Harrison Bader

CF San Francisco Giants

Age 33 R/R 5'11" / 219 lbs MLB HR -15%H -3% Svc 9.174 · Ctrl thru 2027 ILInjured 60-Day (D60)

Overview

MLBIL-6040-MANExtFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	30	MLBNYM	437	.236/.288/.373	12	17	88	1.2
2025	31	MLBPHI	501	.277/.349/.449	17	11	123	2.9
2026	32	MLBSF	111	.170/.200/.358	5	0	56	-0.3
2027PROJ	33	MLBSF	115	.234/.298/.392	4	3	98	0.4
2028PROJ	34	MLBSF	164	.223/.286/.370	5	2	89	-0.2

Last 3 seasons WAR 3.8 · Next 2 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service9.174First FA2028Options2

2027Ext$10M

Skills · percentileStatcast 2024-2026

Bat Spd62

Barrel%52

Speed50

xwOBA39

Avg EV28

CompsMichael A. Taylor (age 33) · Darnell McDonald (age 33) · John Hicks (age 33)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 9998vR 95

AVG/OBP/SLG.234 / .298 / .392

PA115

HR4

K%25

BB%6

BABIP287

ISO162

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · ContractCON 45 / POW 50

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT45

xAVG

220.228

POWER50

Barrel%

528.4

Avg EV

2887.4

Bat Spd

6272.7

EYE40

scouting grade only

SPEED60

Sprint

5027.5

Platoon Splits2024-2026 · 984 PA

vs LHP

vs RHP

Edge

310

674

—

wRC+

106

▶▶R

wOBA

287

325

▶R

ISO

155

150

—

BABIP

270

328

▶▶R

27.1%

23.9%

▶R

BB%

6.8%

5.9%

◀L

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

Status FA

MLB Debut 2017

Service 9.174 yrs.days

Team Control Through 2027

First FA Year 2028

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$10M	+0.3	$1M	-$9M
Totals		$10M		$1M	-$9M

Options · projected decision
2028	MUTUAL OPT	$10.2M / $0.0M buyout	DECLINE
2029	MUTUAL OPT	$10.0M / $1.5M buyout	DECLINE

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)
2015	21	A	Peoria Chiefs	—	228	206	62	11	2	9	15	44	6	15	6	301	366	505	870	204	344	19	7	382	91	—	—	—	—	—	—
2016	22	AAA	Memphis Redbirds	—	161	147	34	7	1	3	11	38	3	2	3	231	298	354	652	122	292	24	7	295	51	—	—	—	—	—	—
2016	22	AA	Springfield Cardinals	—	356	318	90	12	4	16	25	93	10	11	10	283	354	497	851	214	349	26	7	372	98	—	—	—	—	—	—
2016	22	INTL	Glendale Desert Dogs	—	86	79	24	2	1	2	5	14	1	4	2	304	353	430	783	127	344	16	6	346	120	—	—	—	—	—	—
2017	23	MLB	St. Louis Cardinals	—	92	85	20	3	0	3	5	24	1	2	1	235	286	376	662	141	288	26	5	293	82	-2	+0	+1	+2	+2	0.3
2017	23	AAA	Memphis Redbirds	—	479	431	122	18	1	20	34	118	10	15	9	283	349	469	818	186	345	25	7	360	80	—	—	—	—	—	—
2018	24	MLB	St. Louis Cardinals	—	427	379	100	20	2	12	31	125	11	15	3	264	337	422	759	158	358	29	7	336	112	+6	+2	+14	+2	+9	3.3
2019	25	MLB	St. Louis Cardinals	—	406	347	71	14	3	12	46	117	10	11	3	205	315	366	681	161	268	29	11	308	93	-3	+1	+9	+2	+9	1.8
2019	25	AAA	Memphis Redbirds	—	75	63	20	3	0	7	8	16	4	3	0	317	427	698	1.125	381	325	21	11	480	143	—	—	—	—	—	—
2020	26	MLB	St. Louis Cardinals	—	125	106	24	7	2	4	13	40	5	3	1	226	339	443	782	217	317	32	10	346	123	+3	+0	+2	+0	+3	0.9
2021	27	MLB	St. Louis Cardinals	—	401	367	98	21	1	16	27	85	5	9	4	267	326	460	786	193	306	21	7	346	116	+8	+0	+11	+1	+9	2.9
2022	28	MLB	New York Yankees	—	313	292	73	10	3	5	15	62	4	17	3	250	296	356	652	106	300	20	5	292	82	-7	+2	+4	+1	+7	0.8
2022	28	AA	Somerset Patriots	—	23	21	6	2	0	1	2	3	0	1	0	286	348	524	872	238	294	13	9	381	94	—	—	—	—	—	—
2023	29	MLB	Cincinnati Reds	—	344	319	74	12	2	7	17	59	3	20	3	232	277	348	625	116	261	17	5	277	71	-12	+3	+6	+1	+7	0.6
2023	29	AAA	Scranton/Wilkes-Barre RailRiders	—	21	19	2	0	0	0	2	3	0	1	0	105	190	105	296		125	14	10	153	-35	—	—	—	—	—	—
2023	29	AA	Somerset Patriots	—	18	18	3	1	0	0	0	5	0	0	0	167	167	222	389	56	231	28	0	172	-20	—	—	—	—	—	—
2024	30	MLB	New York Mets	—	437	402	95	19	0	12	21	95	8	17	8	236	288	373	661	137	276	22	5	292	88	-6	+0	+7	+2	+9	1.2
2025	31	MLB	Philadelphia Phillies	—	501	448	124	24	1	17	39	136	11	11	7	277	349	449	798	172	359	27	8	354	123	+14	-1	+3	+2	+11	2.9
2026	32	MLB	San Francisco Giants	—	111	106	18	5	0	5	4	34	0	0	0	170	200	358	558	189	191	31	4	242	56	-6	+0	-0	+0	+2	-0.3
2026	32	AAA	Sacramento River Cats	—	23	18	4	0	0	2	3	5	2	1	0	222	391	556	947	333	182	22	13	415	91	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	3157	2851	697	135	14	93	218	777	58	105	33	244	311	400	711	155	301	25	7	315	100	-1	+8	+57	+14	+68	14.9
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2015	21	A MLE	Peoria Chiefs	—	228	211	52	8	2	7	10	60	6	15	6	246	300	403	702	156	309	26	4	302	91	—	—	—	—	—	—
2016	22	AAA MLE	Memphis Redbirds	—	161	150	29	6	1	2	8	50	3	2	3	193	248	287	535	93	275	31	5	243	51	—	—	—	—	—	—
2016	22	AA MLE	Springfield Cardinals	—	356	325	81	10	4	11	18	111	10	11	10	249	309	406	715	157	338	31	5	313	98	—	—	—	—	—	—
2017	23	MLB MLE	St. Louis Cardinals	—	92	86	20	3	0	3	4	24	1	2	1	233	275	372	647	140	288	26	4	290	82	-2	+0	+1	+2	+2	0.3
2017	23	AAA MLE	Memphis Redbirds	—	479	440	102	14	1	16	25	151	10	15	9	232	288	377	666	145	303	32	5	286	80	—	—	—	—	—	—
2018	24	MLB MLE	St. Louis Cardinals	—	427	382	100	19	2	13	28	125	11	15	3	262	330	424	754	162	358	29	7	334	112	+6	+2	+14	+2	+9	3.3
2019	25	MLB MLE	St. Louis Cardinals	—	406	351	71	13	3	13	42	117	10	11	3	202	305	368	673	165	268	29	10	306	93	-3	+1	+9	+2	+9	1.8
2019	25	AAA MLE	Memphis Redbirds	—	75	65	17	3	0	5	6	21	4	3	0	262	360	538	898	277	289	28	8	380	143	—	—	—	—	—	—
2020	26	MLB MLE	St. Louis Cardinals	—	125	106	24	7	2	4	13	40	5	3	1	226	339	443	782	217	317	32	10	350	123	+3	+0	+2	+0	+3	0.9
2021	27	MLB MLE	St. Louis Cardinals	—	401	373	98	20	1	17	21	85	5	9	4	263	311	458	769	196	306	21	5	340	116	+8	+0	+11	+1	+9	2.9
2022	28	MLB MLE	New York Yankees	—	313	292	73	10	3	5	15	62	4	17	3	250	296	356	652	106	300	20	5	290	82	-7	+2	+4	+1	+7	0.8
2022	28	AA MLE	Somerset Patriots	—	23	22	6	2	0	1	1	4	0	1	0	273	304	500	804	227	265	17	4	307	94	—	—	—	—	—	—
2023	29	MLB MLE	Cincinnati Reds	—	344	319	73	12	2	6	17	59	3	20	3	229	274	335	610	107	261	17	5	273	71	-12	+3	+6	+1	+7	0.6
2023	29	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	21	20	2	0	0	0	1	4	0	1	0	100	143	100	243		111	19	5	117	-35	—	—	—	—	—	—
2023	29	AA MLE	Somerset Patriots	—	18	18	3	1	0	0	0	6	0	0	0	167	167	222	389	56	211	33	0	139	-20	—	—	—	—	—	—
2024	30	MLB MLE	New York Mets	—	437	403	98	20	0	12	20	95	8	17	8	243	292	382	674	139	276	22	5	298	88	-6	+0	+7	+2	+9	1.2
2025	31	MLB MLE	Philadelphia Phillies	—	501	448	124	25	1	16	39	136	11	11	7	277	349	444	794	167	359	27	8	350	123	+14	-1	+3	+2	+11	2.9
2026	32	MLB MLE	San Francisco Giants	—	111	106	18	5	0	5	4	34	0	0	0	170	200	358	558	189	191	31	4	250	56	-6	+0	-0	+0	+2	-0.3
2026	32	AAA MLE	Sacramento River Cats	—	23	19	3	0	0	1	2	6	2	1	0	158	304	316	620	158	152	26	9	303	91	—	—	—	—	—	—
2015	21	A MLE	Peoria Chiefs	—	228	211	52	8	2	7	10	60	6	15	6	246	300	403	702	156	310	26	4	302	91	—	—	—	—	—	—
2015	21	A RAW	Peoria Chiefs	—	228	206	62	11	2	9	15	44	6	15	6	301	366	505	870	204	344	19	7	382	91	—	—	—	—	—	—
2016	22	AA MLE	3 teams	—	603	554	130	19	6	16	31	188	14	17	15	235	292	377	669	143	322	31	5	291	83	—	—	—	—	—	—
2016	22	AA RAW	3 teams	—	603	544	148	21	6	21	41	145	14	17	15	272	339	449	787	176	332	24	7	348	83	—	—	—	—	—	—
2017	23	AAA MLE	2 teams	—	571	526	121	16	1	19	29	175	11	17	10	230	284	373	657	143	304	31	5	287	80	—	—	—	—	—	—
2017	23	AAA RAW	2 teams	—	571	516	142	21	1	23	39	142	11	17	10	275	339	453	793	178	335	25	7	349	80	—	—	—	—	—	—
2018	24	MLB MLE	St. Louis Cardinals	—	427	382	100	19	2	13	28	125	11	15	3	262	330	424	754	162	351	29	7	334	112	+6	+2	+14	+2	+9	3.3
2018	24	MLB RAW	St. Louis Cardinals	—	427	379	100	20	2	12	31	125	11	15	3	264	337	422	759	158	358	29	7	336	112	+6	+2	+14	+2	+9	3.3
2019	25	MLB MLE	2 teams	—	481	416	88	16	3	18	48	138	14	14	3	212	314	394	708	183	267	29	10	318	101	+1	+2	+9	+2	+10	2.4
2019	25	MLB RAW	2 teams	—	481	410	91	17	3	19	54	133	14	14	3	222	333	417	750	195	277	28	11	335	101	+1	+2	+9	+2	+10	2.4
2020	26	MLB MLE	St. Louis Cardinals	—	125	106	24	7	2	4	13	40	5	3	1	226	339	443	782	217	317	32	10	350	123	+3	+0	+2	+0	+3	0.9
2020	26	MLB RAW	St. Louis Cardinals	—	125	106	24	7	2	4	13	40	5	3	1	226	339	443	782	217	317	32	10	346	123	+3	+0	+2	+0	+3	0.9
2021	27	MLB MLE	St. Louis Cardinals	—	401	373	98	20	1	17	21	85	5	9	4	263	311	458	769	196	297	21	5	340	116	+8	+0	+11	+1	+9	2.9
2021	27	MLB RAW	St. Louis Cardinals	—	401	367	98	21	1	16	27	85	5	9	4	267	326	460	786	193	306	21	7	346	116	+8	+0	+11	+1	+9	2.9
2022	28	MLB MLE	2 teams	—	336	314	78	12	3	5	16	66	4	18	3	248	293	354	647	105	298	20	5	291	83	-7	+2	+4	+1	+7	0.9
2022	28	MLB RAW	2 teams	—	336	313	79	12	3	6	17	65	4	18	3	252	299	367	667	115	299	19	5	298	83	-7	+2	+4	+1	+7	0.9
2023	29	MLB MLE	3 teams	—	383	357	77	13	2	6	18	69	3	21	3	216	259	314	573	98	248	18	5	258	61	-18	+3	+6	+1	+8	0.1
2023	29	MLB RAW	3 teams	—	383	356	79	13	2	7	19	67	3	21	3	222	267	329	596	107	252	17	5	265	61	-18	+3	+6	+1	+8	0.1
2024	30	MLB MLE	New York Mets	—	437	403	98	20	0	12	20	95	8	17	8	243	292	382	674	139	285	22	5	298	88	-6	+0	+7	+2	+9	1.2
2024	30	MLB RAW	New York Mets	—	437	402	95	19	0	12	21	95	8	17	8	236	288	373	661	137	276	22	5	292	88	-6	+0	+7	+2	+9	1.2
2025	31	MLB MLE	Philadelphia Phillies	—	501	448	124	25	1	16	39	136	11	11	7	277	349	444	794	167	361	27	8	350	123	+14	-1	+3	+2	+11	2.9
2025	31	MLB RAW	Philadelphia Phillies	—	501	448	124	24	1	17	39	136	11	11	7	277	349	449	798	172	359	27	8	354	123	+14	-1	+3	+2	+11	2.9
2026	32	MLB MLE	2 teams	—	134	125	22	5	0	7	6	40	2	1	0	176	226	384	610	208	190	30	4	259	62	-6	+0	-0	+0	+3	-0.3
2026	32	MLB RAW	2 teams	—	134	124	22	5	0	7	7	39	2	1	0	177	233	387	620	210	190	29	5	272	62	-6	+0	-0	+0	+3	-0.3
2015	21	A MLE	Peoria Chiefs	—	228	210	52	8	2	7	10	60	6	15	6	248	300	405	704	157	309	26	4	302	91	—	—	—	—	—	—
2016	22	AA MLE	3 teams	—	603	553	130	19	6	16	31	188	14	17	15	235	292	378	670	143	318	31	5	291	83	—	—	—	—	—	—
2017	23	AAA MLE	2 teams	—	571	526	121	16	1	19	29	175	11	17	10	230	284	373	657	143	301	31	5	287	80	—	—	—	—	—	—
2018	24	MLB MLE	St. Louis Cardinals	—	427	385	100	19	2	13	28	125	11	15	3	260	330	421	751	161	358	29	7	334	112	—	—	—	—	—	—
2019	25	MLB MLE	2 teams	—	481	416	88	16	3	18	48	138	14	14	3	212	314	394	708	183	271	29	10	318	101	—	—	—	—	—	—
2020	26	MLB MLE	St. Louis Cardinals	—	125	106	24	7	2	4	13	40	5	3	1	226	339	443	782	217	317	32	10	350	123	—	—	—	—	—	—
2021	27	MLB MLE	St. Louis Cardinals	—	401	372	98	20	1	17	21	85	5	9	4	263	311	460	770	196	306	21	5	340	116	—	—	—	—	—	—
2022	28	MLB MLE	2 teams	—	336	313	78	12	3	5	16	66	4	18	3	249	293	355	648	105	297	20	5	291	83	—	—	—	—	—	—
2023	29	MLB MLE	3 teams	—	383	359	77	13	2	6	18	69	3	21	3	214	259	312	571	97	250	18	5	258	61	—	—	—	—	—	—
2024	30	MLB MLE	New York Mets	—	437	406	98	20	0	12	20	95	8	17	8	241	292	379	672	138	276	22	5	298	88	—	—	—	—	—	—
2025	31	MLB MLE	Philadelphia Phillies	—	501	446	124	25	1	16	39	136	11	11	7	278	349	446	796	168	359	27	8	350	123	—	—	—	—	—	—
2026	32	MLB MLE	2 teams	—	134	125	22	5	0	7	6	40	2	1	0	176	226	384	610	208	184	30	4	259	62	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	30	MLB MLE	New York Mets	—	437	406	98	20	0	12	20	95	8	17	8	241	292	379	672	138	276	22	5	298	88	—	—	—	—	—	—
2025	31	MLB MLE	Philadelphia Phillies	—	501	446	124	25	1	16	39	136	11	11	7	278	349	446	796	168	359	27	8	350	123	—	—	—	—	—	—
2026	32	MLB MLE	2 teams	—	134	125	22	5	0	7	6	40	2	1	0	176	226	384	610	208	184	30	4	259	62	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	33	MLB MLE	SF	100%	277	252	61	12	1	10	18	71	5	7	1	239	302	405	708	166	291	26	6	314	98	-1	+1	+2	+1	+6	0.3
▸ 2027 — real world (MLB)
2027	33	MLB CTX	SF	100%	115	105	25	5	0	4	7	29	2	3	1	234	298	392	690	158	287	25	6	306	98	-0	+0	+1	+0	+2	0.4
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	34	MLB MLE	SF	100%	164	150	33	6	0	5	10	43	3	2	1	228	291	382	673	154	281	26	6	299	89	-2	+0	-4	+1	+4	-0.2
2028	34	MLB CTX	SF	100%	164	150	33	6	0	5	10	43	3	2	1	223	286	370	656	146	277	26	6	293	89	-2	+0	-4	+1	+4	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3321	3001	730	141	14	98	228	820	61	107	34	243	310	398	707	154	300	25	7	314	94	-4	+8	+53	+14	+72	14.7
/ 162G	—	A+C		—	650	587	143	28	3	19	45	160	12	21	7	244	311	399	709	155	300	25	7	314	94	-1	+2	+10	+3	+14	2.9
Career	—	MLE		—	4906	4470	1070	191	23	149	296	1289	99	163	65	239	301	392	694	153	300	26	6	307	94	-4	+8	+54	+15	+74	15.0
/ 162G	—	MLE		—	650	592	142	25	3	20	39	171	13	22	9	240	301	394	695	154	300	26	6	307	94	-1	+2	+10	+3	+14	2.8

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 AAASacramento River Cats · 23 PAwOBA .404 → .303 (−101)K% 21.7% → 26.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.74%	÷1.000	×1.200	—	—	26.09%
BB% (unintentional) /PA	13.04%	÷1.000	×0.690	—	×0.952	8.57%
HBP% /PA	8.70%	—	×0.940	—	×0.952	7.78%
Singles /BIP	15.38%	÷1.000	×0.930	—	×0.952	13.62%
Doubles /BIP	0.00%	÷1.000	×0.830	—	×0.952	0.00%
Triples /BIP	0.00%	÷1.000	×0.970	—	×0.952	0.00%
Home runs /BIP	15.38%	÷1.000	×0.700	—	×0.952	10.25%

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 32 vs a level average of 27.2 → −4.8% on BB/HBP/hit rates (4.8 yr older than average).

Result: wOBA .404 → .303; ISO .333 → .226; BABIP .182 → .152. 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 AAAScranton/Wilkes-Barre RailRiders · 21 PAwOBA .150 → .117 (−33)K% 14.3% → 17.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.29%	÷0.998	×1.200	—	—	17.18%
BB% (unintentional) /PA	9.52%	÷1.059	×0.690	—	×0.982	6.09%
HBP% /PA	0.00%	—	×0.940	—	×0.982	0.00%
Singles /BIP	12.50%	÷1.029	×0.930	—	×0.982	11.09%
Doubles /BIP	0.00%	÷0.903	×0.830	—	×0.982	0.00%
Triples /BIP	0.00%	÷1.048	×0.970	—	×0.982	0.00%
Home runs /BIP	0.00%	÷1.017	×0.700	—	×0.982	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 103, 1B 106, 2B 81, 3B 110, K 100, BB 112 — applied at half strength. Age: age 29 vs a level average of 27.2 → −1.8% on BB/HBP/hit rates (1.8 yr older than average).

Result: wOBA .150 → .117; ISO .000 → .000; BABIP .125 → .111. 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 AASomerset Patriots · 18 PAwOBA .167 → .139 (−28)K% 27.8% → 33.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.78%	÷1.006	×1.220	—	—	33.68%
BB% (unintentional) /PA	0.00%	÷0.973	×0.700	—	×0.958	0.00%
HBP% /PA	0.00%	—	×0.850	—	×0.958	0.00%
Singles /BIP	15.38%	÷0.987	×0.970	—	×0.958	14.48%
Doubles /BIP	7.69%	÷0.958	×0.860	—	×0.958	6.62%
Triples /BIP	0.00%	÷0.900	×0.950	—	×0.958	0.00%
Home runs /BIP	0.00%	÷1.033	×0.780	—	×0.958	0.00%

Factors used: league row EL. Park (home-season share, regressed): HR 107, 1B 97, 2B 92, 3B 80, K 101, BB 95 — applied at half strength. Age: age 29 vs a level average of 24.8 → −4.2% on BB/HBP/hit rates (4.2 yr older than average).

Result: wOBA .167 → .139; ISO .056 → .044; BABIP .231 → .211. 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 AASomerset Patriots · 23 PAwOBA .370 → .307 (−63)K% 13.0% → 16.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.04%	÷0.998	×1.220	—	—	15.95%
BB% (unintentional) /PA	8.70%	÷0.985	×0.700	—	×0.968	5.98%
HBP% /PA	0.00%	—	×0.850	—	×0.968	0.00%
Singles /BIP	16.67%	÷0.983	×0.970	—	×0.968	15.92%
Doubles /BIP	11.11%	÷0.972	×0.860	—	×0.968	9.51%
Triples /BIP	0.00%	÷0.969	×0.950	—	×0.968	0.00%
Home runs /BIP	5.56%	÷1.032	×0.780	—	×0.968	4.07%

Factors used: league row EL. Park (home-season share, regressed): HR 106, 1B 97, 2B 94, 3B 94, K 100, BB 97 — applied at half strength. Age: age 28 vs a level average of 24.8 → −3.2% on BB/HBP/hit rates (3.2 yr older than average).

Result: wOBA .370 → .307; ISO .238 → .186; BABIP .294 → .265. 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 AAAMemphis Redbirds · 75 PAwOBA .466 → .380 (−86)K% 21.3% → 27.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.33%	÷0.986	×1.290	—	—	27.92%
BB% (unintentional) /PA	10.67%	÷1.035	×0.710	—	×1.033	7.56%
HBP% /PA	5.33%	—	×0.980	—	×1.033	5.40%
Singles /BIP	21.28%	÷1.014	×0.900	—	×1.033	19.51%
Doubles /BIP	6.38%	÷0.917	×0.810	—	×1.033	5.83%
Triples /BIP	0.00%	÷0.900	×0.810	—	×1.033	0.00%
Home runs /BIP	14.89%	÷0.982	×0.780	—	×1.033	12.21%

Factors used: league row PCL. Park (home-season share, regressed): HR 96, 1B 103, 2B 83, 3B 80, K 97, BB 107 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average).

Result: wOBA .466 → .380; ISO .381 → .299; BABIP .325 → .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).

2017 AAAMemphis Redbirds · 479 PAwOBA .352 → .286 (−66)K% 24.6% → 31.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.63%	÷1.010	×1.290	—	—	31.47%
BB% (unintentional) /PA	7.10%	÷0.997	×0.710	—	×1.050	5.31%
HBP% /PA	2.09%	—	×0.980	—	×1.050	2.15%
Singles /BIP	26.52%	÷1.001	×0.900	×0.964	×1.050	24.13%
Doubles /BIP	5.75%	÷1.021	×0.810	×0.964	×1.050	4.62%
Triples /BIP	0.32%	÷1.135	×0.810	×0.964	×1.050	0.23%
Home runs /BIP	6.39%	÷0.980	×0.780	—	×1.050	5.34%

Factors used: league row PCL. Park (home-season share, regressed): HR 96, 1B 100, 2B 104, 3B 127, K 102, BB 99 — applied at half strength. Age: age 23 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (4.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.964.

Result: wOBA .352 → .286; ISO .186 → .143; BABIP .345 → .303. 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 AASpringfield Cardinals · 356 PAwOBA .365 → .313 (−52)K% 26.1% → 31.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.12%	÷1.019	×1.220	—	—	31.26%
BB% (unintentional) /PA	7.02%	÷0.999	×0.700	—	×1.042	5.13%
HBP% /PA	2.81%	—	×0.870	—	×1.042	2.55%
Singles /BIP	25.78%	÷0.966	×0.920	×1.008	×1.042	25.80%
Doubles /BIP	5.33%	÷0.986	×0.840	×1.008	×1.042	4.77%
Triples /BIP	1.78%	÷0.900	×0.940	×1.008	×1.042	1.95%
Home runs /BIP	7.11%	÷1.155	×0.800	—	×1.042	5.13%

Factors used: league row TL. Park (home-season share, regressed): HR 131, 1B 93, 2B 97, 3B 80, K 104, BB 100 — 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 ×1.008.

Result: wOBA .365 → .313; ISO .214 → .165; BABIP .349 → .338. 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 AAAMemphis Redbirds · 161 PAwOBA .288 → .243 (−44)K% 23.6% → 30.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.60%	÷0.988	×1.290	—	—	30.81%
BB% (unintentional) /PA	6.83%	÷0.983	×0.710	—	×1.050	5.18%
HBP% /PA	1.86%	—	×0.980	—	×1.050	1.92%
Singles /BIP	21.10%	÷0.989	×0.900	×1.002	×1.050	20.20%
Doubles /BIP	6.42%	÷0.941	×0.810	×1.002	×1.050	5.82%
Triples /BIP	0.92%	÷0.951	×0.810	×1.002	×1.050	0.82%
Home runs /BIP	2.75%	÷0.931	×0.780	—	×1.050	2.42%

Factors used: league row PCL. Park (home-season share, regressed): HR 86, 1B 98, 2B 88, 3B 90, K 98, BB 97 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.002.

Result: wOBA .288 → .243; ISO .122 → .100; BABIP .292 → .275. 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).

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Franklin Gutierrezlast yr '17 career totals — 11 seasons, 3,333 PA	5.0	3,333	97	78	257	311	408	-10	+73	16.9	16.7
/162	664	19	16	-2.1	+14.5	3.4	pk7: 16
#2Cesar Geronimo'69-'83 * career totals — 13 seasons, 4,229 PA	6.4	4,229	51	82	254*	321*	398*	+2	+52	16.8	16.5
/162	664	8	13	+0.2	+8.2	2.6	pk7: 16
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 12 projected seasons	5.2	3,449	103	110	244	307	400	+10	+70	10.5	10.3
/162	664	20	21	+1.9	+13.5	2.0	pk7: 10
#3Manuel Margotlast yr '24 career totals — 8 seasons, 3,154 PA	4.8	3,154	56	94	254	307	380	-5	+27	8.4	8.8
/162	664	12	20	-1.1	+5.6	1.8	pk7: 9
#4Peter Bourjoslast yr '17 career totals — 8 seasons, 2,241 PA	3.4	2,241	42	66	241	298	382	-0	+38	7.4	7.5
/162	664	12	20	-0.1	+11.3	2.2	pk7: 8
#5Darrin Jackson'85-'99 * career totals — 10 seasons, 2,816 PA	4.2	2,816	80	43	252*	290*	420*	-7	+21	6.2	7.4
/162	664	19	10	-1.7	+5.0	1.5	pk7: 9
#6Bob Dernier'80-'89 * career totals — 8 seasons, 2,757 PA	4.2	2,757	23	218	253*	317*	360*	+2	+22	6.7	7.2
/162	664	6	53	+0.6	+5.3	1.6	pk7: 8

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
Harrison Bader (OGILVIE)	33	45	50	60	40	237/300/402	165	291	4	3	26%	6%	98	+0.3	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Michael A. Taylor 2024 · MLB	33	46→54	52→55	51→60	43	238/296/400	161	303	22	14	29%	7%	95	+1.0	212/271/361	149	296	17	17	33%	7%	77	-0.3	191/251/321	130	276	14	19	34%	7%	61	-0.8
✕Darnell McDonald 2012 · MLB	33	49→55	51→55	49→55	47	250/307/418	168	296	18	12	22%	7%	103	+1.6	210/272/327	117	256	12	10	22%	7%	70	-0.9	186/247/276	90	230	8	9	22%	7%	47	-1.3
✕John Hicks 2023 · MLB	33	40→50	53→55	49→50	35	216/253/385	169	288	21	13	33%	4%	76	-0.4	204/256/330	126	288	13	17	32%	6%	64	-1.3	155/214/229	73	228	6	27	33%	6%	25	-1.4
✕Brooks Conrad 2012 · MLB	32	45→43	52→55	53→50	46	232/302/400	169	296	20	13	28%	8%	98	+1.2	222/284/417	195	294	25	5	32%	8%	95	+1.0	180/239/337	157	233	21	1	32%	6%	60	-0.9
✕Mark Little 2006 · MLB	34	42	51→55	52→55	40	219/289/380	161	284	19	19	30%	6%	89	+0.5	226/308/346	120	311	11	15	29%	7%	88	+0.5	221/318/307	86	323	4	13	29%	6%	80	-0.1
✕Chad Huffman 2017 · AAA	32	46→52	51→50	49→45	48	235/311/404	169	276	18	12	22%	8%	102	+1.5	219/295/367	148	273	16	6	25%	7%	88	+0.4	202/282/340	138	254	15	1	26%	7%	73	-0.3
✕Kevan Smith 2021 · MLB	33	51→54	47→50	49→40	50	252/320/389	137	288	14	7	18%	8%	101	+1.4	221/287/336	115	291	11	8	26%	8%	77	-0.3	162/217/192	30	235	0	0	29%	7%	17	-0.8
✕Cody Ransom 2009 · MLB	33	38→39	53→55	48→50	44	206/269/380	173	255	22	11	29%	7%	81	-0.1	212/273/380	168	268	20	10	28%	7%	82	+0.0	206/286/402	196	277	25	6	34%	9%	92	+0.4
✕Curt Casali 2022 · MLB	33	45	51→50	49→30	51	229/317/393	164	294	19	5	28%	10%	102	+1.5	218/314/337	119	290	12	4	27%	11%	88	+0.5	207/312/292	85	276	8	0	25%	11%	77	-0.1
✕Adonis García 2019 · MLB	34	51→54	48→50	49→50	44	254/296/393	138	277	16	9	16%	4%	93	+0.8	214/271/329	115	258	13	14	22%	6%	70	-0.9	181/235/262	81	221	9	16	22%	4%	39	-1.3
✕Kevin Pillar 2022 · MLB	33	48→58	54→55	47→55	41	252/293/428	177	280	22	10	20%	4%	101	+1.4	239/290/418	179	271	22	11	21%	5%	97	+1.1	231/282/403	173	262	21	15	21%	5%	92	+0.3
●Michael Tucker 2004 · MLB	33	50→51	50→55	50→55	52	250/319/413	164	291	16	17	20%	9%	106	+1.8	242/325/387	145	284	13	10	19%	11%	103	+1.5	233/326/364	131	273	11	9	18%	11%	98	+0.8
✕Mario Valenzuela 2010 · AAA	33	53→57	50→55	50→40	43	268/305/419	150	303	19	10	19%	4%	103	+1.5	261/311/427	166	299	21	6	20%	6%	107	+1.9	263/316/431	167	299	22	2	20%	6%	108	+1.1
✕Hector Luna 2012 · MLB	32	47→49	50→55	49→50	47	242/295/391	149	273	18	8	19%	6%	93	+0.8	236/282/372	136	276	15	8	20%	6%	83	+0.1	237/275/366	129	275	14	3	19%	4%	77	-0.2
✕Tim Beckham 2022 · MLB	32	44→54	54→55	45→50	41	231/279/407	176	294	22	6	29%	6%	91	+0.6	253/306/387	134	334	16	9	28%	6%	96	+1.0	302/351/401	100	411	13	6	28%	5%	109	+0.6
✕Fernando Tatis 2009 · MLB	34	47→52	52→55	47→45	48	241/305/410	169	278	20	7	21%	8%	101	+1.4	250/310/410	160	287	17	7	19%	7%	103	+1.5	273/327/425	151	304	13	6	14%	5%	113	+1.4
✕J.C. Linares 2017 · AAA	32	48→53	47→50	51→40	48	237/306/379	142	286	14	9	22%	8%	94	+0.9	224/288/356	132	260	14	10	19%	8%	82	-0.0	201/271/326	125	212	16	3	14%	8%	68	-0.3
✕Ian Desmond 2019 · MLB	33	48→58	49→60	53→55	47	243/306/388	145	294	17	19	24%	8%	96	+1.0	239/299/417	178	290	20	10	24%	8%	101	+1.4	239/294/437	199	286	22	4	25%	7%	105	+1.3
✕Hernán Pérez 2024 · MLB	33	45→55	45→50	54→55	42	226/273/344	118	287	13	21	26%	6%	73	-0.6	206/254/330	124	263	14	13	27%	6%	63	-1.3	165/208/277	113	202	13	9	26%	5%	32	-1.8
✕Miguel Olivo 2012 · MLB	34	45→50	54→60	45→50	38	236/272/409	172	291	23	8	28%	5%	88	+0.5	234/266/399	165	293	22	6	28%	4%	84	+0.1	230/263/370	140	302	17	9	29%	4%	74	-0.3

Harrison Bader

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps