Cody Bellinger

LF New York Yankees

Age 32 L/L 6'3" / 204 lbs MLB HR +14% Svc 9.930 · Ctrl thru 2026

Overview

MLB40-MANFA 2027

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	29	MLBCHC	569	.266/.328/.426	18	9	106	1.8
2025	30	MLBNYY	656	.272/.338/.480	29	13	122	3.2
2026	31	MLBNYY	562	.264/.342/.429	17	12	114	1.6
2027PROJ	32	MLBNYY	483	.262/.332/.437	17	10	113	1.9
2028PROJ	33	MLBNYY	499	.253/.323/.417	16	6	105	1.0
2029PROJ	34	MLBNYY	393	.242/.311/.393	12	1	96	0.1

Last 3 seasons WAR 6.5 · Next 3 projected WAR 3.1Projected rows: MLB playing time only, park and league context applied.

ContractCONFIRMED

Control thru2026Service9.930First FA2027Options1

Skills · percentileStatcast 2024-2026

xwOBA62

Speed46

Avg EV41

Barrel%40

Bat Spd38

Form.266/.312/.438 · rolling true talent (60d window) · proj .260/.328/.428

CompsJody Gerut (age 32) · Midre Cummings (age 33) · Marvin Benard (age 32)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 120113vR 109

AVG/OBP/SLG.262 / .332 / .437

PA483

HR17

SB10

K%16

BB%9

BABIP279

ISO175

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Recent Form · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

550.255

POWER

Barrel%

406.8

Avg EV

4188.4

Bat Spd

3870.0

SPEED

Sprint

4627.3

Recent Formrolling true talent ⓘ

K%16%·16% over 106 PA (60d) · proj 15%

BB%6%▼▼3% over 106 PA (60d) · proj 9%

ISO.171·.176 over 102 AB (60d) · proj .168

HR/BB5.0%▲5.8% over 86 BBE (60d) · proj 4.4%

BABIP.283·.321 over 81 BIP (60d) · proj .279

SLASH.266/.312/.438·proj .260/.328/.428

Platoon Splits2024-2026 · 1332 PA

vs LHP

vs RHP

Edge

378

954

—

wRC+

135

109

◀◀L

wOBA

367

330

◀L

ISO

191

181

◀L

BABIP

324

262

◀◀L

12.4%

15.3%

◀◀L

BB%

6.1%

9.0%

▶▶R

Contract CONFIRMED · hand-curated extension

Status FA

MLB Debut 2017

Service 9.930 yrs.days

Team Control Through 2026

First FA Year 2027

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
Totals		$0.0M		$0.0M	+$0.0M

Options · projected decision
2027	PLAYER OPT	$25.0M / $0.0M buyout	EXERCISE

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)
2013	18	ROK	AZL Dodgers	—	195	162	34	9	6	1	31	46	1	2	3	210	340	358	698	148	287	24	16	318	34	—	—	—	—	—	—
2014	19	ROK	Ogden Raptors	—	233	215	67	14	6	3	15	40	0	8	0	312	357	474	831	163	366	17	6	361	61	—	—	—	—	—	—
2015	20	A+	Rancho Cucamonga Quakes	—	544	478	126	33	4	30	52	150	4	10	2	264	341	538	878	274	314	28	10	375	87	—	—	—	—	—	—
2016	21	AA	Tulsa Drillers	—	465	399	105	17	1	23	59	94	3	8	2	263	362	484	846	221	287	20	13	371	97	—	—	—	—	—	—
2016	21	INTL	Glendale Desert Dogs	—	85	70	22	8	0	3	14	18	0	0	3	314	429	557	986	243	380	21	16	426	175	—	—	—	—	—	—
2017	22	MLB	Los Angeles Dodgers	—	548	480	128	26	4	39	64	146	1	10	3	267	354	581	935	315	299	27	12	401	149	+32	+1	-4	-11	+12	3.0
2017	22	AAA	Oklahoma City Dodgers	—	77	67	23	4	0	5	9	22	1	7	0	343	429	627	1.055	284	450	29	12	457	129	—	—	—	—	—	—
2018	23	MLB	Los Angeles Dodgers	—	632	557	145	28	7	25	69	151	3	14	1	260	345	470	815	210	312	24	11	358	127	+20	+2	-2	-11	+14	2.3
2019	24	MLB	Los Angeles Dodgers	—	661	558	170	34	3	47	95	108	3	15	5	305	408	629	1.037	324	302	16	14	443	173	+58	+1	+5	-7	+14	7.2
2020	25	MLB	Los Angeles Dodgers	—	243	213	51	10	0	12	30	42	0	6	1	239	333	455	789	216	245	17	12	350	121	+6	+1	+5	+1	+5	1.8
2021	26	MLB	Los Angeles Dodgers	—	350	315	52	9	2	10	31	94	1	3	1	165	242	302	544	137	196	27	9	246	53	-20	+0	+1	+1	+8	-1.0
2021	26	AAA	Oklahoma City Dodgers	—	21	20	4	0	0	2	1	4	0	0	0	200	238	500	738	300	143	19	5	318	43	—	—	—	—	—	—
2022	27	MLB	Los Angeles Dodgers	—	550	504	106	27	3	19	38	150	2	14	3	210	268	389	657	179	255	27	7	288	85	-10	+2	+4	+2	+12	0.9
2023	28	MLB	Chicago Cubs	—	556	499	153	29	1	26	40	87	5	20	6	307	364	525	889	218	319	16	7	382	143	+28	+2	+0	+2	+12	4.5
2024	29	MLB	Chicago Cubs	—	569	516	137	23	3	18	45	89	3	9	2	266	328	426	754	161	287	16	8	333	106	+4	+1	-2	+2	+12	1.8
2025	30	MLB	New York Yankees	—	656	588	160	25	5	29	57	90	2	13	2	272	338	480	818	207	274	14	9	355	122	+17	+2	+5	-7	+14	3.2
2026	31	MLB	New York Yankees	—	562	496	131	25	3	17	59	89	0	12	6	264	342	429	772	165	287	16	10	340	114	+10	+0	+0	-6	+12	1.6
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	5327	4726	1233	236	31	242	528	1046	20	116	30	261	338	478	815	217	284	20	10	356	127	+170	+11	+10	-34	+115	27.9
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2013	18	ROK MLE	AZL Dodgers	—	195	173	25	6	4	1	20	66	1	2	3	145	237	243	480	98	230	34	10	218	34	—	—	—	—	—	—
2014	19	ROK MLE	Ogden Raptors	—	233	221	51	10	4	2	9	58	0	8	0	231	261	339	600	109	289	25	4	259	61	—	—	—	—	—	—
2015	20	A+ MLE	Rancho Cucamonga Quakes	—	544	491	99	22	2	29	39	207	4	10	2	202	266	432	698	230	259	38	7	297	87	—	—	—	—	—	—
2016	21	AA MLE	Tulsa Drillers	—	465	413	94	15	1	19	45	115	3	8	2	228	308	407	715	179	261	25	10	311	97	—	—	—	—	—	—
2017	22	MLB MLE	Los Angeles Dodgers	—	548	493	130	28	5	37	51	146	1	10	3	264	334	566	900	302	299	27	9	388	149	+32	+1	-4	-11	+12	3.0
2017	22	AAA MLE	Oklahoma City Dodgers	—	77	70	20	3	0	4	6	28	1	7	0	286	351	500	851	214	411	36	8	359	129	—	—	—	—	—	—
2018	23	MLB MLE	Los Angeles Dodgers	—	632	566	148	30	8	24	60	151	3	14	1	261	335	470	805	208	312	24	9	356	127	+20	+2	-2	-11	+14	2.3
2019	24	MLB MLE	Los Angeles Dodgers	—	661	580	172	36	4	45	74	108	3	15	5	297	379	605	984	309	302	16	11	424	173	+58	+1	+5	-7	+14	7.2
2020	25	MLB MLE	Los Angeles Dodgers	—	243	215	52	11	0	12	28	42	0	6	1	242	329	460	790	219	245	17	12	347	121	+6	+1	+5	+1	+5	1.8
2021	26	MLB MLE	Los Angeles Dodgers	—	350	317	53	10	2	10	29	94	1	3	1	167	239	306	545	139	196	27	8	246	53	-20	+0	+1	+1	+8	-1.0
2021	26	AAA MLE	Oklahoma City Dodgers	—	21	20	3	0	0	1	1	5	0	0	0	150	190	300	490	150	135	24	5	232	43	—	—	—	—	—	—
2022	27	MLB MLE	Los Angeles Dodgers	—	550	504	109	29	4	18	38	150	2	14	3	216	274	397	671	181	255	27	7	294	85	-10	+2	+4	+2	+12	0.9
2023	28	MLB MLE	Chicago Cubs	—	556	502	153	28	1	27	37	87	5	20	6	305	358	526	884	221	319	16	7	379	143	+28	+2	+0	+2	+12	4.5
2024	29	MLB MLE	Chicago Cubs	—	569	523	137	22	3	19	38	89	3	9	2	262	316	424	740	163	287	16	7	324	106	+4	+1	-2	+2	+12	1.8
2025	30	MLB MLE	New York Yankees	—	656	589	158	25	5	27	56	90	2	13	2	268	334	465	799	197	274	14	9	349	122	+17	+2	+5	-7	+14	3.2
2026	31	MLB MLE	New York Yankees	—	562	496	130	25	3	16	59	89	0	12	6	262	341	421	762	159	287	16	10	337	114	+10	+0	+0	-6	+12	1.6
2013	18	ROK MLE	AZL Dodgers	—	195	173	25	6	4	1	20	66	1	2	3	145	237	243	480	98	226	34	10	218	34	—	—	—	—	—	—
2013	18	ROK RAW	AZL Dodgers	—	195	162	34	9	6	1	31	46	1	2	3	210	340	358	698	148	287	24	16	318	34	—	—	—	—	—	—
2014	19	ROK MLE	Ogden Raptors	—	233	221	51	10	4	2	9	58	0	8	0	231	261	339	600	109	299	25	4	259	61	—	—	—	—	—	—
2014	19	ROK RAW	Ogden Raptors	—	233	215	67	14	6	3	15	40	0	8	0	312	357	474	831	163	366	17	6	361	61	—	—	—	—	—	—
2015	20	A+ MLE	Rancho Cucamonga Quakes	—	544	491	99	22	2	29	39	207	4	10	2	202	266	432	698	230	266	38	7	297	87	—	—	—	—	—	—
2015	20	A+ RAW	Rancho Cucamonga Quakes	—	544	478	126	33	4	30	52	150	4	10	2	264	341	538	878	274	314	28	10	375	87	—	—	—	—	—	—
2016	21	AA MLE	2 teams	—	550	489	111	18	1	22	53	136	3	8	5	227	306	403	709	176	265	25	10	311	97	—	—	—	—	—	—
2016	21	AA RAW	2 teams	—	550	469	127	25	1	26	73	112	3	8	5	271	372	495	867	224	301	20	13	380	97	—	—	—	—	—	—
2017	22	MLB MLE	2 teams	—	625	563	149	31	5	41	57	174	2	17	3	265	334	556	890	291	308	28	9	384	146	+34	+2	-4	-11	+14	3.5
2017	22	MLB RAW	2 teams	—	625	547	151	30	4	44	73	168	2	17	3	276	363	587	950	311	317	27	12	408	146	+34	+2	-4	-11	+14	3.5
2018	23	MLB MLE	Los Angeles Dodgers	—	632	566	148	30	8	24	60	151	3	14	1	261	335	470	805	208	315	24	9	356	127	+20	+2	-2	-11	+14	2.3
2018	23	MLB RAW	Los Angeles Dodgers	—	632	557	145	28	7	25	69	151	3	14	1	260	345	470	815	210	312	24	11	358	127	+20	+2	-2	-11	+14	2.3
2019	24	MLB MLE	Los Angeles Dodgers	—	661	580	172	36	4	45	74	108	3	15	5	297	379	605	984	309	295	16	11	424	173	+58	+1	+5	-7	+14	7.2
2019	24	MLB RAW	Los Angeles Dodgers	—	661	558	170	34	3	47	95	108	3	15	5	305	408	629	1.037	324	302	16	14	443	173	+58	+1	+5	-7	+14	7.2
2020	25	MLB MLE	Los Angeles Dodgers	—	243	215	52	11	0	12	28	42	0	6	1	242	329	460	790	219	248	17	12	347	121	+6	+1	+5	+1	+5	1.8
2020	25	MLB RAW	Los Angeles Dodgers	—	243	213	51	10	0	12	30	42	0	6	1	239	333	455	789	216	245	17	12	350	121	+6	+1	+5	+1	+5	1.8
2021	26	MLB MLE	2 teams	—	371	337	56	10	2	11	30	99	1	3	1	166	236	306	542	139	196	27	8	245	52	-21	+0	+1	+1	+8	-1.1
2021	26	MLB RAW	2 teams	—	371	335	56	9	2	12	32	98	1	3	1	167	242	313	555	146	193	26	9	250	52	-21	+0	+1	+1	+8	-1.1
2022	27	MLB MLE	Los Angeles Dodgers	—	550	504	109	29	4	18	38	150	2	14	3	216	274	397	671	181	266	27	7	294	85	-10	+2	+4	+2	+12	0.9
2022	27	MLB RAW	Los Angeles Dodgers	—	550	504	106	27	3	19	38	150	2	14	3	210	268	389	657	179	255	27	7	288	85	-10	+2	+4	+2	+12	0.9
2023	28	MLB MLE	Chicago Cubs	—	556	502	153	28	1	27	37	87	5	20	6	305	358	526	884	221	315	16	7	379	143	+28	+2	+0	+2	+12	4.5
2023	28	MLB RAW	Chicago Cubs	—	556	499	153	29	1	26	40	87	5	20	6	307	364	525	889	218	319	16	7	382	143	+28	+2	+0	+2	+12	4.5
2024	29	MLB MLE	Chicago Cubs	—	569	523	137	22	3	19	38	89	3	9	2	262	316	424	740	163	281	16	7	324	106	+4	+1	-2	+2	+12	1.8
2024	29	MLB RAW	Chicago Cubs	—	569	516	137	23	3	18	45	89	3	9	2	266	328	426	754	161	287	16	8	333	106	+4	+1	-2	+2	+12	1.8
2025	30	MLB MLE	New York Yankees	—	656	589	158	25	5	27	56	90	2	13	2	268	334	465	799	197	272	14	9	349	122	+17	+2	+5	-7	+14	3.2
2025	30	MLB RAW	New York Yankees	—	656	588	160	25	5	29	57	90	2	13	2	272	338	480	818	207	274	14	9	355	122	+17	+2	+5	-7	+14	3.2
2026	31	MLB MLE	New York Yankees	—	562	496	130	25	3	16	59	89	0	12	6	262	341	421	762	159	286	16	10	337	114	+10	+0	+0	-6	+12	1.6
2026	31	MLB RAW	New York Yankees	—	562	496	131	25	3	17	59	89	0	12	6	264	342	429	772	165	287	16	10	340	114	+10	+0	+0	-6	+12	1.6
2013	18	ROK MLE	AZL Dodgers	—	195	172	25	6	4	1	20	66	1	2	3	145	237	244	481	99	230	34	10	218	34	—	—	—	—	—	—
2014	19	ROK MLE	Ogden Raptors	—	233	222	51	10	4	2	9	58	0	8	0	230	261	338	599	108	289	25	4	259	61	—	—	—	—	—	—
2015	20	A+ MLE	Rancho Cucamonga Quakes	—	544	496	99	22	2	29	39	207	4	10	2	200	266	427	693	228	259	38	7	297	87	—	—	—	—	—	—
2016	21	AA MLE	2 teams	—	550	489	111	18	1	22	53	136	3	8	5	227	306	403	709	176	261	25	10	311	97	—	—	—	—	—	—
2017	22	MLB MLE	2 teams	—	625	561	149	31	5	41	57	174	2	17	3	266	334	558	892	292	312	28	9	384	146	—	—	—	—	—	—
2018	23	MLB MLE	Los Angeles Dodgers	—	632	564	148	30	8	24	60	151	3	14	1	262	335	472	807	209	312	24	9	356	127	—	—	—	—	—	—
2019	24	MLB MLE	Los Angeles Dodgers	—	661	579	172	36	4	45	74	108	3	15	5	297	379	606	985	309	302	16	11	424	173	—	—	—	—	—	—
2020	25	MLB MLE	Los Angeles Dodgers	—	243	213	52	11	0	12	28	42	0	6	1	244	329	465	794	221	245	17	12	347	121	—	—	—	—	—	—
2021	26	MLB MLE	2 teams	—	371	337	56	10	2	11	30	99	1	3	1	166	236	306	542	139	193	27	8	245	52	—	—	—	—	—	—
2022	27	MLB MLE	Los Angeles Dodgers	—	550	505	109	29	4	18	38	150	2	14	3	216	274	396	670	180	255	27	7	294	85	—	—	—	—	—	—
2023	28	MLB MLE	Chicago Cubs	—	556	509	153	28	1	27	37	87	5	20	6	301	358	519	877	218	319	16	7	379	143	—	—	—	—	—	—
2024	29	MLB MLE	Chicago Cubs	—	569	523	137	22	3	19	38	89	3	9	2	262	316	424	740	163	287	16	7	324	106	—	—	—	—	—	—
2025	30	MLB MLE	New York Yankees	—	656	593	158	25	5	27	56	90	2	13	2	266	334	462	796	196	274	14	9	349	122	—	—	—	—	—	—
2026	31	MLB MLE	New York Yankees	—	562	498	130	25	3	16	59	89	0	12	6	261	341	420	760	159	287	16	10	337	114	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	29	MLB MLE	Chicago Cubs	—	569	523	137	22	3	19	38	89	3	9	2	262	316	424	740	163	287	16	7	324	106	—	—	—	—	—	—
2025	30	MLB MLE	New York Yankees	—	656	593	158	25	5	27	56	90	2	13	2	266	334	462	796	196	274	14	9	349	122	—	—	—	—	—	—
2026	31	MLB MLE	New York Yankees	—	562	498	130	25	3	16	59	89	0	12	6	261	341	420	760	159	287	16	10	337	114	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	32	MLB MLE	NYY	100%	553	496	128	22	3	18	51	85	1	12	3	260	331	428	759	168	279	15	9	335	113	+9	+1	+6	-6	+12	2.0
▸ 2027 — real world (MLB)
2027	32	MLB CTX	NYY	100%	483	434	113	19	3	17	45	75	1	10	2	262	332	437	769	175	279	16	9	339	113	+8	+1	+5	-5	+10	1.9
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	33	MLB MLE	NYY	100%	499	450	113	19	3	15	45	80	1	6	2	251	321	409	730	157	272	16	9	324	105	+3	+0	+1	-5	+11	1.0
2029	34	MLB MLE	NYY	100%	393	354	84	13	2	11	35	66	1	1	1	240	309	386	695	145	263	17	9	310	96	-2	-0	-1	-4	+9	0.1
2028	33	MLB CTX	NYY	100%	499	450	113	18	3	16	45	80	1	6	2	253	323	417	740	164	272	16	9	328	105	+3	+0	+1	-5	+11	1.0
2029	34	MLB CTX	NYY	100%	393	354	85	13	2	12	35	66	1	1	1	242	311	393	704	151	263	17	9	313	96	-2	-0	-1	-4	+9	0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	6219	5530	1431	267	36	270	608	1192	22	123	33	259	335	467	801	208	282	19	10	351	112	+171	+11	+10	-44	+135	29.0
/ 162G	—	A+C		—	650	578	150	28	4	28	64	125	2	13	3	260	335	467	803	208	283	19	10	351	112	+18	+1	+1	-5	+14	3.0
Career	—	MLE		—	8322	7487	1859	354	54	336	723	1767	32	168	45	248	317	445	762	196	279	21	9	334	112	+179	+13	+15	-49	+145	30.9
/ 162G	—	MLE		—	650	585	145	28	4	26	56	138	2	13	4	248	315	443	758	195	279	21	9	334	112	+17	+1	+1	-5	+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 AAAOklahoma City Dodgers · 21 PAwOBA .308 → .232 (−75)K% 19.0% → 23.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.05%	÷0.994	×1.200	—	—	22.99%
BB% (unintentional) /PA	4.76%	÷1.015	×0.690	—	×1.018	3.30%
HBP% /PA	0.00%	—	×0.940	—	×1.018	0.00%
Singles /BIP	12.50%	÷0.958	×0.930	—	×1.018	12.35%
Doubles /BIP	0.00%	÷0.941	×0.830	—	×1.018	0.00%
Triples /BIP	0.00%	÷0.900	×0.920	—	×1.018	0.00%
Home runs /BIP	12.50%	÷1.016	×0.700	—	×1.018	8.77%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 103, 1B 92, 2B 88, 3B 80, K 99, BB 103 — 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 .308 → .232; ISO .300 → .204; BABIP .143 → .135. 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 AAAOklahoma City Dodgers · 77 PAwOBA .442 → .359 (−82)K% 28.6% → 36.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.57%	÷1.000	×1.290	—	—	36.86%
BB% (unintentional) /PA	10.39%	÷1.017	×0.710	—	×1.050	7.61%
HBP% /PA	1.30%	—	×0.980	—	×1.050	1.34%
Singles /BIP	31.11%	÷0.978	×0.900	—	×1.050	30.08%
Doubles /BIP	8.89%	÷1.038	×0.810	—	×1.050	7.28%
Triples /BIP	0.00%	÷1.150	×0.810	—	×1.050	0.00%
Home runs /BIP	11.11%	÷0.989	×0.780	—	×1.050	9.20%

Factors used: league row PCL. Park (home-season share, regressed): HR 98, 1B 96, 2B 108, 3B 130, K 100, BB 103 — 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 .442 → .359; ISO .284 → .217; BABIP .450 → .411. 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 AATulsa Drillers · 465 PAwOBA .363 → .311 (−52)K% 20.2% → 24.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.22%	÷0.996	×1.220	—	—	24.76%
BB% (unintentional) /PA	12.26%	÷0.935	×0.700	—	×1.050	9.63%
HBP% /PA	0.65%	—	×0.870	—	×1.050	0.59%
Singles /BIP	20.98%	÷0.990	×0.920	×0.950	×1.050	19.45%
Doubles /BIP	5.57%	÷0.926	×0.840	×0.950	×1.050	5.04%
Triples /BIP	0.33%	÷0.900	×0.940	×0.950	×1.050	0.34%
Home runs /BIP	7.54%	÷1.020	×0.800	—	×1.050	6.21%

Factors used: league row TL. Park (home-season share, regressed): HR 104, 1B 98, 2B 85, 3B 80, K 99, BB 87 — applied at half strength. Age: age 21 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .363 → .311; ISO .221 → .185; BABIP .287 → .261. 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).

2015 A+Rancho Cucamonga Quakes · 544 PAwOBA .369 → .297 (−72)K% 27.6% → 38.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.57%	÷0.970	×1.340	—	—	38.09%
BB% (unintentional) /PA	9.38%	÷0.958	×0.710	—	×1.042	7.24%
HBP% /PA	0.74%	—	×0.790	—	×1.042	0.61%
Singles /BIP	17.99%	÷1.046	×0.910	×0.965	×1.042	15.75%
Doubles /BIP	10.06%	÷1.109	×0.820	×0.965	×1.042	7.48%
Triples /BIP	1.22%	÷1.150	×0.760	×0.965	×1.042	0.81%
Home runs /BIP	9.15%	÷0.898	×0.920	—	×1.042	9.76%

Factors used: league row CAL. Park (home-season share, regressed): HR 80, 1B 109, 2B 122, 3B 130, K 94, BB 92 — 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 ×0.965.

Result: wOBA .369 → .297; ISO .274 → .236; BABIP .314 → .259. 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).

2014 ROKOgden Raptors · 233 PAwOBA .356 → .259 (−97)K% 17.2% → 24.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.17%	÷1.000	×1.440	—	—	24.72%
BB% (unintentional) /PA	6.44%	÷1.000	×0.610	—	×1.008	3.96%
HBP% /PA	0.00%	—	×0.720	—	×1.008	0.00%
Singles /BIP	25.14%	÷1.000	×0.820	×1.000	×1.008	20.78%
Doubles /BIP	8.00%	÷1.000	×0.720	×1.000	×1.008	5.80%
Triples /BIP	3.43%	÷1.000	×0.720	×1.000	×1.008	2.49%
Home runs /BIP	1.71%	÷1.000	×0.750	—	×1.008	1.30%

Factors used: league row PIO. 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 ×1.000.

Result: wOBA .356 → .259; ISO .163 → .113; BABIP .366 → .289. 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).

2013 ROKAZL Dodgers · 195 PAwOBA .311 → .218 (−92)K% 23.6% → 34.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.59%	÷1.000	×1.440	—	—	33.97%
BB% (unintentional) /PA	15.90%	÷1.000	×0.620	—	×1.022	10.08%
HBP% /PA	0.51%	—	×0.720	—	×1.022	0.38%
Singles /BIP	15.52%	÷1.000	×0.820	×1.014	×1.022	13.19%
Doubles /BIP	7.76%	÷1.000	×0.720	×1.014	×1.022	5.79%
Triples /BIP	5.17%	÷1.000	×0.720	×1.014	×1.022	3.86%
Home runs /BIP	0.86%	÷1.000	×0.780	—	×1.022	0.69%

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 18 vs a level average of 19.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.014.

Result: wOBA .311 → .218; ISO .148 → .104; BABIP .287 → .230. 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
#1Carlos Gonzálezlast yr '19 career totals — 12 seasons, 5,551 PA	8.4	5,551	234	122	285	343	500	-50	-23	32.3	30.2
/162	664	28	15	-6.0	-2.7	3.9	pk7: 28
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 13 projected seasons	10.1	6,702	285	133	260	331	465	-72	+1	29.6	28.6
/162	664	28	13	-7.1	+0.1	2.9	pk7: 27
#2Ron Gant'87-'03 * career totals — 15 seasons, 7,320 PA	11.0	7,320	321	243	249*	328*	478*	-50	-5	30.8	27.6
/162	664	29	22	-4.6	-0.5	2.8	pk7: 24
#3Alex Gordonlast yr '20 AS×3GG×7SS career totals — 14 seasons, 7,250 PA	10.9	7,250	190	113	257	338	410	-58	+22	27.4	26.4
/162	664	17	10	-5.3	+2.0	2.5	pk7: 25
#4Raul Mondesi'93-'05 * career totals — 13 seasons, 6,369 PA	9.6	6,369	271	229	262*	319*	474*	-60	-3	27.6	26.0
/162	664	28	24	-6.2	-0.3	2.9	pk7: 24
#5Von Hayes'81-'92 * career totals — 12 seasons, 6,052 PA	9.1	6,052	143	253	265*	354*	446*	-54	+11	27.3	26.0
/162	664	16	28	-6.0	+1.2	3.0	pk7: 25
#6Aubrey Huff'00-'12 * career totals — 13 seasons, 6,786 PA	10.2	6,786	242	37	270*	335*	458*	-92	-24	23.5	23.6
/162	664	24	4	-9.0	-2.3	2.3	pk7: 24

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
Cody Bellinger (OGILVIE)	32	—	—	—	—	258/328/424	167	279	16	10	15%	9%	113	+1.8	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Jody Gerut 2010 · MLB	32	50→56	52→55	49→50	51	255/308/425	171	268	20	12	15%	7%	105	+1.7	241/298/395	154	264	17	8	16%	7%	95	+0.9	237/291/384	147	259	13	0	14%	7%	86	+0.1
✕Midre Cummings 2005 · MLB	33	51	52→50	51→50	50	257/333/427	171	298	19	11	21%	8%	116	+2.5	237/300/392	155	296	19	6	26%	7%	95	+1.0	223/282/365	142	279	19	0	27%	6%	84	+0.1
✕Marvin Benard 2002 · MLB	32	52→54	49→55	51→55	52	261/326/415	154	286	16	16	16%	8%	109	+2.0	247/303/384	137	282	12	14	17%	7%	93	+0.8	276/320/406	130	344	5	23	20%	5%	105	+0.4
✕Greg Dobbs 2010 · MLB	32	52→58	51→55	50	47	263/309/427	164	292	19	7	18%	6%	106	+1.8	249/290/382	133	290	14	6	19%	5%	88	+0.4	267/304/371	103	311	9	3	17%	4%	91	+0.4
✕Josh Reddick 2019 · MLB	32	52→61	50→60	48→50	54	264/325/418	154	284	18	9	15%	8%	109	+2.0	253/307/389	136	282	15	6	16%	7%	97	+1.1	250/301/374	123	282	13	4	16%	7%	90	+0.4
✕Masataka Yoshida 2024 · MLB	31	55→57	49→50	54→45	49	273/324/427	154	296	16	9	14%	6%	112	+2.2	266/327/402	136	288	14	7	13%	7%	107	+1.8	263/330/387	123	283	13	5	12%	7%	106	+0.9
✕Al Martin 2001 · MLB	33	54→57	50	49→50	48	273/322/435	162	303	17	11	17%	6%	112	+2.2	252/313/394	142	293	14	12	18%	8%	99	+1.3	241/306/363	122	287	10	11	19%	8%	90	+0.3
✕Rafael Ortega 2023 · MLB	32	50→55	48→55	48→55	54	248/326/390	142	292	16	18	20%	10%	103	+1.6	217/303/341	124	268	13	21	22%	11%	84	+0.2	200/296/311	111	248	11	26	23%	12%	74	-0.4
✕Jason Kipnis 2019 · MLB	32	46→56	51→55	50→55	52	237/310/406	169	268	19	9	20%	9%	102	+1.5	232/304/391	159	271	18	7	21%	9%	96	+1.0	227/298/382	155	268	18	6	22%	8%	92	+0.4
●Michael Tucker 2002 · MLB	31	49→51	52→55	53→55	54	249/328/427	178	288	18	19	20%	10%	113	+2.3	249/325/411	162	294	16	16	20%	10%	108	+1.9	249/330/407	159	293	15	14	20%	10%	110	+1.7
✕Kolten Wong 2023 · MLB	32	52→58	50	51→55	51	259/335/425	166	293	16	17	17%	8%	116	+2.5	224/296/349	125	267	13	12	20%	7%	84	+0.1	188/256/264	76	231	8	8	22%	7%	50	-0.7
✕David Murphy 2013 · MLB	31	56→59	49→55	48→50	54	279/340/428	149	305	16	13	14%	8%	118	+2.6	252/308/393	141	273	15	5	13%	7%	97	+1.1	246/299/380	133	264	14	1	13%	7%	91	+0.5
✕Kevin Pillar 2021 · MLB	32	51→61	51→55	50→55	43	260/294/430	170	283	18	13	16%	4%	101	+1.4	245/291/428	183	275	23	9	20%	5%	101	+1.4	235/278/425	190	261	26	8	22%	4%	96	+0.4
✕Ricky Ledee 2006 · MLB	32	50→47	52→60	50	51	254/325/427	173	297	19	5	21%	9%	112	+2.2	227/285/368	141	273	16	5	22%	7%	84	+0.1	203/253/318	116	249	15	2	25%	6%	60	-1.0
✕Rangel Ravelo 2023 · MLB	31	54→58	55→50	49→45	54	275/349/464	188	298	22	8	16%	9%	129	+3.4	258/341/390	132	303	14	7	19%	10%	109	+2.0	269/364/379	110	314	13	0	17%	11%	117	+1.1
●Eric Byrnes 2007 · MLB	31	50→56	54→60	55→60	48	257/311/446	188	274	21	18	16%	6%	112	+2.2	256/313/431	175	274	19	27	14%	7%	109	+2.0	252/311/418	167	268	17	30	13%	7%	106	+1.2
●Hunter Pence 2015 · MLB	32	54→63	54→60	53→50	49	278/332/464	186	311	21	12	18%	7%	123	+3.0	278/335/455	177	323	21	8	20%	8%	122	+2.9	276/336/441	165	324	20	3	20%	8%	120	+1.9
✕Bobby Higginson 2003 · MLB	32	56→57	50→55	50	58	277/350/441	165	287	17	15	11%	10%	124	+3.1	243/328/382	139	265	14	10	14%	10%	103	+1.5	234/328/370	135	257	15	7	15%	11%	101	+1.2
●Scott Hairston 2012 · MLB	32	46→51	54→60	49→50	48	238/302/416	178	268	22	10	21%	7%	101	+1.4	243/291/453	210	276	27	10	23%	6%	106	+1.8	244/285/480	236	265	32	10	22%	5%	111	+1.0
✕Max Kepler 2024 · MLB	31	46→56	55→60	47→50	54	242/322/427	185	266	22	5	19%	10%	111	+2.1	236/302/391	155	272	18	4	20%	8%	96	+1.0	224/289/360	136	260	15	3	20%	8%	84	+0.1

Cody Bellinger

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps