Kyle Farmer

2B Gwinnett Stripers

Age 36 R/R 5'11" / 205 lbs AAA Svc 8.593 · Ctrl thru 2027

Overview

AAA40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	33	MLBMIN	242	.214/.296/.353	5	3	82	0.4
2025	34	MLBCOL	300	.227/.282/.365	8	0	74	-0.6
2026	35	AAA/AAATL	121	.227/.292/.255	1	0	23	—	.195/.250/.224
2026	35	MLBATL	19	.222/.222/.278	0	0	29	-0.1
2027PROJ45% MLB	36	MLBATL	53	.229/.285/.347	1	0	78	0.0
2028PROJ	37	MLBATL	80	.217/.271/.321	1	0	67	-0.8

Last 3 seasons WAR -0.3 · Next 2 projected WAR -0.8Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service8.593First FA2028Options2

2027Ext / FA-deal$1M

Skills · percentileStatcast 2024-2026

xwOBA33

Barrel%32

Avg EV24

Bat Spd24

Speed10

CompsHumberto Quintero (age 35) · Lou Merloni (age 36) · Jamie Burke (age 36)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 8378vR 62

AVG/OBP/SLG.229 / .285 / .347

PA53

HR1

K%21

BB%6

BABIP274

ISO102

MLB%45%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · ContractCON 45 / POW 45

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT45

xAVG

200.226

POWER45

Barrel%

325.8

Avg EV

2487.1

Bat Spd

2468.6

EYE45

scouting grade only

SPEED40

Sprint

1024.8

Platoon Splits2024-2025 · 542 PA

vs LHP

vs RHP

Edge

241

301

—

wRC+

112

◀◀L

wOBA

334

249

◀◀L

ISO

174

110

◀◀L

BABIP

290

237

◀◀L

19.5%

22.6%

◀L

BB%

7.5%

5.6%

◀◀L

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

Status FA

MLB Debut 2017

Service 8.593 yrs.days

Team Control Through 2027

First FA Year 2028

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$1M	—	—	—
Totals		$1M		$0.0M	-$1M

Options · projected decision
2027	MUTUAL OPT	$1.0M / $0.0M buyout	DECLINE
2028	MUTUAL OPT	$4.0M / $0.0M 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)
2013	22	ROK	Ogden Raptors	—	184	167	58	19	0	4	7	21	6	1	1	347	394	533	927	186	370	11	4	400	82	—	—	—	—	—	—
2014	23	A+	Rancho Cucamonga Quakes	—	146	130	31	5	1	0	10	28	3	2	0	238	308	292	600	54	301	19	7	273	34	—	—	—	—	—	—
2014	23	A	Great Lakes Loons	—	249	229	71	16	4	2	15	24	3	9	3	310	360	441	801	131	337	10	6	354	74	—	—	—	—	—	—
2015	24	AA	Tulsa Drillers	—	305	283	77	26	1	2	14	55	4	0	1	272	316	392	708	120	326	18	5	312	72	—	—	—	—	—	—
2015	24	A+	Rancho Cucamonga Quakes	—	182	163	55	14	6	1	12	25	5	5	2	337	400	515	915	178	388	14	7	399	89	—	—	—	—	—	—
2015	24	INTL	Glendale Desert Dogs	—	62	58	17	7	0	2	2	11	1	0	0	293	328	517	845	224	326	18	3	363	132	—	—	—	—	—	—
2016	25	AA	Tulsa Drillers	—	297	266	68	18	2	5	25	44	3	2	0	256	327	395	721	139	286	15	8	321	78	—	—	—	—	—	—
2016	25	ROK	AZL Dodgers	—	18	17	5	0	0	2	1	1	0	0	0	294	333	647	980	353	214	6	6	421	88	—	—	—	—	—	—
2017	26	MLB	Los Angeles Dodgers	—	20	20	6	1	0	0	0	3	0	0	0	300	300	350	650	50	353	15	0	290	87	-0	+0	+0	-7	+0	-0.7
2017	26	AAA	Oklahoma City Dodgers	—	240	223	68	16	1	7	13	36	4	0	4	305	354	480	834	175	339	15	5	369	80	—	—	—	—	—	—
2017	26	AA	Tulsa Drillers	—	141	124	42	7	0	3	16	13	0	1	0	339	414	468	882	129	358	9	11	393	98	—	—	—	—	—	—
2018	27	MLB	Los Angeles Dodgers	—	77	68	16	4	1	0	5	15	3	0	0	235	316	324	639	88	296	19	6	291	84	-1	+0	+1	+1	+2	0.3
2018	27	AAA	Oklahoma City Dodgers	—	312	288	83	24	1	7	17	50	4	1	1	288	337	451	788	163	325	16	5	346	63	—	—	—	—	—	—
2019	28	MLB	Cincinnati Reds	—	197	183	42	6	0	9	10	59	3	4	1	230	281	410	690	180	284	30	5	305	85	-4	+0	+2	+1	+4	0.4
2020	29	MLB	Cincinnati Reds	—	70	64	17	3	0	0	5	13	1	1	0	266	329	312	641	47	333	19	7	296	86	-1	+0	+2	+1	+2	0.3
2021	30	MLB	Cincinnati Reds	—	529	483	127	22	2	16	22	97	18	2	3	263	319	416	735	153	296	18	4	325	102	+1	-1	+7	+6	+11	2.5
2022	31	MLB	Cincinnati Reds	—	583	526	134	25	1	14	33	99	16	4	3	255	318	386	704	131	286	17	6	313	95	-3	-0	+2	+6	+13	1.7
2023	32	MLB	Minnesota Twins	—	369	336	86	14	2	11	23	86	8	2	4	256	319	408	727	152	311	23	6	324	105	+2	-1	+3	+1	+8	1.3
2023	32	AAA	St. Paul Saints	—	15	13	4	2	0	1	2	4	0	0	0	308	400	692	1.092	385	375	27	13	463	82	—	—	—	—	—	—
2024	33	MLB	Minnesota Twins	—	242	215	46	13	1	5	19	49	6	3	5	214	296	353	649	140	252	20	8	293	82	-5	-1	+4	+1	+5	0.4
2025	34	MLB	Colorado Rockies	—	300	277	63	14	0	8	17	66	4	0	1	227	282	365	647	137	268	22	6	288	74	-9	-0	-4	+1	+6	-0.6
2026	35	MLB	Atlanta Braves	—	19	18	4	1	0	0	0	5	0	0	0	222	222	278	500	56	286	26	0	210	29	-2	+0	+0	+0	+0	-0.1
2026	35	AAA	Gwinnett Stripers	—	98	90	23	0	0	0	7	18	0	0	0	256	309	256	565		315	18	7	262	29	—	—	—	—	—	—
2026	35	AA	Columbus Clingstones	—	23	20	2	0	0	1	1	4	2	0	0	100	217	250	467	150	67	17	4	224	-1	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	2406	2190	541	103	7	63	134	492	59	16	17	247	308	387	695	140	289	20	6	309	96	-13	-4	+17	+11	+52	6.6
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2013	22	ROK MLE	Ogden Raptors	—	184	170	43	13	0	3	4	30	6	1	1	253	294	382	677	129	277	16	2	289	82	—	—	—	—	—	—
2014	23	A+ MLE	Rancho Cucamonga Quakes	—	146	133	27	4	1	0	7	36	3	2	0	203	259	248	507	45	260	25	5	219	34	—	—	—	—	—	—
2014	23	A MLE	Great Lakes Loons	—	249	234	59	12	3	2	10	30	3	9	3	252	291	355	646	103	275	12	4	277	74	—	—	—	—	—	—
2015	24	AA MLE	Tulsa Drillers	—	305	289	73	22	1	2	8	68	4	0	1	253	282	356	639	104	309	22	3	275	72	—	—	—	—	—	—
2015	24	A+ MLE	Rancho Cucamonga Quakes	—	182	166	43	10	4	1	9	35	5	5	2	259	317	386	702	127	309	19	5	300	89	—	—	—	—	—	—
2016	25	AA MLE	Tulsa Drillers	—	297	273	64	17	2	4	18	54	3	2	0	234	289	355	644	121	273	18	6	283	78	—	—	—	—	—	—
2016	25	ROK MLE	AZL Dodgers	—	18	17	3	0	0	1	1	1	0	0	0	176	222	353	575	176	159	6	6	298	88	—	—	—	—	—	—
2017	26	MLB MLE	Los Angeles Dodgers	—	20	20	6	1	0	0	0	3	0	0	0	300	300	350	650	50	353	15	0	296	87	-0	+0	+0	-7	+0	-0.7
2017	26	AAA MLE	Oklahoma City Dodgers	—	240	227	56	12	1	5	9	47	4	0	4	247	287	374	662	128	286	20	4	286	80	—	—	—	—	—	—
2017	26	AA MLE	Tulsa Drillers	—	141	130	37	6	0	2	10	17	0	1	0	285	336	377	713	92	309	12	7	313	98	—	—	—	—	—	—
2018	27	MLB MLE	Los Angeles Dodgers	—	77	69	16	4	1	0	4	15	3	0	0	232	303	319	621	87	296	19	5	293	84	-1	+0	+1	+1	+2	0.3
2018	27	AAA MLE	Oklahoma City Dodgers	—	312	293	65	17	1	5	12	66	4	1	1	222	262	338	600	116	264	21	4	261	63	—	—	—	—	—	—
2019	28	MLB MLE	Cincinnati Reds	—	197	184	41	6	0	8	9	59	3	4	1	223	270	386	656	163	284	30	5	293	85	-4	+0	+2	+1	+4	0.4
2020	29	MLB MLE	Cincinnati Reds	—	70	64	17	3	0	0	5	13	1	1	0	266	329	312	641	47	333	19	7	295	86	-1	+0	+2	+1	+2	0.3
2021	30	MLB MLE	Cincinnati Reds	—	529	484	126	22	2	15	21	97	18	2	3	260	315	407	723	147	296	18	4	319	102	+1	-1	+7	+6	+11	2.5
2022	31	MLB MLE	Cincinnati Reds	—	583	526	133	25	1	13	33	99	16	4	3	253	317	378	695	125	286	17	6	309	95	-3	-0	+2	+6	+13	1.7
2023	32	MLB MLE	Minnesota Twins	—	369	336	86	14	2	11	23	86	8	2	4	256	319	408	727	152	311	23	6	323	105	+2	-1	+3	+1	+8	1.3
2023	32	AAA MLE	St. Paul Saints	—	15	14	3	1	0	1	1	5	0	0	0	214	267	500	767	286	249	33	7	290	82	—	—	—	—	—	—
2024	33	MLB MLE	Minnesota Twins	—	242	216	46	13	1	5	18	49	6	3	5	213	292	352	644	139	252	20	7	289	82	-5	-1	+4	+1	+5	0.4
2025	34	MLB MLE	Colorado Rockies	—	300	277	61	14	0	7	17	66	4	0	1	220	275	347	622	126	268	22	6	277	74	-9	-0	-4	+1	+6	-0.6
2026	35	MLB MLE	Atlanta Braves	—	19	18	4	1	0	0	0	5	0	0	0	222	222	278	500	56	286	26	0	210	29	-2	+0	+0	+0	+0	-0.1
2026	35	AAA MLE	Gwinnett Stripers	—	98	92	20	0	0	0	5	22	0	0	0	217	258	217	475		270	22	5	211	29	—	—	—	—	—	—
2026	35	AA MLE	Columbus Clingstones	—	23	20	2	0	0	1	1	5	2	0	0	100	217	250	467	150	57	22	4	167	-1	—	—	—	—	—	—
2013	22	ROK MLE	Ogden Raptors	—	184	170	43	13	0	3	4	30	6	1	1	253	294	382	677	129	284	16	2	289	82	—	—	—	—	—	—
2013	22	ROK RAW	Ogden Raptors	—	184	167	58	19	0	4	7	21	6	1	1	347	394	533	927	186	370	11	4	400	82	—	—	—	—	—	—
2014	23	A MLE	2 teams	—	395	366	85	16	4	2	18	66	6	11	3	232	279	314	594	82	276	17	5	256	59	—	—	—	—	—	—
2014	23	A RAW	2 teams	—	395	359	102	21	5	2	25	52	6	11	3	284	341	387	728	103	325	13	6	324	59	—	—	—	—	—	—
2015	24	AA MLE	3 teams	—	549	513	130	36	5	3	19	115	10	5	3	253	293	361	654	107	316	21	3	284	79	—	—	—	—	—	—
2015	24	AA RAW	3 teams	—	549	504	149	47	7	5	28	91	10	5	3	296	345	446	791	151	347	17	5	347	79	—	—	—	—	—	—
2016	25	AA MLE	2 teams	—	315	290	68	17	2	5	19	55	3	2	0	234	288	359	647	124	270	17	6	284	78	—	—	—	—	—	—
2016	25	AA RAW	2 teams	—	315	283	73	18	2	7	26	45	3	2	0	258	327	410	737	152	282	14	8	327	78	—	—	—	—	—	—
2017	26	AAA MLE	3 teams	—	401	377	99	19	1	7	19	66	4	1	4	263	305	374	679	111	302	16	5	296	86	—	—	—	—	—	—
2017	26	AAA RAW	3 teams	—	401	367	116	24	1	10	29	52	4	1	4	316	372	469	841	153	346	13	7	373	86	—	—	—	—	—	—
2018	27	AAA MLE	2 teams	—	389	362	81	21	2	5	16	81	7	1	1	224	270	334	604	110	271	21	4	267	67	—	—	—	—	—	—
2018	27	AAA RAW	2 teams	—	389	356	99	28	2	7	22	65	7	1	1	278	332	427	759	149	319	17	6	335	67	—	—	—	—	—	—
2019	28	MLB MLE	Cincinnati Reds	—	197	184	41	6	0	8	9	59	3	4	1	223	270	386	656	163	280	30	5	293	85	-4	+0	+2	+1	+4	0.4
2019	28	MLB RAW	Cincinnati Reds	—	197	183	42	6	0	9	10	59	3	4	1	230	281	410	690	180	284	30	5	305	85	-4	+0	+2	+1	+4	0.4
2020	29	MLB MLE	Cincinnati Reds	—	70	64	17	3	0	0	5	13	1	1	0	266	329	312	641	47	333	19	7	295	86	-1	+0	+2	+1	+2	0.3
2020	29	MLB RAW	Cincinnati Reds	—	70	64	17	3	0	0	5	13	1	1	0	266	329	312	641	47	333	19	7	296	86	-1	+0	+2	+1	+2	0.3
2021	30	MLB MLE	Cincinnati Reds	—	529	484	126	22	2	15	21	97	18	2	3	260	315	407	723	147	294	18	4	319	102	+1	-1	+7	+6	+11	2.5
2021	30	MLB RAW	Cincinnati Reds	—	529	483	127	22	2	16	22	97	18	2	3	263	319	416	735	153	296	18	4	325	102	+1	-1	+7	+6	+11	2.5
2022	31	MLB MLE	Cincinnati Reds	—	583	526	133	25	1	13	33	99	16	4	3	253	317	378	695	125	286	17	6	309	95	-3	-0	+2	+6	+13	1.7
2022	31	MLB RAW	Cincinnati Reds	—	583	526	134	25	1	14	33	99	16	4	3	255	318	386	704	131	286	17	6	313	95	-3	-0	+2	+6	+13	1.7
2023	32	MLB MLE	2 teams	—	384	350	89	15	2	12	24	91	8	2	4	254	317	411	728	157	309	24	6	322	104	+2	-1	+3	+1	+8	1.3
2023	32	MLB RAW	2 teams	—	384	349	90	16	2	12	25	90	8	2	4	258	322	418	740	160	313	23	7	329	104	+2	-1	+3	+1	+8	1.3
2024	33	MLB MLE	Minnesota Twins	—	242	216	46	13	1	5	18	49	6	3	5	213	292	352	644	139	250	20	7	289	82	-5	-1	+4	+1	+5	0.4
2024	33	MLB RAW	Minnesota Twins	—	242	215	46	13	1	5	19	49	6	3	5	214	296	353	649	140	252	20	8	293	82	-5	-1	+4	+1	+5	0.4
2025	34	MLB MLE	Colorado Rockies	—	300	277	61	14	0	7	17	66	4	0	1	220	275	347	622	126	262	22	6	277	74	-9	-0	-4	+1	+6	-0.6
2025	34	MLB RAW	Colorado Rockies	—	300	277	63	14	0	8	17	66	4	0	1	227	282	365	647	137	268	22	6	288	74	-9	-0	-4	+1	+6	-0.6
2026	35	AAA MLE	3 teams	—	140	131	26	1	0	1	5	31	2	0	0	198	239	229	468	31	248	22	4	204	24	—	—	—	—	—	—
2026	35	AAA RAW	3 teams	—	140	128	29	1	0	1	8	27	2	0	0	227	283	258	540	31	275	19	6	249	24	—	—	—	—	—	—
2013	22	ROK MLE	Ogden Raptors	—	184	172	43	13	0	3	4	30	6	1	1	250	294	378	672	128	277	16	2	289	82	—	—	—	—	—	—
2014	23	A MLE	2 teams	—	395	368	85	16	4	2	18	66	6	11	3	231	279	312	592	82	269	17	5	256	59	—	—	—	—	—	—
2015	24	AA MLE	3 teams	—	549	515	130	36	5	3	19	115	10	5	3	252	293	359	653	107	309	21	3	284	79	—	—	—	—	—	—
2016	25	AA MLE	2 teams	—	315	290	68	17	2	5	19	55	3	2	0	234	288	359	647	124	266	17	6	284	78	—	—	—	—	—	—
2017	26	AAA MLE	3 teams	—	401	375	99	19	1	7	19	66	4	1	4	264	305	376	681	112	297	16	5	296	86	—	—	—	—	—	—
2018	27	AAA MLE	2 teams	—	389	363	81	21	2	5	16	81	7	1	1	223	270	333	603	110	270	21	4	267	67	—	—	—	—	—	—
2019	28	MLB MLE	Cincinnati Reds	—	197	183	41	6	0	8	9	59	3	4	1	224	270	388	658	164	284	30	5	293	85	—	—	—	—	—	—
2020	29	MLB MLE	Cincinnati Reds	—	70	64	17	3	0	0	5	13	1	1	0	266	329	312	641	47	333	19	7	295	86	—	—	—	—	—	—
2021	30	MLB MLE	Cincinnati Reds	—	529	485	126	22	2	15	21	97	18	2	3	260	315	406	722	146	296	18	4	319	102	—	—	—	—	—	—
2022	31	MLB MLE	Cincinnati Reds	—	583	529	133	25	1	13	33	99	16	4	3	251	317	376	693	125	286	17	6	309	95	—	—	—	—	—	—
2023	32	MLB MLE	2 teams	—	384	349	89	15	2	12	24	91	8	2	4	255	317	413	729	158	309	24	6	322	104	—	—	—	—	—	—
2024	33	MLB MLE	Minnesota Twins	—	242	216	46	13	1	5	18	49	6	3	5	213	292	352	644	139	252	20	7	289	82	—	—	—	—	—	—
2025	34	MLB MLE	Colorado Rockies	—	300	276	61	14	0	7	17	66	4	0	1	221	275	348	623	127	268	22	6	277	74	—	—	—	—	—	—
2026	35	AAA MLE	3 teams	—	140	132	26	1	0	1	5	31	2	0	0	197	239	227	466	30	237	22	4	204	24	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	33	MLB MLE	Minnesota Twins	—	242	216	46	13	1	5	18	49	6	3	5	213	292	352	644	139	252	20	7	289	82	—	—	—	—	—	—
2025	34	MLB MLE	Colorado Rockies	—	300	276	61	14	0	7	17	66	4	0	1	221	275	348	623	127	268	22	6	277	74	—	—	—	—	—	—
2026	35	AAA MLE	3 teams	—	140	132	26	1	0	1	5	31	2	0	0	197	239	227	466	30	237	22	4	204	24	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	36	MLB MLE	ATL	45%	189	173	41	8	1	4	11	41	3	2	1	229	285	347	632	118	274	22	6	283	78	-5	+0	+0	+1	+4	0.0
▸ 2027 — real world (MLB)
2027	36	MLB CTX	ATL	45%	53	49	11	2	0	1	3	11	1	0	0	229	285	347	632	118	274	21	6	283	78	-1	+0	+0	+0	+1	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	37	MLB MLE	ATL	100%	80	75	15	3	0	1	4	18	1	0	0	217	271	321	592	104	264	22	5	267	67	-3	+0	-7	+0	+2	-0.8
2028	37	MLB CTX	ATL	100%	80	75	15	3	0	1	4	18	1	0	0	217	271	321	592	104	264	22	5	267	67	-3	+0	-7	+0	+2	-0.8
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2486	2265	556	106	7	64	138	510	60	16	17	245	306	383	689	138	288	21	6	308	82	-16	-4	+10	+12	+54	5.7
/ 162G	—	A+C		—	650	592	146	28	2	17	36	133	16	4	4	247	307	387	694	140	289	20	6	308	82	-4	-1	+3	+3	+14	1.5
Career	—	MLE		—	4875	4492	1084	229	20	89	238	961	97	38	29	241	294	361	655	119	286	20	5	289	82	-19	-3	+10	+12	+56	5.8
/ 162G	—	MLE		—	650	599	145	31	3	12	32	128	13	5	4	242	295	364	659	122	286	20	5	289	82	-5	-1	+3	+3	+14	1.4

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.

2026 AAAGwinnett Stripers · 98 PAwOBA .258 → .211 (−47)K% 18.4% → 22.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.37%	÷1.000	×1.200	—	—	22.04%
BB% (unintentional) /PA	7.14%	÷1.000	×0.690	—	×0.940	4.63%
HBP% /PA	0.00%	—	×0.940	—	×0.940	0.00%
Singles /BIP	31.94%	÷1.000	×0.930	×0.982	×0.940	27.41%
Doubles /BIP	0.00%	÷1.000	×0.830	×0.982	×0.940	0.00%
Triples /BIP	0.00%	÷1.000	×0.970	×0.982	×0.940	0.00%
Home runs /BIP	0.00%	÷1.000	×0.700	—	×0.940	0.00%

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 36 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (8.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.982.

Result: wOBA .258 → .211; ISO .000 → .000; BABIP .315 → .270. 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 AAColumbus Clingstones · 23 PAwOBA .218 → .167 (−51)K% 17.4% → 21.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.39%	÷1.000	×1.220	—	—	21.22%
BB% (unintentional) /PA	4.35%	÷1.000	×0.680	—	×0.940	2.78%
HBP% /PA	8.70%	—	×0.840	—	×0.940	6.87%
Singles /BIP	6.25%	÷1.000	×0.920	—	×0.940	5.41%
Doubles /BIP	0.00%	÷1.000	×0.910	—	×0.940	0.00%
Triples /BIP	0.00%	÷1.000	×0.880	—	×0.940	0.00%
Home runs /BIP	6.25%	÷1.000	×0.800	—	×0.940	4.70%

Factors used: league row SL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 36 vs a level average of 24.8 → −6.0% on BB/HBP/hit rates (11.2 yr older than average).

Result: wOBA .218 → .167; ISO .150 → .112; BABIP .067 → .057. 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 AAASt. Paul Saints · 15 PAwOBA .450 → .290 (−161)K% 26.7% → 32.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.67%	÷0.973	×1.200	—	—	32.87%
BB% (unintentional) /PA	13.33%	÷1.067	×0.690	—	×0.942	8.12%
HBP% /PA	0.00%	—	×0.940	—	×0.942	0.00%
Singles /BIP	11.11%	÷0.964	×0.930	—	×0.942	10.09%
Doubles /BIP	22.22%	÷1.341	×0.830	—	×0.942	12.96%
Triples /BIP	0.00%	÷0.977	×0.970	—	×0.942	0.00%
Home runs /BIP	11.11%	÷1.009	×0.700	—	×0.942	7.26%

Factors used: league row International League. Park (home-season share, regressed): HR 102, 1B 93, 2B 168, 3B 95, K 95, BB 113 — applied at half strength. Age: age 33 vs a level average of 27.2 → −5.8% on BB/HBP/hit rates (5.8 yr older than average).

Result: wOBA .450 → .290; ISO .385 → .237; BABIP .375 → .249. 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 AAAOklahoma City Dodgers · 312 PAwOBA .340 → .261 (−78)K% 16.0% → 21.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.03%	÷0.970	×1.290	—	—	21.32%
BB% (unintentional) /PA	5.45%	÷1.021	×0.710	—	×0.992	3.76%
HBP% /PA	1.28%	—	×0.980	—	×0.992	1.25%
Singles /BIP	21.43%	÷0.992	×0.900	×0.950	×0.992	18.32%
Doubles /BIP	10.08%	÷1.029	×0.810	×0.950	×0.992	7.48%
Triples /BIP	0.42%	÷1.020	×0.810	×0.950	×0.992	0.31%
Home runs /BIP	2.94%	÷1.020	×0.780	—	×0.992	2.23%

Factors used: league row PCL. Park (home-season share, regressed): HR 104, 1B 98, 2B 106, 3B 104, K 94, BB 104 — applied at half strength. Age: age 28 vs a level average of 27.2 → −0.8% on BB/HBP/hit rates (0.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .340 → .261; ISO .163 → .118; BABIP .325 → .264. 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 AAAOklahoma City Dodgers · 240 PAwOBA .359 → .286 (−73)K% 15.0% → 19.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.00%	÷1.000	×1.290	—	—	19.35%
BB% (unintentional) /PA	5.42%	÷1.017	×0.710	—	×1.003	3.79%
HBP% /PA	1.67%	—	×0.980	—	×1.003	1.64%
Singles /BIP	23.53%	÷0.978	×0.900	×0.964	×1.003	20.95%
Doubles /BIP	8.56%	÷1.038	×0.810	×0.964	×1.003	6.46%
Triples /BIP	0.53%	÷1.150	×0.810	×0.964	×1.003	0.36%
Home runs /BIP	3.74%	÷0.989	×0.780	—	×1.003	2.96%

Factors used: league row PCL. Park (home-season share, regressed): HR 98, 1B 96, 2B 108, 3B 130, K 100, BB 103 — applied at half strength. Age: age 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.964.

Result: wOBA .359 → .286; ISO .175 → .130; BABIP .339 → .286. 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 AATulsa Drillers · 141 PAwOBA .383 → .313 (−70)K% 9.2% → 11.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	9.22%	÷0.955	×1.220	—	—	11.77%
BB% (unintentional) /PA	10.64%	÷1.058	×0.700	—	×0.978	6.89%
HBP% /PA	0.00%	—	×0.870	—	×0.978	0.00%
Singles /BIP	28.83%	÷1.005	×0.920	×0.989	×0.978	25.54%
Doubles /BIP	6.31%	÷1.000	×0.840	×0.989	×0.978	5.12%
Triples /BIP	0.00%	÷1.150	×0.940	×0.989	×0.978	0.00%
Home runs /BIP	2.70%	÷1.295	×0.800	—	×0.978	1.63%

Factors used: league row TL. Park (home-season share, regressed): HR 159, 1B 101, 2B 100, 3B 130, K 91, BB 112 — applied at half strength. Age: age 27 vs a level average of 24.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.989.

Result: wOBA .383 → .313; ISO .129 → .093; BABIP .358 → .309. 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 AATulsa Drillers · 297 PAwOBA .316 → .283 (−33)K% 14.8% → 18.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.81%	÷0.996	×1.220	—	—	18.14%
BB% (unintentional) /PA	8.42%	÷0.935	×0.700	—	×0.988	6.22%
HBP% /PA	1.01%	—	×0.870	—	×0.988	0.87%
Singles /BIP	19.37%	÷0.990	×0.920	×1.048	×0.988	18.64%
Doubles /BIP	8.11%	÷0.926	×0.840	×1.048	×0.988	7.61%
Triples /BIP	0.90%	÷0.900	×0.940	×1.048	×0.988	0.97%
Home runs /BIP	2.25%	÷1.020	×0.800	—	×0.988	1.75%

Factors used: league row TL. Park (home-season share, regressed): HR 104, 1B 98, 2B 85, 3B 80, K 99, BB 87 — applied at half strength. Age: age 26 vs a level average of 24.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.048.

Result: wOBA .316 → .283; ISO .139 → .124; BABIP .286 → .273. 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 ROKAZL Dodgers · 18 PAwOBA .408 → .298 (−109)K% 5.6% → 8.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	5.56%	÷1.000	×1.440	—	—	8.00%
BB% (unintentional) /PA	5.56%	÷1.000	×0.620	—	×0.940	3.24%
HBP% /PA	0.00%	—	×0.720	—	×0.940	0.00%
Singles /BIP	18.75%	÷1.000	×0.820	—	×0.940	14.45%
Doubles /BIP	0.00%	÷1.000	×0.720	—	×0.940	0.00%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.940	0.00%
Home runs /BIP	12.50%	÷1.000	×0.780	—	×0.940	9.16%

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 26 vs a level average of 19.5 → −6.0% on BB/HBP/hit rates (6.5 yr older than average).

Result: wOBA .408 → .298; ISO .353 → .258; BABIP .214 → .159. 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
#1Sean Rodríguezlast yr '19 career totals — 11 seasons, 2,871 PA	4.3	2,871	79	42	226	302	380	+10	+16	8.1	8.5
/162	664	18	10	+2.3	+3.7	1.9	pk7: 9
#2Gordon Beckhamlast yr '19 career totals — 10 seasons, 3,764 PA	5.7	3,764	80	34	237	301	368	+13	+19	8.2	8.4
/162	664	14	6	+2.4	+3.4	1.4	pk7: 9
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 9 projected seasons	3.8	2,500	66	17	246	304	386	+7	+21	5.6	5.6
/162	664	17	4	+1.9	+5.5	1.5	pk7: 6
#3Jack Brohamer'72-'80 * career totals — 9 seasons, 2,795 PA	4.2	2,795	30	9	246*	309*	364*	+7	+23	4.8	5.5
/162	664	7	2	+1.6	+5.4	1.1	pk7: 6
#4Ed Spiezio'64-'72 * career totals — 7 seasons, 1,716 PA	2.6	1,716	39	16	238*	304*	389*	+5	+8	4.7	4.9
/162	664	15	6	+1.9	+3.3	1.8	pk7: 5
#5Keith Lockhart'94-'03 * career totals — 10 seasons, 2,529 PA	3.8	2,529	44	30	249*	304*	372*	+6	+16	3.9	4.5
/162	664	12	8	+1.7	+4.1	1.0	pk7: 5
#6Dustin Ackleylast yr '16 career totals — 6 seasons, 2,347 PA	3.5	2,347	46	31	241	304	367	-5	+7	3.8	3.8
/162	664	13	9	-1.3	+1.9	1.1	pk7: 4

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
Kyle Farmer (OGILVIE)	36	45	45	40	45	227/282/344	117	274	2	1	21%	6%	78	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Humberto Quintero 2015 · MLB	35	47	44→45	41→40	38	233/263/350	118	284	11	5	22%	3%	70	-0.8	225/257/325	100	280	10	7	23%	3%	63	-1.4	220/242/296	76	267	11	3	22%	2%	47	-1.3
✕Lou Merloni 2007 · MLB	36	48→44	42→45	40	46	234/291/341	107	271	9	4	17%	6%	79	-0.2	215/270/303	88	250	7	5	16%	6%	63	-1.4	201/254/264	63	234	3	1	15%	6%	45	-2.0
✕Jamie Burke 2008 · MLB	36	49→45	43→45	40→30	46	237/286/347	110	262	10	3	15%	5%	79	-0.2	225/275/317	92	264	8	5	17%	5%	68	-1.0	203/251/265	62	245	4	1	18%	5%	46	-0.6
✕Jonathan Aceves 2014 · AAA	36	41	47→50	44→30	44	210/261/340	131	253	15	5	24%	6%	68	-1.0	220/279/335	115	266	13	3	22%	6%	74	-0.6	228/295/332	104	273	11	1	20%	7%	78	-0.2
✕Issmael Salas 2017 · AAA	35	48	42→45	42→50	44	236/275/342	107	266	10	7	16%	4%	73	-0.6	233/279/343	110	256	11	6	14%	5%	75	-0.5	231/277/333	102	249	11	3	12%	5%	71	-0.5
✕Nick Green 2013 · MLB	34	42→46	46→50	42→45	41	215/261/349	134	257	14	5	23%	4%	70	-0.8	201/249/317	116	260	13	6	27%	5%	59	-1.7	161/207/246	84	213	10	1	29%	4%	24	-2.9
✕Iker Franco 2017 · AAA	36	51→47	41→50	43→40	47	245/299/336	91	296	9	4	20%	7%	80	-0.1	221/273/327	106	279	12	7	24%	6%	70	-0.9	156/195/247	91	190	13	0	26%	5%	19	-0.9
✕Hernando Arredondo 2014 · AAA	37	46→53	47→50	41→50	40	235/262/371	136	267	15	6	19%	3%	76	-0.4	229/267/341	112	272	12	5	20%	4%	70	-0.8	225/265/311	86	270	10	2	20%	4%	59	-0.5
✕Gary Bennett 2007 · MLB	35	46	42→40	43→40	50	223/281/323	100	253	10	4	17%	7%	72	-0.7	234/286/354	120	252	13	7	13%	6%	80	-0.1	241/277/321	80	257	7	4	9%	4%	69	-0.3
✕Matt Treanor 2011 · MLB	35	44	42→40	42→40	51	217/292/318	101	250	11	5	18%	8%	75	-0.5	213/311/316	103	260	10	7	21%	11%	82	+0.0	192/310/272	79	243	7	5	22%	12%	71	-0.3
✕Sean Kazmar Jr. 2021 · AAA	36	44→51	44→45	45	44	216/261/327	112	241	12	5	17%	5%	65	-1.2	201/244/317	116	234	14	9	21%	5%	56	-1.9	160/194/251	91	179	13	6	20%	4%	20	-2.1
✕Doug Bernier 2017 · AAA	37	46→52	40	42→45	44	223/276/313	90	281	9	7	24%	6%	67	-1.1	214/268/306	92	282	9	7	26%	6%	63	-1.4	186/236/233	47	249	5	0	26%	5%	31	-1.6
✕Juan Castro 2008 · MLB	36	48	41→50	43→40	45	230/265/335	105	262	8	4	16%	5%	68	-1.0	222/269/308	86	262	8	4	18%	6%	63	-1.4	215/260/273	58	256	4	0	17%	6%	51	-0.6
✕Mike DiFelice 2006 · MLB	37	40	48→50	42→30	45	210/270/351	141	249	16	5	23%	7%	74	-0.5	214/272/317	103	279	10	4	26%	6%	67	-1.1	208/260/284	76	277	6	0	26%	5%	54	-0.8
✕Bobby Wilson 2018 · MLB	35	39→49	46→50	44→40	42	205/255/327	122	252	16	3	26%	6%	63	-1.4	194/249/313	119	246	14	4	26%	7%	57	-1.8	158/214/253	96	199	11	0	27%	7%	30	-1.1
✕Rolando Acosta 2019 · AAA	36	45→55	41→50	42→45	44	217/278/310	93	256	9	8	19%	5%	68	-1.0	219/261/318	99	271	10	9	22%	5%	63	-1.4	198/215/243	45	243	5	0	21%	2%	25	-0.9
✕Clint Barmes 2015 · MLB	36	45→55	42→55	41→50	43	220/265/318	99	259	10	4	20%	5%	64	-1.3	220/270/334	114	272	9	5	22%	5%	70	-0.9	209/250/316	107	266	7	0	23%	3%	58	-0.5
✕Hector Hurtado 2008 · AAA	37	46	42→40	41→30	38	226/266/322	96	282	10	3	24%	3%	65	-1.2	213/251/291	78	270	7	4	23%	3%	52	-2.2	206/236/255	49	259	4	0	22%	2%	34	-1.0
✕Tim Laker 2005 · MLB	35	45	46→45	44→45	44	228/274/350	123	271	14	7	22%	6%	75	-0.5	200/251/311	111	257	11	4	26%	6%	58	-1.7	176/227/272	96	230	9	0	27%	6%	37	-1.6
✕John Flaherty 2004 · MLB	36	50→52	46→45	44→40	45	246/284/384	137	274	13	5	16%	5%	86	+0.3	228/270/380	152	256	17	5	19%	5%	80	-0.1	202/234/347	145	222	18	0	19%	3%	61	-0.3

Kyle Farmer

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps