Bryan Reynolds

LF Pittsburgh Pirates

Age 32 S/R 6'2" / 210 lbs MLB HR -15%K -5% Svc 7.948 · Ctrl thru 2030

Overview

MLB40-MANExtFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	29	MLBPIT	692	.275/.345/.447	24	10	125	1.7
2025	30	MLBPIT	654	.245/.320/.402	16	3	104	0.6
2026	31	MLBPIT	699	.261/.366/.424	17	9	125	2.9
2027PROJ	32	MLBPIT	571	.259/.352/.433	17	8	124	2.1
2028PROJ	33	MLBPIT	532	.250/.342/.413	15	3	116	1.0
2029PROJ	34	MLBPIT	473	.239/.330/.389	12	2	106	0.2

Last 3 seasons WAR 5.1 · Next 3 projected WAR 3.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2030Service7.948First FA2028Options2NTC

2027Ext$13M2028Ext$13M2029Ext$13M2030Ext$13M

Skills · percentileStatcast 2024-2026

xwOBA85

Avg EV72

Speed68

Barrel%64

Bat Spd64

Form.264/.351/.440 · rolling true talent (60d window) · proj .260/.350/.439

CompsRobbie Grossman (age 32) · Dexter Fowler (age 32) · Emil Brown (age 31)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 124124vR 124

AVG/OBP/SLG.259 / .352 / .433

PA571

HR17

SB8

K%24

BB%11

BABIP322

ISO178

MLB%100%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$11M ctrl surplus

Tools · Recent Form · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

610.260

POWER

Barrel%

6410.3

Avg EV

7290.6

Bat Spd

6472.8

SPEED

Sprint

6828.2

Recent Formrolling true talent ⓘ

K%22%▲▲20% over 108 PA (60d) · proj 24%

BB%11%·10% over 108 PA (60d) · proj 11%

ISO.177·.172 over 93 AB (60d) · proj .179

HR/BB4.1%▼2.8% over 72 BBE (60d) · proj 5.0%

BABIP.320·.314 over 70 BIP (60d) · proj .320

SLASH.264/.351/.440·proj .260/.350/.439

Platoon Splits2024-2026 · 1461 PA

vs LHP

vs RHP

Edge

406

1055

—

wRC+

107

113

▶R

wOBA

326

336

—

ISO

161

163

—

BABIP

324

326

—

26.1%

24.1%

▶R

BB%

8.4%

8.8%

▶R

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

Status FA

MLB Debut 2019

Service 7.948 yrs.days

Team Control Through 2030

First FA Year 2028

NTCOPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$13M	+2.4	$19M	+$6M
2028	Ext	$13M	+1.0	$7M	-$5M
2029	Ext	$13M	+0.2	$0.7M	-$10M
2030	Ext	beyond projection horizon · no WAR estimate
Totals		$40M		$27M	-$9M

Options · projected decision
2031	CLUB OPT	$13.3M / $0.0M buyout	DECLINE
2032	CLUB OPT	$20.0M / $2.0M 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)
2016	21	A	Augusta GreenJackets	—	66	63	20	5	0	1	3	20	0	1	0	317	348	444	793	127	452	30	5	352	68	—	—	—	—	—	—
2017	22	A+	San Jose Giants	—	541	491	153	26	9	10	37	106	6	5	3	312	366	462	829	151	376	20	7	364	95	—	—	—	—	—	—
2018	23	AA	Altoona Curve	—	383	331	100	18	3	7	43	73	3	4	4	302	387	438	825	136	362	19	11	365	109	—	—	—	—	—	—
2018	23	INTL	Surprise Saguaros	—	76	60	11	1	0	0	14	13	1	1	0	183	347	200	547	17	229	17	18	274	72	—	—	—	—	—	—
2019	24	MLB	Pittsburgh Pirates	—	546	491	154	37	4	16	46	121	6	3	2	314	379	503	882	189	387	22	8	387	150	+32	-0	+1	-6	+12	3.9
2019	24	AAA	Indianapolis Indians	—	57	49	18	1	1	5	7	11	0	3	2	367	439	735	1.173	367	394	19	12	494	183	—	—	—	—	—	—
2020	25	MLB	Pittsburgh Pirates	—	208	185	35	6	2	7	21	57	1	1	1	189	274	357	631	168	231	27	10	284	81	-5	-0	+2	-2	+5	-0.1
2021	26	MLB	Pittsburgh Pirates	—	646	559	169	35	8	24	75	119	8	5	2	302	393	522	915	220	345	18	12	400	153	+41	+0	+9	+2	+14	6.7
2022	27	MLB	Pittsburgh Pirates	—	614	542	142	19	4	27	56	141	14	7	3	262	346	461	808	199	306	23	9	358	128	+20	+0	-6	+2	+13	3.1
2023	28	MLB	Pittsburgh Pirates	—	640	574	151	31	5	24	53	138	7	12	1	263	333	460	793	197	304	22	8	347	123	+17	+2	-6	-7	+14	2.1
2024	29	MLB	Pittsburgh Pirates	—	692	622	171	29	3	24	57	156	10	10	2	275	345	447	792	172	330	23	8	351	125	+21	+1	-13	-7	+15	1.7
2025	30	MLB	Pittsburgh Pirates	—	654	587	144	38	3	16	57	173	7	3	2	245	320	402	722	157	319	26	9	322	104	+3	-0	-5	-7	+14	0.6
2026	31	MLB	Pittsburgh Pirates	—	699	595	155	40	3	17	89	162	11	9	0	261	366	424	790	163	329	23	13	354	125	+21	+2	-2	-7	+15	2.9
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4699	4155	1121	235	32	155	454	1067	64	50	13	270	351	454	804	184	327	23	10	356	127	+151	+5	-20	-33	+102	20.9
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2016	21	A MLE	Augusta GreenJackets	—	66	65	16	4	0	1	1	26	0	1	0	246	258	354	611	108	400	39	2	268	68	—	—	—	—	—	—
2017	22	A+ MLE	San Jose Giants	—	541	501	137	21	8	9	28	140	6	5	3	273	320	401	721	128	348	26	5	308	95	—	—	—	—	—	—
2018	23	AA MLE	Altoona Curve	—	383	343	97	17	3	7	31	90	3	4	4	283	347	411	759	128	346	23	8	330	109	—	—	—	—	—	—
2019	24	MLB MLE	Pittsburgh Pirates	—	546	491	153	35	4	17	46	121	6	3	2	312	378	503	881	191	387	22	8	390	150	+32	-0	+1	-6	+12	3.9
2019	24	AAA MLE	Indianapolis Indians	—	57	52	18	1	1	5	5	13	0	3	2	346	404	692	1.096	346	369	23	9	439	183	—	—	—	—	—	—
2020	25	MLB MLE	Pittsburgh Pirates	—	208	186	36	6	2	8	21	57	1	1	1	194	279	376	655	183	231	27	10	288	81	-5	-0	+2	-2	+5	-0.1
2021	26	MLB MLE	Pittsburgh Pirates	—	646	568	171	34	8	26	66	119	8	5	2	301	382	526	908	225	345	18	10	394	153	+41	+0	+9	+2	+14	6.7
2022	27	MLB MLE	Pittsburgh Pirates	—	614	548	143	18	4	29	50	141	14	7	3	261	338	467	805	206	306	23	8	357	128	+20	+0	-6	+2	+13	3.1
2023	28	MLB MLE	Pittsburgh Pirates	—	640	576	152	30	5	26	51	138	7	12	1	264	331	469	800	205	304	22	8	350	123	+17	+2	-6	-7	+14	2.1
2024	29	MLB MLE	Pittsburgh Pirates	—	692	625	173	28	3	26	54	156	10	10	2	277	344	456	800	179	330	23	8	353	125	+21	+1	-13	-7	+15	1.7
2025	30	MLB MLE	Pittsburgh Pirates	—	654	588	143	36	3	17	56	173	7	3	2	243	316	401	718	158	319	26	9	323	104	+3	-0	-5	-7	+14	0.6
2026	31	MLB MLE	Pittsburgh Pirates	—	699	599	154	38	3	18	86	162	11	9	0	257	361	421	781	164	329	23	12	353	125	+21	+2	-2	-7	+15	2.9
2016	21	A MLE	Augusta GreenJackets	—	66	65	16	4	0	1	1	26	0	1	0	246	258	354	611	108	395	39	2	268	68	—	—	—	—	—	—
2016	21	A RAW	Augusta GreenJackets	—	66	63	20	5	0	1	3	20	0	1	0	317	348	444	793	127	452	30	5	352	68	—	—	—	—	—	—
2017	22	A+ MLE	San Jose Giants	—	541	501	137	21	8	9	28	140	6	5	3	273	320	401	721	128	359	26	5	308	95	—	—	—	—	—	—
2017	22	A+ RAW	San Jose Giants	—	541	491	153	26	9	10	37	106	6	5	3	312	366	462	829	151	376	20	7	364	95	—	—	—	—	—	—
2018	23	AA MLE	2 teams	—	459	411	116	21	3	8	37	107	4	5	4	282	347	406	754	124	356	23	8	330	109	—	—	—	—	—	—
2018	23	AA RAW	2 teams	—	459	391	111	19	3	7	57	86	4	5	4	284	381	402	782	118	341	19	12	350	109	—	—	—	—	—	—
2019	24	MLB MLE	2 teams	—	603	543	171	36	5	22	51	134	6	6	4	315	380	521	901	206	382	22	8	394	153	+38	-0	+1	-6	+13	4.6
2019	24	MLB RAW	2 teams	—	603	540	172	38	5	21	53	132	6	6	4	319	385	524	909	206	387	22	9	397	153	+38	-0	+1	-6	+13	4.6
2020	25	MLB MLE	Pittsburgh Pirates	—	208	186	36	6	2	8	21	57	1	1	1	194	279	376	655	183	231	27	10	288	81	-5	-0	+2	-2	+5	-0.1
2020	25	MLB RAW	Pittsburgh Pirates	—	208	185	35	6	2	7	21	57	1	1	1	189	274	357	631	168	231	27	10	284	81	-5	-0	+2	-2	+5	-0.1
2021	26	MLB MLE	Pittsburgh Pirates	—	646	568	171	34	8	26	66	119	8	5	2	301	382	526	908	225	340	18	10	394	153	+41	+0	+9	+2	+14	6.7
2021	26	MLB RAW	Pittsburgh Pirates	—	646	559	169	35	8	24	75	119	8	5	2	302	393	522	915	220	345	18	12	400	153	+41	+0	+9	+2	+14	6.7
2022	27	MLB MLE	Pittsburgh Pirates	—	614	548	143	18	4	29	50	141	14	7	3	261	338	467	805	206	300	23	8	357	128	+20	+0	-6	+2	+13	3.1
2022	27	MLB RAW	Pittsburgh Pirates	—	614	542	142	19	4	27	56	141	14	7	3	262	346	461	808	199	306	23	9	358	128	+20	+0	-6	+2	+13	3.1
2023	28	MLB MLE	Pittsburgh Pirates	—	640	576	152	30	5	26	51	138	7	12	1	264	331	469	800	205	301	22	8	350	123	+17	+2	-6	-7	+14	2.1
2023	28	MLB RAW	Pittsburgh Pirates	—	640	574	151	31	5	24	53	138	7	12	1	263	333	460	793	197	304	22	8	347	123	+17	+2	-6	-7	+14	2.1
2024	29	MLB MLE	Pittsburgh Pirates	—	692	625	173	28	3	26	54	156	10	10	2	277	344	456	800	179	330	23	8	353	125	+21	+1	-13	-7	+15	1.7
2024	29	MLB RAW	Pittsburgh Pirates	—	692	622	171	29	3	24	57	156	10	10	2	275	345	447	792	172	330	23	8	351	125	+21	+1	-13	-7	+15	1.7
2025	30	MLB MLE	Pittsburgh Pirates	—	654	588	143	36	3	17	56	173	7	3	2	243	316	401	718	158	314	26	9	323	104	+3	-0	-5	-7	+14	0.6
2025	30	MLB RAW	Pittsburgh Pirates	—	654	587	144	38	3	16	57	173	7	3	2	245	320	402	722	157	319	26	9	322	104	+3	-0	-5	-7	+14	0.6
2026	31	MLB MLE	Pittsburgh Pirates	—	699	599	154	38	3	18	86	162	11	9	0	257	361	421	781	164	322	23	12	353	125	+21	+2	-2	-7	+15	2.9
2026	31	MLB RAW	Pittsburgh Pirates	—	699	595	155	40	3	17	89	162	11	9	0	261	366	424	790	163	329	23	13	354	125	+21	+2	-2	-7	+15	2.9
2016	21	A MLE	Augusta GreenJackets	—	66	65	16	4	0	1	1	26	0	1	0	246	258	354	611	108	400	39	2	268	68	—	—	—	—	—	—
2017	22	A+ MLE	San Jose Giants	—	541	502	137	21	8	9	28	140	6	5	3	273	320	400	720	127	348	26	5	308	95	—	—	—	—	—	—
2018	23	AA MLE	2 teams	—	459	415	116	21	3	8	37	107	4	5	4	280	347	402	750	123	346	23	8	330	109	—	—	—	—	—	—
2019	24	MLB MLE	2 teams	—	603	541	171	36	5	22	51	134	6	6	4	316	380	523	903	207	385	22	8	394	153	—	—	—	—	—	—
2020	25	MLB MLE	Pittsburgh Pirates	—	208	184	36	6	2	8	21	57	1	1	1	196	279	380	659	185	231	27	10	288	81	—	—	—	—	—	—
2021	26	MLB MLE	Pittsburgh Pirates	—	646	567	171	34	8	26	66	119	8	5	2	302	382	527	909	226	345	18	10	394	153	—	—	—	—	—	—
2022	27	MLB MLE	Pittsburgh Pirates	—	614	545	143	18	4	29	50	141	14	7	3	262	338	470	808	207	306	23	8	357	128	—	—	—	—	—	—
2023	28	MLB MLE	Pittsburgh Pirates	—	640	577	152	30	5	26	51	138	7	12	1	263	331	468	799	205	304	22	8	350	123	—	—	—	—	—	—
2024	29	MLB MLE	Pittsburgh Pirates	—	692	623	173	28	3	26	54	156	10	10	2	278	344	457	801	180	330	23	8	353	125	—	—	—	—	—	—
2025	30	MLB MLE	Pittsburgh Pirates	—	654	586	143	36	3	17	56	173	7	3	2	244	316	403	719	159	319	26	9	323	104	—	—	—	—	—	—
2026	31	MLB MLE	Pittsburgh Pirates	—	699	597	154	38	3	18	86	162	11	9	0	258	361	422	783	164	329	23	12	353	125	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	29	MLB MLE	Pittsburgh Pirates	—	692	623	173	28	3	26	54	156	10	10	2	278	344	457	801	180	330	23	8	353	125	—	—	—	—	—	—
2025	30	MLB MLE	Pittsburgh Pirates	—	654	586	143	36	3	17	56	173	7	3	2	244	316	403	719	159	319	26	9	323	104	—	—	—	—	—	—
2026	31	MLB MLE	Pittsburgh Pirates	—	699	597	154	38	3	18	86	162	11	9	0	258	361	422	783	164	329	23	12	353	125	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	32	MLB MLE	PIT	100%	623	540	141	32	3	20	69	148	9	8	2	260	353	439	792	179	320	24	11	351	124	+18	+1	-3	-7	+13	2.4
▸ 2027 — real world (MLB)
2027	32	MLB CTX	PIT	100%	571	495	130	31	3	17	63	136	8	8	2	259	352	433	785	173	322	24	11	349	124	+16	+1	-3	-6	+12	2.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	33	MLB MLE	PIT	100%	532	462	116	26	2	16	58	130	7	3	1	251	343	419	762	168	312	24	11	340	116	+10	+0	-7	-6	+12	1.0
2029	34	MLB MLE	PIT	100%	473	414	99	21	2	13	50	119	6	2	1	240	331	395	726	155	301	25	11	325	106	+4	+0	-7	-5	+10	0.2
2028	33	MLB CTX	PIT	100%	532	462	116	27	2	15	58	130	7	3	1	250	342	413	755	163	313	24	11	337	116	+10	+0	-7	-6	+12	1.0
2029	34	MLB CTX	PIT	100%	473	414	98	22	2	12	50	119	6	2	1	239	330	389	719	151	302	25	11	323	106	+4	+0	-7	-5	+10	0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	5704	5031	1335	284	36	182	562	1316	77	55	15	265	348	445	793	179	324	23	10	351	121	+165	+5	-34	-44	+124	22.0
/ 162G	—	A+C		—	650	573	152	32	4	21	64	150	9	6	2	265	348	445	793	180	323	23	10	351	121	+19	+1	-4	-5	+14	2.5
Career	—	MLE		—	7398	6581	1756	348	51	237	672	1738	95	77	26	267	343	443	787	176	327	23	9	347	121	+181	+6	-36	-50	+136	24.1
/ 162G	—	MLE		—	650	578	154	31	4	21	59	153	8	7	2	266	343	443	786	176	326	24	9	347	121	+19	+1	-4	-5	+14	2.5

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.

2019 AAAIndianapolis Indians · 57 PAwOBA .480 → .439 (−41)K% 19.3% → 22.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.30%	÷1.013	×1.200	—	—	22.86%
BB% (unintentional) /PA	12.28%	÷1.010	×0.690	—	×1.048	8.79%
HBP% /PA	0.00%	—	×0.940	—	×1.048	0.00%
Singles /BIP	28.95%	÷1.026	×0.930	—	×1.048	27.51%
Doubles /BIP	2.63%	÷0.901	×0.830	—	×1.048	2.54%
Triples /BIP	2.63%	÷1.150	×0.970	—	×1.048	2.33%
Home runs /BIP	13.16%	÷0.953	×0.840	—	×1.048	12.15%

Factors used: league row IL. Park (home-season share, regressed): HR 91, 1B 105, 2B 80, 3B 130, K 103, BB 102 — applied at half strength. Age: age 24 vs a level average of 27.2 → +4.8% on BB/HBP/hit rates (3.2 yr younger than average).

Result: wOBA .480 → .439; ISO .367 → .347; BABIP .394 → .369. 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).

2018 AAAltoona Curve · 383 PAwOBA .359 → .330 (−29)K% 19.1% → 23.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.06%	÷0.993	×1.220	—	—	23.42%
BB% (unintentional) /PA	10.44%	÷0.929	×0.700	—	×1.027	8.08%
HBP% /PA	0.78%	—	×0.850	—	×1.027	0.68%
Singles /BIP	27.91%	÷1.035	×0.970	×1.002	×1.027	26.92%
Doubles /BIP	6.98%	÷0.936	×0.860	×1.002	×1.027	6.60%
Triples /BIP	1.16%	÷1.150	×0.950	×1.002	×1.027	0.99%
Home runs /BIP	2.71%	÷0.857	×0.780	—	×1.027	2.54%

Factors used: league row EL. Park (home-season share, regressed): HR 71, 1B 107, 2B 87, 3B 130, K 99, BB 86 — applied at half strength. Age: age 23 vs a level average of 24.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.002.

Result: wOBA .359 → .330; ISO .136 → .127; BABIP .362 → .346. 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 A+San Jose Giants · 541 PAwOBA .357 → .308 (−49)K% 19.6% → 25.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.59%	÷1.018	×1.340	—	—	25.78%
BB% (unintentional) /PA	6.84%	÷0.968	×0.710	—	×1.012	5.08%
HBP% /PA	1.11%	—	×0.790	—	×1.012	0.89%
Singles /BIP	28.05%	÷0.990	×0.910	×1.025	×1.012	26.73%
Doubles /BIP	6.75%	÷1.008	×0.820	×1.025	×1.012	5.70%
Triples /BIP	2.34%	÷0.900	×0.760	×1.025	×1.012	2.05%
Home runs /BIP	2.60%	÷1.010	×0.920	—	×1.012	2.39%

Factors used: league row CAL. Park (home-season share, regressed): HR 102, 1B 98, 2B 102, 3B 80, K 104, BB 94 — applied at half strength. Age: age 22 vs a level average of 22.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.025.

Result: wOBA .357 → .308; ISO .151 → .128; BABIP .376 → .348. 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 AAugusta GreenJackets · 66 PAwOBA .337 → .268 (−70)K% 30.3% → 39.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.30%	÷1.025	×1.340	—	—	39.63%
BB% (unintentional) /PA	3.03%	÷1.020	×0.660	—	×1.015	1.99%
HBP% /PA	0.00%	—	×0.770	—	×1.015	0.00%
Singles /BIP	32.56%	÷1.054	×0.920	—	×1.015	28.85%
Doubles /BIP	11.63%	÷0.944	×0.820	—	×1.015	10.25%
Triples /BIP	0.00%	÷0.919	×0.940	—	×1.015	0.00%
Home runs /BIP	2.33%	÷0.834	×0.820	—	×1.015	2.32%

Factors used: league row SAL. Park (home-season share, regressed): HR 67, 1B 111, 2B 89, 3B 84, K 105, BB 104 — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average).

Result: wOBA .337 → .268; ISO .127 → .105; BABIP .452 → .400. 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
#1Paul O'Neill'85-'01 * career totals — 15 seasons, 8,329 PA	12.5	8,329	281	141	279*	353*	474*	-90	-11	40.4	34.5
/162	664	22	11	-7.2	-0.9	3.2	pk7: 29
#2Ryan Klesko'92-'07 * career totals — 13 seasons, 6,516 PA	9.8	6,516	278	91	267*	355*	487*	-92	-37	33.7	29.2
/162	664	28	9	-9.3	-3.8	3.4	pk7: 25
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 11 projected seasons	9.5	6,275	202	62	267	347	448	-67	-39	28.2	26.4
/162	664	21	7	-7.1	-4.2	3.0	pk7: 25
#3Nick Swisherlast yr '15 career totals — 12 seasons, 6,308 PA	9.5	6,308	245	13	249	351	447	-62	-56	24.5	24.4
/162	664	26	1	-6.5	-5.9	2.6	pk7: 24
#4Aubrey 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
#5Steve Kemp'77-'88 * career totals — 9 seasons, 4,714 PA	7.1	4,714	130	39	273*	366*	456*	-56	-12	20.9	20.4
/162	664	18	5	-7.9	-1.7	2.9	pk7: 20
#6Yasiel Puiglast yr '19 career totals — 7 seasons, 3,376 PA	5.1	3,376	132	79	277	348	475	-36	-12	17.1	17.1
/162	664	26	16	-7.1	-2.3	3.4	pk7: 17

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
Bryan Reynolds (OGILVIE)	32	—	—	—	—	258/350/435	177	320	18	8	24%	11%	124	+2.9	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Robbie Grossman 2022 · MLB	32	48→58	53→50	53→50	59	243/347/420	177	285	20	17	22%	13%	119	+2.7	228/331/366	138	292	14	9	24%	13%	101	+1.4	218/324/333	115	286	10	5	25%	13%	91	+0.4
●Dexter Fowler 2018 · MLB	32	52→62	53→55	53→55	58	261/359/452	191	311	19	12	22%	12%	130	+3.5	232/330/402	170	280	20	9	23%	12%	109	+2.0	217/320/372	156	262	20	8	24%	12%	101	+0.8
●Emil Brown 2006 · MLB	31	55→57	50	54→50	51	276/339/441	165	314	17	10	18%	8%	120	+2.8	266/327/412	146	303	15	10	17%	8%	109	+2.0	259/318/396	136	292	14	9	16%	7%	103	+1.2
✕Rob Refsnyder 2023 · MLB	32	53→63	49→50	48→50	50	257/340/409	152	330	16	7	26%	9%	114	+2.3	256/343/405	149	324	16	10	24%	10%	114	+2.4	257/348/410	153	321	17	9	24%	11%	117	+1.1
✕Chris Coghlan 2017 · MLB	32	47→57	49→50	51→55	54	237/317/395	159	279	15	10	21%	10%	101	+1.4	213/291/339	126	259	12	6	22%	9%	80	-0.2	183/263/277	94	225	8	2	22%	8%	53	-0.6
✕Chris Taylor 2023 · MLB	32	51→61	51→60	55	48	244/326/413	170	342	17	13	31%	10%	109	+2.0	228/310/378	150	325	16	16	32%	10%	96	+1.0	216/302/355	139	307	16	18	32%	9%	90	+0.3
✕Steven Souza Jr. 2021 · MLB	32	46→56	51→60	54→55	49	229/310/394	165	309	17	14	30%	10%	99	+1.3	221/302/391	170	308	19	10	32%	9%	96	+1.0	198/285/370	171	275	19	9	33%	9%	83	+0.0
✕Adam Eaton 2021 · MLB	32	54→64	47→50	55	54	264/341/410	147	302	13	13	17%	9%	114	+2.3	227/301/369	142	277	14	9	23%	8%	91	+0.6	198/279/322	124	250	12	6	25%	8%	72	-0.3
✕Austin Slater 2024 · MLB	31	55→62	50→55	52→55	51	264/346/418	154	349	17	16	28%	10%	118	+2.6	233/315/344	111	323	12	10	29%	10%	89	+0.5	218/300/302	84	311	8	10	30%	10%	74	-0.2
✕Gary Matthews Jr. 2007 · MLB	32	57→63	51→55	49→50	52	286/346/463	177	316	17	10	16%	8%	127	+3.3	258/326/407	149	299	15	12	18%	9%	107	+1.9	244/318/377	133	289	13	13	19%	9%	98	+1.0
●Morgan Burkhart 2003 · MLB	31	49→46	52→55	49→30	50	248/331/417	169	313	20	9	26%	10%	112	+2.2	242/328/404	162	279	20	6	20%	9%	109	+2.0	236/342/382	146	269	17	1	18%	10%	107	+1.3
✕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
●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
●Kit Pellow 2006 · MLB	32	52→55	48→60	51→40	43	250/322/399	149	340	15	8	29%	7%	105	+1.7	246/312/434	188	277	25	5	21%	6%	110	+2.1	253/318/453	200	277	28	3	20%	5%	117	+1.7
●Edgar Quintero 2010 · AAA	32	56→64	50→55	49→50	46	276/329/432	156	341	17	8	24%	7%	114	+2.4	259/306/423	164	343	21	6	29%	6%	104	+1.6	246/291/410	164	330	23	5	32%	6%	96	+0.7
✕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
✕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
✕Juan Miranda 2015 · AAA	32	53→58	52→55	46→40	53	265/353/426	161	318	20	5	22%	10%	122	+3.0	239/333/365	126	294	14	5	22%	10%	102	+1.5	231/331/345	114	285	13	3	22%	10%	95	+0.5
✕Rene Reyes 2010 · AAA	32	57→62	47→50	52→50	50	281/333/424	143	315	13	15	15%	7%	114	+2.3	257/312/396	139	292	14	15	17%	7%	100	+1.3	255/319/389	134	310	12	8	21%	8%	99	+0.8
✕Stephen Drew 2014 · MLB	31	47→57	49→55	51→45	52	237/311/400	164	291	15	6	24%	10%	100	+1.3	211/281/378	167	242	18	4	21%	9%	85	+0.2	217/288/392	175	232	21	0	17%	9%	92	+0.3

Bryan Reynolds

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps