Francisco Toledo

Francisco ToledoC St. Lucie Mets

Age 21 R/R 5'9" / 160 lbs A H +5%HR +3% Svc 0.0 · Ctrl thru 2036 peak 2.2 · 2032

wRC+†58

AVG/OBP/SLG.209 / .274 / .306

PA89

HR1

K%29

BB%7

MLB%0%

trajectory · 10 yrs

2.1peak

2031

Contract

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

Status MiLB

MLB Debut 2031

Service 0 yrs (est)

Team Control Through 2036

First FA Year 2037

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2031
2027	MiLB	still in minors · estimated debut 2031
2028	MiLB	still in minors · estimated debut 2031
2029	MiLB	still in minors · estimated debut 2031
2030	MiLB	still in minors · estimated debut 2031
2031	Arb-3	$0.9M	+2.1	$19M	+$19M
2032	Ext / FA-deal	$0.9M	+2.2	$21M	+$20M
2033	Ext / FA-deal	$1.0M	+2.0	$20M	+$19M
2034	Ext / FA-deal	$4M	+1.8	$18M	+$15M
2035	Ext / FA-deal	$5M	+1.6	$17M	+$11M
2036	Ext / FA-deal	$6M	+1.3	$14M	+$8M
Totals		$18M		$109M	+$91M

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
2022	17	ROK	DSL Mets 2	46	43	10	1	1	1	2	10	1	4	1	.233	.283	.372	.655	.140	.281	22	4	.259	56	-2	+0	+0	+1	+1	0.0
2024	19	ROK	FCL Mets	104	95	17	1	0	0	8	33	1	1	0	.179	.250	.189	.439	.011	.274	32	8	.199	11	-11	+0	+0	+2	+3	-0.6
2025	20	ROK	FCL Mets	80	72	11	2	0	0	8	19	0	0	1	.153	.237	.181	.418	.028	.208	24	10	.200	11	-8	-0	+0	+1	+2	-0.5
▸ 2026 Season (actual · ROS · total)
2026	21	A	St. Lucie Mets	20	17	3	0	0	0	3	7	0	0	1	.176	.300	.176	.476	.000	.300	35	15	.249	49	-1	-0	+0	+0	+1	-0.1
ROS	21	MLB	NYM	69	63	12	2	0	1	5	20	1	1	0	.190	.261	.270	.531	.079	.288	29	7	.265	61	-3	+0	+0	+1	+2	0.0
TOT	21	MLB	NYM	89	80	15	2	0	1	8	27	1	1	1	.188	.270	.250	.520	.062	.269	30	9	.262	58	-4	-0	+0	+2	+3	-0.0
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	22	MLB 11%	NYM	191	172	38	7	1	4	15	52	2	3	1	.221	.291	.343	.634	.122	.290	27	8	.285	76	-5	+0	+0	+3	+5	0.4
2028	23	MLB 28%	NYM	306	274	62	11	2	7	26	81	3	5	1	.226	.300	.358	.658	.131	.292	26	8	.296	85	-5	+1	+0	+5	+9	1.0
2029	24	MLB 45%	NYM	388	348	79	14	2	10	33	101	4	7	1	.227	.301	.365	.666	.138	.292	26	9	.304	91	-4	+1	+0	+7	+11	1.5
2030	25	MLB 60%	NYM	435	390	91	16	3	12	38	112	4	7	2	.233	.308	.382	.690	.149	.293	26	9	.309	94	-3	+1	+0	+8	+12	1.8
2031	26	MLB 77%	NYM	463	413	97	17	3	13	42	120	5	8	2	.235	.313	.385	.698	.150	.294	26	9	.311	96	-2	+1	+0	+8	+13	2.1
2032	27	MLB 92%	NYM	476	425	99	17	3	14	43	123	5	8	1	.233	.311	.386	.697	.153	.294	26	9	.311	96	-2	+1	+0	+8	+13	2.2
2033	28	MLB	NYM	479	427	98	17	3	13	44	125	5	7	1	.230	.309	.375	.684	.145	.294	26	9	.310	95	-3	+1	-1	+9	+14	2.0
2034	29	MLB	NYM	474	422	97	17	3	13	44	125	5	6	1	.230	.310	.377	.687	.147	.293	26	9	.308	94	-3	+1	-1	+8	+13	1.8
2035	30	MLB	NYM	467	417	95	16	3	13	43	125	4	5	0	.228	.306	.374	.680	.146	.291	27	9	.305	91	-5	+1	-2	+8	+13	1.6
2036	31	MLB	NYM	441	393	88	15	2	12	41	120	4	3	0	.224	.304	.364	.668	.140	.290	27	9	.301	88	-6	+1	-3	+8	+12	1.3
2037	32	MLB	NYM	412	367	81	14	2	10	38	114	4	1	0	.221	.301	.351	.652	.131	.288	28	9	.296	85	-7	+0	-4	+7	+12	0.9
2038	33	MLB	NYM	372	332	72	12	2	9	34	106	3	0	0	.217	.295	.346	.642	.130	.287	28	9	.291	81	-8	+0	-4	+7	+11	0.5
2039	34	MLB	NYM	321	286	61	10	2	7	29	94	3	0	0	.213	.292	.336	.628	.122	.285	29	9	.284	76	-9	+0	-5	+6	+9	0.1
2040	35	MLB	NYM	264	236	49	8	1	6	24	80	2	0	0	.208	.286	.326	.613	.119	.283	30	9	.277	70	-9	+0	-6	+5	+7	-0.2
2041	36	MLB	NYM	208	186	37	6	1	4	18	65	2	0	0	.199	.277	.306	.583	.108	.280	31	9	.268	63	-9	+0	-6	+4	+6	-0.5
▸ Career Totals (MLE all levels + projections)
Career	—			5996	5361	1194	203	34	149	535	1625	58	66	12	.223	.300	.357	.657	.134	.289	27	9	.296	85	-103	+8	-31	+107	+170	15.4
/ 162G	—			650	581	130	22	4	16	58	176	6	7	1	.224	.301	.358	.659	.134	.291	27	9	.296	85	-11	+1	-3	+12	+18	1.7

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
2022	17	ROK	DSL Mets 2	46	41	12	1	1	1	4	7	1	4	1	.293	.370	.439	.809	.146	.333	15	9	.362	135	+2	+0	—	—	+1	0.4
2024	19	ROK	FCL Mets	104	89	20	1	0	0	14	22	1	1	0	.225	.337	.236	.572	.011	.299	21	13	.279	71	-3	+0	—	—	+3	-0.0
2025	20	ROK	FCL Mets	80	68	15	3	0	0	12	13	0	0	1	.221	.338	.265	.602	.044	.273	16	15	.289	79	-2	-0	—	—	+2	-0.0

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
Francisco Toledo (OGILVIE)	21	—	—	—	—	.209/.274/.306	.097	.288	1	1	29%	7%	61	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Agustín Ramírez 2023 · A	21	43→45	45→55	50	43	.213/.273/.339	.126	.289	12	10	30%	7%	69	-0.4	.229/.292/.389	.160	.276	19	13	24%	8%	90	+1.0	.230/.293/.405	.176	.264	22	16	22%	7%	92	+1.1
●Chun-Hsiu Chen 2010 · A	21	43→53	41→50	48→45	40	.209/.263/.306	.097	.302	8	6	32%	7%	55	-1.4	.250/.309/.388	.138	.334	12	4	27%	7%	96	+1.5	.256/.318/.393	.137	.347	12	4	28%	8%	99	+1.3
●Bo Naylor 2021 · A	21	41→43	44→55	50	43	.203/.259/.325	.122	.273	11	7	29%	7%	59	-1.1	.199/.278/.352	.153	.276	18	12	33%	9%	75	-0.0	.216/.308/.399	.183	.269	22	12	28%	11%	97	+1.2
●James McCann 2012 · A	22	41→51	42→50	49→45	39	.203/.260/.306	.103	.288	9	7	32%	6%	55	-1.4	.223/.261/.310	.087	.291	6	6	24%	4%	55	-1.4	.254/.315/.415	.161	.331	20	4	28%	7%	104	+1.1
✕Luis Torrens 2017 · A	21	43→49	41→55	46→30	47	.210/.281/.305	.094	.262	9	6	23%	8%	64	-0.8	.214/.267/.307	.093	.269	7	3	22%	6%	57	-1.2	.228/.285/.376	.148	.288	19	0	27%	7%	82	+0.3
✕Tucker Mitchell 2022 · A	21	43	39→50	51→45	39	.202/.262/.293	.090	.301	6	7	33%	6%	52	-1.6	.193/.267/.305	.112	.296	13	8	37%	7%	59	-1.1	.178/.253/.291	.113	.253	15	7	34%	7%	47	-0.8
●Hunter Goodman 2022 · A	22	46→47	42→65	50→40	43	.220/.291/.330	.111	.304	9	7	29%	7%	75	-0.0	.215/.268/.415	.200	.284	26	4	34%	6%	88	+0.9	.221/.275/.455	.234	.259	32	2	29%	6%	99	+1.4
●Derek Norris 2009 · A	20	40→50	42→55	49→50	43	.194/.269/.300	.106	.295	9	6	35%	9%	58	-1.2	.209/.301/.372	.163	.281	20	6	31%	11%	91	+1.1	.254/.332/.403	.149	.311	15	5	22%	10%	106	+1.6
●Lou Marson 2007 · A	21	44→54	40	53→50	44	.211/.271/.304	.093	.282	6	6	27%	7%	58	-1.2	.248/.316/.343	.095	.329	7	4	24%	9%	88	+0.9	.265/.339/.354	.089	.347	6	4	23%	9%	97	+1.1
●Tyler Stephenson 2019 · A	22	43→53	42→50	46→30	44	.212/.280/.315	.103	.285	10	3	28%	8%	66	-0.6	.232/.305/.347	.115	.297	11	3	24%	8%	85	+0.7	.253/.327/.399	.146	.323	16	1	25%	9%	102	+1.3
✕Blaze Alexander 2021 · A	22	45→48	42→50	51→50	43	.218/.284/.328	.110	.300	9	11	29%	7%	71	-0.3	.204/.275/.332	.128	.317	14	12	38%	7%	69	-0.4	.220/.308/.345	.126	.328	13	10	34%	8%	84	+0.4
●Francisco Cervelli 2007 · A	21	43→53	39→45	50→45	43	.205/.271/.292	.086	.286	6	7	29%	7%	56	-1.3	.237/.314/.327	.090	.313	4	5	24%	7%	83	+0.6	.252/.365/.369	.117	.312	10	4	20%	13%	113	+1.6
✕Blake Ochoa 2007 · A	21	45	40→45	46→40	44	.215/.280/.308	.092	.280	6	5	24%	6%	64	-0.8	.217/.270/.311	.094	.277	7	4	23%	6%	60	-1.0	.236/.301/.377	.140	.278	16	2	21%	7%	89	+0.3
✕Max Stassi 2012 · A	21	40→43	44→55	43→40	41	.198/.260/.309	.111	.287	12	5	34%	7%	56	-1.3	.218/.270/.362	.144	.290	17	4	30%	5%	74	-0.1	.208/.295/.359	.151	.271	20	0	30%	10%	81	+0.2
✕Eddys Leonard 2021 · A	20	42→46	40→50	46→45	45	.200/.274/.295	.095	.288	7	9	31%	8%	59	-1.1	.227/.293/.378	.151	.302	17	5	29%	7%	89	+0.9	.224/.290/.376	.152	.290	17	4	28%	6%	83	+0.5
✕Sam McWilliams 2019 · A	21	46→53	39→55	54→50	43	.215/.280/.307	.092	.311	6	14	31%	7%	63	-0.8	.213/.273/.319	.106	.326	8	10	35%	7%	63	-0.8	.244/.305/.407	.163	.380	18	10	38%	7%	98	+1.1
●Tyler Nevin 2018 · A	21	46→54	41→50	45	43	.225/.276/.329	.104	.286	8	9	24%	6%	67	-0.5	.231/.283/.339	.108	.294	10	6	24%	6%	72	-0.2	.240/.318/.386	.146	.290	17	4	22%	8%	98	+1.1
✕Jakson Reetz 2017 · A	21	43→34	39→60	47→45	44	.201/.284/.294	.093	.288	6	7	30%	8%	63	-0.8	.196/.270/.295	.099	.288	9	5	33%	7%	57	-1.2	.197/.277/.397	.201	.245	26	4	31%	7%	84	+0.3
✕Nick Hundley 2006 · A	22	46→45	41→55	50→40	42	.219/.279/.317	.098	.303	8	8	29%	7%	66	-0.6	.216/.273/.358	.142	.269	16	3	25%	7%	74	-0.1	.254/.322/.429	.174	.319	17	4	25%	8%	107	+1.2
✕Ryan McKenna 2018 · A	21	43→53	42→50	52→55	39	.210/.265/.317	.107	.297	9	12	31%	6%	59	-1.1	.226/.289/.332	.106	.311	9	12	28%	7%	73	-0.1	.218/.295/.357	.140	.319	16	13	34%	9%	80	+0.2

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)