Christopher Morel

LF Syracuse Mets

Age 28 R/R 6'0" / 200 lbs AAA H -5% Svc 4.436 · Ctrl thru 2028

Overview

AAA40-MANArb-2FA 2029

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	25	MLBTB	611	.196/.290/.346	21	8	79	-1.1
2025	26	MLBTB	305	.219/.289/.396	11	7	87	-0.6
2026	27	AAA/INTL2 orgs	168	.291/.355/.603	13	0	106	—	.244/.299/.480
2026	27	MLBNYM	105	.173/.229/.245	1	1	38	-0.8
2027PROJ45% MLB	28	MLBNYM	107	.211/.283/.394	5	2	93	-0.0
2028PROJ	29	MLBNYM	246	.209/.280/.387	10	3	90	-0.3

Last 3 seasons WAR -2.6 · Next 2 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2028Service4.436First FA2029

2027Arb-2$0.4M2028Arb-3$0.6M

Skills · percentileStatcast 2024-2026

Bat Spd90

Barrel%68

Avg EV59

Speed55

xwOBA44

CompsBobby Dalbec (age 28) · Jabari Blash (age 27) · Mike Wilson (age 28)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 9493vR 89

AVG/OBP/SLG.211 / .283 / .394

PA107

HR5

K%30

BB%8

BABIP260

ISO198

MLB%45%

Value2027 · WAR

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

Tools · Splits · ContractCON 40 / POW 55

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT40

xAVG

100.214

POWER55

Barrel%

6810.9

Avg EV

5989.8

Bat Spd

9076.0

EYE50

scouting grade only

SPEED55

Sprint

5527.7

Platoon Splits2024-2025 · 916 PA

vs LHP

vs RHP

Edge

287

629

—

wRC+

▶R

wOBA

277

296

▶R

ISO

165

155

◀L

BABIP

244

269

▶R

30.3%

28.8%

▶R

BB%

8.7%

9.2%

▶R

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

Status Arb-2

MLB Debut 2022

Service 4.436 yrs.days

Team Control Through 2028

First FA Year 2029

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-2	$0.4M	+0.0	$0.2M	+$0.0M (cut)
2028	Arb-3	$0.6M	—	—	—
Totals		$0.0M		$-0.9M	+$0.0M

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral

Methodology▸ how these numbers are built

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2027 = full-season projection (no games played yet). 2028+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	MLB%	PA	AB	H	2B	3B	HR	BB	SO	HBP	SB	CS	AVG	OBP	SLG	OPS	ISO	BABIP	K%	BB%	wOBA	wRC+	BAT	RUN	FLD	POS	REP	WAR
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
2017	18	ROK	DSL Cubs 1	—	268	223	49	6	2	7	35	37	5	23	10	220	338	359	697	139	228	14	13	315	24	—	—	—	—	—	—
2018	19	ROK	AZL Cubs 1	—	128	113	29	6	0	2	11	28	2	1	4	257	333	363	696	106	321	22	9	313	37	—	—	—	—	—	—
2019	20	A	South Bend Cubs	—	278	257	73	15	7	6	11	60	4	9	6	284	324	467	790	183	345	22	4	340	65	—	—	—	—	—	—
2021	22	AAA	Iowa Cubs	—	39	35	9	1	0	1	4	10	0	2	0	257	333	371	705	114	333	26	10	320	61	—	—	—	—	—	—
2021	22	AA	Tennessee Smokies	—	417	368	81	17	5	17	41	124	3	16	3	220	303	432	735	212	276	30	10	322	58	—	—	—	—	—	—
2021	22	INTL	Aguilas Cibaenas	—	55	49	13	2	1	0	4	14	1	3	0	265	333	347	680	82	361	25	7	305	92	—	—	—	—	—	—
2022	23	MLB	Chicago Cubs	—	425	379	89	19	4	16	38	137	3	10	7	235	310	433	742	198	320	32	9	325	105	+3	-1	-6	+2	+9	0.8
2022	23	AA	Tennessee Smokies	—	122	108	33	5	1	7	10	30	3	3	3	306	380	565	945	259	366	25	8	409	112	—	—	—	—	—	—
2023	24	MLB	Chicago Cubs	—	429	388	96	17	3	26	36	133	2	6	2	247	315	508	822	260	303	31	8	356	128	+14	+0	-5	+2	+9	2.2
2023	24	AAA	Iowa Cubs	—	134	115	38	9	2	11	17	41	2	4	1	330	425	730	1.156	400	429	31	13	489	142	—	—	—	—	—	—
2023	24	INTL	Aguilas Cibaenas	—	103	83	18	4	2	3	16	25	4	5	1	217	369	422	791	205	273	24	16	358	128	—	—	—	—	—	—
2024	25	MLB	Tampa Bay Rays	—	611	535	105	11	3	21	61	159	10	8	7	196	290	346	636	150	233	26	10	288	79	-15	-1	-10	+2	+13	-1.1
2025	26	MLB	Tampa Bay Rays	—	305	278	61	16	0	11	25	109	2	7	2	219	289	396	684	176	316	36	8	305	87	-5	+1	-6	-3	+7	-0.6
2026	27	MLB	New York Mets	—	105	98	17	4	0	1	6	35	1	1	0	173	229	245	473	71	258	33	6	219	38	-8	+0	+0	-3	+2	-0.8
2026	27	AAA	Syracuse Mets	—	139	123	38	7	0	12	13	33	1	0	1	309	380	659	1.038	350	325	24	9	439	114	—	—	—	—	—	—
2026	27	INTL	Aguilas Cibaenas	—	29	28	6	1	0	1	0	10	1	0	0	214	241	357	599	143	294	34	0	266	66	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1875	1678	368	67	10	75	166	573	18	32	18	219	296	405	702	186	282	31	9	311	96	-8	-1	-26	+0	+41	0.7
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2017	18	ROK MLE	DSL Cubs 1	—	268	234	31	4	1	3	24	45	5	23	10	132	228	197	425	64	143	17	9	203	24	—	—	—	—	—	—
2018	19	ROK MLE	AZL Cubs 1	—	128	117	21	4	0	1	7	40	2	1	4	179	238	239	477	60	260	31	5	223	37	—	—	—	—	—	—
2019	20	A MLE	South Bend Cubs	—	278	260	59	11	5	5	8	84	4	9	6	227	261	365	626	138	299	30	3	265	65	—	—	—	—	—	—
2021	22	AAA MLE	Iowa Cubs	—	39	36	8	1	0	1	3	12	0	2	0	222	282	333	615	111	308	31	8	258	61	—	—	—	—	—	—
2021	22	AA MLE	Tennessee Smokies	—	417	381	70	14	4	13	28	153	3	16	3	184	245	344	589	160	253	37	7	254	58	—	—	—	—	—	—
2022	23	MLB MLE	Chicago Cubs	—	425	379	88	18	3	17	38	137	3	10	7	232	307	430	737	198	320	32	9	324	105	+3	-1	-6	+2	+9	0.8
2022	23	AA MLE	Tennessee Smokies	—	122	111	29	5	1	5	7	38	3	3	3	261	322	459	782	198	343	31	6	334	112	—	—	—	—	—	—
2023	24	MLB MLE	Chicago Cubs	—	429	388	97	17	3	27	36	133	2	6	2	250	317	518	835	268	303	31	8	357	128	+14	+0	-5	+2	+9	2.2
2023	24	AAA MLE	Iowa Cubs	—	134	120	31	7	2	8	12	48	2	4	1	258	336	550	886	292	370	36	9	378	142	—	—	—	—	—	—
2024	25	MLB MLE	Tampa Bay Rays	—	611	538	105	11	3	22	58	159	10	8	7	195	285	349	635	154	233	26	9	285	79	-15	-1	-10	+2	+13	-1.1
2025	26	MLB MLE	Tampa Bay Rays	—	305	278	59	15	0	11	25	109	2	7	2	212	282	385	667	173	316	36	8	297	87	-5	+1	-6	-3	+7	-0.6
2026	27	MLB MLE	New York Mets	—	105	98	17	4	0	1	6	35	1	1	0	173	229	245	473	71	258	33	6	225	38	-8	+0	+0	-3	+2	-0.8
2026	27	AAA MLE	Syracuse Mets	—	139	127	31	6	0	8	9	40	1	0	1	244	299	480	780	236	277	29	6	336	114	—	—	—	—	—	—
2017	18	ROK MLE	DSL Cubs 1	—	268	234	31	4	1	3	24	45	5	23	10	132	228	197	425	64	147	17	9	203	24	—	—	—	—	—	—
2017	18	ROK RAW	DSL Cubs 1	—	268	223	49	6	2	7	35	37	5	23	10	220	338	359	697	139	228	14	13	315	24	—	—	—	—	—	—
2018	19	ROK MLE	AZL Cubs 1	—	128	117	21	4	0	1	7	40	2	1	4	179	238	239	477	60	260	31	5	223	37	—	—	—	—	—	—
2018	19	ROK RAW	AZL Cubs 1	—	128	113	29	6	0	2	11	28	2	1	4	257	333	363	696	106	321	22	9	313	37	—	—	—	—	—	—
2019	20	A MLE	South Bend Cubs	—	278	260	59	11	5	5	8	84	4	9	6	227	261	365	626	138	310	30	3	265	65	—	—	—	—	—	—
2019	20	A RAW	South Bend Cubs	—	278	257	73	15	7	6	11	60	4	9	6	284	324	467	790	183	345	22	4	340	65	—	—	—	—	—	—
2021	22	AA MLE	3 teams	—	511	467	87	17	4	15	34	185	4	21	3	186	248	336	584	150	264	36	7	254	58	—	—	—	—	—	—
2021	22	AA RAW	3 teams	—	511	452	103	20	6	18	49	148	4	21	3	228	309	418	727	190	291	29	10	320	58	—	—	—	—	—	—
2022	23	MLB MLE	2 teams	—	547	490	117	23	4	22	45	175	6	13	10	239	311	437	747	198	322	32	8	326	107	+5	-1	-6	+2	+12	1.2
2022	23	MLB RAW	2 teams	—	547	487	122	24	5	23	48	167	6	13	10	251	325	462	787	211	331	31	9	344	107	+5	-1	-6	+2	+12	1.2
2023	24	MLB MLE	3 teams	—	666	598	152	28	6	42	57	214	8	15	4	254	327	532	859	278	320	32	9	362	131	+25	+1	-5	+2	+14	3.9
2023	24	MLB RAW	3 teams	—	666	586	152	30	7	40	69	199	8	15	4	259	345	539	885	280	321	30	10	383	131	+25	+1	-5	+2	+14	3.9
2024	25	MLB MLE	Tampa Bay Rays	—	611	538	105	11	3	22	58	159	10	8	7	195	285	349	635	154	229	26	9	285	79	-15	-1	-10	+2	+13	-1.1
2024	25	MLB RAW	Tampa Bay Rays	—	611	535	105	11	3	21	61	159	10	8	7	196	290	346	636	150	233	26	10	288	79	-15	-1	-10	+2	+13	-1.1
2025	26	MLB MLE	Tampa Bay Rays	—	305	278	59	15	0	11	25	109	2	7	2	212	282	385	667	173	304	36	8	297	87	-5	+1	-6	-3	+7	-0.6
2025	26	MLB RAW	Tampa Bay Rays	—	305	278	61	16	0	11	25	109	2	7	2	219	289	396	684	176	316	36	8	305	87	-5	+1	-6	-3	+7	-0.6
2026	27	AAA MLE	3 teams	—	273	251	54	11	0	10	17	83	3	1	1	215	273	378	652	163	275	30	6	288	81	—	—	—	—	—	—
2026	27	AAA RAW	3 teams	—	273	249	61	12	0	14	19	78	3	1	1	245	306	462	768	217	296	29	7	336	81	—	—	—	—	—	—
2017	18	ROK MLE	DSL Cubs 1	—	268	237	31	4	1	3	24	45	5	23	10	131	228	194	422	63	143	17	9	203	24	—	—	—	—	—	—
2018	19	ROK MLE	AZL Cubs 1	—	128	118	21	4	0	1	7	40	2	1	4	178	238	237	475	59	260	31	5	223	37	—	—	—	—	—	—
2019	20	A MLE	South Bend Cubs	—	278	264	59	11	5	5	8	84	4	9	6	223	261	360	621	136	299	30	3	265	65	—	—	—	—	—	—
2021	22	AA MLE	3 teams	—	511	468	87	17	4	15	34	185	4	21	3	186	248	335	583	150	258	36	7	254	58	—	—	—	—	—	—
2022	23	MLB MLE	2 teams	—	547	491	117	23	4	22	45	175	6	13	10	238	311	436	746	198	325	32	8	326	107	—	—	—	—	—	—
2023	24	MLB MLE	3 teams	—	666	596	152	28	6	42	57	214	8	15	4	255	327	534	861	279	319	32	9	362	131	—	—	—	—	—	—
2024	25	MLB MLE	Tampa Bay Rays	—	611	538	105	11	3	22	58	159	10	8	7	195	285	349	635	154	233	26	9	285	79	—	—	—	—	—	—
2025	26	MLB MLE	Tampa Bay Rays	—	305	275	59	15	0	11	25	109	2	7	2	215	282	389	671	175	316	36	8	297	87	—	—	—	—	—	—
2026	27	AAA MLE	3 teams	—	273	251	54	11	0	10	17	83	3	1	1	215	273	378	652	163	269	30	6	288	81	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	25	MLB MLE	Tampa Bay Rays	—	611	538	105	11	3	22	58	159	10	8	7	195	285	349	635	154	233	26	9	285	79	—	—	—	—	—	—
2025	26	MLB MLE	Tampa Bay Rays	—	305	275	59	15	0	11	25	109	2	7	2	215	282	389	671	175	316	36	8	297	87	—	—	—	—	—	—
2026	27	AAA MLE	3 teams	—	273	251	54	11	0	10	17	83	3	1	1	215	273	378	652	163	269	30	6	288	81	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	28	MLB MLE	NYM	45%	349	314	68	12	1	15	28	104	4	5	1	217	288	402	690	185	269	30	8	305	93	-3	+1	-2	-4	+8	0.1
▸ 2027 — real world (MLB)
2027	28	MLB CTX	NYM	45%	107	96	21	4	0	5	9	32	1	2	0	211	283	394	677	183	260	30	8	300	93	-1	+0	-1	-1	+2	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	29	MLB MLE	NYM	100%	246	223	47	9	0	10	19	74	2	3	1	214	285	395	680	181	267	30	8	301	90	-3	+0	-3	-3	+5	-0.3
2028	29	MLB CTX	NYM	100%	246	223	46	8	0	10	19	74	2	3	1	209	280	387	667	178	258	30	8	296	90	-3	+0	-3	-3	+5	-0.3
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2121	1901	414	75	10	85	185	647	20	35	19	218	294	402	696	184	279	31	9	309	85	-11	-1	-29	-2	+46	0.3
/ 162G	—	A+C		—	650	583	127	23	3	26	57	198	6	11	6	218	295	401	696	184	279	30	9	309	85	-3	-0	-9	-1	+14	0.1
Career	—	MLE		—	4070	3670	778	141	24	151	313	1239	48	104	49	212	283	387	669	175	272	30	8	294	85	-13	-0	-30	-5	+51	0.3
/ 162G	—	MLE		—	650	586	125	23	4	24	50	198	8	17	8	213	284	389	673	176	274	30	8	294	85	-4	-0	-8	-1	+14	0.1

How the minor-league lines were translated

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

2026 AAASyracuse Mets · 139 PAwOBA .432 → .336 (−96)K% 23.7% → 28.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.74%	÷1.000	×1.200	—	—	28.49%
BB% (unintentional) /PA	9.35%	÷1.000	×0.690	—	×1.003	6.47%
HBP% /PA	0.72%	—	×0.940	—	×1.003	0.68%
Singles /BIP	21.11%	÷1.000	×0.930	×0.983	×1.003	19.35%
Doubles /BIP	7.78%	÷1.000	×0.830	×0.983	×1.003	6.36%
Triples /BIP	0.00%	÷1.000	×0.970	×0.983	×1.003	0.00%
Home runs /BIP	13.33%	÷1.000	×0.700	—	×1.003	9.36%

Factors used: league row International League. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.983.

Result: wOBA .432 → .336; ISO .350 → .251; BABIP .325 → .277. 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 · 134 PAwOBA .475 → .378 (−97)K% 30.6% → 36.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.60%	÷1.019	×1.200	—	—	36.03%
BB% (unintentional) /PA	12.69%	÷1.014	×0.690	—	×1.048	9.05%
HBP% /PA	1.49%	—	×0.940	—	×1.048	1.47%
Singles /BIP	21.62%	÷1.025	×0.930	×0.975	×1.048	20.05%
Doubles /BIP	12.16%	÷1.049	×0.830	×0.975	×1.048	9.83%
Triples /BIP	2.70%	÷0.916	×0.970	×0.975	×1.048	2.92%
Home runs /BIP	14.86%	÷0.965	×0.700	—	×1.048	11.30%

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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.975.

Result: wOBA .475 → .378; ISO .400 → .309; BABIP .429 → .370. 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 · 122 PAwOBA .397 → .334 (−64)K% 24.6% → 31.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.59%	÷0.958	×1.220	—	—	31.33%
BB% (unintentional) /PA	8.20%	÷0.940	×0.680	—	×1.027	6.09%
HBP% /PA	2.46%	—	×0.840	—	×1.027	2.12%
Singles /BIP	25.64%	÷0.982	×0.920	×0.983	×1.027	24.25%
Doubles /BIP	6.41%	÷0.929	×0.910	×0.983	×1.027	6.34%
Triples /BIP	1.28%	÷0.973	×0.880	×0.983	×1.027	1.17%
Home runs /BIP	8.97%	÷1.010	×0.800	—	×1.027	7.30%

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 ×0.983.

Result: wOBA .397 → .334; ISO .259 → .209; BABIP .366 → .343. 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 · 417 PAwOBA .317 → .254 (−63)K% 29.7% → 36.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	29.74%	÷0.990	×1.220	—	—	36.66%
BB% (unintentional) /PA	9.83%	÷1.066	×0.690	—	×1.042	6.63%
HBP% /PA	0.72%	—	×0.850	—	×1.042	0.64%
Singles /BIP	17.21%	÷0.970	×0.940	×0.968	×1.042	16.82%
Doubles /BIP	6.97%	÷1.015	×0.870	×0.968	×1.042	6.02%
Triples /BIP	2.05%	÷1.150	×0.920	×0.968	×1.042	1.65%
Home runs /BIP	6.97%	÷1.050	×0.780	—	×1.042	5.40%

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 ×0.968.

Result: wOBA .317 → .254; ISO .212 → .162; BABIP .276 → .253. 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 AAAIowa Cubs · 39 PAwOBA .312 → .258 (−54)K% 25.6% → 29.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.64%	÷1.032	×1.200	—	—	29.81%
BB% (unintentional) /PA	10.26%	÷1.023	×0.690	—	×1.050	7.27%
HBP% /PA	0.00%	—	×0.940	—	×1.050	0.00%
Singles /BIP	28.00%	÷1.039	×0.930	—	×1.050	26.31%
Doubles /BIP	4.00%	÷0.963	×0.830	—	×1.050	3.62%
Triples /BIP	0.00%	÷0.988	×0.920	—	×1.050	0.00%
Home runs /BIP	4.00%	÷1.081	×0.700	—	×1.050	2.72%

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 22 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (5.2 yr younger than average).

Result: wOBA .312 → .258; ISO .114 → .083; BABIP .333 → .308. 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 ASouth Bend Cubs · 278 PAwOBA .334 → .265 (−69)K% 21.6% → 30.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.58%	÷0.968	×1.360	—	—	30.33%
BB% (unintentional) /PA	3.96%	÷0.994	×0.690	—	×1.030	2.83%
HBP% /PA	1.44%	—	×0.780	—	×1.030	1.16%
Singles /BIP	22.84%	÷0.987	×0.920	×0.950	×1.030	20.83%
Doubles /BIP	7.61%	÷1.026	×0.830	×0.950	×1.030	6.03%
Triples /BIP	3.55%	÷1.150	×0.910	×0.950	×1.030	2.75%
Home runs /BIP	3.05%	÷0.914	×0.800	—	×1.030	2.75%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 83, 1B 97, 2B 105, 3B 130, K 94, BB 99 — applied at half strength. Age: age 20 vs a level average of 22.0 → +3.0% on BB/HBP/hit rates (2.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .334 → .265; ISO .183 → .140; BABIP .345 → .299. 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 · 128 PAwOBA .307 → .223 (−84)K% 21.9% → 31.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.88%	÷1.000	×1.440	—	—	31.50%
BB% (unintentional) /PA	8.59%	÷1.000	×0.620	—	×1.008	5.37%
HBP% /PA	1.56%	—	×0.720	—	×1.008	1.13%
Singles /BIP	24.71%	÷1.000	×0.820	×1.013	×1.008	20.68%
Doubles /BIP	7.06%	÷1.000	×0.720	×1.013	×1.008	5.19%
Triples /BIP	0.00%	÷1.000	×0.720	×1.013	×1.008	0.00%
Home runs /BIP	2.35%	÷1.000	×0.780	—	×1.008	1.85%

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 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.013.

Result: wOBA .307 → .223; ISO .106 → .075; BABIP .321 → .260. 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 DSLDSL Cubs 1 · 268 PAwOBA .312 → .203 (−109)K% 13.8% → 16.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.81%	÷1.000	×1.220	—	—	16.84%
BB% (unintentional) /PA	12.69%	÷1.000	×0.700	—	×1.008	8.95%
HBP% /PA	1.87%	—	×0.700	—	×1.008	1.32%
Singles /BIP	18.28%	÷1.000	×0.680	×0.956	×1.008	11.98%
Doubles /BIP	3.23%	÷1.000	×0.600	×0.956	×1.008	1.86%
Triples /BIP	1.08%	÷1.000	×0.600	×0.956	×1.008	0.62%
Home runs /BIP	3.76%	÷1.000	×0.470	—	×1.008	1.78%

Factors used: level-wide DSL 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 18 vs a level average of 18.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.956.

Result: wOBA .312 → .203; ISO .139 → .074; BABIP .228 → .143. 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
#1Cory Snyder'86-'94 * career totals — 9 seasons, 3,933 PA	5.9	3,933	149	28	243*	290*	445*	-35	-18	4.7	5.7
/162	664	25	5	-5.9	-3.0	0.8	pk7: 7
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	3.4	2,228	90	36	220	293	406	-24	-41	2.4	2.4
/162	664	27	11	-7.1	-12.1	0.7	pk7: 2
#2Charlie Spikes'72-'80 * career totals — 6 seasons, 2,232 PA	3.4	2,232	65	27	246*	307*	433*	-26	-16	1.3	1.7
/162	664	19	8	-7.6	-4.6	0.4	pk7: 2
#3Eric Anthony'89-'97 * career totals — 9 seasons, 2,243 PA	3.4	2,243	78	24	225*	300*	410*	-22	-22	0.1	0.6
/162	664	23	7	-6.7	-6.6	0.0	pk7: 1
#4Seth Brownlast yr '25 career totals — 6 seasons, 1,799 PA	2.7	1,799	74	24	227	293	421	-23	-34	-0.8	-0.8
/162	664	27	9	-8.6	-12.4	-0.3	pk7: -1
#5Rowdy Tellezlast yr '25 career totals — 8 seasons, 2,617 PA	3.9	2,617	122	5	234	300	437	-47	-55	-1.6	-1.1
/162	664	31	1	-11.9	-14.1	-0.4	pk7: -1
#6Domonic Brownlast yr '15 career totals — 6 seasons, 1,748 PA	2.6	1,748	54	23	246	305	405	-19	-39	-1.1	-1.1
/162	664	21	9	-7.1	-14.7	-0.4	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
Christopher Morel (OGILVIE)	28	40	55	55	50	215/286/399	184	269	10	3	30%	8%	93	+0.3	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Bobby Dalbec 2023 · MLB	28	42	59→60	53→50	41	227/291/432	205	299	28	6	34%	7%	101	+1.4	204/276/370	166	314	22	12	40%	8%	82	-0.0	189/264/347	158	301	21	13	42%	8%	69	-0.8
✕Jabari Blash 2016 · AAA	27	39→41	58→60	48→50	44	214/293/415	202	277	26	9	32%	8%	99	+1.2	210/311/399	189	307	24	7	36%	11%	101	+1.4	197/311/390	192	295	25	6	38%	12%	98	+0.8
✕Mike Wilson 2011 · AAA	28	40→50	54→55	50	45	215/291/387	173	274	23	12	30%	8%	91	+0.7	229/296/384	155	306	19	8	30%	8%	92	+0.7	227/293/374	147	307	17	4	30%	7%	85	+0.1
✕Valentino Pascucci 2008 · AAA	29	42	58→55	51→45	46	228/307/430	202	285	27	10	30%	8%	107	+1.9	215/298/385	170	281	22	5	30%	10%	93	+0.8	202/291/365	164	262	22	3	31%	10%	83	+0.1
✕Weston Wilson 2022 · AAA	27	41→42	54→55	51→55	46	222/286/397	175	270	23	14	27%	8%	91	+0.7	208/273/352	144	285	18	22	32%	8%	76	-0.4	204/282/368	164	260	22	25	30%	9%	82	-0.0
✕Stone Garrett 2024 · MLB	28	45→39	55	51→50	41	235/287/421	186	303	23	14	30%	6%	97	+1.1	211/279/321	110	323	11	8	35%	8%	71	-0.8	193/267/252	59	314	4	3	36%	8%	48	-1.3
✕Jaylin Davis 2022 · MLB	28	42→47	56→50	48→45	41	222/291/408	187	300	24	10	34%	7%	96	+1.0	195/272/323	128	296	14	7	36%	8%	70	-0.9	176/260/292	116	270	12	4	37%	9%	55	-1.2
✕David Villar 2024 · MLB	27	42→44	56→60	46→40	47	223/308/415	192	286	25	5	30%	9%	104	+1.6	219/296/353	134	293	15	5	29%	9%	84	+0.2	211/289/324	113	284	13	2	29%	9%	74	-0.4
✕Kyle Lewis 2023 · MLB	28	42→48	54→55	49→40	50	225/307/394	170	280	24	7	29%	10%	99	+1.2	251/317/419	168	321	22	5	27%	8%	107	+1.9	273/336/441	168	351	22	0	27%	8%	116	+1.5
✕Casper Wells 2013 · MLB	28	45→44	55→60	48→50	47	232/306/425	193	286	21	8	27%	8%	105	+1.7	205/273/323	118	285	12	7	30%	8%	69	-0.9	126/186/148	22	188	0	0	30%	7%	-4	-1.1
✕Shelley Duncan 2009 · MLB	29	40→44	57→60	46→45	48	223/291/416	194	255	26	7	25%	8%	97	+1.1	226/296/414	188	261	24	4	24%	8%	99	+1.2	223/294/408	186	254	24	2	23%	8%	96	+0.8
✕Jason Perry 2009 · MLB	28	43→51	54→55	52→45	43	225/297/407	182	291	22	7	30%	7%	98	+1.2	221/298/387	166	291	20	9	30%	8%	93	+0.8	167/268/315	147	210	19	4	30%	10%	66	-0.2
✕Michael Restovich 2007 · MLB	28	45→48	54→55	47→30	43	234/294/415	181	300	22	4	29%	7%	99	+1.2	232/282/405	173	304	21	4	30%	6%	92	+0.7	227/275/385	158	294	18	2	29%	6%	82	-0.0
✕Sam Hilliard 2022 · MLB	28	35→45	57→55	55	41	198/261/395	197	267	26	15	36%	8%	82	-0.0	213/286/383	170	292	21	16	33%	9%	88	+0.4	208/281/383	175	283	19	18	32%	9%	85	+0.2
✕Jon Knott 2007 · MLB	28	40	55	44→40	45	218/281/411	193	254	23	4	25%	7%	93	+0.8	218/284/387	169	268	20	5	26%	8%	88	+0.5	207/277/367	160	254	19	3	26%	8%	78	-0.2
✕Donnie Murphy 2011 · MLB	28	44→40	57→65	48→45	41	236/287/440	204	289	25	5	28%	6%	102	+1.5	221/282/406	185	268	22	6	26%	6%	92	+0.7	209/273/393	185	253	23	5	27%	6%	85	+0.1
✕Aristides Aquino 2022 · MLB	28	40→41	62→65	48→50	47	224/304/447	222	276	31	9	31%	9%	109	+2.0	216/283/388	172	314	21	8	36%	8%	88	+0.5	198/256/367	169	293	22	6	39%	6%	73	-0.4
✕Luken Baker 2024 · MLB	27	41→47	57→60	45→30	46	225/292/415	190	274	26	2	28%	8%	98	+1.2	203/282/380	177	256	23	2	29%	10%	86	+0.3	178/263/342	163	225	21	1	30%	10%	69	-0.6
✕Joe Mather 2010 · MLB	28	40→44	54→60	50	46	216/281/394	178	236	22	12	21%	6%	89	+0.5	216/267/334	118	270	11	10	24%	6%	69	-0.9	205/255/310	105	257	10	8	24%	6%	59	-0.7
✕Kody Clemens 2024 · MLB	28	39→43	53→60	50→45	45	211/271/385	174	257	21	9	27%	7%	82	+0.0	224/280/416	192	262	24	9	24%	6%	93	+0.8	225/282/430	205	254	26	9	23%	6%	97	+0.9

Christopher Morel

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps