Fernando Gonzalez

C San Jose Giants

Age 25 R/R 5'10" / 205 lbs A HR -15%H -3% Svc 0.0 · Ctrl thru 2037

Overview

APROSPECTMiLBFA 2038

OGV OFP35OGV rank#903ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2025	23	ASF	114	.229/.351/.375	3	0	39	—	.158/.254/.248
2026	24	AAA/A/ROKSF	218	.247/.388/.362	4	1	75	—	.217/.323/.322
2027PROJMLE	25	MLBSF	268	.228/.311/.345	5	4	88	0.5
2028PROJ38% MLB	26	MLBSF	75	.225/.308/.340	1	1	88	0.2
2029PROJ52% MLB	27	MLBSF	122	.224/.308/.340	2	2	88	0.4

Next 3 projected WAR 1.1Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2037Service0.0First FA2038

2027MiLB2028MiLB2029MiLB2030MiLB2031MiLB2032Pre-Arb$0.9M2033Pre-Arb$0.9M2034Ext$1.0M+3

Skills · percentileMiLB Statcast 2026 A

K%99

Whiff%92

Z-Con%90

BB%47

Chase%45

wOBA36

Career WAR0.0 WAR median (P10 0.0 / P90 0.2, comp-based) · star 0% · didn't stick 96%

CompsBlake Swihart (age 25) · Ryan Adams (age 25) · Patrick Frick (age 25)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 144 proj PA

wRC+†88

AVG/OBP/SLG.226 / .309 / .342

PA144

HR3

K%25

BB%9

ISO118

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$10M ctrl surplus

Tools · ContractCON 59 / POW 36

Toolsscout grade

CONTACT59

scouting grade only

POWER36

scouting grade only

EYE49

scouting grade only

SPEED43

scouting grade only

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	+0.2	$0.5M	+$0.0M
2033	Pre-Arb	$0.9M	+0.1	$0.3M	+$0.0M (cut)
2034	Ext	beyond projection horizon · no WAR estimate
2035	Ext	beyond projection horizon · no WAR estimate
2036	Ext	beyond projection horizon · no WAR estimate
2037	Ext	beyond projection horizon · no WAR estimate
Totals		$0.9M		$0.8M	+$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. Catcher framing: only 2027 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run 1-3 WAR low.

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)
2025	23	A	San Jose Giants	—	114	96	22	5	0	3	14	22	4	0	0	229	351	375	726	146	268	19	12	334	39	—	—	—	—	—	—
2026	24	AAA	Sacramento River Cats	—	34	25	7	0	1	1	6	11	1	0	0	280	438	480	917	200	462	32	18	387	119	—	—	—	—	—	—
2026	24	A	San Jose Giants	—	168	138	32	4	0	2	20	14	8	1	0	232	361	304	666	72	242	8	12	313	57	—	—	—	—	—	—
2026	24	ROK	ACL Giants	—	16	11	4	2	0	1	4	1	1	0	0	364	562	818	1.381	455	333	6	25	567	164	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2025	23	A MLE	San Jose Giants	—	114	101	16	3	0	2	9	31	4	0	0	158	254	248	502	89	212	27	8	226	39	—	—	—	—	—	—
2026	24	AAA MLE	Sacramento River Cats	—	34	27	7	0	1	1	4	13	1	0	0	259	375	444	819	185	437	38	12	344	119	—	—	—	—	—	—
2026	24	A MLE	San Jose Giants	—	168	145	29	3	0	2	13	19	8	1	0	200	301	262	563	62	210	11	8	253	57	—	—	—	—	—	—
2026	24	ROK MLE	ACL Giants	—	16	13	4	2	0	1	2	1	1	0	0	308	438	692	1.130	385	231	6	12	410	164	—	—	—	—	—	—
2025	23	A MLE	San Jose Giants	—	114	101	16	3	0	2	9	31	4	0	0	158	254	248	502	89	206	27	8	226	39	—	—	—	—	—	—
2025	23	A RAW	San Jose Giants	—	114	96	22	5	0	3	14	22	4	0	0	229	351	375	726	146	268	19	12	334	39	—	—	—	—	—	—
2026	24	A MLE	3 teams	—	218	184	39	5	1	3	20	34	10	1	0	212	322	299	621	87	242	16	9	279	75	—	—	—	—	—	—
2026	24	A RAW	3 teams	—	218	174	43	6	1	4	30	26	10	1	0	247	388	362	750	115	267	12	14	343	75	—	—	—	—	—	—
2025	23	A MLE	San Jose Giants	—	114	100	16	3	0	2	9	31	4	0	0	160	254	250	504	90	212	27	8	226	39	—	—	—	—	—	—
2026	24	A MLE	3 teams	—	218	186	39	5	1	3	20	34	10	1	0	210	322	296	618	86	247	16	9	279	75	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2025	23	A MLE	San Jose Giants	—	114	100	16	3	0	2	9	31	4	0	0	160	254	250	504	90	212	27	8	226	39	—	—	—	—	—	—
2026	24	A MLE	3 teams	—	218	186	39	5	1	3	20	34	10	1	0	210	322	296	618	86	247	16	9	279	75	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	25	MLB MLE	SF	0%	268	237	54	9	2	5	24	67	5	4	1	228	311	345	656	118	294	25	9	298	88	-4	+0	+0	+5	+6	0.5
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	26	MLB MLE	SF	38%	200	177	40	7	1	4	18	50	3	3	1	228	312	348	660	120	293	25	9	299	88	-3	+0	+0	+4	+4	0.5
2029	27	MLB MLE	SF	52%	235	208	48	8	2	5	21	59	4	3	1	228	311	349	660	121	293	25	9	299	88	-3	+0	+0	+4	+5	0.6
2030	28	MLB MLE	SF	60%	261	232	53	9	2	5	23	65	4	3	1	227	310	347	657	120	292	25	9	297	87	-4	+0	-1	+5	+6	0.6
2031	29	MLB MLE	SF	62%	266	236	53	9	2	5	24	67	4	2	1	226	307	344	651	118	290	25	9	295	86	-5	+0	-1	+5	+6	0.5
2032	30	MLB MLE	SF	63%	271	241	55	10	2	5	24	69	4	1	1	224	304	339	644	115	289	25	9	292	84	-5	-0	-2	+5	+6	0.3
2033	31	MLB MLE	SF	63%	244	218	47	8	1	4	21	63	3	1	0	220	300	329	629	110	286	26	9	286	80	-6	+0	-3	+4	+5	0.1
2028	26	MLB CTX	SF	38%	75	67	14	3	0	1	7	19	1	1	0	225	308	340	648	115	289	25	9	294	88	-1	+0	+0	+1	+2	0.2
2029	27	MLB CTX	SF	52%	122	108	24	4	1	2	11	30	2	2	0	224	308	340	647	116	289	25	9	294	88	-2	+0	+0	+2	+3	0.4
2030	28	MLB CTX	SF	60%	156	139	32	6	1	3	14	39	2	2	1	223	306	338	644	115	288	25	9	292	87	-2	+0	-0	+3	+3	0.3
2031	29	MLB CTX	SF	62%	164	145	33	6	1	3	15	41	3	1	0	222	304	335	639	113	287	25	9	290	86	-3	+0	-1	+3	+4	0.3
2032	30	MLB CTX	SF	63%	170	151	33	6	1	3	15	43	2	1	0	220	301	331	632	111	285	25	9	287	84	-3	+0	-1	+3	+4	0.2
2033	31	MLB CTX	SF	63%	155	138	30	5	1	3	14	40	2	1	0	216	296	321	617	105	282	26	9	281	80	-4	+0	-2	+3	+3	0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	842	748	166	30	5	15	76	212	12	8	1	222	304	336	639	114	287	25	9	289	82	-15	+1	-4	+15	+18	1.5
/ 162G	—	A+C		—	650	577	129	23	4	12	59	164	9	6	1	224	305	340	645	116	289	25	9	289	82	-12	+1	-3	+12	+14	1.2
Career	—	MLE		—	1953	1725	380	64	12	36	173	474	38	16	6	220	305	334	639	114	281	24	9	289	82	-28	+1	-7	+29	+35	3.0
/ 162G	—	MLE		—	650	574	126	21	4	12	58	158	13	5	2	220	306	333	639	113	280	24	9	289	82	-11	+0	-3	+12	+14	1.2

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 ASan Jose Giants · 168 PAwOBA .310 → .253 (−57)K% 8.3% → 11.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.33%	÷1.000	×1.360	—	—	11.33%
BB% (unintentional) /PA	11.90%	÷1.000	×0.690	—	×0.970	7.97%
HBP% /PA	4.76%	—	×0.780	—	×0.970	3.60%
Singles /BIP	20.97%	÷1.000	×0.920	×0.988	×0.970	18.48%
Doubles /BIP	3.23%	÷1.000	×0.830	×0.988	×0.970	2.57%
Triples /BIP	0.00%	÷1.000	×0.910	×0.988	×0.970	0.00%
Home runs /BIP	1.61%	÷1.000	×0.800	—	×0.970	1.25%

Factors used: level-wide A 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 25 vs a level average of 22.0 → −3.0% on BB/HBP/hit rates (3.0 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.988.

Result: wOBA .310 → .253; ISO .072 → .059; BABIP .242 → .210. 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).

2026 AAASacramento River Cats · 34 PAwOBA .378 → .344 (−33)K% 32.4% → 38.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	32.35%	÷1.000	×1.200	—	—	38.82%
BB% (unintentional) /PA	17.65%	÷1.000	×0.690	—	×1.033	12.58%
HBP% /PA	2.94%	—	×0.940	—	×1.033	2.86%
Singles /BIP	35.71%	÷1.000	×0.930	—	×1.033	34.31%
Doubles /BIP	0.00%	÷1.000	×0.830	—	×1.033	0.00%
Triples /BIP	7.14%	÷1.000	×0.970	—	×1.033	7.16%
Home runs /BIP	7.14%	÷1.000	×0.700	—	×1.033	5.16%

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 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average).

Result: wOBA .378 → .344; ISO .200 → .185; BABIP .462 → .437. 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).

2026 ROKACL Giants · 16 PAwOBA .553 → .410 (−144)K% 6.2% → 9.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	6.25%	÷1.000	×1.440	—	—	9.00%
BB% (unintentional) /PA	25.00%	÷1.000	×0.620	—	×0.945	14.65%
HBP% /PA	6.25%	—	×0.720	—	×0.945	4.25%
Singles /BIP	10.00%	÷1.000	×0.820	—	×0.945	7.75%
Doubles /BIP	20.00%	÷1.000	×0.720	—	×0.945	13.61%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.945	0.00%
Home runs /BIP	10.00%	÷1.000	×0.780	—	×0.945	7.37%

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 25 vs a level average of 19.5 → −5.5% on BB/HBP/hit rates (5.5 yr older than average).

Result: wOBA .553 → .410; ISO .455 → .375; BABIP .333 → .231. 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).

2025 ASan Jose Giants · 114 PAwOBA .325 → .226 (−99)K% 19.3% → 27.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.30%	÷0.962	×1.360	—	—	27.30%
BB% (unintentional) /PA	12.28%	÷1.055	×0.690	—	×0.980	7.87%
HBP% /PA	3.51%	—	×0.780	—	×0.980	2.68%
Singles /BIP	18.92%	÷1.007	×0.920	×0.950	×0.980	16.09%
Doubles /BIP	6.76%	÷1.138	×0.830	×0.950	×0.980	4.59%
Triples /BIP	0.00%	÷0.902	×0.910	×0.950	×0.980	0.00%
Home runs /BIP	4.05%	÷1.358	×0.800	—	×0.980	2.34%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 172, 1B 101, 2B 128, 3B 80, K 92, BB 111 — applied at half strength. Age: age 24 vs a level average of 22.0 → −2.0% on BB/HBP/hit rates (2.0 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .325 → .226; ISO .146 → .086; BABIP .268 → .212. 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
#1Josh Bardlast yr '11 career totals — 9 seasons, 1,958 PA	2.9	1,958	38	1	252	318	381	+33	+24	10.4	10.4
/162	664	13	0	+11.1	+8.0	3.5	pk7: 11
#2Jacob Stallingslast yr '25 career totals — 7 seasons, 1,850 PA	2.8	1,850	33	0	229	310	340	+33	+50	10.3	10.3
/162	664	12	0	+11.9	+17.9	3.7	pk7: 10
#3Curt Casalilast yr '24 career totals — 10 seasons, 1,566 PA	2.4	1,566	47	2	217	311	367	+28	+19	7.8	7.9
/162	664	20	1	+11.9	+7.9	3.3	pk7: 8
#4Scott Servais'91-'01 * career totals — 9 seasons, 2,778 PA	4.2	2,778	63	3	235*	296*	373*	+49	+0	6.5	6.9
/162	664	15	1	+11.7	+0.1	1.6	pk7: 7
#5Jake Gibbs'63-'71 * career totals — 7 seasons, 1,795 PA	2.7	1,795	25	28	244*	299*	362*	+32	+0	5.4	5.4
/162	664	9	10	+11.9	+0.0	2.0	pk7: 5
#6Jerry McNertney'64-'73 * career totals — 8 seasons, 1,605 PA	2.4	1,605	27	3	243*	301*	372*	+27	+0	4.6	4.5
/162	664	11	1	+11.2	+0.1	1.9	pk7: 4
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 4 projected seasons	1.5	986	19	9	227	305	344	+18	+16	2.8	2.8
/162	664	12	6	+11.9	+10.8	1.9	pk7: 3

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
Fernando Gonzalez (OGILVIE)	25	59	36	43	49	226/309/342	117	294	3	2	25%	9%	88	+0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Blake Swihart 2017 · MLB	25	53→54	42→45	47→45	47	256/311/365	109	321	9	8	22%	7%	92	+0.7	206/266/309	103	279	10	9	28%	7%	63	-1.4	173/238/282	110	233	14	7	31%	8%	46	-0.9
✕Ryan Adams 2012 · MLB	25	53→57	43→45	43→45	40	254/301/373	119	342	10	5	28%	5%	91	+0.6	234/288/351	117	316	9	6	27%	6%	80	-0.1	226/281/336	109	303	7	3	26%	6%	71	-0.3
✕Patrick Frick 2022 · AA	25	50→51	42→45	49→45	46	239/315/346	107	322	10	7	27%	8%	90	+0.6	220/284/293	73	300	5	7	26%	7%	66	-1.1	208/269/251	43	286	1	4	26%	6%	50	-0.9
✕Jamie Ritchie 2018 · AA	25	50→53	39→40	47→45	53	234/321/318	83	305	6	6	23%	10%	86	+0.3	236/313/333	97	310	7	6	24%	9%	86	+0.3	247/328/340	93	319	6	3	22%	9%	90	+0.3
✕Lou Marson 2010 · MLB	24	58→57	39→40	45→50	52	268/341/360	91	345	5	5	22%	10%	102	+1.5	224/304/316	92	285	6	11	21%	10%	78	-0.3	207/297/292	85	262	5	13	21%	11%	71	-0.4
✕Andrew Knapp 2018 · MLB	26	52→56	44→45	45→40	46	246/311/365	119	333	10	4	28%	8%	92	+0.7	225/312/341	116	325	10	5	30%	11%	88	+0.4	184/272/276	91	285	8	1	35%	9%	59	-0.5
✕Andre Lipcius 2023 · AAA	25	48→51	45	49→45	53	235/311/363	129	286	11	9	22%	10%	92	+0.7	232/298/362	130	288	15	7	24%	8%	87	+0.4	221/286/351	129	272	16	5	24%	7%	78	-0.3
✕Christopher Bostick 2018 · MLB	25	51→58	42→45	46→55	43	245/297/354	108	314	8	11	24%	6%	84	+0.1	235/285/353	118	310	10	8	26%	6%	80	-0.2	226/275/346	120	300	10	7	27%	5%	71	-0.6
✕Francisco Urbaez 2023 · AAA	25	50→57	41→45	47→45	48	239/302/339	101	293	7	6	20%	7%	83	+0.1	237/298/341	104	288	8	8	20%	7%	82	-0.0	243/303/350	107	288	8	7	17%	7%	85	+0.1
✕Andrew Knizner 2020 · MLB	25	50	47→50	47→40	46	251/303/379	129	282	15	5	18%	6%	93	+0.8	223/294/333	110	269	11	5	21%	7%	79	-0.2	229/296/347	118	278	13	3	22%	6%	83	+0.0
✕Andruw Monasterio 2022 · AAA	25	49→54	42→45	45→55	43	231/294/340	108	329	9	9	31%	8%	80	-0.2	238/312/344	106	317	9	17	25%	9%	88	+0.4	242/322/341	99	313	8	23	24%	9%	91	+0.4
✕Michael Garciaparra 2008 · AAA	25	52	38→40	45	48	246/319/321	75	309	6	9	21%	7%	85	+0.2	235/292/313	78	309	6	7	24%	6%	73	-0.6	237/284/304	67	314	6	3	25%	5%	64	-0.3
●James McCann 2015 · AAA	25	52→55	41→50	46→45	40	251/292/357	106	316	8	8	23%	4%	83	+0.1	248/294/379	131	311	14	4	24%	5%	89	+0.5	258/317/420	162	336	21	4	28%	7%	109	+1.1
✕Ronny Cedeno 2009 · MLB	26	54→60	44→45	46→50	45	264/306/380	116	310	11	10	19%	5%	93	+0.8	237/276/356	119	286	11	10	21%	5%	77	-0.3	244/284/355	111	301	7	7	21%	5%	80	-0.1
✕Tyler Smith 2016 · AA	25	51→54	39→40	47→50	50	242/309/332	90	305	6	9	22%	8%	84	+0.1	221/275/307	86	285	7	7	24%	6%	65	-1.2	207/257/288	81	268	7	5	24%	5%	52	-1.2
✕J.R. Towles 2009 · MLB	25	46→53	47→50	44→50	46	233/307/373	140	269	15	10	20%	6%	94	+0.9	218/299/349	131	257	13	8	20%	7%	86	+0.3	201/284/313	112	235	10	6	18%	7%	71	-0.3
✕Justin Sellers 2011 · AAA	25	49→56	42→45	45→50	49	234/299/340	105	280	8	9	19%	8%	82	+0.0	221/287/347	126	270	11	7	22%	7%	80	-0.2	211/270/313	102	252	8	4	19%	6%	65	-0.9
✕Gilberto Celestino 2024 · MLB	25	48→53	41→45	48→55	53	230/313/330	100	290	8	8	22%	10%	86	+0.3	244/311/333	89	322	7	15	24%	8%	85	+0.2	250/314/326	76	336	6	19	25%	8%	80	-0.1
✕Trey Harris 2021 · AA	25	51→53	45	47→45	43	248/303/380	132	304	12	7	22%	5%	93	+0.8	225/279/319	94	288	9	7	24%	5%	70	-0.9	219/274/299	80	285	7	7	24%	5%	61	-0.9
✕Isiah Kiner-Falefa 2021 · MLB	26	52→58	40	49→55	48	248/307/345	96	291	7	13	17%	7%	86	+0.3	259/308/346	87	297	7	19	15%	6%	86	+0.3	255/306/343	88	296	8	20	16%	6%	86	+0.2

Fernando Gonzalez

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps