Miguel Amaya

C Chicago Cubs

Age 28 R/R 6'1" / 230 lbs MLB HR -8% Svc 3.756 · Ctrl thru 2029

Overview

MLB40-MANArb-1FA 2030

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	25	MLBCHC	363	.232/.290/.357	8	0	78	1.0
2025	26	AAACHC	45	.195/.250/.195	0	0	17	—	.190/.227/.190
2025	26	MLBCHC	103	.281/.317/.500	4	0	123	1.0
2026	27	MLBCHC	254	.237/.340/.377	6	0	104	1.3
2027PROJ	28	MLBCHC	167	.219/.299/.360	4	1	87	0.4
2028PROJ82% MLB	29	MLBCHC	166	.216/.296/.353	4	0	84	0.2

Last 3 seasons WAR 3.3 · Next 2 projected WAR 0.7Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2029Service3.756First FA2030

2027Arb-1$0.9M2028Arb-2$1M2029Ext$2M

Skills · percentileStatcast 2024-2026

xwOBA41

Barrel%34

Avg EV34

Bat Spd20

Speed10

Form.216/.289/.366 · rolling true talent (60d window) · proj .217/.296/.360

CompsLuis Torrens (age 28) · Kevin Plawecki (age 28) · Pedro Severino (age 28)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 8987vR 80

AVG/OBP/SLG.219 / .299 / .360

PA167

HR4

K%25

BB%8

BABIP271

ISO142

MLB%100%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$4M ctrl surplus

Tools · Recent Form · Splits · ContractCON 50 / POW 40

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT50

xAVG

270.232

POWER40

Barrel%

346.1

Avg EV

3487.9

Bat Spd

2068.1

EYE40

scouting grade only

SPEED40

Sprint

1025.4

Recent Formrolling true talent ⓘ

K%26%▼28% over 39 PA (60d) · proj 25%

BB%7%▼5% over 39 PA (60d) · proj 8%

ISO.151·.194 over 31 AB (60d) · proj .142

BABIP.272·.400 over 20 BIP (60d) · proj .269

SLASH.216/.289/.366·proj .217/.296/.360

Platoon Splits2024-2026 · 517 PA

vs LHP

vs RHP

Edge

135

382

—

wRC+

105

▶▶R

wOBA

236

323

▶▶R

ISO

099

155

▶▶R

BABIP

214

298

▶▶R

18.5%

18.8%

—

BB%

6.7%

6.3%

◀L

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

Status Arb-1

MLB Debut 2023

Service 3.756 yrs.days

Team Control Through 2029

First FA Year 2030

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-1	$0.9M	+0.5	$2M	+$1M
2028	Arb-2	$1M	+0.2	$0.7M	+$0.0M (cut)
2029	Ext	beyond projection horizon · no WAR estimate
Totals		$0.9M		$3M	+$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. Catcher framing: only 2027 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run 1-3 WAR low.

Year	Age	Lvl	Team	MLB%	PA	AB	H	2B	3B	HR	BB	SO	HBP	SB	CS	AVG	OBP	SLG	OPS	ISO	BABIP	K%	BB%	wOBA	wRC+	BAT	RUN	FLD	POS	REP	WAR
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
2016	17	ROK	DSL Cubs 2	—	242	208	51	12	0	1	21	27	11	9	3	245	346	317	663	72	276	11	9	308	28	—	—	—	—	—	—
2018	19	A	South Bend Cubs	—	479	414	106	21	2	12	50	91	11	1	0	256	352	403	755	147	298	19	10	339	76	—	—	—	—	—	—
2019	20	A+	Myrtle Beach Pelicans	—	410	341	80	24	0	11	54	69	10	2	0	235	356	402	757	167	259	17	13	340	78	—	—	—	—	—	—
2019	20	INTL	Mesa Solar Sox	—	55	49	11	3	0	0	5	12	0	0	0	224	296	286	582	61	289	22	9	265	66	—	—	—	—	—	—
2020	21	INTL	Criollos de Caguas	—	38	23	6	2	0	2	8	3	7	0	0	261	553	609	1.161	348	222	8	21	507	229	—	—	—	—	—	—
2021	22	AA	Tennessee Smokies	—	106	79	17	4	0	1	21	22	5	2	0	215	410	304	713	89	281	21	20	343	81	—	—	—	—	—	—
2022	23	AA	Tennessee Smokies	—	116	97	27	6	1	4	14	28	3	0	0	278	386	485	871	206	343	24	12	380	108	—	—	—	—	—	—
2022	23	ROK	ACL Cubs	—	44	37	8	0	0	2	7	13	0	0	0	216	341	378	719	162	273	30	16	329	26	—	—	—	—	—	—
2023	24	MLB	Chicago Cubs	—	156	131	28	4	0	5	12	40	11	0	0	214	331	359	690	145	264	26	8	315	100	+0	+0	+4	+5	+3	1.2
2023	24	AAA	Iowa Cubs	—	60	48	15	5	0	1	11	14	1	0	0	312	450	479	929	167	424	23	18	418	120	—	—	—	—	—	—
2023	24	AA	Tennessee Smokies	—	56	44	12	5	0	4	8	17	3	1	0	273	418	659	1.077	386	333	30	14	451	131	—	—	—	—	—	—
2024	25	MLB	Chicago Cubs	—	363	328	76	13	2	8	23	62	4	0	0	232	290	357	647	125	261	17	6	285	78	-9	+0	+4	+6	+8	1.0
2025	26	MLB	Chicago Cubs	—	103	96	27	9	0	4	4	22	1	0	0	281	317	500	817	219	324	21	4	350	123	+3	+0	+2	+3	+2	1.0
2025	26	AAA	Iowa Cubs	—	45	41	8	0	0	0	3	7	0	0	0	195	250	195	445		229	16	7	207	17	—	—	—	—	—	—
2026	27	MLB	Chicago Cubs	—	254	215	51	12	0	6	23	67	11	0	0	237	340	377	717	140	315	26	9	322	104	+1	+0	+1	+5	+6	1.3
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	876	770	182	38	2	23	62	191	27	0	0	236	315	381	696	144	283	22	7	309	95	-5	+0	+12	+19	+19	4.5
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2016	17	ROK MLE	DSL Cubs 2	—	242	214	35	8	0	0	15	33	11	9	3	164	254	201	455	37	186	14	6	209	28	—	—	—	—	—	—
2018	19	A MLE	South Bend Cubs	—	479	430	95	16	2	11	34	123	11	1	0	221	295	344	639	123	272	26	7	281	76	—	—	—	—	—	—
2019	20	A+ MLE	Myrtle Beach Pelicans	—	410	361	74	20	0	11	34	97	10	2	0	205	291	352	643	147	239	24	8	283	78	—	—	—	—	—	—
2021	22	AA MLE	Tennessee Smokies	—	106	86	17	4	0	1	14	27	5	2	0	198	343	279	622	81	268	25	13	288	81	—	—	—	—	—	—
2022	23	AA MLE	Tennessee Smokies	—	116	101	25	6	1	3	10	36	3	0	0	248	333	416	749	168	330	31	9	328	108	—	—	—	—	—	—
2022	23	ROK MLE	ACL Cubs	—	44	40	5	0	0	1	4	19	0	0	0	125	205	200	405	75	213	43	9	207	26	—	—	—	—	—	—
2023	24	MLB MLE	Chicago Cubs	—	156	131	28	4	0	5	12	40	11	0	0	214	331	359	690	145	264	26	8	317	100	+0	+0	+4	+5	+3	1.2
2023	24	AAA MLE	Iowa Cubs	—	60	52	14	4	0	1	7	16	1	0	0	269	367	404	771	135	382	27	12	346	120	—	—	—	—	—	—
2023	24	AA MLE	Tennessee Smokies	—	56	47	11	5	0	3	5	21	3	1	0	234	345	532	877	298	295	38	9	362	131	—	—	—	—	—	—
2024	25	MLB MLE	Chicago Cubs	—	363	328	76	13	2	8	23	62	4	0	0	232	290	357	647	125	261	17	6	284	78	-9	+0	+4	+6	+8	1.0
2025	26	MLB MLE	Chicago Cubs	—	103	96	27	9	0	4	4	22	1	0	0	281	317	500	817	219	324	21	4	350	123	+3	+0	+2	+3	+2	1.0
2025	26	AAA MLE	Iowa Cubs	—	45	42	8	0	0	0	2	9	0	0	0	190	227	190	418		228	20	4	194	17	—	—	—	—	—	—
2026	27	MLB MLE	Chicago Cubs	—	254	216	51	12	0	6	23	67	11	0	0	236	340	375	715	139	315	26	9	322	104	+1	+0	+1	+5	+6	1.3
2016	17	ROK MLE	DSL Cubs 2	—	242	214	35	8	0	0	15	33	11	9	3	164	254	201	455	37	192	14	6	209	28	—	—	—	—	—	—
2016	17	ROK RAW	DSL Cubs 2	—	242	208	51	12	0	1	21	27	11	9	3	245	346	317	663	72	276	11	9	308	28	—	—	—	—	—	—
2018	19	A MLE	South Bend Cubs	—	479	430	95	16	2	11	34	123	11	1	0	221	295	344	639	123	280	26	7	281	76	—	—	—	—	—	—
2018	19	A RAW	South Bend Cubs	—	479	414	106	21	2	12	50	91	11	1	0	256	352	403	755	147	298	19	10	339	76	—	—	—	—	—	—
2019	20	A+ MLE	2 teams	—	465	410	84	23	0	12	39	110	10	2	0	205	290	349	639	144	245	24	8	283	78	—	—	—	—	—	—
2019	20	A+ RAW	2 teams	—	465	390	91	27	0	11	59	81	10	2	0	233	349	387	736	154	263	17	13	331	78	—	—	—	—	—	—
2020	21	INTL MLE	Criollos de Caguas	—	38	23	6	2	0	2	8	3	7	0	0	261	553	609	1.161	348	222	8	21	—	—	—	—	—	—	—	—
2020	21	INTL RAW	Criollos de Caguas	—	38	23	6	2	0	2	8	3	7	0	0	261	553	609	1.161	348	222	8	21	507	229	—	—	—	—	—	—
2021	22	AA MLE	Tennessee Smokies	—	106	86	17	4	0	1	14	27	5	2	0	198	343	279	622	81	271	25	13	288	81	—	—	—	—	—	—
2021	22	AA RAW	Tennessee Smokies	—	106	79	17	4	0	1	21	22	5	2	0	215	410	304	713	89	281	21	20	343	81	—	—	—	—	—	—
2022	23	AA MLE	2 teams	—	160	141	31	6	1	5	14	55	3	0	0	220	304	383	687	163	313	34	9	295	86	—	—	—	—	—	—
2022	23	AA RAW	2 teams	—	160	134	35	6	1	6	21	41	3	0	0	261	373	455	829	194	326	26	13	366	86	—	—	—	—	—	—
2023	24	MLB MLE	3 teams	—	272	230	53	13	0	9	24	77	15	1	0	230	342	404	746	174	301	28	9	333	111	+4	+0	+4	+5	+6	1.9
2023	24	MLB RAW	3 teams	—	272	223	55	14	0	10	31	71	15	1	0	247	375	444	819	197	312	26	11	366	111	+4	+0	+4	+5	+6	1.9
2024	25	MLB MLE	Chicago Cubs	—	363	328	76	13	2	8	23	62	4	0	0	232	290	357	647	125	261	17	6	284	78	-9	+0	+4	+6	+8	1.0
2024	25	MLB RAW	Chicago Cubs	—	363	328	76	13	2	8	23	62	4	0	0	232	290	357	647	125	261	17	6	285	78	-9	+0	+4	+6	+8	1.0
2025	26	MLB MLE	2 teams	—	148	138	35	9	0	4	6	31	1	0	0	254	290	406	695	152	295	21	4	303	91	-2	+0	+2	+3	+3	0.7
2025	26	MLB RAW	2 teams	—	148	137	35	9	0	4	7	29	1	0	0	255	297	409	705	153	292	20	5	307	91	-2	+0	+2	+3	+3	0.7
2026	27	MLB MLE	Chicago Cubs	—	254	216	51	12	0	6	23	67	11	0	0	236	340	375	715	139	312	26	9	322	104	+1	+0	+1	+5	+6	1.3
2026	27	MLB RAW	Chicago Cubs	—	254	215	51	12	0	6	23	67	11	0	0	237	340	377	717	140	315	26	9	322	104	+1	+0	+1	+5	+6	1.3
2016	17	ROK MLE	DSL Cubs 2	—	242	214	35	8	0	0	15	33	11	9	3	164	254	201	455	37	186	14	6	209	28	—	—	—	—	—	—
2018	19	A MLE	South Bend Cubs	—	479	431	95	16	2	11	34	123	11	1	0	220	295	343	638	123	272	26	7	281	76	—	—	—	—	—	—
2019	20	A+ MLE	2 teams	—	465	413	84	23	0	12	39	110	10	2	0	203	290	346	636	143	239	24	8	283	78	—	—	—	—	—	—
2021	22	AA MLE	Tennessee Smokies	—	106	86	17	4	0	1	14	27	5	2	0	198	343	279	622	81	268	25	13	288	81	—	—	—	—	—	—
2022	23	AA MLE	2 teams	—	160	142	31	6	1	5	14	55	3	0	0	218	304	380	684	162	298	34	9	295	86	—	—	—	—	—	—
2023	24	MLB MLE	3 teams	—	272	231	53	13	0	9	24	77	15	1	0	229	342	403	745	173	297	28	9	333	111	—	—	—	—	—	—
2024	25	MLB MLE	Chicago Cubs	—	363	333	76	13	2	8	23	62	4	0	0	228	290	351	641	123	261	17	6	284	78	—	—	—	—	—	—
2025	26	MLB MLE	2 teams	—	148	140	35	9	0	4	6	31	1	0	0	250	290	400	690	150	295	21	4	303	91	—	—	—	—	—	—
2026	27	MLB MLE	Chicago Cubs	—	254	218	51	12	0	6	23	67	11	0	0	234	340	372	712	138	315	26	9	322	104	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	25	MLB MLE	Chicago Cubs	—	363	333	76	13	2	8	23	62	4	0	0	228	290	351	641	123	261	17	6	284	78	—	—	—	—	—	—
2025	26	MLB MLE	2 teams	—	148	140	35	9	0	4	6	31	1	0	0	250	290	400	690	150	295	21	4	303	91	—	—	—	—	—	—
2026	27	MLB MLE	Chicago Cubs	—	254	218	51	12	0	6	23	67	11	0	0	234	340	372	712	138	315	26	9	322	104	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	28	MLB MLE	CHC	100%	269	240	52	11	1	7	21	67	6	1	0	218	298	360	658	142	269	25	8	296	87	-4	+0	+0	+5	+6	0.5
▸ 2027 — real world (MLB)
2027	28	MLB CTX	CHC	100%	167	148	32	7	1	4	13	41	4	1	0	219	299	360	659	141	271	25	8	297	87	-3	+0	+0	+3	+4	0.4
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	29	MLB MLE	CHC	82%	203	180	40	9	1	5	16	51	5	0	0	215	295	353	648	138	267	25	8	292	84	-4	+0	-1	+4	+4	0.3
2028	29	MLB CTX	CHC	82%	166	148	31	7	0	4	13	42	4	0	0	216	296	353	650	137	270	25	8	293	84	-3	+0	-1	+3	+4	0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1042	918	213	45	2	27	75	233	31	0	0	232	311	374	685	142	280	22	7	306	79	-8	+0	+10	+21	+23	4.7
/ 162G	—	A+C		—	650	573	133	28	1	17	47	145	19	0	0	232	311	373	684	141	280	22	7	306	79	-5	+0	+7	+13	+14	3.0
Career	—	MLE		—	2897	2544	554	122	6	67	229	680	87	16	3	218	304	349	654	132	267	23	8	284	79	-11	+0	+10	+25	+27	5.2
/ 162G	—	MLE		—	650	571	124	27	1	15	51	153	20	4	1	217	304	347	650	130	267	24	8	284	79	-6	+0	+5	+13	+14	2.7

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 · 45 PAwOBA .207 → .194 (−13)K% 15.6% → 18.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.56%	÷0.989	×1.200	—	—	18.88%
BB% (unintentional) /PA	6.67%	÷1.005	×0.690	—	×1.018	4.66%
HBP% /PA	0.00%	—	×0.940	—	×1.018	0.00%
Singles /BIP	23.53%	÷0.949	×0.930	—	×1.018	23.47%
Doubles /BIP	0.00%	÷1.033	×0.830	—	×1.018	0.00%
Triples /BIP	0.00%	÷0.939	×0.970	—	×1.018	0.00%
Home runs /BIP	0.00%	÷1.125	×0.700	—	×1.018	0.00%

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 26 vs a level average of 27.2 → +1.8% on BB/HBP/hit rates (1.2 yr younger than average).

Result: wOBA .207 → .194; ISO .000 → .000; BABIP .229 → .228. 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 AAAIowa Cubs · 60 PAwOBA .403 → .346 (−57)K% 23.3% → 27.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.33%	÷1.019	×1.200	—	—	27.48%
BB% (unintentional) /PA	16.67%	÷1.014	×0.690	—	×1.048	11.88%
HBP% /PA	1.67%	—	×0.940	—	×1.048	1.64%
Singles /BIP	26.47%	÷1.025	×0.930	—	×1.048	25.18%
Doubles /BIP	14.71%	÷1.049	×0.830	—	×1.048	12.20%
Triples /BIP	0.00%	÷0.916	×0.970	—	×1.048	0.00%
Home runs /BIP	2.94%	÷0.965	×0.700	—	×1.048	2.23%

Factors used: league row International League. Park (home-season share, regressed): HR 93, 1B 105, 2B 110, 3B 83, K 104, BB 103 — 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 .403 → .346; ISO .167 → .139; BABIP .424 → .382. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2023 AATennessee Smokies · 56 PAwOBA .447 → .362 (−85)K% 30.4% → 36.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.36%	÷1.008	×1.220	—	—	36.75%
BB% (unintentional) /PA	14.29%	÷1.059	×0.680	—	×1.012	9.28%
HBP% /PA	5.36%	—	×0.840	—	×1.012	4.55%
Singles /BIP	11.11%	÷0.975	×0.920	—	×1.012	10.61%
Doubles /BIP	18.52%	÷1.023	×0.910	—	×1.012	16.67%
Triples /BIP	0.00%	÷0.966	×0.880	—	×1.012	0.00%
Home runs /BIP	14.81%	÷1.082	×0.800	—	×1.012	11.08%

Factors used: league row SL. Park (home-season share, regressed): HR 116, 1B 95, 2B 105, 3B 93, K 102, BB 112 — 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).

Result: wOBA .447 → .362; ISO .386 → .314; BABIP .333 → .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).

2022 AATennessee Smokies · 116 PAwOBA .377 → .328 (−49)K% 24.1% → 30.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.14%	÷0.958	×1.220	—	—	30.76%
BB% (unintentional) /PA	12.07%	÷0.940	×0.680	—	×1.027	8.97%
HBP% /PA	2.59%	—	×0.840	—	×1.027	2.23%
Singles /BIP	23.19%	÷0.982	×0.920	×1.002	×1.027	22.35%
Doubles /BIP	8.70%	÷0.929	×0.910	×1.002	×1.027	8.76%
Triples /BIP	1.45%	÷0.973	×0.880	×1.002	×1.027	1.35%
Home runs /BIP	5.80%	÷1.010	×0.800	—	×1.027	4.71%

Factors used: league row SL. Park (home-season share, regressed): HR 102, 1B 96, 2B 86, 3B 95, K 92, BB 88 — applied at half strength. Age: age 23 vs a level average of 24.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.002.

Result: wOBA .377 → .328; ISO .206 → .178; BABIP .343 → .330. 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 ROKACL Cubs · 44 PAwOBA .321 → .207 (−114)K% 29.5% → 43.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	29.55%	÷0.981	×1.440	—	—	43.36%
BB% (unintentional) /PA	15.91%	÷1.083	×0.620	—	×0.965	8.79%
HBP% /PA	0.00%	—	×0.720	—	×0.965	0.00%
Singles /BIP	25.00%	÷0.993	×0.820	—	×0.965	19.91%
Doubles /BIP	0.00%	÷0.970	×0.720	—	×0.965	0.00%
Triples /BIP	0.00%	÷1.054	×0.720	—	×0.965	0.00%
Home runs /BIP	8.33%	÷0.963	×0.780	—	×0.965	6.52%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 93, 1B 99, 2B 94, 3B 111, K 96, BB 117 — applied at half strength. Age: age 23 vs a level average of 19.5 → −3.5% on BB/HBP/hit rates (3.5 yr older than average).

Result: wOBA .321 → .207; ISO .162 → .111; BABIP .273 → .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).

2021 AATennessee Smokies · 106 PAwOBA .339 → .288 (−52)K% 20.8% → 25.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.75%	÷0.990	×1.220	—	—	25.59%
BB% (unintentional) /PA	19.81%	÷1.066	×0.690	—	×1.042	13.37%
HBP% /PA	4.72%	—	×0.850	—	×1.042	4.18%
Singles /BIP	21.05%	÷0.970	×0.940	×0.975	×1.042	20.73%
Doubles /BIP	7.02%	÷1.015	×0.870	×0.975	×1.042	6.11%
Triples /BIP	0.00%	÷1.150	×0.920	×0.975	×1.042	0.00%
Home runs /BIP	1.75%	÷1.050	×0.780	—	×1.042	1.36%

Factors used: level-wide AA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 110, 1B 94, 2B 103, 3B 130, K 98, BB 113 — 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 ×0.975.

Result: wOBA .339 → .288; ISO .089 → .078; BABIP .281 → .268. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2019 A+Myrtle Beach Pelicans · 410 PAwOBA .336 → .283 (−53)K% 16.8% → 23.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.83%	÷1.009	×1.420	—	—	23.68%
BB% (unintentional) /PA	13.17%	÷1.041	×0.630	—	×1.042	8.31%
HBP% /PA	2.44%	—	×0.860	—	×1.042	2.19%
Singles /BIP	16.54%	÷0.967	×0.940	×0.950	×1.042	15.92%
Doubles /BIP	8.82%	÷0.968	×0.830	×0.950	×1.042	7.49%
Triples /BIP	0.00%	÷0.964	×0.800	×0.950	×1.042	0.00%
Home runs /BIP	4.04%	÷0.956	×0.900	—	×1.042	3.97%

Factors used: league row CAR. Park (home-season share, regressed): HR 91, 1B 93, 2B 94, 3B 93, K 102, BB 108 — applied at half strength. Age: age 20 vs a level average of 22.8 → +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 .336 → .283; ISO .167 → .154; BABIP .259 → .239. 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 · 479 PAwOBA .329 → .281 (−48)K% 19.0% → 25.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.00%	÷1.005	×1.360	—	—	25.72%
BB% (unintentional) /PA	9.39%	÷0.968	×0.690	—	×1.045	7.00%
HBP% /PA	2.30%	—	×0.780	—	×1.045	1.87%
Singles /BIP	21.98%	÷0.982	×0.920	×0.976	×1.045	21.00%
Doubles /BIP	6.50%	÷1.092	×0.830	×0.976	×1.045	5.04%
Triples /BIP	0.62%	÷1.000	×0.910	×0.976	×1.045	0.57%
Home runs /BIP	3.72%	÷0.881	×0.800	—	×1.045	3.53%

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 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.976.

Result: wOBA .329 → .281; ISO .147 → .127; BABIP .298 → .272. 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
#1Kelly Shoppachlast yr '13 career totals — 8 seasons, 1,839 PA	2.8	1,839	70	1	225	314	417	+33	+14	11.3	11.5
/162	664	25	0	+11.9	+5.0	4.1	pk7: 12
#2Jorge Alfarolast yr '23 career totals — 7 seasons, 1,693 PA	2.5	1,693	48	18	254	303	396	+30	+17	9.1	9.1
/162	664	19	7	+11.9	+6.6	3.6	pk7: 9
#3Elrod Hendricks'68-'79 * career totals — 9 seasons, 2,155 PA	3.2	2,155	62	1	224*	308*	401*	+37	-0	8.7	8.7
/162	664	19	0	+11.4	-0.1	2.7	pk7: 9
#4Jim Essian'73-'84 * career totals — 9 seasons, 2,146 PA	3.2	2,146	33	9	239*	326*	368*	+34	-1	8.0	7.9
/162	664	10	3	+10.5	-0.4	2.5	pk7: 8
#5Curt Casalilast yr '24 career totals — 10 seasons, 1,566 PA	2.4	1,566	47	2	217	311	367	+28	+19	7.8	7.9
/162	664	20	1	+11.9	+7.9	3.3	pk7: 8
#6Jerry May'64-'73 * career totals — 7 seasons, 1,716 PA	2.6	1,716	15	1	236*	314*	355*	+31	+0	5.6	5.6
/162	664	6	0	+11.8	+0.0	2.2	pk7: 6
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	1.8	1,209	32	1	230	305	372	+22	+17	4.6	4.6
/162	664	17	1	+11.9	+9.6	2.5	pk7: 5

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
Miguel Amaya (OGILVIE)	28	50	40	40	40	216/296/357	141	269	4	1	25%	8%	87	+0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Luis Torrens 2024 · MLB	28	46→49	49→50	42→40	42	231/284/377	145	302	17	3	29%	6%	85	+0.2	235/291/373	138	291	14	4	24%	7%	87	+0.4	235/293/375	140	282	15	2	22%	6%	89	+0.2
✕Kevin Plawecki 2019 · MLB	28	48→58	47→45	43→30	49	239/313/380	142	280	15	3	20%	8%	97	+1.1	247/316/379	132	291	13	5	19%	7%	98	+1.2	238/303/331	93	278	8	0	17%	7%	82	+0.0
✕Pedro Severino 2021 · MLB	28	46→49	48→50	48→45	49	235/302/377	141	277	17	6	22%	8%	92	+0.7	239/299/371	132	304	15	6	25%	7%	89	+0.5	230/286/351	121	293	13	6	25%	7%	78	-0.1
✕Riley Adams 2024 · MLB	28	46→44	50	45→40	43	227/302/390	163	315	16	3	32%	8%	95	+1.0	222/294/370	148	308	17	4	32%	7%	88	+0.4	209/288/350	140	291	18	2	33%	7%	80	-0.1
✕Andrew Knizner 2024 · MLB	29	45	49→50	46→40	47	229/296/370	141	274	17	5	23%	7%	88	+0.5	230/299/355	125	276	13	5	21%	7%	86	+0.3	226/301/342	116	269	12	2	20%	7%	83	+0.0
●James McCann 2018 · MLB	28	48→55	50	45	44	245/302/395	150	299	18	3	24%	6%	96	+1.0	249/304/400	151	317	19	4	26%	6%	98	+1.2	258/317/420	162	336	21	4	28%	7%	109	+1.1
✕Josmil Pinto 2016 · MLB	27	48→58	48→50	39→40	49	240/306/383	142	286	16	2	22%	8%	95	+0.9	229/281/369	140	296	16	5	27%	6%	82	+0.0	230/273/375	145	301	16	0	28%	6%	78	-0.2
✕Tucker Barnhart 2019 · MLB	28	51→53	44→45	40	53	248/316/371	123	288	11	3	18%	9%	95	+1.0	236/311/372	136	288	15	3	22%	9%	95	+0.9	229/307/361	132	288	15	1	24%	9%	90	+0.3
✕Jett Bandy 2018 · MLB	28	44	49→50	44→45	43	227/290/369	142	268	17	5	22%	6%	86	+0.3	212/275/353	141	265	18	6	27%	5%	78	-0.3	185/249/306	121	238	16	2	29%	4%	56	-0.7
✕Anthony Recker 2012 · MLB	28	45→48	50	44→45	46	230/296/386	157	295	18	7	28%	8%	93	+0.8	216/284/372	156	288	19	7	30%	8%	84	+0.2	196/263/350	153	262	20	3	32%	8%	71	-0.3
✕Austin Wynns 2019 · MLB	28	47→51	44→45	47→40	45	235/286/345	109	285	13	3	22%	6%	78	-0.3	223/277/322	99	272	12	4	22%	6%	70	-0.8	233/301/333	100	289	11	3	22%	7%	80	-0.0
✕Gerald Laird 2009 · MLB	29	50→47	45→50	42→50	46	247/300/376	128	293	12	6	20%	6%	91	+0.6	226/291/334	108	263	9	7	17%	7%	78	-0.3	262/328/360	98	303	6	3	14%	8%	98	+0.3
✕Tony Sanchez 2016 · MLB	28	43→51	45→50	43→40	45	215/284/342	127	273	13	5	26%	7%	78	-0.3	215/279/317	102	281	10	4	26%	7%	70	-0.9	219/278/310	92	289	9	1	26%	6%	65	-0.5
✕Steve Holm 2009 · MLB	29	47	46→50	43→40	50	234/308/364	130	275	13	5	20%	8%	92	+0.7	209/272/314	105	258	9	4	22%	7%	66	-1.1	184/245/274	89	232	7	1	23%	6%	47	-1.0
✕Michael McKenry 2013 · MLB	28	44→47	50→55	43→40	47	227/294/384	157	281	18	3	26%	8%	91	+0.7	242/314/406	164	293	19	6	23%	9%	103	+1.6	228/324/383	154	292	16	5	26%	11%	101	+0.5
✕Phillip Evans 2021 · MLB	28	47→57	48→45	39→40	50	236/307/379	143	269	16	5	19%	8%	95	+0.9	224/293/323	99	268	10	4	19%	8%	76	-0.4	225/295/311	86	267	8	2	18%	8%	73	-0.5
✕Bryan Anderson 2015 · MLB	28	45→55	46→45	44→30	45	226/286/361	135	286	14	4	26%	7%	82	+0.0	198/253/306	108	285	10	4	32%	6%	57	-1.8	160/212/240	80	244	6	0	36%	5%	24	-1.7
✕Curt Casali 2019 · MLB	30	47	45→50	38→30	47	235/297/355	120	288	13	3	23%	7%	85	+0.2	238/316/395	157	299	19	5	26%	9%	102	+1.5	217/309/355	139	284	17	0	28%	11%	90	+0.2
✕Carlos Pérez 2019 · MLB	28	47→49	46→55	47→45	46	237/286/363	126	276	14	6	20%	6%	82	+0.0	211/256/362	151	231	19	4	19%	5%	72	-0.7	207/273/379	172	226	22	0	20%	7%	81	-0.1
✕Elias Díaz 2019 · MLB	28	52→59	45→50	45	47	257/301/379	123	290	14	5	17%	6%	91	+0.7	247/301/371	124	283	14	3	17%	7%	90	+0.6	236/292/382	147	273	17	0	20%	7%	91	+0.5

Miguel Amaya

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps