Rafael Devers

1B San Francisco Giants

Age 30 L/R 6'0" / 235 lbs MLB HR -15%H -3% Svc 9.407 · Ctrl thru 2033 ILInjured 60-Day (D60)

Overview

MLBIL-6040-MANExtFA 2034

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	27	MLBBOS	601	.272/.358/.516	28	3	128	3.3
2025	28	MLBSF	729	.252/.374/.479	35	1	141	3.7
2026	29	MLBSF	633	.258/.342/.525	37	0	143	3.4
2027PROJ	30	MLBSF	279	.246/.335/.484	14	1	135	1.3
2028PROJ	31	MLBSF	614	.240/.329/.472	30	2	130	2.2
2029PROJ	32	MLBSF	614	.233/.321/.456	29	1	123	1.6

Last 3 seasons WAR 10.4 · Next 3 projected WAR 5.1Projected rows: MLB playing time only, park and league context applied.

ContractCONFIRMED

Control thru2033Service9.407First FA2034

2027Ext$31M2028Ext$31M2029Ext$31M2030Ext$31M2031Ext$31M2032Ext$31M2033Ext$31M

Skills · percentileStatcast 2024-2026

xwOBA90

Avg EV90

Barrel%89

Bat Spd49

Speed22

Form.273/.370/.603 ▲▲ rolling true talent (60d window) · proj .252/.338/.504

CompsJoc Pederson (age 29) · Brandon Moss (age 30) · Jorge Soler (age 30)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 117135vR 141

AVG/OBP/SLG.246 / .335 / .484

PA279

HR14

K%25

BB%11

BABIP284

ISO238

MLB%100%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$111M ctrl surplus

Tools · Recent Form · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

470.249

POWER

Barrel%

8914.0

Avg EV

9093.2

Bat Spd

4971.2

SPEED

Sprint

2226.1

Recent Formrolling true talent ⓘ

K%24%▲23% over 60 PA (60d) · proj 25%

BB%13%▲▲17% over 60 PA (60d) · proj 11%

ISO.330▲▲.580 over 50 AB (60d) · proj .252

HR/BB12.1%▲▲22.2% over 36 BBE (60d) · proj 8.7%

BABIP.291·.357 over 28 BIP (60d) · proj .289

SLASH.273/.370/.603▲▲proj .252/.338/.504

Platoon Splits2024-2026 · 1443 PA

vs LHP

vs RHP

Edge

503

940

—

wRC+

146

▶▶R

wOBA

313

384

▶▶R

ISO

155

262

▶▶R

BABIP

327

306

◀L

29.0%

24.4%

▶▶R

BB%

7.2%

13.1%

▶▶R

Contract CONFIRMED · hand-curated extension

Status FA

MLB Debut 2017

Service 9.407 yrs.days

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$31M	+1.3	$10M	-$21M
2028	Ext	$31M	+2.2	$16M	-$12M
2029	Ext	$31M	+1.6	$11M	-$14M
2030	Ext	$31M	+0.7	$2M	-$21M
2031	Ext	$31M	—	—	—
2032	Ext	beyond projection horizon · no WAR estimate
2033	Ext	beyond projection horizon · no WAR estimate
Totals		$157M		$40M	-$89M

Underwater contract
Projected production over the remaining contract is worth -$89M less than the salary owed. Most often this reflects an aging-curve fade that was visible at signing — the team paid a premium for the early years.

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)
2014	17	ROK	GCL Red Sox	—	302	261	84	17	5	7	35	50	3	5	1	322	408	506	914	184	372	17	12	400	89	—	—	—	—	—	—
2015	18	A	Greenville Drive	—	508	469	135	38	1	11	24	84	8	3	2	288	333	443	777	156	326	17	5	340	87	—	—	—	—	—	—
2015	18	INTL	Leones del Escogido	—	47	43	12	3	0	0	4	8	0	0	0	279	340	349	689	70	343	17	9	315	99	—	—	—	—	—	—
2016	19	A+	Salem Red Sox	—	546	503	142	32	8	11	40	94	1	18	6	282	336	443	780	161	328	17	7	344	82	—	—	—	—	—	—
2016	19	INTL	Leones del Escogido	—	78	74	18	4	0	0	4	13	0	0	0	243	282	297	579	54	295	17	5	264	65	—	—	—	—	—	—
2017	20	MLB	Boston Red Sox	—	240	222	63	14	0	10	18	57	0	3	1	284	338	482	819	198	342	24	8	361	119	+5	+0	-4	+2	+5	0.9
2017	20	AAA	Pawtucket Red Sox	—	38	35	14	1	0	2	3	8	0	0	0	400	447	600	1.047	200	480	21	8	460	153	—	—	—	—	—	—
2017	20	AA	Portland Sea Dogs	—	320	287	86	19	3	18	31	55	1	0	3	300	370	575	945	275	316	17	10	408	124	—	—	—	—	—	—
2018	21	MLB	Boston Red Sox	—	490	450	108	24	0	21	38	121	0	5	2	240	299	433	733	193	281	25	8	323	94	-3	+0	-4	+2	+11	0.6
2018	21	AAA	Pawtucket Red Sox	—	22	21	7	2	0	1	1	6	0	0	0	333	364	571	935	238	429	27	5	408	97	—	—	—	—	—	—
2019	22	MLB	Boston Red Sox	—	702	647	201	54	4	32	48	119	4	8	8	311	362	555	917	244	339	17	7	398	144	+37	-2	+14	+3	+15	6.8
2020	23	MLB	Boston Red Sox	—	248	232	61	16	1	11	13	67	3	0	0	263	310	483	793	220	325	27	5	348	116	+5	+0	-2	+1	+5	0.9
2021	24	MLB	Boston Red Sox	—	664	591	165	37	1	38	62	143	7	5	5	279	355	538	893	259	307	22	9	387	139	+31	-1	-7	+2	+14	4.0
2022	25	MLB	Boston Red Sox	—	614	555	164	42	1	27	50	114	6	3	1	295	360	521	881	225	329	19	8	385	132	+23	+0	+0	+2	+13	4.0
2023	26	MLB	Boston Red Sox	—	656	580	157	34	0	33	62	126	11	5	1	271	352	500	852	229	292	19	9	374	127	+21	+1	-5	+2	+14	3.4
2024	27	MLB	Boston Red Sox	—	601	525	143	34	5	28	67	147	3	3	0	272	358	516	874	244	323	24	11	379	128	+20	+1	-3	+2	+13	3.3
2025	28	MLB	San Francisco Giants	—	729	607	153	33	0	35	112	192	6	1	1	252	374	479	853	227	307	26	15	377	141	+36	-0	-2	-13	+16	3.7
2026	29	MLB	San Francisco Giants	—	633	558	144	36	1	37	69	161	2	0	0	258	342	525	867	267	294	25	11	376	143	+32	+0	-1	-11	+14	3.4
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	5577	4967	1359	324	13	272	539	1247	42	33	19	274	350	508	858	235	313	22	10	375	140	+263	-1	-15	-8	+121	36.7
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2014	17	ROK MLE	GCL Red Sox	—	302	275	68	13	4	5	21	72	3	5	1	247	308	378	686	131	306	24	7	300	89	—	—	—	—	—	—
2015	18	A MLE	Greenville Drive	—	508	476	125	31	1	9	17	110	8	3	2	263	299	389	688	126	314	22	3	297	87	—	—	—	—	—	—
2016	19	A+ MLE	Salem Red Sox	—	546	518	126	25	5	12	25	140	1	18	6	243	279	380	660	137	311	26	5	289	82	—	—	—	—	—	—
2017	20	MLB MLE	Boston Red Sox	—	240	225	60	12	0	10	15	57	0	3	1	267	312	453	766	187	342	24	6	344	119	+5	+0	-4	+2	+5	0.9
2017	20	AAA MLE	Pawtucket Red Sox	—	38	36	13	1	0	2	2	10	0	0	0	361	395	556	950	194	465	26	5	394	153	—	—	—	—	—	—
2017	20	AA MLE	Portland Sea Dogs	—	320	299	82	16	3	14	19	69	1	0	3	274	320	488	808	214	315	22	6	352	124	—	—	—	—	—	—
2018	21	MLB MLE	Boston Red Sox	—	490	456	105	21	0	22	32	121	0	5	2	230	281	421	702	191	281	25	7	308	94	-3	+0	-4	+2	+11	0.6
2018	21	AAA MLE	Pawtucket Red Sox	—	22	21	7	2	0	1	1	7	0	0	0	333	364	571	935	238	386	32	5	311	97	—	—	—	—	—	—
2019	22	MLB MLE	Boston Red Sox	—	702	654	194	48	4	33	41	119	4	8	8	297	342	534	876	237	339	17	6	381	144	+37	-2	+14	+3	+15	6.8
2020	23	MLB MLE	Boston Red Sox	—	248	232	59	14	1	11	13	67	3	0	0	254	302	466	768	211	325	27	5	340	116	+5	+0	-2	+1	+5	0.9
2021	24	MLB MLE	Boston Red Sox	—	664	598	161	33	1	39	55	143	7	5	5	269	338	523	861	254	307	22	8	373	139	+31	-1	-7	+2	+14	4.0
2022	25	MLB MLE	Boston Red Sox	—	614	566	159	37	1	28	39	114	6	3	1	281	334	498	832	217	329	19	6	363	132	+23	+0	+0	+2	+13	4.0
2023	26	MLB MLE	Boston Red Sox	—	656	590	153	30	0	34	52	126	11	5	1	259	331	483	814	224	292	19	8	356	127	+21	+1	-5	+2	+14	3.4
2024	27	MLB MLE	Boston Red Sox	—	601	539	140	30	6	29	53	147	3	3	0	260	329	499	828	239	323	24	9	357	128	+20	+1	-3	+2	+13	3.3
2025	28	MLB MLE	San Francisco Giants	—	729	617	157	33	0	38	102	192	6	1	1	254	366	493	858	238	307	26	14	377	141	+36	-0	-2	-13	+16	3.7
2026	29	MLB MLE	San Francisco Giants	—	633	565	148	36	1	40	62	161	2	0	0	262	337	542	879	280	294	25	10	379	143	+32	+0	-1	-11	+14	3.4
2014	17	ROK MLE	GCL Red Sox	—	302	275	68	13	4	5	21	72	3	5	1	247	308	378	686	131	313	24	7	300	89	—	—	—	—	—	—
2014	17	ROK RAW	GCL Red Sox	—	302	261	84	17	5	7	35	50	3	5	1	322	408	506	914	184	372	17	12	400	89	—	—	—	—	—	—
2015	18	A MLE	2 teams	—	555	522	137	34	1	10	18	120	8	3	2	262	297	389	686	126	319	22	3	297	87	—	—	—	—	—	—
2015	18	A RAW	2 teams	—	555	512	147	41	1	11	28	92	8	3	2	287	334	436	769	148	328	17	5	338	87	—	—	—	—	—	—
2016	19	A+ MLE	2 teams	—	624	592	145	29	6	14	29	160	1	18	6	245	281	385	666	140	312	26	5	289	82	—	—	—	—	—	—
2016	19	A+ RAW	2 teams	—	624	577	160	36	8	11	44	107	1	18	6	277	330	425	754	147	323	17	7	334	82	—	—	—	—	—	—
2017	20	AA MLE	3 teams	—	598	560	157	30	3	26	36	136	1	3	4	280	325	484	809	204	328	23	6	351	124	—	—	—	—	—	—
2017	20	AA RAW	3 teams	—	598	544	163	34	3	30	52	120	1	3	4	300	362	539	900	239	337	20	9	393	124	—	—	—	—	—	—
2018	21	MLB MLE	2 teams	—	512	477	111	23	0	22	33	128	0	5	2	233	282	419	702	187	271	25	6	308	94	-3	+0	-4	+2	+11	0.6
2018	21	MLB RAW	2 teams	—	512	471	115	26	0	22	39	127	0	5	2	244	302	439	741	195	287	25	8	326	94	-3	+0	-4	+2	+11	0.6
2019	22	MLB MLE	Boston Red Sox	—	702	654	194	48	4	33	41	119	4	8	8	297	342	534	876	237	319	17	6	381	144	+37	-2	+14	+3	+15	6.8
2019	22	MLB RAW	Boston Red Sox	—	702	647	201	54	4	32	48	119	4	8	8	311	362	555	917	244	339	17	7	398	144	+37	-2	+14	+3	+15	6.8
2020	23	MLB MLE	Boston Red Sox	—	248	232	59	14	1	11	13	67	3	0	0	254	302	466	768	211	312	27	5	340	116	+5	+0	-2	+1	+5	0.9
2020	23	MLB RAW	Boston Red Sox	—	248	232	61	16	1	11	13	67	3	0	0	263	310	483	793	220	325	27	5	348	116	+5	+0	-2	+1	+5	0.9
2021	24	MLB MLE	Boston Red Sox	—	664	598	161	33	1	39	55	143	7	5	5	269	338	523	861	254	290	22	8	373	139	+31	-1	-7	+2	+14	4.0
2021	24	MLB RAW	Boston Red Sox	—	664	591	165	37	1	38	62	143	7	5	5	279	355	538	893	259	307	22	9	387	139	+31	-1	-7	+2	+14	4.0
2022	25	MLB MLE	Boston Red Sox	—	614	566	159	37	1	28	39	114	6	3	1	281	334	498	832	217	307	19	6	363	132	+23	+0	+0	+2	+13	4.0
2022	25	MLB RAW	Boston Red Sox	—	614	555	164	42	1	27	50	114	6	3	1	295	360	521	881	225	329	19	8	385	132	+23	+0	+0	+2	+13	4.0
2023	26	MLB MLE	Boston Red Sox	—	656	590	153	30	0	34	52	126	11	5	1	259	331	483	814	224	275	19	8	356	127	+21	+1	-5	+2	+14	3.4
2023	26	MLB RAW	Boston Red Sox	—	656	580	157	34	0	33	62	126	11	5	1	271	352	500	852	229	292	19	9	374	127	+21	+1	-5	+2	+14	3.4
2024	27	MLB MLE	Boston Red Sox	—	601	539	140	30	6	29	53	147	3	3	0	260	329	499	828	239	301	24	9	357	128	+20	+1	-3	+2	+13	3.3
2024	27	MLB RAW	Boston Red Sox	—	601	525	143	34	5	28	67	147	3	3	0	272	358	516	874	244	323	24	11	379	128	+20	+1	-3	+2	+13	3.3
2025	28	MLB MLE	San Francisco Giants	—	729	617	157	33	0	38	102	192	6	1	1	254	366	493	858	238	304	26	14	377	141	+36	-0	-2	-13	+16	3.7
2025	28	MLB RAW	San Francisco Giants	—	729	607	153	33	0	35	112	192	6	1	1	252	374	479	853	227	307	26	15	377	141	+36	-0	-2	-13	+16	3.7
2026	29	MLB MLE	San Francisco Giants	—	633	565	148	36	1	40	62	161	2	0	0	262	337	542	879	280	293	25	10	379	143	+32	+0	-1	-11	+14	3.4
2026	29	MLB RAW	San Francisco Giants	—	633	558	144	36	1	37	69	161	2	0	0	258	342	525	867	267	294	25	11	376	143	+32	+0	-1	-11	+14	3.4
2014	17	ROK MLE	GCL Red Sox	—	302	275	68	13	4	5	21	72	3	5	1	247	308	378	686	131	306	24	7	300	89	—	—	—	—	—	—
2015	18	A MLE	2 teams	—	555	524	137	34	1	10	18	120	8	3	2	261	297	387	685	126	314	22	3	297	87	—	—	—	—	—	—
2016	19	A+ MLE	2 teams	—	624	589	145	29	6	14	29	160	1	18	6	246	281	387	668	141	311	26	5	289	82	—	—	—	—	—	—
2017	20	AA MLE	3 teams	—	598	556	157	30	3	26	36	136	1	3	4	282	325	487	812	205	335	23	6	351	124	—	—	—	—	—	—
2018	21	MLB MLE	2 teams	—	512	474	111	23	0	22	33	128	0	5	2	234	282	422	704	188	285	25	6	308	94	—	—	—	—	—	—
2019	22	MLB MLE	Boston Red Sox	—	702	651	194	48	4	33	41	119	4	8	8	298	342	536	878	238	339	17	6	381	144	—	—	—	—	—	—
2020	23	MLB MLE	Boston Red Sox	—	248	230	59	14	1	11	13	67	3	0	0	257	302	470	772	213	325	27	5	340	116	—	—	—	—	—	—
2021	24	MLB MLE	Boston Red Sox	—	664	597	161	33	1	39	55	143	7	5	5	270	338	524	862	255	307	22	8	373	139	—	—	—	—	—	—
2022	25	MLB MLE	Boston Red Sox	—	614	564	159	37	1	28	39	114	6	3	1	282	334	500	834	218	329	19	6	363	132	—	—	—	—	—	—
2023	26	MLB MLE	Boston Red Sox	—	656	588	153	30	0	34	52	126	11	5	1	260	331	485	815	224	292	19	8	356	127	—	—	—	—	—	—
2024	27	MLB MLE	Boston Red Sox	—	601	540	140	30	6	29	53	147	3	3	0	259	329	498	828	239	323	24	9	357	128	—	—	—	—	—	—
2025	28	MLB MLE	San Francisco Giants	—	729	615	157	33	0	38	102	192	6	1	1	255	366	494	860	239	307	26	14	377	141	—	—	—	—	—	—
2026	29	MLB MLE	San Francisco Giants	—	633	564	148	36	1	40	62	161	2	0	0	262	337	543	880	280	294	25	10	379	143	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	27	MLB MLE	Boston Red Sox	—	601	540	140	30	6	29	53	147	3	3	0	259	329	498	828	239	323	24	9	357	128	—	—	—	—	—	—
2025	28	MLB MLE	San Francisco Giants	—	729	615	157	33	0	38	102	192	6	1	1	255	366	494	860	239	307	26	14	377	141	—	—	—	—	—	—
2026	29	MLB MLE	San Francisco Giants	—	633	564	148	36	1	40	62	161	2	0	0	262	337	543	880	280	294	25	10	379	143	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	30	MLB MLE	SF	100%	551	482	121	28	1	30	61	140	3	2	1	252	340	504	844	252	289	25	11	367	135	+23	+0	-0	-10	+12	1.3
▸ 2027 — real world (MLB)
2027	30	MLB CTX	SF	100%	279	244	60	14	1	14	31	71	2	1	0	246	335	484	818	238	284	25	11	357	135	+11	+0	-0	-5	+6	1.3
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	31	MLB MLE	SF	100%	614	538	133	31	1	33	68	159	3	2	0	247	335	492	826	245	284	26	11	360	130	+22	+0	-3	-11	+13	2.2
2029	32	MLB MLE	SF	100%	614	539	130	30	1	32	67	162	3	1	0	239	327	475	802	236	277	26	11	350	123	+17	+0	-4	-11	+13	1.6
2030	33	MLB MLE	SF	100%	517	454	105	23	1	26	56	139	2	1	0	230	317	455	771	224	268	27	11	338	115	+9	+0	-4	-9	+11	0.7
2031	34	MLB MLE	SF	100%	422	373	81	18	0	20	45	116	1	1	0	219	305	430	734	211	256	27	11	323	105	+3	+0	-5	-8	+9	-0.1
2028	31	MLB CTX	SF	100%	614	538	129	31	1	30	68	159	3	2	0	240	329	472	801	232	280	26	11	350	130	+22	+0	-3	-11	+13	2.2
2029	32	MLB CTX	SF	100%	614	539	126	30	1	29	67	162	3	1	0	233	321	456	778	223	273	26	11	341	123	+17	+0	-4	-11	+13	1.6
2030	33	MLB CTX	SF	100%	517	454	103	24	1	24	56	139	2	1	0	224	312	436	748	212	264	27	11	329	115	+9	+0	-4	-9	+11	0.7
2031	34	MLB CTX	SF	100%	422	373	80	18	0	19	45	116	1	1	0	213	300	412	712	199	252	27	11	315	105	+3	+0	-5	-8	+9	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	7744	6871	1797	427	16	374	775	1823	51	38	19	262	341	492	832	230	302	24	10	364	122	+313	+0	-31	-47	+168	41.2
/ 162G	—	A+C		—	650	577	150	36	1	31	65	153	4	3	2	260	339	487	826	227	301	24	10	364	122	+26	+0	-3	-4	+14	3.5
Career	—	MLE		—	9884	8935	2299	506	32	455	821	2332	66	65	31	257	324	474	798	217	297	24	8	348	122	+325	+0	-31	-52	+174	42.5
/ 162G	—	MLE		—	650	588	151	33	2	30	54	153	4	4	2	257	324	473	796	216	297	24	8	348	122	+26	+0	-3	-4	+14	3.4

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.

2018 AAAPawtucket Red Sox · 22 PAwOBA .396 → .311 (−85)K% 27.3% → 32.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.27%	÷0.994	×1.200	—	—	32.92%
BB% (unintentional) /PA	4.55%	÷1.082	×0.690	—	×1.050	3.04%
HBP% /PA	0.00%	—	×0.940	—	×1.050	0.00%
Singles /BIP	26.67%	÷1.000	×0.930	—	×1.050	26.05%
Doubles /BIP	13.33%	÷1.067	×0.830	—	×1.050	10.89%
Triples /BIP	0.00%	÷0.900	×0.970	—	×1.050	0.00%
Home runs /BIP	6.67%	÷1.342	×0.840	—	×1.050	4.38%

Factors used: league row IL. Park (home-season share, regressed): HR 168, 1B 100, 2B 113, 3B 80, K 99, BB 116 — 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 .396 → .311; ISO .238 → .161; BABIP .429 → .386. 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 AAPortland Sea Dogs · 320 PAwOBA .394 → .352 (−42)K% 17.2% → 21.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.19%	÷0.974	×1.220	—	—	21.52%
BB% (unintentional) /PA	8.44%	÷1.067	×0.700	—	×1.050	5.81%
HBP% /PA	0.31%	—	×0.850	—	×1.050	0.28%
Singles /BIP	19.83%	÷0.984	×0.970	×1.036	×1.050	21.26%
Doubles /BIP	8.19%	÷1.085	×0.860	×1.036	×1.050	7.07%
Triples /BIP	1.29%	÷1.010	×0.950	×1.036	×1.050	1.32%
Home runs /BIP	7.76%	÷1.020	×0.780	—	×1.050	6.23%

Factors used: league row EL. Park (home-season share, regressed): HR 104, 1B 97, 2B 117, 3B 102, K 95, BB 114 — 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 ×1.036.

Result: wOBA .394 → .352; ISO .275 → .229; BABIP .316 → .315. 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 AAAPawtucket Red Sox · 38 PAwOBA .447 → .394 (−54)K% 21.1% → 25.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.05%	÷0.985	×1.200	—	—	25.65%
BB% (unintentional) /PA	7.89%	÷0.937	×0.690	—	×1.050	6.10%
HBP% /PA	0.00%	—	×0.940	—	×1.050	0.00%
Singles /BIP	40.74%	÷0.987	×0.930	—	×1.050	40.33%
Doubles /BIP	3.70%	÷0.954	×0.830	—	×1.050	3.38%
Triples /BIP	0.00%	÷1.000	×0.970	—	×1.050	0.00%
Home runs /BIP	7.41%	÷1.106	×0.840	—	×1.050	5.91%

Factors used: league row IL. Park (home-season share, regressed): HR 121, 1B 97, 2B 91, 3B 100, K 97, BB 87 — applied at half strength. Age: age 21 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (6.2 yr younger than average).

Result: wOBA .447 → .394; ISO .200 → .156; BABIP .480 → .465. 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 A+Salem Red Sox · 546 PAwOBA .335 → .289 (−46)K% 17.2% → 25.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.22%	÷0.951	×1.420	—	—	25.71%
BB% (unintentional) /PA	6.96%	÷0.989	×0.630	—	×1.042	4.62%
HBP% /PA	0.18%	—	×0.860	—	×1.042	0.16%
Singles /BIP	22.25%	÷1.000	×0.940	×1.017	×1.042	22.17%
Doubles /BIP	7.82%	÷1.030	×0.830	×1.017	×1.042	6.68%
Triples /BIP	1.96%	÷1.150	×0.800	×1.017	×1.042	1.44%
Home runs /BIP	2.69%	÷0.787	×0.900	—	×1.042	3.21%

Factors used: league row CAR. Park (home-season share, regressed): HR 57, 1B 100, 2B 106, 3B 130, K 90, BB 98 — 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 ×1.017.

Result: wOBA .335 → .289; ISO .161 → .145; BABIP .328 → .311. 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 AGreenville Drive · 508 PAwOBA .335 → .297 (−37)K% 16.5% → 21.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.54%	÷1.019	×1.340	—	—	21.74%
BB% (unintentional) /PA	4.72%	÷0.993	×0.660	—	×1.045	3.28%
HBP% /PA	1.57%	—	×0.770	—	×1.045	1.27%
Singles /BIP	22.08%	÷0.981	×0.920	×1.041	×1.045	22.54%
Doubles /BIP	9.87%	÷1.063	×0.820	×1.041	×1.045	8.29%
Triples /BIP	0.26%	÷1.069	×0.940	×1.041	×1.045	0.25%
Home runs /BIP	2.86%	÷0.979	×0.820	—	×1.045	2.50%

Factors used: league row SAL. Park (home-season share, regressed): HR 96, 1B 96, 2B 113, 3B 114, K 104, BB 99 — 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 ×1.041.

Result: wOBA .335 → .297; ISO .156 → .130; BABIP .326 → .314. 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 ROKGCL Red Sox · 302 PAwOBA .393 → .300 (−93)K% 16.6% → 23.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.56%	÷1.000	×1.440	—	—	23.84%
BB% (unintentional) /PA	11.26%	÷1.000	×0.620	—	×1.022	7.14%
HBP% /PA	0.99%	—	×0.720	—	×1.022	0.73%
Singles /BIP	26.07%	÷1.000	×0.820	×1.024	×1.022	22.38%
Doubles /BIP	8.06%	÷1.000	×0.720	×1.024	×1.022	6.07%
Triples /BIP	2.37%	÷1.000	×0.720	×1.024	×1.022	1.79%
Home runs /BIP	3.32%	÷1.000	×0.780	—	×1.022	2.65%

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 ×1.024.

Result: wOBA .393 → .300; ISO .184 → .139; BABIP .372 → .306. 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
#1Mark Teixeiralast yr '16 AS×3GG×5SS×3 career totals — 14 seasons, 8,029 PA	12.1	8,029	409	26	268	360	509	-143	-74	42.1	38.1
/162	664	34	2	-11.9	-6.1	3.5	pk7: 34
#2Boog Powell'61-'77 * career totals — 16 seasons, 7,810 PA	11.8	7,810	339	20	272*	367*	510*	-127	-22	40.8	35.0
/162	664	29	2	-10.8	-1.9	3.5	pk7: 29
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 15 projected seasons	12.1	8,054	400	39	264	340	500	-159	-14	37.6	33.2
/162	664	33	3	-13.1	-1.2	3.1	pk7: 29
#3Paul Konerko'97-'14 * career totals — 17 seasons, 9,505 PA	14.3	9,505	439	9	271*	348*	481*	-177	-20	36.7	32.1
/162	664	31	1	-12.4	-1.4	2.6	pk7: 27
#4Kent Hrbek'81-'94 * career totals — 14 seasons, 7,137 PA	10.7	7,137	293	37	279*	366*	503*	-130	-20	34.4	28.7
/162	664	27	3	-12.1	-1.9	3.2	pk7: 23
#5Anthony Rizzolast yr '24 career totals — 14 seasons, 7,336 PA	11.0	7,336	303	72	261	361	467	-131	-79	28.7	27.3
/162	664	27	7	-11.9	-7.1	2.6	pk7: 26
#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
Rafael Devers (OGILVIE)	30	—	—	—	—	250/338/499	250	289	17	1	25%	11%	135	+2.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
●Joc Pederson 2021 · MLB	29	42→52	65	43→55	51	241/323/492	251	254	34	4	22%	9%	127	+3.3	248/328/459	211	286	27	4	23%	9%	121	+2.9	259/358/487	228	294	30	5	22%	11%	139	+3.0
●Brandon Moss 2014 · MLB	30	46→53	67→65	45	47	256/325/515	259	299	36	6	28%	8%	133	+3.7	238/316/463	225	287	30	3	28%	9%	118	+2.6	227/308/447	220	273	30	1	28%	9%	113	+2.0
●Jorge Soler 2022 · MLB	30	42→52	62→70	45	53	236/325/466	230	269	31	2	25%	11%	122	+2.9	238/325/460	222	279	29	2	26%	11%	120	+2.8	240/331/469	229	281	30	1	25%	11%	125	+2.6
✕Luke Voit 2021 · MLB	30	50→54	63→65	44→30	52	269/351/502	234	313	33	2	25%	10%	139	+4.2	237/319/434	197	308	27	3	30%	9%	112	+2.2	219/306/397	179	295	24	2	33%	9%	99	+0.8
●Adam Dunn 2011 · MLB	31	47→49	66→70	39→50	56	254/354/514	260	305	34	2	28%	13%	143	+4.4	210/320/422	212	276	28	2	33%	13%	110	+2.1	210/321/437	227	260	33	1	32%	13%	115	+2.4
●Lucas Duda 2016 · MLB	30	47→56	60→65	36→30	53	248/341/469	221	290	27	3	25%	11%	128	+3.3	237/320/466	229	277	30	2	26%	10%	120	+2.8	225/305/452	227	261	31	1	27%	9%	113	+1.3
●Chris Davis 2016 · MLB	30	42→52	66→70	40	50	237/326/489	252	292	35	3	31%	10%	127	+3.3	213/306/414	201	286	28	3	34%	11%	103	+1.5	194/288/371	177	265	25	1	35%	11%	88	+0.4
★Kyle Schwarber 2022 · MLB	29	43→49	68→70	42→45	56	247/346/511	264	281	37	3	27%	12%	139	+4.2	221/334/476	255	257	36	5	29%	14%	127	+3.3	231/350/489	258	271	37	5	29%	14%	136	+4.7
✕Logan Morrison 2018 · MLB	30	43→53	61→65	46→45	54	240/326/464	224	263	30	5	22%	10%	121	+2.9	227/304/450	223	245	31	4	22%	9%	111	+2.1	208/282/428	220	213	32	1	22%	8%	96	+0.6
✕Matt Adams 2019 · MLB	30	45→55	64→65	44→40	45	253/307/491	237	274	34	2	23%	7%	121	+2.9	234/286/446	212	287	30	4	30%	6%	103	+1.6	196/238/361	165	258	24	0	35%	5%	64	-0.8
●Carlos Pena 2008 · MLB	30	47→48	66→70	45	57	257/356/510	253	287	34	3	24%	12%	143	+4.4	235/350/494	259	271	34	4	27%	14%	137	+4.0	218/341/469	251	250	34	3	28%	14%	129	+3.4
●Nick Castellanos 2022 · MLB	30	53→61	62→65	42→45	45	281/334/522	240	319	30	4	22%	6%	138	+4.1	267/313/444	177	325	21	7	24%	6%	112	+2.2	259/306/423	164	318	19	8	24%	6%	105	+1.8
✕Marcus Thames 2007 · MLB	30	46	67→70	45→40	49	257/328/522	264	284	36	4	24%	9%	135	+3.9	247/303/493	246	279	35	4	26%	7%	120	+2.8	248/309/461	213	287	32	0	26%	8%	115	+1.3
●Michael Morse 2012 · MLB	30	55→58	60→65	39→45	45	287/341/506	219	327	28	3	22%	6%	137	+4.0	268/316/459	191	319	25	2	24%	5%	117	+2.6	263/311/443	180	319	23	0	25%	5%	112	+1.6
●Carlos Quentin 2013 · MLB	30	48→52	61→65	39→45	53	255/349/486	230	259	28	3	15%	8%	135	+3.9	249/341/442	193	274	22	3	18%	9%	122	+3.0	244/341/434	190	272	21	0	19%	10%	121	+1.1
●Brad Hawpe 2009 · MLB	30	55→57	59→60	40	56	280/365/500	220	331	26	3	23%	12%	143	+4.5	264/349/462	198	332	21	3	25%	11%	128	+3.4	258/344/447	189	331	19	2	26%	11%	124	+2.0
●Adam LaRoche 2009 · MLB	29	51→53	58→65	40	51	268/333/482	215	307	25	2	22%	9%	128	+3.3	256/321/451	195	310	23	3	24%	9%	116	+2.5	249/331/445	196	278	26	3	21%	11%	119	+2.8
✕Justin Bour 2018 · MLB	30	51→55	62→65	47→40	51	275/338/501	226	299	32	3	20%	9%	135	+3.8	234/323/432	198	276	27	4	25%	11%	113	+2.3	206/307/387	181	243	25	2	26%	12%	96	+0.6
✕Pedro Álvarez 2017 · MLB	30	44→48	62→65	47→45	49	242/309/464	222	279	31	5	26%	9%	116	+2.5	226/278/410	184	274	26	3	27%	7%	91	+0.7	213/260/384	171	257	25	1	28%	6%	76	-0.3
✕Jason Kubel 2013 · MLB	31	47→56	57→60	42→40	49	250/315/453	203	292	25	2	24%	8%	114	+2.4	231/300/373	142	315	16	4	30%	9%	90	+0.6	215/285/303	88	318	8	1	32%	9%	69	-0.4

Rafael Devers

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps