Brandon Nimmo — OGILVIE

Brandon NimmoLF Texas Rangers

Age 33 L/R 6'1" / 206 lbs MLB K +3% Svc 9.244 · Ctrl thru 2030 peak 3.3 · 2026

wRC+†vL 114136vR 122

AVG/OBP/SLG.259 / .341 / .442

PA572

HR22

SB8

K%22

BB%10

xwOBA.363

Barrel%11.8%

MLB%100%

Scouting · now → future

HIT

50→50

PWR

50→50

SPD

50→50

EYE

55→55

trajectory · 10 yrs

2.5peak

2026

Contract

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

Status FA

MLB Debut 2016

Service 9.244 yrs.days

Team Control Through 2030

First FA Year 2031

NTC

Year	Status	Salary	Proj WAR	Value	Surplus
2026	Ext / FA-deal	$20M	+3.3	$26M	+$6M
2027	Ext / FA-deal	$20M	+2.1	$17M	-$3M
2028	Ext / FA-deal	$20M	+1.3	$11M	-$9M
2029	Ext / FA-deal	$20M	+0.7	$3M	-$17M
2030	Ext / FA-deal	$20M	—	—	—
Totals		$101M		$58M	-$43M

Underwater contract
Projected production over the remaining contract is worth -$43M less than the salary owed. Most often this reflects an aging-curve fade that was visible at signing — the team paid a premium for the early years.

Career Projections (MLE)

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2026 = actual YTD + projected ROS + total. 2027+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	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
2011	18	ROK	Kingsport Mets	44	40	5	0	0	1	4	20	0	0	0	.125	.205	.200	.405	.075	.211	45	9	.207	17	-4	+0	+0	-0	+1	-0.3
2013	20	A	Savannah Sand Gnats	480	422	93	13	6	2	44	174	11	10	7	.220	.310	.294	.604	.073	.367	36	9	.270	65	-19	-1	+0	-5	+14	-1.2
2014	21	AA	3 teams	656	582	138	23	7	10	67	167	4	16	5	.237	.320	.352	.672	.115	.315	25	10	.298	86	-10	+1	+0	-7	+19	0.3
2015	22	AA	3 teams	434	392	92	13	4	4	32	102	8	5	6	.235	.306	.319	.624	.084	.306	24	7	.278	71	-14	-1	+0	-5	+12	-0.8
2016	23	AAA	2 teams	524	478	137	19	7	9	39	117	4	7	8	.287	.345	.412	.758	.126	.363	22	7	.328	109	+5	-2	-0	-6	+15	1.3
2017	24	MLB	3 teams	436	369	82	23	2	8	60	133	4	2	0	.222	.337	.360	.698	.138	.322	31	14	.312	97	-1	+0	+0	-5	+12	0.7
2018	25	MLB	New York Mets	535	433	120	31	7	18	80	140	22	9	6	.277	.415	.506	.921	.229	.371	26	15	.400	164	+39	-1	+1	-6	+15	4.9
2019	26	MLB	3 teams	315	251	53	13	2	8	54	84	6	6	1	.211	.363	.375	.738	.163	.278	27	17	.331	112	+4	+1	-0	+1	+9	1.5
2020	27	MLB	New York Mets	225	186	54	7	5	8	33	43	6	1	2	.290	.413	.511	.924	.220	.341	19	15	.412	173	+19	-1	-2	+1	+6	2.4
2021	28	MLB	2 teams	422	356	100	18	4	8	57	83	7	5	4	.281	.390	.421	.812	.140	.347	20	14	.360	134	+16	-1	+2	+2	+12	3.2
2022	29	MLB	New York Mets	673	580	165	33	7	16	71	116	16	3	2	.284	.378	.448	.826	.164	.330	17	11	.359	133	+25	-0	+2	+2	+19	5.0
2023	30	MLB	New York Mets	682	592	166	31	7	24	74	146	11	3	3	.280	.371	.478	.849	.198	.333	21	11	.366	138	+30	-1	-1	+2	+19	5.1
2024	31	MLB	New York Mets	663	571	128	24	2	23	77	158	12	15	0	.224	.329	.394	.723	.170	.267	24	12	.318	102	+1	+3	-2	-7	+19	1.4
2025	32	MLB	New York Mets	652	587	148	27	0	24	50	141	7	13	1	.252	.318	.421	.739	.169	.289	22	8	.324	106	+4	+2	-2	-7	+18	1.6
▸ 2026 Season (actual · ROS · total)
2026	33	MLB	Texas Rangers	115	102	31	7	1	4	11	24	2	1	0	.304	.383	.510	.892	.206	.365	21	10	.383	151	+7	+0	-1	-1	+3	0.8
ROS	33	MLB	TEX	457	403	109	21	2	17	44	100	7	7	2	.270	.352	.459	.811	.189	.318	22	10	.358	132	+17	+1	-1	-5	+13	2.5
TOT	33	MLB	TEX	572	505	140	28	3	21	55	124	9	8	2	.277	.359	.469	.828	.192	.329	22	10	.363	136	+23	+1	-2	-6	+16	3.3
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	34	MLB	TEX	523	460	123	23	3	19	50	95	8	7	1	.267	.349	.454	.804	.187	.294	18	10	.351	127	+16	+1	-6	-6	+15	2.0
2028	35	MLB	TEX	467	413	106	20	2	16	44	90	7	5	1	.257	.338	.431	.769	.174	.292	19	9	.343	120	+11	+1	-7	-5	+13	1.3
2029	36	MLB	TEX	405	358	90	17	2	13	38	82	6	4	0	.251	.333	.419	.752	.168	.289	20	9	.333	113	+6	+1	-7	-4	+11	0.7
2030	37	MLB	TEX	339	300	73	13	2	10	31	72	5	3	0	.243	.324	.400	.724	.157	.285	21	9	.322	105	+2	+1	-8	-4	+10	0.0
2031	38	MLB	TEX	269	239	56	10	1	7	24	59	4	1	0	.234	.315	.372	.687	.138	.280	22	9	.310	96	-1	+0	-8	-3	+8	-0.5
2032	39	MLB	TEX	194	172	40	7	1	5	17	44	3	0	0	.233	.312	.372	.685	.140	.274	23	9	.298	87	-3	+0	-9	-2	+5	-0.9
▸ Career Totals (MLE all levels + projections)
Career	—			9395	8184	2078	386	73	250	990	2166	158	122	49	.254	.346	.411	.756	.157	.315	23	11	.333	113	+141	+5	-49	-68	+266	30.2
/ 162G	—			650	566	144	27	5	17	68	150	11	8	3	.254	.346	.410	.756	.155	.316	23	10	.333	113	+10	+0	-3	-5	+18	2.1

Historical Stats — Raw (Per Stint)

Actual MLB + MiLB stats as they happened, one row per stint at each level. Use this to see what really got recorded; the table above shows MLB-equivalent translations + projections.

Year	Age	Lvl	Team	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
2011	18	ROK	Kingsport Mets	44	38	8	0	0	2	6	14	0	0	0	.211	.318	.368	.687	.158	.273	32	14	.313	98	-0	+0	—	—	+1	0.1
2013	20	A	Savannah Sand Gnats	480	395	108	16	6	2	71	131	11	10	7	.273	.398	.359	.758	.086	.402	27	15	.350	126	+14	-1	—	—	+14	2.7
2014	21	AA	Binghamton Mets	279	240	57	12	4	6	36	54	1	5	1	.237	.339	.396	.735	.158	.283	19	13	.329	110	+3	+1	—	—	+8	1.2
2014	21	A+	St. Lucie Mets	279	227	73	9	5	4	50	51	2	9	3	.322	.448	.458	.906	.137	.401	18	18	.409	171	+22	+1	—	—	+8	3.2
2014	21	INTL	Scottsdale Scorpions	98	84	17	3	0	0	12	28	1	2	1	.202	.309	.238	.547	.036	.298	29	12	.262	58	-5	+0	—	—	+3	-0.2
2015	22	AAA	Las Vegas 51s	112	91	24	3	1	3	18	20	2	5	4	.264	.396	.418	.814	.154	.304	18	16	.367	139	+5	-1	—	—	+3	0.8
2015	22	AA	Binghamton Mets	302	269	75	12	3	2	26	55	6	0	2	.279	.355	.368	.724	.089	.343	18	9	.329	110	+3	-1	—	—	+9	1.1
2015	22	A+	St. Lucie Mets	20	16	2	1	0	0	4	3	0	0	0	.125	.300	.188	.487	.062	.154	15	20	.249	49	-1	+0	—	—	+1	-0.1
2016	23	MLB	New York Mets	80	73	20	1	0	1	6	20	1	0	0	.274	.338	.329	.666	.055	.365	25	8	.307	93	-1	+0	-0	-6	+2	-0.4
2016	23	AAA	Las Vegas 51s	444	392	138	25	8	11	46	73	3	7	8	.352	.424	.541	.965	.189	.411	16	10	.422	181	+41	-2	—	—	+13	5.2
2017	24	MLB	New York Mets	215	177	46	11	1	5	33	60	2	2	0	.260	.382	.418	.800	.158	.360	28	15	.358	132	+8	+0	+0	-5	+6	1.0
2017	24	AAA	Las Vegas 51s	198	163	37	12	1	3	33	49	2	0	0	.227	.364	.368	.732	.141	.306	25	17	.337	116	+4	+0	—	—	+6	0.9
2017	24	A+	St. Lucie Mets	23	18	4	2	0	1	5	4	0	0	0	.222	.391	.500	.891	.278	.231	17	22	.393	159	+2	+0	—	—	+1	0.2
2018	25	MLB	New York Mets	535	433	114	28	8	17	80	140	22	9	6	.263	.404	.483	.886	.219	.351	26	15	.395	161	+37	-1	+1	-6	+15	4.7
2019	26	MLB	New York Mets	254	199	44	11	1	8	46	71	5	3	0	.221	.380	.407	.787	.186	.293	28	18	.354	129	+8	+1	-0	+1	+7	1.8
2019	26	AAA	Syracuse Mets	44	35	7	2	0	1	8	8	1	3	0	.200	.364	.343	.706	.143	.231	18	18	.331	112	+1	+1	—	—	+1	0.2
2019	26	A+	St. Lucie Mets	17	14	3	0	1	0	3	2	0	0	1	.214	.353	.357	.710	.143	.250	12	18	.325	107	+0	-0	—	—	+0	0.0
2020	27	MLB	New York Mets	225	186	52	8	3	8	33	43	6	1	2	.280	.404	.484	.888	.204	.326	19	15	.396	161	+16	-1	-2	+1	+6	2.1
2021	28	MLB	New York Mets	386	325	95	17	3	8	54	79	5	5	4	.292	.401	.437	.838	.145	.366	20	14	.376	146	+20	-1	+2	+2	+11	3.5
2021	28	AAA	Syracuse Mets	36	29	5	1	0	0	5	3	2	0	0	.172	.333	.207	.540	.034	.192	8	14	.274	68	-1	+0	—	—	+1	-0.0
2022	29	MLB	New York Mets	673	580	159	30	7	16	71	116	16	3	2	.274	.369	.433	.802	.159	.317	17	11	.357	131	+24	-0	+2	+2	+19	4.9
2023	30	MLB	New York Mets	682	592	162	30	6	24	74	146	11	3	3	.274	.365	.466	.831	.193	.324	21	11	.367	139	+30	-1	-1	+2	+19	5.1
2024	31	MLB	New York Mets	663	571	128	25	3	23	77	158	12	15	0	.224	.329	.399	.728	.175	.267	24	12	.327	109	+7	+3	-2	-7	+19	1.9
2025	32	MLB	New York Mets	652	587	154	27	0	25	50	141	7	13	1	.262	.328	.436	.764	.174	.301	22	8	.336	115	+11	+2	-2	-7	+18	2.3
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			4365	3723	974	188	32	135	524	974	87	54	18	.262	.366	.438	.804	.176	.318	22	12	.358	132	+159	+4	-1	-22	+124	26.9

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
Brandon Nimmo (OGILVIE)	33	50	50	50	55	.268/.350/.455	.188	.296	21	9	17%	10%	132	+3.8	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Jacque Jones 2008 · MLB	33	54→61	51→60	49→50	49	.272/.327/.441	.169	.307	19	10	18%	7%	118	+3.0	.245/.299/.363	.118	.295	10	7	20%	7%	85	+0.7	.219/.263/.299	.080	.289	5	4	25%	5%	49	-0.8
✕Alex Dickerson 2022 · MLB	32	49→54	56→55	48→45	48	.255/.326/.453	.198	.293	24	4	22%	8%	121	+3.2	.222/.282/.386	.164	.268	20	5	25%	7%	85	+0.7	.196/.249/.341	.145	.238	17	1	25%	6%	56	-0.8
✕David Peralta 2021 · MLB	33	56→59	54→60	50→45	49	.284/.341/.468	.185	.328	22	4	20%	8%	131	+3.9	.260/.320/.406	.146	.312	12	4	20%	8%	105	+2.1	.253/.313/.395	.142	.302	11	3	19%	7%	93	+1.0
✕Midre Cummings 2005 · MLB	33	50	52→50	51→50	50	.255/.331/.425	.170	.297	19	11	21%	8%	116	+2.8	.245/.309/.405	.160	.307	20	5	26%	7%	102	+1.8	.236/.298/.387	.150	.297	20	0	27%	7%	95	+0.7
●Brian Daubach 2005 · MLB	33	50→52	53→60	47→40	55	.250/.342/.431	.181	.309	20	5	25%	12%	122	+3.3	.249/.329/.421	.172	.293	19	4	21%	10%	114	+2.7	.247/.327/.417	.171	.287	20	1	21%	10%	111	+1.5
✕Jody Gerut 2009 · MLB	31	54→56	55	50	52	.275/.331/.465	.190	.290	22	12	15%	8%	126	+3.5	.250/.305/.413	.163	.269	18	10	15%	7%	102	+1.8	.234/.288/.381	.147	.251	16	7	14%	7%	82	+0.2
●Adam Lind 2016 · MLB	33	56→61	54→60	46→40	56	.283/.356/.467	.184	.317	21	2	18%	10%	137	+4.3	.260/.320/.446	.186	.289	24	2	19%	8%	117	+2.9	.245/.296/.426	.181	.269	25	1	20%	7%	95	+0.8
✕John Mabry 2004 · MLB	33	47	54→60	46→30	51	.243/.317/.425	.181	.273	22	5	20%	8%	110	+2.4	.252/.321/.428	.176	.297	21	3	22%	9%	112	+2.6	.242/.310/.404	.162	.290	20	0	23%	9%	96	+0.6
✕Ricky Ledee 2006 · MLB	32	50→47	53→60	50	54	.254/.332/.434	.180	.296	20	5	21%	10%	118	+3.0	.233/.295/.379	.146	.281	16	5	22%	8%	89	+0.9	.215/.269/.337	.122	.265	15	2	25%	6%	65	-0.4
●Dexter Fowler 2019 · MLB	33	48→58	52→55	51→55	59	.243/.344/.422	.179	.288	19	11	22%	12%	121	+3.2	.238/.334/.413	.175	.291	21	9	24%	12%	115	+2.7	.240/.345/.423	.183	.295	23	8	25%	12%	119	+1.7
●Mark Canha 2022 · MLB	33	50→57	54→60	52→50	60	.252/.374/.438	.187	.295	21	9	21%	13%	137	+4.3	.255/.359/.399	.144	.299	15	9	19%	10%	121	+3.2	.255/.356/.383	.128	.300	13	8	18%	10%	112	+2.2
✕Eric Hinske 2011 · MLB	33	48→55	56→60	47→50	54	.250/.337/.450	.200	.290	23	7	22%	11%	124	+3.4	.230/.308/.388	.158	.292	18	3	26%	10%	97	+1.5	.213/.291/.351	.138	.274	16	0	27%	10%	72	-0.1
✕Juan Miranda 2016 · AAA	33	55→61	52→55	45→40	55	.274/.372/.440	.167	.323	21	5	21%	10%	137	+4.3	.240/.329/.376	.136	.298	15	6	23%	9%	102	+1.9	.220/.303/.354	.134	.276	16	4	25%	9%	84	+0.2
●Hunter Pence 2016 · MLB	33	54→63	55→60	52→50	49	.277/.332/.470	.193	.309	23	13	19%	8%	128	+3.6	.268/.325/.428	.160	.316	19	6	21%	8%	114	+2.7	.263/.318/.401	.139	.314	16	4	21%	7%	99	+1.3
✕Matt Joyce 2018 · MLB	33	44→54	56→60	42→50	60	.232/.338/.430	.198	.264	24	4	22%	13%	120	+3.1	.247/.348/.416	.169	.293	20	4	21%	13%	121	+3.2	.251/.359/.382	.131	.309	15	1	22%	14%	111	+0.9
✕Seth Smith 2017 · MLB	34	50→56	52→60	46→50	57	.253/.343/.430	.177	.292	18	2	20%	11%	122	+3.3	.254/.337/.427	.173	.299	20	5	21%	10%	119	+3.1	.256/.340/.425	.169	.303	19	3	21%	10%	111	+1.6
●Roberto Mendez 2006 · AAA	33	55→59	54→50	43→45	56	.280/.357/.461	.181	.315	21	6	18%	10%	135	+4.2	.272/.355/.418	.146	.314	16	8	18%	12%	123	+3.3	.264/.355/.389	.124	.304	14	8	17%	12%	115	+1.8
✕Corey Hart 2014 · MLB	32	50→56	56→60	47→55	48	.260/.326/.456	.196	.304	24	7	23%	8%	122	+3.3	.223/.281/.375	.152	.275	18	6	25%	6%	82	+0.5	.197/.252/.330	.132	.243	17	3	26%	5%	53	-0.5
●Alex Gordon 2017 · MLB	33	50→60	51→55	46→50	53	.252/.343/.415	.163	.309	19	8	24%	10%	118	+3.0	.236/.320/.372	.136	.290	15	9	23%	9%	98	+1.6	.247/.329/.374	.127	.290	14	7	19%	9%	96	+1.1
●Raul Ibanez 2004 · MLB	32	56→61	54→60	46→45	53	.286/.343/.479	.192	.303	21	6	14%	8%	134	+4.1	.289/.348/.465	.176	.313	20	5	14%	8%	133	+4.0	.288/.354/.487	.199	.314	23	1	16%	9%	131	+4.4

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)