Tanner Mally

OF San Jose Giants

Age 22 R/R A HR -15%H -3% Svc 0.0 · Ctrl thru 2037

Overview

APROSPECTMiLBFA 2038

ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2026	21	ASF	107	.383/.528/.494	0	8	158	—	.356/.472/.460
2027PROJ0% MLB	22	MLBSF	217	.221/.304/.321	3	7	79	0.0
2028PROJ34% MLB	23	MLBSF	67	.220/.303/.323	1	2	82	0.0
2029PROJ46% MLB	24	MLBSF	140	.222/.305/.330	2	5	85	0.0

Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2037Service0.0First FA2038

2027MiLB2028MiLB2029MiLB2030MiLB2031MiLB2032Pre-Arb$0.9M2033Pre-Arb$0.9M2034Pre-Arb$1.0M+3

Skills · percentileMiLB Statcast 2026 A

wOBA99

wRC+98

Chase%95

Speed94

BB%91

K%89

Career WAR0 WAR median (P10 -0 / P90 3, comp-based) · star 3% · didn't stick 86%

CompsDarnell Sweeney (age 22) · Troy Stokes Jr. (age 21) · Corey Julks (age 23)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 108 proj PA

wRC+†79

AVG/OBP/SLG.219 / .302 / .318

PA108

HR1

K%26

BB%9

ISO100

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$0M ctrl surplus

Tools · Contract

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

Status MiLB

MLB Debut 2032

Service 0 yrs (est)

Team Control Through 2037

First FA Year 2038

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2032
2028	MiLB	still in minors · estimated debut 2032
2029	MiLB	still in minors · estimated debut 2032
2030	MiLB	still in minors · estimated debut 2032
2031	MiLB	still in minors · estimated debut 2032
2032	Pre-Arb	$0.9M	+0.1	$0.3M	+$0.0M (cut)
2033	Pre-Arb	$0.9M	+0.1	$0.3M	+$0.0M (cut)
2034	Pre-Arb	$1.0M	—	—	—
2035	Arb-1	$0.2M	—	—	—
2036	Ext	beyond projection horizon · no WAR estimate
2037	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$-0.1M	+$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 = actual YTD + projected ROS + total. 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)
2026	21	A	San Jose Giants	—	107	81	31	3	3	0	20	16	5	8	1	383	528	494	1.022	111	470	15	19	457	158	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2026	21	A MLE	San Jose Giants	—	107	87	31	3	3	0	14	22	5	8	1	356	472	460	931	103	449	21	13	401	158	—	—	—	—	—	—
2026	21	A MLE	San Jose Giants	—	107	87	31	3	3	0	14	22	5	8	1	356	472	460	931	103	470	21	13	401	158	—	—	—	—	—	—
2026	21	A RAW	San Jose Giants	—	107	81	31	3	3	0	20	16	5	8	1	383	528	494	1.022	111	470	15	19	457	158	—	—	—	—	—	—
2026	21	A MLE	San Jose Giants	—	107	87	31	3	3	0	14	22	5	8	1	356	472	460	931	103	449	21	13	401	158	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2026	21	A MLE	San Jose Giants	—	107	87	31	3	3	0	14	22	5	8	1	356	472	460	931	103	449	21	13	401	158	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	SF	0%	217	192	43	6	3	3	19	55	4	7	1	221	304	321	625	100	292	25	9	285	79	-5	+1	+0	-1	+5	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	SF	34%	194	172	38	5	2	3	17	49	3	7	1	224	307	330	637	106	293	25	9	290	82	-4	+1	+0	-1	+4	-0.0
2029	24	MLB MLE	SF	46%	303	268	61	9	3	5	27	76	5	11	2	226	309	338	647	112	294	25	9	293	85	-6	+1	+0	-2	+7	0.1
2030	25	MLB MLE	SF	52%	368	326	74	11	4	6	33	92	6	13	2	228	310	344	654	116	294	25	9	296	87	-6	+2	+0	-2	+8	0.2
2031	26	MLB MLE	SF	54%	410	364	82	12	4	7	36	102	7	15	3	229	310	348	659	119	294	25	9	298	88	-6	+2	+0	-2	+9	0.2
2032	27	MLB MLE	SF	54%	430	382	87	13	4	8	38	107	7	16	3	229	310	349	659	120	293	25	9	298	88	-6	+2	+0	-3	+9	0.2
2033	28	MLB MLE	SF	54%	439	390	89	13	5	8	39	110	7	15	3	227	308	344	652	117	292	25	9	295	86	-7	+2	-1	-3	+10	0.1
2034	29	MLB MLE	SF	53%	437	389	87	13	4	8	38	111	7	15	3	224	305	337	642	113	291	25	9	291	83	-9	+2	-1	-3	+9	-0.1
2035	30	MLB MLE	SF	52%	432	385	84	12	4	7	38	111	6	15	3	221	301	329	631	108	289	26	9	287	80	-10	+2	-2	-3	+9	-0.4
2028	23	MLB CTX	SF	34%	67	60	14	2	1	1	6	17	1	2	0	220	303	323	626	103	289	25	9	285	82	-1	+0	+0	-0	+1	0.0
2029	24	MLB CTX	SF	46%	140	125	28	4	2	2	12	35	2	5	1	222	305	330	635	107	290	25	9	289	85	-3	+1	+0	-1	+3	0.0
2030	25	MLB CTX	SF	52%	190	168	38	6	2	3	17	47	3	7	1	224	306	335	642	111	290	25	9	291	87	-3	+1	+0	-1	+4	0.1
2031	26	MLB CTX	SF	54%	222	196	45	7	2	4	20	55	4	8	1	225	307	340	646	115	290	25	9	293	88	-3	+1	+0	-1	+5	0.1
2032	27	MLB CTX	SF	54%	233	206	46	7	2	4	21	58	4	8	1	225	306	340	646	115	289	25	9	293	88	-3	+1	+0	-1	+5	0.1
2033	28	MLB CTX	SF	54%	238	211	47	7	2	4	21	60	4	8	1	223	304	335	640	112	288	25	9	290	86	-4	+1	-0	-1	+5	0.1
2034	29	MLB CTX	SF	53%	232	206	46	7	2	4	20	59	4	8	1	220	302	329	631	109	287	25	9	287	83	-5	+1	-1	-1	+5	-0.1
2035	30	MLB CTX	SF	52%	226	201	43	6	2	3	20	58	3	8	1	217	298	321	619	104	285	26	9	282	80	-5	+1	-1	-1	+5	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1548	1373	307	46	15	25	137	389	25	54	7	224	306	334	639	110	292	25	9	289	87	-28	+8	-2	-9	+34	0.2
/ 162G	—	A+C		—	650	577	128	19	6	10	58	163	10	23	3	222	304	328	632	106	290	25	9	289	87	-12	+3	-1	-4	+14	0.1
Career	—	MLE		—	3228	2858	654	94	34	53	290	808	55	119	22	229	312	341	653	112	298	25	9	297	87	-57	+14	-4	-19	+68	0.2
/ 162G	—	MLE		—	650	575	132	19	7	11	58	163	11	24	4	230	312	344	656	115	300	25	9	297	87	-12	+3	-1	-4	+14	0.0

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Willie Harrislast yr '11 career totals — 10 seasons, 2,743 PA	4.1	2,743	39	106	241	331	351	-11	-2	5.3	6.2
/162	664	9	26	-2.7	-0.5	1.3	pk7: 7
#2Michael Saunderslast yr '17 career totals — 8 seasons, 2,711 PA	4.1	2,711	81	55	233	305	399	-12	-13	4.1	4.5
/162	664	20	13	-2.9	-3.2	1.0	pk7: 5
#3Jake Powell'30-'45 * career totals — 8 seasons, 2,767 PA	4.2	2,767	22	65	248*	294*	373*	-14	-2	0.2	2.0
/162	664	5	16	-3.3	-0.5	0.0	pk7: 4
#4Eric Young Jr.last yr '18 career totals — 9 seasons, 1,925 PA	2.9	1,925	13	161	245	312	332	-11	-8	1.2	1.6
/162	664	4	56	-3.9	-2.7	0.4	pk7: 2
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 5 projected seasons	2.5	1,657	28	58	227	305	341	-10	+0	1.2	1.2
/162	664	11	23	-4.0	+0.0	0.5	pk7: 1
#5James Mouton'94-'01 * career totals — 8 seasons, 1,795 PA	2.7	1,795	18	109	235*	314*	329*	-11	-0	0.7	1.0
/162	664	7	40	-4.2	-0.1	0.3	pk7: 1
#6Eric Owens'95-'03 * career totals — 7 seasons, 2,576 PA	3.9	2,576	26	126	253*	303*	334*	-18	+1	-0.9	0.4
/162	664	7	32	-4.5	+0.2	-0.2	pk7: 2

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
Tanner Mally (OGILVIE)	22	—	—	—	—	219/302/318	99	292	1	4	26%	9%	79	-0.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Darnell Sweeney 2013 · A	22	49→51	41→50	58→55	46	236/292/339	103	298	8	21	23%	7%	79	-0.2	232/286/361	129	319	10	22	29%	7%	82	-0.0	230/286/363	133	314	11	23	29%	7%	80	-0.1
✕Troy Stokes Jr. 2017 · A	21	44→40	39→50	55	45	212/283/303	91	280	6	19	25%	7%	68	-1.0	207/280/342	135	279	13	18	29%	8%	76	-0.4	195/275/337	142	264	15	19	30%	8%	71	-0.6
✕Corey Julks 2019 · A	23	46→50	43→50	52→55	43	222/280/337	115	306	10	18	30%	7%	74	-0.5	214/275/320	106	297	9	13	29%	7%	68	-1.0	231/290/385	154	289	18	21	26%	7%	87	+0.3
✕Ryan Vilade 2021 · A	22	48→54	41→50	51→50	46	233/291/336	103	297	8	13	24%	7%	78	-0.3	232/291/324	92	302	6	11	23%	7%	75	-0.5	227/293/385	158	282	18	14	26%	7%	89	+0.4
✕Phillip Ervin 2015 · A	23	42→51	43→50	56→55	43	208/262/325	118	265	9	16	25%	6%	65	-1.2	211/283/329	118	266	11	24	24%	8%	74	-0.5	240/304/385	144	304	14	21	24%	7%	93	+0.6
✕Albertson Asigen 2024 · A	22	48	37→40	56→55	48	223/301/297	74	312	3	19	27%	9%	73	-0.6	211/293/300	89	335	7	20	35%	9%	72	-0.7	189/281/275	86	310	8	25	38%	9%	59	-0.6
✕Alexis Hernandez 2024 · A	21	44→50	39→50	52→50	48	209/282/296	87	276	7	15	26%	8%	66	-1.1	216/289/327	111	296	11	18	29%	8%	76	-0.4	220/295/346	126	292	14	18	28%	8%	80	-0.1
✕David Kandilas 2014 · A	23	45→44	39→45	55	45	215/275/304	90	283	7	19	26%	7%	65	-1.2	210/271/308	98	277	7	16	25%	7%	64	-1.3	195/259/302	107	251	7	17	24%	6%	56	-1.2
✕Tyler Goeddel 2014 · A	21	44→52	41→45	59→55	40	211/262/313	103	297	7	20	30%	6%	61	-1.5	227/284/341	114	305	9	18	27%	7%	76	-0.4	229/290/345	116	300	9	18	25%	7%	78	-0.2
✕Stuart Fairchild 2019 · A	23	44→43	40→50	53→55	40	211/273/310	98	303	7	14	31%	6%	65	-1.2	218/286/346	128	290	12	10	27%	7%	79	-0.2	222/308/380	158	297	16	16	29%	8%	94	+0.5
✕Adam Engel 2014 · A	22	46→48	38→50	55→60	44	220/277/302	81	268	5	22	19%	5%	65	-1.2	210/263/302	92	299	6	30	30%	6%	59	-1.6	223/282/358	135	299	13	23	29%	5%	79	-0.1
✕Wes Rogers 2015 · A	21	45→51	41→40	57→65	42	217/270/314	97	294	8	18	28%	6%	65	-1.2	225/283/314	89	299	5	34	25%	7%	70	-0.9	229/287/320	92	301	5	42	24%	7%	70	-0.7
✕Joey Rickard 2014 · A	23	46→56	41→45	52→55	48	219/300/322	104	288	7	16	25%	8%	79	-0.2	243/317/336	93	310	5	16	21%	9%	88	+0.4	260/325/362	103	324	6	16	20%	8%	95	+0.6
✕Charcer Burks 2017 · A	22	41→48	40	52→50	44	200/267/293	93	278	6	17	29%	7%	59	-1.6	209/281/303	94	291	7	14	28%	8%	68	-1.0	205/279/290	85	284	6	14	28%	8%	62	-1.2
✕Cade Gotta 2015 · A	23	40→50	39→45	54→55	46	193/267/282	90	272	5	16	29%	8%	57	-1.8	217/266/317	100	285	7	21	25%	6%	64	-1.3	240/299/336	96	305	5	36	21%	7%	79	-0.1
✕Angel Aponte 2022 · A	22	45	40	55	39	215/275/308	93	307	7	20	31%	6%	66	-1.1	201/254/295	94	292	8	19	32%	5%	55	-1.9	180/231/267	87	261	8	23	33%	5%	38	-1.2
✕Kristopher Negrón 2008 · A	22	43→49	37→45	55	43	204/269/274	70	275	4	18	26%	6%	56	-1.9	226/287/322	96	290	7	20	23%	6%	74	-0.6	231/294/333	102	293	8	23	23%	6%	76	-0.4
✕Daz Cameron 2018 · A	21	42→48	45→50	53→55	40	206/268/336	130	291	12	19	32%	6%	70	-0.8	209/279/335	126	306	11	17	33%	7%	74	-0.5	227/297/394	166	289	18	26	27%	8%	92	+0.3
✕Alerick Soularie 2022 · A	23	43	42→45	54→60	45	206/285/309	103	308	10	15	34%	9%	70	-0.8	197/279/312	115	290	12	22	34%	9%	70	-0.9	181/270/293	112	261	13	29	33%	9%	60	-0.7
✕Wenceel Pérez 2022 · A	22	45→49	38→55	55	44	217/269/302	86	282	5	15	24%	6%	61	-1.5	236/296/374	138	290	12	17	22%	7%	88	+0.5	237/301/388	150	285	13	19	21%	8%	92	+0.6

Tanner Mally

Career Stats + Projections

Career Comps

Career Path Comps