕Ryan LaMarre 2023 · MLB	34	48→52	45	51→60	44	231/309/356	124	315	12	21	29%	7%	91	+0.6	217/290/341	124	310	13	19	32%	7%	80	-0.2	141/221/232	91	216	10	33	38%	7%	26	-0.7
✕Drew Maggi 2022 · AAA	33	41→51	46→45	49→60	41	205/283/331	126	293	14	14	33%	7%	75	-0.5	184/251/269	85	261	7	20	31%	6%	49	-2.4	156/223/217	61	220	4	22	29%	6%	24	-1.4
✕Eric Young Jr. 2019 · MLB	34	48→58	42→45	56→65	44	234/286/343	109	292	9	24	22%	6%	78	-0.3	223/280/331	108	282	9	16	23%	6%	73	-0.6	205/264/289	84	257	6	15	22%	6%	56	-0.8
✕Brian Bogusevic 2017 · MLB	33	50→54	45	53→55	43	248/295/367	120	307	13	18	24%	6%	86	+0.3	238/282/377	139	289	16	11	23%	5%	84	+0.2	236/274/376	140	280	16	6	22%	4%	79	-0.1
✕Cliff Pennington 2018 · MLB	34	47→54	42→45	49→55	47	229/291/327	97	299	10	8	26%	8%	76	-0.4	198/269/298	100	262	9	10	26%	8%	62	-1.4	157/235/234	77	210	6	9	27%	9%	34	-1.3
✕Matt Carson 2015 · MLB	34	43→50	45→60	51→50	39	215/264/334	119	286	14	14	30%	5%	68	-1.0	207/268/322	115	270	12	13	27%	6%	68	-1.0	161/232/243	82	201	8	11	24%	6%	35	-1.1
✕Brandon Barnes 2019 · MLB	33	44→53	43→55	50	38	214/265/330	115	302	11	16	32%	5%	67	-1.1	213/263/378	165	288	21	13	33%	5%	78	-0.3	191/237/377	187	240	27	11	34%	5%	66	-1.0
✕Mark Little 2006 · MLB	34	42	51→55	52→55	40	219/289/380	161	284	19	19	30%	6%	89	+0.5	226/308/346	120	311	11	15	29%	7%	88	+0.5	221/318/307	86	323	4	13	29%	6%	80	-0.1
✕Dewayne Wise 2012 · MLB	34	47→40	47→60	56→55	38	233/269/377	144	289	13	19	24%	4%	80	-0.2	233/273/376	143	289	15	23	24%	5%	81	-0.1	230/267/376	145	281	16	29	24%	4%	78	-0.1
✕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
✕Jake Marisnick 2024 · MLB	33	45→55	45→60	55	41	219/284/349	130	298	11	20	29%	6%	79	-0.2	214/279/365	151	293	16	15	31%	7%	81	-0.1	207/274/385	178	281	21	15	33%	7%	81	-0.0
✕Trinidad Robles 2007 · AAA	34	49	42→40	49→45	43	238/291/342	103	297	9	12	23%	6%	79	-0.2	216/270/303	87	266	7	7	21%	6%	63	-1.4	210/265/282	72	256	6	3	20%	6%	54	-1.0
✕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

Greg Allen

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps