Nico Hoerner

2B Chicago Cubs

Age 30 R/R 5'11" / 200 lbs MLB HR -8% Svc 7.081 · Ctrl thru 2027

Overview

MLB40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	27	MLBCHC	641	.273/.337/.373	7	31	101	3.0
2025	28	MLBCHC	649	.297/.347/.394	7	29	108	4.0
2026	29	MLBCHC	689	.263/.320/.350	8	23	89	1.4
2027PROJ	30	MLBCHC	564	.283/.339/.380	7	22	103	2.6
2028PROJ	31	MLBCHC	614	.278/.333/.369	7	18	99	2.1
2029PROJ	32	MLBCHC	614	.272/.326/.354	6	11	93	1.5

Last 3 seasons WAR 8.3 · Next 3 projected WAR 6.2Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service7.081First FA2028NTC

2027Ext / FA-deal$22M

Skills · percentileStatcast 2024-2026

Speed71

xwOBA61

Bat Spd18

Avg EV11

Barrel%10

Form.282/.323/.360 ▼ rolling true talent (60d window) · proj .281/.335/.377

CompsNick Van Stratten (age 31) · Eric Owens (age 30) · Norris Hopper (age 30)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 110103vR 83

AVG/OBP/SLG.283 / .339 / .380

PA564

HR7

SB22

K%9

BB%6

BABIP300

ISO97

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Recent Form · Splits · ContractCON 60 / POW 35

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT60

xAVG

900.290

POWER35

Barrel%

101.6

Avg EV

1186.1

Bat Spd

1867.9

EYE45

scouting grade only

SPEED60

Sprint

7128.3

Recent Formrolling true talent ⓘ

K%8%▲7% over 110 PA (60d) · proj 9%

BB%5%▼▼3% over 110 PA (60d) · proj 6%

ISO.077▼.049 over 103 AB (60d) · proj .096

HR/BB1.3%·1.0% over 96 BBE (60d) · proj 1.6%

BABIP.296·.284 over 95 BIP (60d) · proj .298

SLASH.282/.323/.360▼proj .281/.335/.377

Platoon Splits2024-2026 · 1413 PA

vs LHP

vs RHP

Edge

333

1080

—

wRC+

150

◀◀L

wOBA

390

306

◀◀L

ISO

149

091

◀◀L

BABIP

366

285

◀◀L

8.1%

9.3%

◀L

BB%

4.5%

7.1%

▶▶R

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

Status FA

MLB Debut 2019

Service 7.081 yrs.days

Team Control Through 2027

First FA Year 2028

NTCDEF 20%

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$22M	+2.7	$23M	+$1M
Totals		$22M		$23M	+$1M

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)
2018	21	A	South Bend Cubs	—	17	15	6	1	0	1	2	1	0	0	0	400	471	667	1.137	267	385	6	12	493	174	—	—	—	—	—	—
2018	21	ROK	AZL Cubs 1	—	15	12	3	1	1	0	2	0	1	2	0	250	400	500	900	250	250	0	13	396	80	—	—	—	—	—	—
2018	21	INTL	Mesa Solar Sox	—	94	89	30	4	4	1	2	16	2	1	1	337	366	506	871	169	397	17	2	378	142	—	—	—	—	—	—
2019	22	MLB	Chicago Cubs	—	82	78	22	1	1	3	3	11	0	0	0	282	309	436	745	154	292	13	4	325	100	-0	+0	+3	+4	+2	0.9
2019	22	AA	Tennessee Smokies	—	294	268	76	16	3	3	21	31	4	8	4	284	345	399	744	116	311	11	7	334	72	—	—	—	—	—	—
2019	22	ROK	AZL Cubs 2	—	21	20	8	1	0	0	1	1	0	0	0	400	429	450	879	50	421	5	5	396	86	—	—	—	—	—	—
2020	23	MLB	Chicago Cubs	—	126	108	24	4	0	0	12	24	3	3	2	222	315	259	574	37	279	19	10	268	67	-5	-0	+5	+0	+3	0.3
2021	24	MLB	Chicago Cubs	—	170	149	45	10	0	0	17	25	3	5	3	302	385	369	754	67	360	15	10	345	109	+2	-0	+9	+1	+4	1.5
2021	24	AAA	Iowa Cubs	—	28	26	7	1	0	0	0	6	2	0	0	269	321	308	629	38	350	21	0	292	61	—	—	—	—	—	—
2022	25	MLB	Chicago Cubs	—	517	481	135	22	5	10	28	57	6	20	2	281	328	410	738	129	300	11	5	328	103	+2	+3	+13	+6	+11	3.5
2023	26	MLB	Chicago Cubs	—	688	619	175	27	4	9	49	83	14	43	7	283	349	383	732	100	312	12	7	329	108	+6	+6	+11	+2	+15	4.1
2024	27	MLB	Chicago Cubs	—	641	582	159	35	1	7	44	66	12	31	6	273	337	373	710	100	297	10	7	321	101	+1	+4	+8	+2	+14	3.0
2025	28	MLB	Chicago Cubs	—	649	599	178	29	4	7	39	49	7	29	6	297	347	394	741	97	313	8	6	332	108	+6	+3	+13	+2	+14	4.0
2026	29	MLB	Chicago Cubs	—	689	628	165	29	1	8	43	58	10	23	5	263	320	350	670	88	275	8	6	302	89	-9	+3	+2	+2	+15	1.4
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	3562	3244	903	157	16	44	235	373	55	154	31	278	337	377	715	99	301	10	7	321	104	+15	+18	+64	+20	+77	19.9
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2018	21	A MLE	South Bend Cubs	—	17	16	6	1	0	1	1	1	0	0	0	375	412	625	1.037	250	350	6	6	426	174	—	—	—	—	—	—
2018	21	ROK MLE	AZL Cubs 1	—	15	13	3	1	1	0	1	0	1	2	0	231	333	462	795	231	186	0	7	287	80	—	—	—	—	—	—
2019	22	MLB MLE	Chicago Cubs	—	82	79	22	1	1	3	2	11	0	0	0	278	296	430	727	152	292	13	2	315	100	-0	+0	+3	+4	+2	0.9
2019	22	AA MLE	Tennessee Smokies	—	294	275	67	15	3	2	14	39	4	8	4	244	290	342	632	98	273	13	5	275	72	—	—	—	—	—	—
2019	22	ROK MLE	AZL Cubs 2	—	21	20	7	1	0	0	1	1	0	0	0	350	381	400	781	50	331	5	5	295	86	—	—	—	—	—	—
2020	23	MLB MLE	Chicago Cubs	—	126	109	24	4	0	0	12	24	3	3	2	220	315	257	571	37	279	19	10	267	67	-5	-0	+5	+0	+3	0.3
2021	24	MLB MLE	Chicago Cubs	—	170	152	45	10	0	0	14	25	3	5	3	296	367	362	729	66	360	15	8	330	109	+2	-0	+9	+1	+4	1.5
2021	24	AAA MLE	Iowa Cubs	—	28	26	6	1	0	0	0	7	2	0	0	231	286	269	555	38	327	25	0	258	61	—	—	—	—	—	—
2022	25	MLB MLE	Chicago Cubs	—	517	485	133	21	4	10	24	57	6	20	2	274	317	396	712	122	300	11	5	320	103	+2	+3	+13	+6	+11	3.5
2023	26	MLB MLE	Chicago Cubs	—	688	619	173	26	3	9	49	83	14	43	7	279	346	375	721	95	312	12	7	327	108	+6	+6	+11	+2	+15	4.1
2024	27	MLB MLE	Chicago Cubs	—	641	583	158	34	1	7	43	66	12	31	6	271	334	369	703	98	297	10	7	318	101	+1	+4	+8	+2	+14	3.0
2025	28	MLB MLE	Chicago Cubs	—	649	600	176	28	3	7	38	49	7	29	6	293	343	385	728	92	313	8	6	328	108	+6	+3	+13	+2	+14	4.0
2026	29	MLB MLE	Chicago Cubs	—	689	628	164	28	1	8	43	58	10	23	5	261	319	347	666	86	275	8	6	300	89	-9	+3	+2	+2	+15	1.4
2018	21	INTL MLE	3 teams	—	126	112	32	6	3	4	10	5	3	3	1	286	360	500	860	214	269	4	8	361	130	—	—	—	—	—	—
2018	21	INTL RAW	3 teams	—	126	116	39	6	5	2	6	17	3	3	1	336	384	526	910	190	378	13	5	396	130	—	—	—	—	—	—
2019	22	AA MLE	3 teams	—	397	374	94	16	4	5	17	51	4	8	4	251	291	356	647	104	278	13	4	284	79	—	—	—	—	—	—
2019	22	AA RAW	3 teams	—	397	366	106	18	4	6	25	43	4	8	4	290	342	410	752	120	313	11	6	335	79	—	—	—	—	—	—
2020	23	MLB MLE	Chicago Cubs	—	126	109	24	4	0	0	12	24	3	3	2	220	315	257	571	37	276	19	10	267	67	-5	-0	+5	+0	+3	0.3
2020	23	MLB RAW	Chicago Cubs	—	126	108	24	4	0	0	12	24	3	3	2	222	315	259	574	37	279	19	10	268	67	-5	-0	+5	+0	+3	0.3
2021	24	MLB MLE	2 teams	—	198	178	51	11	0	0	14	32	5	5	3	287	355	348	704	62	347	16	7	320	102	+1	-0	+9	+1	+4	1.4
2021	24	MLB RAW	2 teams	—	198	175	52	11	0	0	17	31	5	5	3	297	376	360	736	63	359	16	9	337	102	+1	-0	+9	+1	+4	1.4
2022	25	MLB MLE	Chicago Cubs	—	517	485	133	21	4	10	24	57	6	20	2	274	317	396	712	122	293	11	5	320	103	+2	+3	+13	+6	+11	3.5
2022	25	MLB RAW	Chicago Cubs	—	517	481	135	22	5	10	28	57	6	20	2	281	328	410	738	129	300	11	5	328	103	+2	+3	+13	+6	+11	3.5
2023	26	MLB MLE	Chicago Cubs	—	688	619	173	26	3	9	49	83	14	43	7	279	346	375	721	95	308	12	7	327	108	+6	+6	+11	+2	+15	4.1
2023	26	MLB RAW	Chicago Cubs	—	688	619	175	27	4	9	49	83	14	43	7	283	349	383	732	100	312	12	7	329	108	+6	+6	+11	+2	+15	4.1
2024	27	MLB MLE	Chicago Cubs	—	641	583	158	34	1	7	43	66	12	31	6	271	334	369	703	98	294	10	7	318	101	+1	+4	+8	+2	+14	3.0
2024	27	MLB RAW	Chicago Cubs	—	641	582	159	35	1	7	44	66	12	31	6	273	337	373	710	100	297	10	7	321	101	+1	+4	+8	+2	+14	3.0
2025	28	MLB MLE	Chicago Cubs	—	649	600	176	28	3	7	38	49	7	29	6	293	343	385	728	92	308	8	6	328	108	+6	+3	+13	+2	+14	4.0
2025	28	MLB RAW	Chicago Cubs	—	649	599	178	29	4	7	39	49	7	29	6	297	347	394	741	97	313	8	6	332	108	+6	+3	+13	+2	+14	4.0
2026	29	MLB MLE	Chicago Cubs	—	689	628	164	28	1	8	43	58	10	23	5	261	319	347	666	86	274	8	6	300	89	-9	+3	+2	+2	+15	1.4
2026	29	MLB RAW	Chicago Cubs	—	689	628	165	29	1	8	43	58	10	23	5	263	320	350	670	88	275	8	6	302	89	-9	+3	+2	+2	+15	1.4
2018	21	INTL MLE	3 teams	—	126	112	32	6	3	4	10	5	3	3	1	286	360	500	860	214	273	4	8	361	130	—	—	—	—	—	—
2019	22	AA MLE	3 teams	—	397	373	94	16	4	5	17	51	4	8	4	252	291	357	648	105	280	13	4	284	79	—	—	—	—	—	—
2020	23	MLB MLE	Chicago Cubs	—	126	110	24	4	0	0	12	24	3	3	2	218	315	255	569	36	279	19	10	267	67	—	—	—	—	—	—
2021	24	MLB MLE	2 teams	—	198	177	51	11	0	0	14	32	5	5	3	288	355	350	706	62	355	16	7	320	102	—	—	—	—	—	—
2022	25	MLB MLE	Chicago Cubs	—	517	482	133	21	4	10	24	57	6	20	2	276	317	398	715	122	300	11	5	320	103	—	—	—	—	—	—
2023	26	MLB MLE	Chicago Cubs	—	688	620	173	26	3	9	49	83	14	43	7	279	346	374	720	95	312	12	7	327	108	—	—	—	—	—	—
2024	27	MLB MLE	Chicago Cubs	—	641	581	158	34	1	7	43	66	12	31	6	272	334	370	704	98	297	10	7	318	101	—	—	—	—	—	—
2025	28	MLB MLE	Chicago Cubs	—	649	599	176	28	3	7	38	49	7	29	6	294	343	386	728	92	313	8	6	328	108	—	—	—	—	—	—
2026	29	MLB MLE	Chicago Cubs	—	689	631	164	28	1	8	43	58	10	23	5	260	319	345	664	86	275	8	6	300	89	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	27	MLB MLE	Chicago Cubs	—	641	581	158	34	1	7	43	66	12	31	6	272	334	370	704	98	297	10	7	318	101	—	—	—	—	—	—
2025	28	MLB MLE	Chicago Cubs	—	649	599	176	28	3	7	38	49	7	29	6	294	343	386	728	92	313	8	6	328	108	—	—	—	—	—	—
2026	29	MLB MLE	Chicago Cubs	—	689	631	164	28	1	8	43	58	10	23	5	260	319	345	664	86	275	8	6	300	89	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	30	MLB MLE	CHC	100%	618	565	159	26	2	8	39	55	9	24	5	282	337	377	714	95	298	9	6	321	103	+2	+3	+7	+2	+13	2.7
▸ 2027 — real world (MLB)
2027	30	MLB CTX	CHC	100%	564	515	147	25	2	7	36	50	8	22	5	283	339	380	719	96	300	9	6	323	103	+2	+2	+6	+2	+12	2.6
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	31	MLB MLE	CHC	100%	614	563	155	25	1	7	38	57	8	18	4	277	332	366	698	89	295	9	6	314	99	-1	+2	+4	+2	+13	2.1
2029	32	MLB MLE	CHC	100%	614	564	153	24	1	7	37	60	8	11	3	270	324	352	676	81	290	10	6	305	93	-5	+1	+4	+2	+13	1.5
2030	33	MLB MLE	CHC	100%	485	447	117	18	1	4	29	50	6	5	2	262	315	334	650	72	285	10	6	294	85	-8	+0	+1	+2	+11	0.5
2028	31	MLB CTX	CHC	100%	614	563	157	26	2	7	38	57	8	18	4	278	333	369	702	90	297	9	6	316	99	-1	+2	+4	+2	+13	2.1
2029	32	MLB CTX	CHC	100%	614	564	153	25	1	6	37	60	8	11	3	272	326	354	680	82	292	10	6	307	93	-5	+1	+4	+2	+13	1.5
2030	33	MLB CTX	CHC	100%	485	447	118	18	1	4	29	50	6	5	2	264	317	337	653	73	287	10	6	296	85	-8	+0	+1	+2	+11	0.5
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	5275	4818	1331	226	20	61	339	540	77	188	40	276	334	369	703	93	299	10	6	317	98	+0	+22	+73	+27	+114	24.0
/ 162G	—	A+C		—	650	594	164	28	2	8	42	67	9	23	5	276	333	370	704	94	298	10	6	317	98	+0	+3	+9	+3	+14	3.0
Career	—	MLE		—	6308	5777	1575	265	23	75	390	642	94	221	50	273	329	365	694	93	294	10	6	313	98	+2	+24	+79	+29	+127	26.6
/ 162G	—	MLE		—	650	595	162	27	2	8	40	66	10	23	5	272	329	365	693	92	293	10	6	313	98	+0	+3	+9	+3	+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.

2021 AAAIowa Cubs · 28 PAwOBA .285 → .258 (−27)K% 21.4% → 24.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.43%	÷1.032	×1.200	—	—	24.91%
BB% (unintentional) /PA	0.00%	÷1.023	×0.690	—	×1.048	0.00%
HBP% /PA	7.14%	—	×0.940	—	×1.048	7.04%
Singles /BIP	30.00%	÷1.039	×0.930	—	×1.048	28.13%
Doubles /BIP	5.00%	÷0.963	×0.830	—	×1.048	4.52%
Triples /BIP	0.00%	÷0.988	×0.920	—	×1.048	0.00%
Home runs /BIP	0.00%	÷1.081	×0.700	—	×1.048	0.00%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 116, 1B 108, 2B 93, 3B 98, K 106, BB 105 — applied at half strength. Age: age 24 vs a level average of 27.2 → +4.8% on BB/HBP/hit rates (3.2 yr younger than average).

Result: wOBA .285 → .258; ISO .038 → .033; BABIP .350 → .327. 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 AATennessee Smokies · 294 PAwOBA .326 → .275 (−51)K% 10.5% → 13.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.54%	÷0.972	×1.220	—	—	13.23%
BB% (unintentional) /PA	7.14%	÷1.047	×0.680	—	×1.042	4.83%
HBP% /PA	1.36%	—	×0.840	—	×1.042	1.19%
Singles /BIP	22.78%	÷1.051	×0.920	×0.950	×1.042	19.74%
Doubles /BIP	6.75%	÷0.977	×0.910	×0.950	×1.042	6.23%
Triples /BIP	1.27%	÷0.957	×0.880	×0.950	×1.042	1.15%
Home runs /BIP	1.27%	÷1.142	×0.800	—	×1.042	0.92%

Factors used: league row SL. Park (home-season share, regressed): HR 128, 1B 110, 2B 95, 3B 91, K 94, BB 109 — applied at half strength. Age: age 22 vs a level average of 24.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .326 → .275; ISO .116 → .100; BABIP .311 → .273. 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 ROKAZL Cubs 2 · 21 PAwOBA .385 → .295 (−90)K% 4.8% → 6.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	4.76%	÷1.000	×1.440	—	—	6.86%
BB% (unintentional) /PA	4.76%	÷1.000	×0.620	—	×0.975	2.88%
HBP% /PA	0.00%	—	×0.720	—	×0.975	0.00%
Singles /BIP	36.84%	÷1.000	×0.820	—	×0.975	29.46%
Doubles /BIP	5.26%	÷1.000	×0.720	—	×0.975	3.69%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.975	0.00%
Home runs /BIP	0.00%	÷1.000	×0.780	—	×0.975	0.00%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 22 vs a level average of 19.5 → −2.5% on BB/HBP/hit rates (2.5 yr older than average).

Result: wOBA .385 → .295; ISO .050 → .035; BABIP .421 → .331. 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 ASouth Bend Cubs · 17 PAwOBA .479 → .426 (−53)K% 5.9% → 8.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	5.88%	÷1.005	×1.360	—	—	7.96%
BB% (unintentional) /PA	11.76%	÷0.968	×0.690	—	×1.015	8.52%
HBP% /PA	0.00%	—	×0.780	—	×1.015	0.00%
Singles /BIP	28.57%	÷0.982	×0.920	—	×1.015	27.17%
Doubles /BIP	7.14%	÷1.092	×0.830	—	×1.015	5.51%
Triples /BIP	0.00%	÷1.000	×0.910	—	×1.015	0.00%
Home runs /BIP	7.14%	÷0.881	×0.800	—	×1.015	6.58%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 76, 1B 96, 2B 118, 3B 100, K 101, BB 94 — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average).

Result: wOBA .479 → .426; ISO .267 → .239; BABIP .385 → .350. 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 ROKAZL Cubs 1 · 15 PAwOBA .386 → .287 (−100)K% 0.0% → 0.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	0.00%	÷1.000	×1.440	—	—	0.00%
BB% (unintentional) /PA	13.33%	÷1.000	×0.620	—	×0.985	8.14%
HBP% /PA	6.67%	—	×0.720	—	×0.985	4.73%
Singles /BIP	8.33%	÷1.000	×0.820	—	×0.985	6.73%
Doubles /BIP	8.33%	÷1.000	×0.720	—	×0.985	5.91%
Triples /BIP	8.33%	÷1.000	×0.720	—	×0.985	5.91%
Home runs /BIP	0.00%	÷1.000	×0.780	—	×0.985	0.00%

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

Result: wOBA .386 → .287; ISO .250 → .193; BABIP .250 → .186. 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
#1Jose Iglesiaslast yr '25 career totals — 12 seasons, 4,671 PA	7.0	4,671	54	70	279	321	380	+46	+81	24.3	21.4
/162	664	8	10	+6.5	+11.5	3.5	pk7: 18
#2Erick Aybarlast yr '17 career totals — 11 seasons, 5,588 PA	8.4	5,588	58	154	271	314	372	+58	+49	22.0	21.3
/162	664	7	18	+6.9	+5.8	2.6	pk7: 21
#3Jody Reed'87-'97 * career totals — 10 seasons, 5,248 PA	7.9	5,248	27	40	265*	345*	365*	+24	+76	21.7	20.8
/162	664	3	5	+3.1	+9.6	2.7	pk7: 20
#4Jason Bartlettlast yr '12 career totals — 8 seasons, 3,503 PA	5.3	3,503	31	121	271	337	368	+38	+56	20.3	20.5
/162	664	6	23	+7.1	+10.7	3.8	pk7: 21
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 12 projected seasons	8.8	5,839	70	210	278	331	371	+21	+104	19.3	18.0
/162	664	8	24	+2.4	+11.8	2.2	pk7: 17
#5Harold Reynolds'83-'94 * career totals — 11 seasons, 5,398 PA	8.1	5,398	21	250	255*	325*	359*	+18	+53	13.8	14.7
/162	664	3	31	+2.3	+6.6	1.7	pk7: 16
#6Marty Barrett'82-'91 * career totals — 7 seasons, 3,833 PA	5.8	3,833	18	57	275*	337*	362*	+12	+34	11.2	11.6
/162	664	3	10	+2.2	+6.0	1.9	pk7: 12

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
Nico Hoerner (OGILVIE)	30	60	35	60	45	279/335/374	95	298	7	22	9%	6%	103	+1.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Nick Van Stratten 2016 · AAA	31	63→58	40	58→55	47	300/341/400	100	336	7	24	13%	5%	110	+2.1	262/303/353	91	291	6	20	12%	5%	86	+0.3	269/303/337	68	293	1	24	8%	4%	78	-0.1
✕Eric Owens 2001 · MLB	30	58→61	40	54→55	52	280/331/375	95	303	7	24	10%	7%	101	+1.4	262/310/351	89	287	7	22	11%	6%	88	+0.4	257/303/333	75	282	5	24	10%	6%	81	-0.0
✕Norris Hopper 2009 · MLB	30	60→69	35→30	53→55	50	284/326/345	62	314	3	21	11%	6%	92	+0.7	250/291/300	50	277	2	21	10%	5%	68	-1.0	254/292/286	32	280	0	24	9%	5%	62	-1.1
✕Ryan Theriot 2010 · MLB	30	60→65	38→40	51→55	56	282/346/359	78	313	5	19	12%	9%	103	+1.6	270/321/336	66	304	3	15	11%	7%	88	+0.5	267/315/320	53	300	1	15	11%	6%	83	+0.1
✕Alejandro Ahumada 2009 · AAA	30	58→68	39→40	54→55	44	275/311/361	87	323	6	22	17%	4%	90	+0.6	237/285/307	70	294	4	14	20%	4%	69	-0.9	255/303/316	61	320	4	10	20%	5%	73	-0.3
✕Erick Aybar 2013 · MLB	29	57→63	43→45	57→60	47	275/315/401	125	299	9	23	12%	5%	101	+1.4	272/307/380	108	297	7	15	11%	4%	93	+0.8	269/304/361	92	294	5	14	10%	4%	88	+0.5
✕Julio Lugo 2006 · MLB	30	58→62	42→45	56→60	54	280/345/398	118	315	8	24	14%	8%	112	+2.2	262/326/379	117	297	9	27	14%	8%	101	+1.4	252/320/362	110	287	9	29	15%	9%	95	+0.8
✕Alcides Escobar 2017 · MLB	30	54→64	39→45	54→55	45	259/292/344	85	290	6	17	13%	4%	79	-0.2	241/275/340	99	278	7	9	16%	4%	72	-0.7	237/281/345	108	288	8	6	20%	4%	75	-0.3
✕Mike McCoy 2011 · MLB	30	53→58	40	59→60	54	252/322/345	93	299	6	29	17%	9%	91	+0.7	228/308/307	79	276	6	30	18%	10%	78	-0.3	218/302/282	64	264	5	33	18%	10%	68	-0.7
●David Eckstein 2004 · MLB	29	56→64	39→40	51→55	53	266/337/351	85	281	6	19	8%	7%	99	+1.2	275/340/354	79	293	5	13	8%	7%	100	+1.3	291/353/368	76	306	4	10	6%	6%	109	+1.9
✕Christian Quintero 2006 · AAA	30	58→63	45	58→55	48	283/323/417	134	298	12	21	10%	5%	108	+1.9	274/307/384	110	293	10	23	10%	4%	95	+0.9	275/313/392	117	296	12	21	11%	5%	97	+0.9
✕Doug Glanville 2001 · MLB	30	55→56	41→45	56→55	47	262/298/365	103	284	8	24	12%	5%	86	+0.3	254/285/359	105	278	11	22	13%	4%	80	-0.1	251/279/349	99	273	11	22	13%	3%	76	-0.3
✕Endy Chavez 2007 · MLB	29	56→61	41→45	56→55	50	266/307/374	108	288	6	21	11%	6%	92	+0.7	263/304/356	93	287	6	16	10%	6%	86	+0.3	266/302/351	85	286	6	20	9%	5%	84	+0.1
●Jason Bartlett 2009 · MLB	29	58→65	38→45	55	49	274/327/364	91	312	4	21	14%	6%	97	+1.1	274/337/388	114	318	8	22	15%	8%	107	+1.8	267/335/374	107	312	7	22	16%	8%	103	+1.5
✕Willie Bloomquist 2008 · MLB	30	53→55	38→40	53→60	49	252/307/326	74	295	6	24	16%	7%	81	-0.1	259/317/338	79	305	6	28	16%	8%	87	+0.4	293/322/363	70	348	1	7	15%	4%	94	+0.3
✕Michael Spidale 2012 · AAA	30	61→66	36→40	51→55	45	288/324/356	68	327	4	19	13%	4%	94	+0.9	260/291/331	71	293	5	14	13%	3%	76	-0.4	265/278/302	37	290	1	13	9%	1%	59	-0.8
✕Jose Macias 2002 · MLB	30	53→61	43→45	56→50	52	257/310/379	122	275	10	18	11%	7%	95	+0.9	247/290/370	123	278	11	13	15%	5%	85	+0.2	284/326/405	122	299	8	8	8%	6%	103	+1.0
✕Alfredo Amezaga 2008 · MLB	30	55→56	39→40	54→55	53	258/319/349	92	289	5	21	13%	8%	91	+0.6	247/300/348	101	285	7	14	15%	6%	84	+0.1	253/302/326	73	298	5	6	16%	6%	77	-0.2
✕Craig Gentry 2014 · MLB	30	56→55	39→40	62→60	50	262/336/357	95	311	5	35	17%	7%	100	+1.3	232/293/302	70	287	5	30	20%	7%	71	-0.8	218/282/291	73	279	4	29	22%	7%	64	-0.4
✕Isiah Kiner-Falefa 2024 · MLB	29	53→58	40	52→55	49	253/307/341	88	291	8	21	16%	6%	85	+0.2	255/302/350	95	298	8	18	17%	5%	85	+0.2	256/301/341	85	300	6	19	16%	5%	83	+0.1

Nico Hoerner

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps