Jon Berti

3B Chicago Cubs

Age 37 R/R 5'10" / 190 lbs MLB HR -8% Svc 9.000 · Ctrl thru 2027

Overview

MLBExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2023	33	MLBMIA	424	.294/.346/.405	7	16	116	2.7
2024	34	AAA/AA2 orgs	54	.311/.415/.467	2	1	100	—	.269/.343/.414
2024	34	MLBNYY	74	.273/.342/.318	1	5	90	0.1
2025	35	MLBCHC	107	.210/.262/.230	0	11	42	-0.5
2026	36	No MLB games played
2027PROJ	37	MLBCHC	88	.253/.318/.342	1	4	87	0.1
2028PROJ	38	MLBCHC	80	.242/.306/.319	1	2	77	-0.8

Last 3 seasons WAR 2.3 · Next 2 projected WAR -0.7Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service9.000First FA2028

2027Ext / FA-deal$1M

Skills · percentileStatcast 2023-2025

Speed71

Bat Spd59

xwOBA55

Barrel%17

Avg EV10

CompsRoyce Clayton (age 37) · Miguel Flores (age 37) · Willie Bloomquist (age 35)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 8987vR 81

AVG/OBP/SLG.253 / .318 / .342

PA88

HR1

K%22

BB%7

BABIP317

ISO74

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · ContractCON 55 / POW 35

Toolsscout grade · Statcast %ile · 2023-2025

CONTACT55

xAVG

770.273

POWER35

Barrel%

174.0

Avg EV

1085.6

Bat Spd

5972.3

EYE60

scouting grade only

SPEED55

Sprint

7128.3

Platoon Splits2024-2025 · 181 PA

vs LHP

vs RHP

Edge

121

—

wRC+

▶▶R

wOBA

232

271

▶R

ISO

—

046

—

BABIP

274

309

▶R

13.3%

23.1%

◀◀L

BB%

3.3%

7.4%

▶▶R

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

Status FA

MLB Debut 2018

Service 9.000 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$1M	+0.1	$0.4M	-$0.6M
Totals		$1M		$0.4M	-$0.6M

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)
2012	22	A+	Dunedin Blue Jays	—	206	174	33	7	5	0	26	49	3	8	3	190	305	287	593	98	258	24	13	274	36	—	—	—	—	—	—
2012	22	A	Lansing Lugnuts	—	267	224	63	8	2	2	34	41	7	26	8	281	392	362	754	80	335	15	13	347	77	—	—	—	—	—	—
2013	23	A+	Dunedin Blue Jays	—	576	505	126	18	5	3	57	90	11	56	19	250	339	323	661	73	298	16	10	305	57	—	—	—	—	—	—
2013	23	INTL	Canberra Cavalry	—	214	178	55	11	3	1	30	13	6	31	9	309	425	421	847	112	329	6	14	386	147	—	—	—	—	—	—
2014	24	AA	New Hampshire Fisher Cats	—	594	541	146	21	7	7	35	82	9	40	15	270	325	373	698	104	305	14	6	310	77	—	—	—	—	—	—
2014	24	INTL	Mesa Solar Sox	—	79	65	19	0	0	3	12	16	2	6	0	292	418	431	848	138	348	20	15	387	148	—	—	—	—	—	—
2015	25	AAA	Buffalo Bisons	—	166	149	34	3	1	2	14	25	3	4	3	228	307	302	609	74	262	15	8	283	61	—	—	—	—	—	—
2015	25	AA	New Hampshire Fisher Cats	—	297	256	67	12	2	1	26	38	8	19	4	262	348	336	684	74	300	13	9	309	76	—	—	—	—	—	—
2016	26	AAA	Buffalo Bisons	—	22	20	3	1	0	1	2	3	0	2	0	150	227	350	577	200	125	14	9	258	19	—	—	—	—	—	—
2016	26	AA	New Hampshire Fisher Cats	—	319	272	69	10	7	2	36	56	9	29	9	254	360	364	724	110	312	18	11	330	77	—	—	—	—	—	—
2016	26	ROK	GCL Blue Jays	—	21	20	8	0	0	1	1	1	0	5	0	400	429	550	979	150	389	5	5	434	99	—	—	—	—	—	—
2017	27	AAA	Buffalo Bisons	—	237	215	44	8	4	3	20	53	0	23	4	205	272	321	593	116	256	22	8	267	40	—	—	—	—	—	—
2018	28	MLB	Toronto Blue Jays	—	15	15	4	1	1	0	0	4	0	1	0	267	267	467	733	200	364	27	0	314	96	-0	+0	-1	+1	+0	0.1
2018	28	AAA	Columbus Clippers	—	81	68	15	1	0	0	9	16	2	8	1	221	329	235	564	15	283	20	11	268	52	—	—	—	—	—	—
2018	28	AA	New Hampshire Fisher Cats	—	316	277	87	13	7	8	29	46	10	21	9	314	399	498	897	184	354	15	9	398	120	—	—	—	—	—	—
2019	29	MLB	Miami Marlins	—	287	256	70	14	1	6	24	73	6	17	3	273	350	406	756	133	360	25	8	340	124	+8	+2	-0	+4	+6	2.1
2019	29	AAA	New Orleans Baby Cakes	—	79	62	18	1	0	4	15	11	1	5	0	290	436	500	936	210	292	14	19	412	105	—	—	—	—	—	—
2020	30	MLB	Miami Marlins	—	149	120	31	5	0	2	23	37	3	9	2	258	390	350	740	92	354	25	15	339	121	+4	+1	-2	+1	+3	0.6
2021	31	MLB	Miami Marlins	—	271	233	49	10	1	4	32	61	3	8	4	210	313	313	627	103	265	23	12	288	87	-4	+0	+0	+1	+6	0.3
2022	32	MLB	Miami Marlins	—	404	358	86	17	3	4	42	89	3	41	5	240	325	338	663	98	308	22	10	303	98	-1	+6	+4	+2	+9	1.9
2022	32	AAA	Jacksonville Jumbo Shrimp	—	17	14	1	0	0	0	3	7	0	1	0	71	235	71	307		143	41	18	176	-32	—	—	—	—	—	—
2023	33	MLB	Miami Marlins	—	424	388	114	16	3	7	29	77	2	16	6	294	346	405	751	111	349	18	7	333	116	+8	+1	+4	+5	+9	2.7
2024	34	MLB	New York Yankees	—	74	66	18	0	0	1	6	14	1	5	1	273	342	318	661	45	333	19	8	303	90	-1	+1	-1	+0	+2	0.1
2024	34	AAA	Scranton/Wilkes-Barre RailRiders	—	20	17	9	1	0	1	2	2	0	0	0	529	579	765	1.344	235	533	10	10	555	215	—	—	—	—	—	—
2024	34	AA	Somerset Patriots	—	34	28	5	0	0	1	5	11	1	1	0	179	324	286	609	107	250	32	15	292	32	—	—	—	—	—	—
2025	35	MLB	Chicago Cubs	—	107	100	21	2	0	0	5	22	2	11	3	210	262	230	492	20	269	21	5	231	42	-7	+1	-1	+0	+2	-0.5
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1731	1536	393	65	9	24	161	377	20	108	24	256	334	357	691	101	323	22	9	313	98	-4	+12	+2	+14	+38	6.3
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	22	A+ MLE	Dunedin Blue Jays	—	206	181	28	6	4	0	19	69	3	8	3	155	246	232	478	77	238	33	9	221	36	—	—	—	—	—	—
2012	22	A MLE	Lansing Lugnuts	—	267	236	58	7	2	2	22	59	7	26	8	246	328	318	646	72	307	22	8	282	77	—	—	—	—	—	—
2013	23	A+ MLE	Dunedin Blue Jays	—	576	521	111	17	4	2	41	127	11	56	19	213	284	273	557	60	275	22	7	253	57	—	—	—	—	—	—
2014	24	AA MLE	New Hampshire Fisher Cats	—	594	553	144	20	8	5	23	102	9	40	15	260	301	353	653	92	302	17	4	282	77	—	—	—	—	—	—
2015	25	AAA MLE	Buffalo Bisons	—	166	153	35	3	1	2	10	30	3	4	3	229	289	301	590	72	269	18	6	259	61	—	—	—	—	—	—
2015	25	AA MLE	New Hampshire Fisher Cats	—	297	264	68	10	2	1	18	48	8	19	4	258	324	322	646	64	295	16	6	280	76	—	—	—	—	—	—
2016	26	AAA MLE	Buffalo Bisons	—	22	21	3	1	0	1	1	4	0	2	0	143	182	333	515	190	114	18	5	197	19	—	—	—	—	—	—
2016	26	AA MLE	New Hampshire Fisher Cats	—	319	286	68	9	7	1	22	70	9	29	9	238	312	329	641	91	303	22	7	282	77	—	—	—	—	—	—
2016	26	ROK MLE	GCL Blue Jays	—	21	20	6	0	0	1	1	1	0	5	0	300	333	450	783	150	295	5	5	315	99	—	—	—	—	—	—
2017	27	AAA MLE	Buffalo Bisons	—	237	221	41	7	4	3	14	67	0	23	4	186	234	294	528	109	247	28	6	228	40	—	—	—	—	—	—
2018	28	MLB MLE	Toronto Blue Jays	—	15	15	4	1	1	0	0	4	0	1	0	267	267	467	733	200	364	27	0	310	96	-0	+0	-1	+1	+0	0.1
2018	28	AAA MLE	Columbus Clippers	—	81	71	15	1	0	0	6	19	2	8	1	211	291	225	516	14	280	23	7	245	52	—	—	—	—	—	—
2018	28	AA MLE	New Hampshire Fisher Cats	—	316	285	83	12	6	6	21	54	10	21	9	291	361	439	799	147	340	17	7	346	120	—	—	—	—	—	—
2019	29	MLB MLE	Miami Marlins	—	287	256	72	15	1	6	24	73	6	17	3	281	357	418	775	137	360	25	8	351	124	+8	+2	-0	+4	+6	2.1
2019	29	AAA MLE	New Orleans Baby Cakes	—	79	67	16	1	0	3	10	15	1	5	0	239	346	388	734	149	258	19	13	323	105	—	—	—	—	—	—
2020	30	MLB MLE	Miami Marlins	—	149	120	31	5	0	2	23	37	3	9	2	258	390	350	740	92	354	25	15	347	121	+4	+1	-2	+1	+3	0.6
2021	31	MLB MLE	Miami Marlins	—	271	233	51	11	1	4	32	61	3	8	4	219	321	326	647	107	265	23	12	296	87	-4	+0	+0	+1	+6	0.3
2022	32	MLB MLE	Miami Marlins	—	404	358	89	19	3	4	42	89	3	41	5	249	333	352	684	103	308	22	10	313	98	-1	+6	+4	+2	+9	1.9
2022	32	AAA MLE	Jacksonville Jumbo Shrimp	—	17	15	1	0	0	0	2	9	0	1	0	67	176	67	243		120	53	12	121	-32	—	—	—	—	—	—
2023	33	MLB MLE	Miami Marlins	—	424	390	116	17	3	7	27	77	2	16	6	297	346	410	756	113	349	18	6	340	116	+8	+1	+4	+5	+9	2.7
2024	34	MLB MLE	New York Yankees	—	74	66	18	0	0	1	6	14	1	5	1	273	342	318	661	45	333	19	8	301	90	-1	+1	-1	+0	+2	0.1
2024	34	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	20	18	9	1	0	1	1	2	0	0	0	500	526	722	1.249	222	457	10	5	486	215	—	—	—	—	—	—
2024	34	AA MLE	Somerset Patriots	—	34	30	4	0	0	1	3	13	1	1	0	133	235	233	469	100	213	38	9	215	32	—	—	—	—	—	—
2025	35	MLB MLE	Chicago Cubs	—	107	100	21	2	0	0	5	22	2	11	3	210	262	230	492	20	269	21	5	230	42	-7	+1	-1	+0	+2	-0.5
2012	22	A MLE	2 teams	—	473	416	86	13	6	2	42	128	10	34	11	207	295	281	576	75	290	27	9	255	59	—	—	—	—	—	—
2012	22	A RAW	2 teams	—	473	398	96	15	7	2	60	90	10	34	11	241	355	329	684	88	303	19	13	315	59	—	—	—	—	—	—
2013	23	A+ MLE	2 teams	—	790	714	153	23	6	3	56	174	17	87	28	214	287	276	563	62	279	22	7	253	57	—	—	—	—	—	—
2013	23	A+ RAW	2 teams	—	790	683	181	29	8	4	87	103	17	87	28	265	362	348	711	83	307	13	11	327	57	—	—	—	—	—	—
2014	24	AA MLE	2 teams	—	673	627	163	22	9	6	26	116	11	46	15	260	301	352	654	93	308	17	4	282	77	—	—	—	—	—	—
2014	24	AA RAW	2 teams	—	673	606	165	21	7	10	47	98	11	46	15	272	336	380	715	107	309	15	7	319	77	—	—	—	—	—	—
2015	25	AA MLE	2 teams	—	463	418	102	13	3	3	27	78	11	23	7	244	307	311	618	67	291	17	6	272	71	—	—	—	—	—	—
2015	25	AA RAW	2 teams	—	463	405	101	15	3	3	40	63	11	23	7	249	333	323	657	74	287	14	9	300	71	—	—	—	—	—	—
2016	26	AA MLE	3 teams	—	362	327	77	10	7	3	24	76	9	36	9	235	306	336	642	101	297	21	7	279	75	—	—	—	—	—	—
2016	26	AA RAW	3 teams	—	362	312	80	11	7	4	39	60	9	36	9	256	356	375	731	119	305	17	11	332	75	—	—	—	—	—	—
2017	27	AAA MLE	Buffalo Bisons	—	237	221	41	7	4	3	14	67	0	23	4	186	234	294	528	109	250	28	6	228	40	—	—	—	—	—	—
2017	27	AAA RAW	Buffalo Bisons	—	237	215	44	8	4	3	20	53	0	23	4	205	272	321	593	116	256	22	8	267	40	—	—	—	—	—	—
2018	28	AA MLE	3 teams	—	412	371	102	14	7	6	27	77	12	30	10	275	344	399	743	124	332	19	7	325	106	—	—	—	—	—	—
2018	28	AA RAW	3 teams	—	412	360	106	15	8	8	38	66	12	30	10	294	380	447	828	153	341	16	9	369	106	—	—	—	—	—	—
2019	29	MLB MLE	2 teams	—	366	323	88	16	1	9	34	88	7	22	3	272	354	412	766	139	346	24	9	345	119	+8	+3	-0	+4	+8	2.4
2019	29	MLB RAW	2 teams	—	366	318	88	15	1	10	39	84	7	22	3	277	368	425	793	148	345	23	11	356	119	+8	+3	-0	+4	+8	2.4
2020	30	MLB MLE	Miami Marlins	—	149	120	31	5	0	2	23	37	3	9	2	258	390	350	740	92	354	25	15	347	121	+4	+1	-2	+1	+3	0.6
2020	30	MLB RAW	Miami Marlins	—	149	120	31	5	0	2	23	37	3	9	2	258	390	350	740	92	354	25	15	339	121	+4	+1	-2	+1	+3	0.6
2021	31	MLB MLE	Miami Marlins	—	271	233	51	11	1	4	32	61	3	8	4	219	321	326	647	107	276	23	12	296	87	-4	+0	+0	+1	+6	0.3
2021	31	MLB RAW	Miami Marlins	—	271	233	49	10	1	4	32	61	3	8	4	210	313	313	627	103	265	23	12	288	87	-4	+0	+0	+1	+6	0.3
2022	32	MLB MLE	2 teams	—	421	373	90	19	3	4	44	98	3	42	5	241	326	340	667	99	316	23	10	305	92	-4	+6	+4	+2	+9	1.7
2022	32	MLB RAW	2 teams	—	421	372	87	17	3	4	45	96	3	42	5	234	321	328	649	94	304	23	11	298	92	-4	+6	+4	+2	+9	1.7
2023	33	MLB MLE	Miami Marlins	—	424	390	116	17	3	7	27	77	2	16	6	297	346	410	756	113	353	18	6	340	116	+8	+1	+4	+5	+9	2.7
2023	33	MLB RAW	Miami Marlins	—	424	388	114	16	3	7	29	77	2	16	6	294	346	405	751	111	349	18	7	333	116	+8	+1	+4	+5	+9	2.7
2024	34	MLB MLE	3 teams	—	128	113	30	1	0	2	11	30	2	6	1	265	341	327	669	62	341	23	9	307	94	-1	+1	-1	+0	+3	0.3
2024	34	MLB RAW	3 teams	—	128	111	32	1	0	3	13	27	2	6	1	288	373	378	751	90	354	21	10	339	94	-1	+1	-1	+0	+3	0.3
2025	35	MLB MLE	Chicago Cubs	—	107	100	21	2	0	0	5	22	2	11	3	210	262	230	492	20	269	21	5	230	42	-7	+1	-1	+0	+2	-0.5
2025	35	MLB RAW	Chicago Cubs	—	107	100	21	2	0	0	5	22	2	11	3	210	262	230	492	20	269	21	5	231	42	-7	+1	-1	+0	+2	-0.5
2012	22	A MLE	2 teams	—	473	418	86	13	6	2	42	128	10	34	11	206	295	280	575	74	277	27	9	255	59	—	—	—	—	—	—
2013	23	A+ MLE	2 teams	—	790	711	153	23	6	3	56	174	17	87	28	215	287	277	564	62	275	22	7	253	57	—	—	—	—	—	—
2014	24	AA MLE	2 teams	—	673	631	163	22	9	6	26	116	11	46	15	258	301	350	651	92	302	17	4	282	77	—	—	—	—	—	—
2015	25	AA MLE	2 teams	—	463	422	102	13	3	3	27	78	11	23	7	242	307	308	615	66	286	17	6	272	71	—	—	—	—	—	—
2016	26	AA MLE	3 teams	—	362	326	77	10	7	3	24	76	9	36	9	236	306	337	643	101	291	21	7	279	75	—	—	—	—	—	—
2017	27	AAA MLE	Buffalo Bisons	—	237	221	41	7	4	3	14	67	0	23	4	186	234	294	528	109	247	28	6	228	40	—	—	—	—	—	—
2018	28	AA MLE	3 teams	—	412	370	102	14	7	6	27	77	12	30	10	276	344	400	744	124	329	19	7	325	106	—	—	—	—	—	—
2019	29	MLB MLE	2 teams	—	366	322	88	16	1	9	34	88	7	22	3	273	354	413	767	140	338	24	9	345	119	—	—	—	—	—	—
2020	30	MLB MLE	Miami Marlins	—	149	122	31	5	0	2	23	37	3	9	2	254	390	344	735	90	354	25	15	347	121	—	—	—	—	—	—
2021	31	MLB MLE	Miami Marlins	—	271	234	51	11	1	4	32	61	3	8	4	218	321	325	646	107	265	23	12	296	87	—	—	—	—	—	—
2022	32	MLB MLE	2 teams	—	421	371	90	19	3	4	44	98	3	42	5	243	326	342	669	100	301	23	10	305	92	—	—	—	—	—	—
2023	33	MLB MLE	Miami Marlins	—	424	392	116	17	3	7	27	77	2	16	6	296	346	408	754	112	349	18	6	340	116	—	—	—	—	—	—
2024	34	MLB MLE	3 teams	—	128	114	30	1	0	2	11	30	2	6	1	263	341	325	666	61	321	23	9	307	94	—	—	—	—	—	—
2025	35	MLB MLE	Chicago Cubs	—	107	99	21	2	0	0	5	22	2	11	3	212	262	232	494	20	269	21	5	230	42	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	34	MLB MLE	3 teams	—	128	114	30	1	0	2	11	30	2	6	1	263	341	325	666	61	321	23	9	307	94	—	—	—	—	—	—
2025	35	MLB MLE	Chicago Cubs	—	107	99	21	2	0	0	5	22	2	11	3	212	262	232	494	20	269	21	5	230	42	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	37	MLB MLE	CHC	100%	142	129	33	5	1	2	10	31	2	6	1	251	317	338	655	88	314	22	7	297	87	-2	+1	-0	+1	+3	0.1
▸ 2027 — real world (MLB)
2027	37	MLB CTX	CHC	100%	88	81	19	3	0	1	6	19	1	4	1	253	318	342	660	89	317	22	7	299	87	-1	+0	-0	+0	+2	0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	38	MLB MLE	CHC	100%	80	73	18	3	0	1	6	18	1	2	0	240	304	316	620	75	305	22	8	283	77	-2	+0	-8	+0	+2	-0.8
2028	38	MLB CTX	CHC	100%	80	73	18	3	0	1	6	18	1	2	0	242	306	319	625	77	308	22	8	285	77	-2	+0	-8	+0	+2	-0.8
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1811	1609	411	68	9	25	167	395	21	110	24	255	333	356	689	100	322	22	9	312	81	-6	+12	-6	+14	+39	5.5
/ 162G	—	A+C		—	650	577	147	24	3	9	60	142	8	39	9	255	333	354	687	99	322	22	9	312	81	-2	+4	-2	+5	+14	2.0
Career	—	MLE		—	5444	4900	1188	179	50	56	404	1166	94	399	109	242	312	334	646	91	306	21	7	288	81	-8	+13	-6	+14	+41	5.6
/ 162G	—	MLE		—	650	585	142	21	6	7	48	139	11	48	13	243	312	335	647	92	305	21	7	288	81	-3	+4	-2	+5	+14	1.9

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.

2024 AASomerset Patriots · 34 PAwOBA .285 → .215 (−70)K% 32.4% → 38.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	32.35%	÷1.018	×1.220	—	—	38.76%
BB% (unintentional) /PA	14.71%	÷0.972	×0.700	—	×0.940	9.96%
HBP% /PA	2.94%	—	×0.850	—	×0.940	2.35%
Singles /BIP	23.53%	÷1.050	×0.970	—	×0.940	20.43%
Doubles /BIP	0.00%	÷0.902	×0.860	—	×0.940	0.00%
Triples /BIP	0.00%	÷0.934	×0.950	—	×0.940	0.00%
Home runs /BIP	5.88%	÷1.027	×0.780	—	×0.940	4.20%

Factors used: league row EL. Park (home-season share, regressed): HR 105, 1B 110, 2B 80, 3B 87, K 104, BB 94 — applied at half strength. Age: age 34 vs a level average of 24.8 → −6.0% on BB/HBP/hit rates (9.2 yr older than average).

Result: wOBA .285 → .215; ISO .107 → .075; BABIP .250 → .213. 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 · 20 PAwOBA .568 → .486 (−82)K% 10.0% → 12.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.00%	÷0.990	×1.200	—	—	12.12%
BB% (unintentional) /PA	10.00%	÷1.011	×0.690	—	×0.940	6.42%
HBP% /PA	0.00%	—	×0.940	—	×0.940	0.00%
Singles /BIP	46.67%	÷0.976	×0.930	—	×0.940	41.78%
Doubles /BIP	6.67%	÷1.072	×0.830	—	×0.940	4.85%
Triples /BIP	0.00%	÷0.900	×0.970	—	×0.940	0.00%
Home runs /BIP	6.67%	÷1.045	×0.700	—	×0.940	4.20%

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 34 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (6.8 yr older than average).

Result: wOBA .568 → .486; ISO .235 → .167; BABIP .533 → .457. 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 AAAJacksonville Jumbo Shrimp · 17 PAwOBA .174 → .121 (−53)K% 41.2% → 51.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	41.18%	÷0.966	×1.200	—	—	51.17%
BB% (unintentional) /PA	17.65%	÷0.978	×0.690	—	×0.952	11.86%
HBP% /PA	0.00%	—	×0.940	—	×0.952	0.00%
Singles /BIP	14.29%	÷1.054	×0.930	—	×0.952	12.00%
Doubles /BIP	0.00%	÷0.898	×0.830	—	×0.952	0.00%
Triples /BIP	0.00%	÷0.930	×0.970	—	×0.952	0.00%
Home runs /BIP	0.00%	÷1.032	×0.700	—	×0.952	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 106, 1B 111, 2B 80, 3B 86, K 93, BB 96 — 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).

Result: wOBA .174 → .121; ISO .000 → .000; BABIP .143 → .120. 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 AAANew Orleans Baby Cakes · 79 PAwOBA .407 → .323 (−84)K% 13.9% → 18.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.92%	÷0.950	×1.290	—	—	18.92%
BB% (unintentional) /PA	18.99%	÷1.085	×0.710	—	×0.982	12.20%
HBP% /PA	1.27%	—	×0.980	—	×0.982	1.22%
Singles /BIP	25.49%	÷0.971	×0.900	—	×0.982	23.21%
Doubles /BIP	1.96%	÷0.952	×0.810	—	×0.982	1.64%
Triples /BIP	0.00%	÷0.900	×0.810	—	×0.982	0.00%
Home runs /BIP	7.84%	÷1.100	×0.780	—	×0.982	5.46%

Factors used: league row PCL. Park (home-season share, regressed): HR 120, 1B 94, 2B 90, 3B 80, K 90, BB 117 — 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 .407 → .323; ISO .210 → .155; BABIP .292 → .258. 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 AANew Hampshire Fisher Cats · 316 PAwOBA .387 → .346 (−41)K% 14.6% → 17.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.56%	÷1.033	×1.220	—	—	17.19%
BB% (unintentional) /PA	9.18%	÷0.961	×0.700	—	×0.968	6.47%
HBP% /PA	3.16%	—	×0.850	—	×0.968	2.60%
Singles /BIP	25.54%	÷0.995	×0.970	×1.050	×0.968	25.31%
Doubles /BIP	5.63%	÷0.980	×0.860	×1.050	×0.968	5.02%
Triples /BIP	3.03%	÷1.086	×0.950	×1.050	×0.968	2.69%
Home runs /BIP	3.46%	÷0.945	×0.780	—	×0.968	2.77%

Factors used: league row EL. Park (home-season share, regressed): HR 89, 1B 99, 2B 96, 3B 117, K 107, BB 92 — applied at half strength. Age: age 28 vs a level average of 24.8 → −3.2% on BB/HBP/hit rates (3.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .387 → .346; ISO .184 → .157; BABIP .354 → .340. 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 · 81 PAwOBA .265 → .245 (−20)K% 19.8% → 23.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.75%	÷1.017	×1.200	—	—	23.31%
BB% (unintentional) /PA	11.11%	÷0.972	×0.690	—	×0.992	7.82%
HBP% /PA	2.47%	—	×0.940	—	×0.992	2.30%
Singles /BIP	26.92%	÷0.974	×0.930	×1.050	×0.992	26.77%
Doubles /BIP	1.92%	÷0.958	×0.830	×1.050	×0.992	1.73%
Triples /BIP	0.00%	÷0.900	×0.970	×1.050	×0.992	0.00%
Home runs /BIP	0.00%	÷1.135	×0.840	—	×0.992	0.00%

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 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 ×1.050.

Result: wOBA .265 → .245; ISO .015 → .014; BABIP .283 → .280. 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 AAABuffalo Bisons · 237 PAwOBA .261 → .228 (−33)K% 22.4% → 28.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.36%	÷0.950	×1.200	—	—	28.24%
BB% (unintentional) /PA	8.44%	÷1.027	×0.690	—	×1.003	5.68%
HBP% /PA	0.00%	—	×0.940	—	×1.003	0.00%
Singles /BIP	17.90%	÷1.021	×0.930	×1.050	×1.003	17.17%
Doubles /BIP	4.94%	÷0.940	×0.830	×1.050	×1.003	4.59%
Triples /BIP	2.47%	÷0.961	×0.970	×1.050	×1.003	2.62%
Home runs /BIP	1.85%	÷0.903	×0.840	—	×1.003	1.73%

Factors used: league row IL. Park (home-season share, regressed): HR 80, 1B 104, 2B 88, 3B 92, K 90, BB 106 — 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 ×1.050.

Result: wOBA .261 → .228; ISO .116 → .109; BABIP .256 → .247. 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 AANew Hampshire Fisher Cats · 319 PAwOBA .322 → .282 (−40)K% 17.6% → 22.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.55%	÷0.969	×1.220	—	—	22.10%
BB% (unintentional) /PA	10.97%	÷1.079	×0.700	—	×0.988	7.03%
HBP% /PA	2.82%	—	×0.850	—	×0.988	2.37%
Singles /BIP	23.15%	÷0.995	×0.970	×1.039	×0.988	23.17%
Doubles /BIP	4.63%	÷1.000	×0.860	×1.039	×0.988	4.08%
Triples /BIP	3.24%	÷1.031	×0.950	×1.039	×0.988	3.06%
Home runs /BIP	0.93%	÷1.292	×0.780	—	×0.988	0.55%

Factors used: league row EL. Park (home-season share, regressed): HR 158, 1B 99, 2B 100, 3B 106, K 94, BB 116 — 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 ×1.039.

Result: wOBA .322 → .282; ISO .110 → .095; BABIP .312 → .303. 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
#1Brock Holtlast yr '21 career totals — 10 seasons, 2,661 PA	4.0	2,661	25	41	262	332	362	+5	+3	7.4	7.8
/162	664	6	10	+1.2	+0.6	1.9	pk7: 8
#2Bill Pecota'86-'94 * career totals — 8 seasons, 1,729 PA	2.6	1,729	22	52	246*	322*	374*	+6	+24	6.8	6.7
/162	664	8	20	+2.3	+9.4	2.6	pk7: 6
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 9 projected seasons	2.8	1,884	26	112	256	330	355	+4	+5	6.1	6.3
/162	664	9	40	+1.6	+1.9	2.1	pk7: 6
#3Tony Kemplast yr '23 career totals — 7 seasons, 2,198 PA	3.3	2,198	35	52	238	326	354	-4	-3	4.3	4.3
/162	664	11	16	-1.3	-0.8	1.3	pk7: 4
#4Dave Nelson'68-'77 * career totals — 10 seasons, 2,875 PA	4.3	2,875	20	187	249*	310*	352*	+6	-15	3.3	4.0
/162	664	5	43	+1.5	-3.5	0.8	pk7: 5
#5Bobby Valentine'71-'79 * career totals — 9 seasons, 1,909 PA	2.9	1,909	12	27	258*	316*	358*	+2	+1	3.1	3.8
/162	664	4	9	+0.6	+0.2	1.1	pk7: 4
#6Alexi Casillalast yr '13 career totals — 7 seasons, 1,883 PA	2.8	1,883	12	80	248	302	332	+8	+3	2.7	2.7
/162	664	4	28	+2.8	+0.9	1.0	pk7: 3

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
Jon Berti (OGILVIE)	37	55	35	55	60	248/314/336	87	314	1	4	22%	7%	87	+0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Royce Clayton 2007 · MLB	37	55→57	39→45	49→50	47	258/308/350	92	311	4	14	18%	6%	87	+0.4	238/292/340	102	304	7	11	22%	7%	79	-0.2	222/273/305	84	305	2	5	26%	6%	64	-0.5
✕Miguel Flores 2008 · AAA	37	55→58	38→30	54→55	52	259/309/333	74	274	5	21	8%	6%	83	+0.1	253/303/325	72	277	5	16	10%	6%	79	-0.2	273/324/328	55	298	1	14	8%	7%	84	+0.1
✕Willie Bloomquist 2013 · MLB	35	56→55	39→40	47→60	45	269/305/357	89	310	5	19	15%	5%	87	+0.4	264/302/345	81	311	5	9	16%	5%	83	+0.1	295/328/351	56	346	2	2	15%	4%	93	+0.2
✕So Taguchi 2007 · MLB	38	55→58	42→45	52→50	50	265/317/373	108	297	8	16	14%	7%	96	+1.0	253/316/344	91	283	7	13	13%	7%	89	+0.5	244/311/315	71	273	5	11	12%	7%	81	-0.0
✕Eric Young Sr. 2004 · MLB	37	54→62	44→45	53→60	57	261/329/382	120	268	11	29	8%	8%	103	+1.5	253/336/368	115	268	8	22	9%	10%	102	+1.5	249/338/351	102	268	5	22	8%	10%	100	+0.6
✕Henry Mateo 2014 · AAA	37	55→62	38→45	57→60	46	262/307/340	78	310	4	28	17%	5%	84	+0.1	239/286/319	80	287	4	19	17%	5%	72	-0.7	238/283/301	64	285	2	20	16%	5%	65	-1.1
✕Manny Martinez 2008 · AAA	37	51→56	44→45	51→55	51	251/312/370	119	280	12	23	15%	7%	94	+0.9	236/296/335	99	283	8	18	18%	7%	80	-0.2	234/295/315	80	284	5	17	18%	6%	73	-0.4
✕Scott Podsednik 2012 · MLB	36	57→64	40→45	58→65	49	274/323/376	103	316	6	27	15%	7%	98	+1.2	243/287/323	80	289	6	20	17%	6%	73	-0.6	249/284/290	41	297	2	25	16%	4%	63	-0.9
✕Jeff Reboulet 2001 · MLB	37	50	38→40	48→40	57	235/313/313	78	275	5	10	16%	10%	81	-0.1	241/324/347	106	291	7	5	18%	11%	93	+0.8	244/328/348	104	292	7	2	17%	10%	96	+0.5
✕Ramon Valdez 2013 · AAA	36	54	38→30	56→55	49	253/316/331	78	284	5	25	12%	6%	86	+0.3	239/319/324	85	276	6	18	15%	8%	86	+0.3	220/328/259	38	258	0	15	13%	9%	74	-0.2
✕Jason Bourgeois 2017 · MLB	35	52→58	38→45	53→65	46	242/278/325	82	269	5	17	12%	5%	70	-0.9	231/269/323	92	271	8	13	17%	5%	66	-1.1	219/247/280	61	263	7	9	19%	4%	45	-1.1
✕Miguel Cairo 2011 · MLB	37	52→58	42→45	52→55	48	251/301/357	106	280	9	11	14%	6%	86	+0.3	238/292/361	123	262	12	11	14%	6%	84	+0.2	229/281/348	119	248	12	10	13%	5%	77	-0.1
✕Willy Taveras 2017 · AAA	35	51→61	41→45	58→65	44	244/294/345	101	290	7	24	18%	5%	81	-0.1	241/294/353	112	295	10	19	21%	4%	83	+0.1	242/295/349	106	300	10	22	22%	3%	80	-0.1
✕Julio Lugo 2011 · MLB	35	53→62	38→45	49→60	51	251/316/331	80	303	4	15	18%	8%	86	+0.3	227/287/328	101	274	9	11	20%	7%	74	-0.5	166/219/225	58	202	4	5	19%	6%	23	-0.8
✕Agustin Murillo 2019 · AAA	37	49→59	41→45	47→55	49	237/287/332	95	262	9	14	14%	6%	76	-0.4	228/283/339	111	259	12	15	17%	6%	76	-0.4	222/277/317	95	248	12	16	16%	5%	68	-0.8
✕Tony Womack 2006 · MLB	36	56→63	37→40	58→60	47	264/300/331	67	295	4	30	12%	5%	79	-0.2	252/306/350	98	285	9	22	14%	7%	86	+0.3	273/339/349	76	302	6	21	11%	9%	97	+0.2
✕Jerry Owens 2016 · AAA	35	52→62	42→40	56→65	49	251/312/362	111	307	8	21	20%	8%	91	+0.7	257/305/355	98	301	8	14	17%	6%	87	+0.4	329/358/368	39	371	0	14	11%	4%	105	+0.3
✕Olmo Rosario 2017 · AAA	36	56→60	40→45	46→50	47	270/307/363	93	294	8	14	12%	5%	90	+0.6	260/304/358	98	283	8	11	11%	5%	87	+0.4	264/310/358	93	283	8	6	10%	5%	88	+0.3
✕Abel Martinez 2014 · AAA	37	52→62	42→45	46→50	47	250/294/354	103	267	10	14	11%	5%	83	+0.1	249/297/344	95	278	8	12	13%	5%	82	-0.0	256/303/332	76	283	6	10	12%	5%	78	-0.1
✕Raul Sanchez 2009 · AAA	36	53→52	40→45	48→50	45	253/298/344	91	289	8	14	16%	5%	82	+0.0	240/294/323	83	287	6	9	18%	6%	76	-0.4	254/301/341	88	302	6	4	17%	5%	81	-0.0

Jon Berti

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps