Jonathan Rodríguez

Pos1B

B/TR/R

Born1989-08-21

Age (2027)37

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2019

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2017	27	AAA/AA2 orgs	544	.303/.413/.518	22	2	109	—	.253/.335/.421
2018	28	AAA/INTL2 orgs	411	.232/.354/.412	15	2	73	—	.195/.283/.344
2019	29	INTLAtenienses de…	19	.222/.263/.333	0	0	67	—

Contract

No contract data on file.

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)
2009	19	ROK	Johnson City Cardinals	—	197	165	51	13	1	2	29	32	3	4	1	309	421	436	858	127	374	16	15	389	82	—	—	—	—	—	—
2011	21	A	Quad Cities River Bandits	—	488	394	99	27	0	20	77	109	14	4	5	251	392	472	864	221	295	22	16	384	84	—	—	—	—	—	—
2012	22	A+	Palm Beach Cardinals	—	248	222	56	16	0	6	22	68	3	2	2	252	328	405	733	153	336	27	9	328	59	—	—	—	—	—	—
2012	22	INTL	Cangrejeros de Santurce	—	42	34	8	2	0	1	7	14	1	0	1	235	381	382	763	147	368	33	17	352	124	—	—	—	—	—	—
2013	23	A+	Palm Beach Cardinals	—	523	455	129	34	1	18	60	101	6	21	4	284	374	481	856	198	328	19	11	378	89	—	—	—	—	—	—
2013	23	INTL	Cangrejeros de Santurce	—	104	93	18	7	0	2	8	24	1	1	2	194	265	333	598	140	235	23	8	265	66	—	—	—	—	—	—
2014	24	AA	Springfield Cardinals	—	469	406	108	19	2	11	56	96	4	8	2	266	361	404	764	138	321	20	12	344	71	—	—	—	—	—	—
2014	24	INTL	Cangrejeros de Santurce	—	116	97	15	7	0	0	17	37	1	1	2	155	287	227	514	72	246	32	15	248	54	—	—	—	—	—	—
2015	25	AA	Springfield Cardinals	—	513	454	125	24	0	13	56	100	1	9	4	275	356	414	770	139	327	19	11	346	72	—	—	—	—	—	—
2015	25	INTL	Gigantes de Carolina	—	106	87	19	8	0	0	17	33	2	0	0	218	358	310	669	92	352	31	16	317	100	—	—	—	—	—	—
2016	26	AAA	Memphis Redbirds	—	145	135	35	6	0	7	10	46	0	3	1	259	310	459	770	200	341	32	7	339	59	—	—	—	—	—	—
2016	26	AA	Springfield Cardinals	—	347	302	77	14	1	8	40	86	3	1	4	255	348	387	735	132	329	25	12	332	68	—	—	—	—	—	—
2016	26	INTL	Indios de Mayaguez	—	116	105	26	13	1	0	9	26	1	0	2	248	313	390	704	143	325	22	8	312	97	—	—	—	—	—	—
2017	27	AAA	Rochester Red Wings	—	20	18	3	0	0	1	1	5	1	0	0	167	250	333	583	167	167	25	5	266	32	—	—	—	—	—	—
2017	27	AA	Chattanooga Lookouts	—	524	434	134	31	0	21	80	113	3	2	0	309	420	525	945	217	368	22	15	412	112	—	—	—	—	—	—
2018	28	AAA	New Orleans Baby Cakes	—	344	286	71	14	0	14	50	94	3	2	0	248	366	444	810	196	313	27	15	358	76	—	—	—	—	—	—
2018	28	INTL	Cangrejeros de Santurce	—	67	54	8	2	0	1	11	16	0	0	0	148	292	241	533	93	184	24	16	251	56	—	—	—	—	—	—
2019	29	INTL	Atenienses de Manati	—	19	18	4	2	0	0	1	5	0	0	1	222	263	333	596	111	308	26	5	267	67	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2009	19	ROK MLE	Johnson City Cardinals	—	197	175	43	10	1	2	19	46	3	4	1	246	330	349	679	103	311	23	10	289	82	—	—	—	—	—	—
2011	21	A MLE	Quad Cities River Bandits	—	488	425	85	22	0	17	46	139	14	4	5	200	299	372	671	172	244	28	9	293	84	—	—	—	—	—	—
2012	22	A+ MLE	Palm Beach Cardinals	—	248	229	45	13	0	6	15	99	3	2	2	197	255	332	587	135	309	40	6	255	59	—	—	—	—	—	—
2013	23	A+ MLE	Palm Beach Cardinals	—	523	473	107	29	1	15	42	147	6	21	4	226	298	387	684	161	295	28	8	300	89	—	—	—	—	—	—
2014	24	AA MLE	Springfield Cardinals	—	469	425	95	16	2	7	37	121	4	8	2	224	292	320	612	96	289	26	8	273	71	—	—	—	—	—	—
2015	25	AA MLE	Springfield Cardinals	—	513	473	110	20	0	9	37	125	1	9	4	233	290	332	622	99	292	24	7	274	72	—	—	—	—	—	—
2016	26	AAA MLE	Memphis Redbirds	—	145	138	28	5	0	5	7	60	0	3	1	203	241	348	589	145	313	41	5	255	59	—	—	—	—	—	—
2016	26	AA MLE	Springfield Cardinals	—	347	315	69	12	1	5	27	103	3	1	4	219	287	311	598	92	302	30	8	268	68	—	—	—	—	—	—
2017	27	AAA MLE	Rochester Red Wings	—	20	18	3	0	0	1	1	6	1	0	0	167	250	333	583	167	149	30	5	215	32	—	—	—	—	—	—
2017	27	AA MLE	Chattanooga Lookouts	—	524	460	118	26	0	17	54	137	3	2	0	257	338	424	762	167	314	26	10	333	112	—	—	—	—	—	—
2018	28	AAA MLE	New Orleans Baby Cakes	—	344	302	59	12	0	11	34	115	3	2	0	195	283	344	628	149	260	33	10	280	76	—	—	—	—	—	—
2009	19	ROK MLE	Johnson City Cardinals	—	197	175	43	10	1	2	19	46	3	4	1	246	330	349	679	103	323	23	10	289	82	—	—	—	—	—	—
2009	19	ROK RAW	Johnson City Cardinals	—	197	165	51	13	1	2	29	32	3	4	1	309	421	436	858	127	374	16	15	389	82	—	—	—	—	—	—
2011	21	A MLE	Quad Cities River Bandits	—	488	425	85	22	0	17	46	139	14	4	5	200	299	372	671	172	250	28	9	293	84	—	—	—	—	—	—
2011	21	A RAW	Quad Cities River Bandits	—	488	394	99	27	0	20	77	109	14	4	5	251	392	472	864	221	295	22	16	384	84	—	—	—	—	—	—
2012	22	A+ MLE	2 teams	—	290	267	52	15	0	7	18	116	4	2	3	195	256	330	586	135	310	40	6	255	59	—	—	—	—	—	—
2012	22	A+ RAW	2 teams	—	290	256	64	18	0	7	29	82	4	2	3	250	336	402	738	152	339	28	10	332	59	—	—	—	—	—	—
2013	23	A+ MLE	2 teams	—	627	565	129	35	1	18	51	177	7	22	6	228	300	389	690	161	298	28	8	300	89	—	—	—	—	—	—
2013	23	A+ RAW	2 teams	—	627	548	147	41	1	20	68	125	7	22	6	268	356	456	813	188	313	20	11	359	89	—	—	—	—	—	—
2014	24	AA MLE	2 teams	—	585	530	119	20	2	9	46	150	5	9	4	225	293	321	613	96	293	26	8	273	71	—	—	—	—	—	—
2014	24	AA RAW	2 teams	—	585	503	123	26	2	11	73	133	5	9	4	245	346	370	716	125	309	23	12	325	71	—	—	—	—	—	—
2015	25	AA MLE	2 teams	—	619	569	132	24	0	11	45	150	3	9	4	232	292	332	624	100	295	24	7	274	72	—	—	—	—	—	—
2015	25	AA RAW	2 teams	—	619	541	144	32	0	13	73	133	3	9	4	266	357	397	754	131	330	21	12	341	72	—	—	—	—	—	—
2016	26	AA MLE	3 teams	—	608	559	119	20	1	13	42	202	4	4	7	213	273	322	595	109	305	33	7	264	65	—	—	—	—	—	—
2016	26	AA RAW	3 teams	—	608	542	138	33	2	15	59	158	4	4	7	255	332	406	738	151	331	26	10	330	65	—	—	—	—	—	—
2017	27	AA MLE	2 teams	—	544	478	120	26	0	18	55	143	4	2	0	251	333	418	752	167	315	26	10	329	109	—	—	—	—	—	—
2017	27	AA RAW	2 teams	—	544	452	137	31	0	22	81	118	4	2	0	303	413	518	931	215	361	22	15	406	109	—	—	—	—	—	—
2018	28	AAA MLE	2 teams	—	411	361	71	15	0	13	40	137	3	2	0	197	282	346	628	150	269	33	10	280	76	—	—	—	—	—	—
2018	28	AAA RAW	2 teams	—	411	340	79	16	0	15	61	110	3	2	0	232	354	412	766	179	291	27	15	341	76	—	—	—	—	—	—
2019	29	INTL MLE	Atenienses de Manati	—	19	18	4	2	0	0	1	5	0	0	1	222	263	333	596	111	308	26	5	—	—	—	—	—	—	—	—
2019	29	INTL RAW	Atenienses de Manati	—	19	18	4	2	0	0	1	5	0	0	1	222	263	333	596	111	308	26	5	267	67	—	—	—	—	—	—
2009	19	ROK MLE	Johnson City Cardinals	—	197	173	43	10	1	2	19	46	3	4	1	249	330	353	683	104	311	23	10	289	82	—	—	—	—	—	—
2011	21	A MLE	Quad Cities River Bandits	—	488	425	85	22	0	17	46	139	14	4	5	200	299	372	671	172	244	28	9	293	84	—	—	—	—	—	—
2012	22	A+ MLE	2 teams	—	290	266	52	15	0	7	18	116	4	2	3	195	256	331	587	135	309	40	6	255	59	—	—	—	—	—	—
2013	23	A+ MLE	2 teams	—	627	564	129	35	1	18	51	177	7	22	6	229	300	390	690	161	295	28	8	300	89	—	—	—	—	—	—
2014	24	AA MLE	2 teams	—	585	529	119	20	2	9	46	150	5	9	4	225	293	321	614	96	289	26	8	273	71	—	—	—	—	—	—
2015	25	AA MLE	2 teams	—	619	566	132	24	0	11	45	150	3	9	4	233	292	334	626	101	292	24	7	274	72	—	—	—	—	—	—
2016	26	AA MLE	3 teams	—	608	557	119	20	1	13	42	202	4	4	7	214	273	323	596	110	305	33	7	264	65	—	—	—	—	—	—
2017	27	AA MLE	2 teams	—	544	480	120	26	0	18	55	143	4	2	0	250	333	417	750	167	308	26	10	329	109	—	—	—	—	—	—
2018	28	AAA MLE	2 teams	—	411	365	71	15	0	13	40	137	3	2	0	195	282	342	625	148	260	33	10	280	76	—	—	—	—	—	—
▸ Career Totals
Career	—	MLE		—	4388	3947	874	189	5	108	363	1265	47	58	31	221	295	354	649	133	294	29	8	284	78	-113	-1	+0	-78	+95	-9.9
/ 162G	—	MLE		—	650	585	130	28	1	16	54	187	7	9	5	222	296	356	651	133	295	29	8	284	78	-17	-0	+0	-12	+14	-1.5

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.

2018 AAANew Orleans Baby Cakes · 344 PAwOBA .351 → .280 (−71)K% 27.3% → 33.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.33%	÷1.055	×1.290	—	—	33.42%
BB% (unintentional) /PA	13.95%	÷0.990	×0.710	—	×0.982	9.82%
HBP% /PA	0.87%	—	×0.980	—	×0.982	0.84%
Singles /BIP	22.40%	÷1.054	×0.900	×0.992	×0.982	18.63%
Doubles /BIP	7.29%	÷0.906	×0.810	×0.992	×0.982	6.35%
Triples /BIP	0.00%	÷1.031	×0.810	×0.992	×0.982	0.00%
Home runs /BIP	7.29%	÷0.952	×0.780	—	×0.982	5.87%

Factors used: league row PCL. Park (home-season share, regressed): HR 90, 1B 111, 2B 81, 3B 106, K 111, BB 98 — applied at half strength. Age: age 29 vs a level average of 27.2 → −1.8% on BB/HBP/hit rates (1.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.992.

Result: wOBA .351 → .280; ISO .196 → .161; BABIP .313 → .260. 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 AAChattanooga Lookouts · 524 PAwOBA .405 → .333 (−72)K% 21.6% → 26.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.56%	÷1.008	×1.220	—	—	26.11%
BB% (unintentional) /PA	14.89%	÷0.940	×0.680	—	×0.968	10.43%
HBP% /PA	0.57%	—	×0.840	—	×0.968	0.47%
Singles /BIP	25.55%	÷1.007	×0.920	×0.999	×0.968	22.58%
Doubles /BIP	9.66%	÷1.084	×0.910	×0.999	×0.968	7.85%
Triples /BIP	0.00%	÷1.018	×0.880	×0.999	×0.968	0.00%
Home runs /BIP	6.54%	÷0.975	×0.800	—	×0.968	5.20%

Factors used: league row SL. Park (home-season share, regressed): HR 95, 1B 101, 2B 117, 3B 104, K 102, BB 88 — applied at half strength. Age: age 28 vs a level average of 24.8 → −3.2% on BB/HBP/hit rates (3.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.999.

Result: wOBA .405 → .333; ISO .217 → .178; BABIP .368 → .314. 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 AAARochester Red Wings · 20 PAwOBA .259 → .215 (−44)K% 25.0% → 30.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷0.997	×1.200	—	—	30.09%
BB% (unintentional) /PA	5.00%	÷1.080	×0.690	—	×0.992	3.17%
HBP% /PA	5.00%	—	×0.940	—	×0.992	4.66%
Singles /BIP	15.38%	÷1.019	×0.930	—	×0.992	13.93%
Doubles /BIP	0.00%	÷1.085	×0.830	—	×0.992	0.00%
Triples /BIP	0.00%	÷1.085	×0.970	—	×0.992	0.00%
Home runs /BIP	7.69%	÷0.956	×0.840	—	×0.992	6.71%

Factors used: league row IL. Park (home-season share, regressed): HR 91, 1B 104, 2B 117, 3B 117, K 99, BB 116 — 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).

Result: wOBA .259 → .215; ISO .167 → .139; BABIP .167 → .149. 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 AASpringfield Cardinals · 347 PAwOBA .324 → .268 (−56)K% 24.8% → 29.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.78%	÷1.019	×1.220	—	—	29.66%
BB% (unintentional) /PA	11.24%	÷0.999	×0.700	—	×0.978	7.70%
HBP% /PA	0.86%	—	×0.870	—	×0.978	0.74%
Singles /BIP	25.00%	÷0.966	×0.920	×1.019	×0.978	23.73%
Doubles /BIP	6.48%	÷0.986	×0.840	×1.019	×0.978	5.50%
Triples /BIP	0.46%	÷0.900	×0.940	×1.019	×0.978	0.48%
Home runs /BIP	3.70%	÷1.155	×0.800	—	×0.978	2.51%

Factors used: league row TL. Park (home-season share, regressed): HR 131, 1B 93, 2B 97, 3B 80, K 104, BB 100 — 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 ×1.019.

Result: wOBA .324 → .268; ISO .132 → .100; BABIP .329 → .302. 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 AAAMemphis Redbirds · 145 PAwOBA .329 → .255 (−74)K% 31.7% → 41.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	31.72%	÷0.988	×1.290	—	—	41.41%
BB% (unintentional) /PA	6.90%	÷0.983	×0.710	—	×1.003	5.00%
HBP% /PA	0.00%	—	×0.980	—	×1.003	0.00%
Singles /BIP	24.72%	÷0.989	×0.900	×1.032	×1.003	23.27%
Doubles /BIP	6.74%	÷0.941	×0.810	×1.032	×1.003	6.01%
Triples /BIP	0.00%	÷0.951	×0.810	×1.032	×1.003	0.00%
Home runs /BIP	7.87%	÷0.931	×0.780	—	×1.003	6.61%

Factors used: league row PCL. Park (home-season share, regressed): HR 86, 1B 98, 2B 88, 3B 90, K 98, BB 97 — 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 ×1.032.

Result: wOBA .329 → .255; ISO .200 → .149; BABIP .341 → .313. 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).

2015 AASpringfield Cardinals · 513 PAwOBA .337 → .274 (−62)K% 19.5% → 24.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.49%	÷0.978	×1.220	—	—	24.33%
BB% (unintentional) /PA	10.53%	÷1.000	×0.700	—	×0.988	7.28%
HBP% /PA	0.19%	—	×0.870	—	×0.988	0.17%
Singles /BIP	24.86%	÷0.982	×0.920	×1.001	×0.988	23.03%
Doubles /BIP	6.78%	÷1.003	×0.840	×1.001	×0.988	5.61%
Triples /BIP	0.00%	÷1.003	×0.940	×1.001	×0.988	0.00%
Home runs /BIP	3.67%	÷1.140	×0.800	—	×0.988	2.55%

Factors used: league row TL. Park (home-season share, regressed): HR 128, 1B 96, 2B 101, 3B 101, K 96, BB 100 — 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 ×1.001.

Result: wOBA .337 → .274; ISO .139 → .102; BABIP .327 → .292. 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).

2014 AASpringfield Cardinals · 469 PAwOBA .336 → .273 (−63)K% 20.5% → 25.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.47%	÷0.972	×1.220	—	—	25.69%
BB% (unintentional) /PA	11.51%	÷1.033	×0.700	—	×0.998	7.78%
HBP% /PA	0.85%	—	×0.870	—	×0.998	0.74%
Singles /BIP	24.52%	÷0.974	×0.920	×0.984	×0.998	22.74%
Doubles /BIP	6.13%	÷0.982	×0.840	×0.984	×0.998	5.15%
Triples /BIP	0.65%	÷0.991	×0.940	×0.984	×0.998	0.60%
Home runs /BIP	3.55%	÷1.221	×0.800	—	×0.998	2.32%

Factors used: league row TL. Park (home-season share, regressed): HR 144, 1B 95, 2B 96, 3B 98, K 94, BB 107 — applied at half strength. Age: age 25 vs a level average of 24.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.984.

Result: wOBA .336 → .273; ISO .138 → .101; BABIP .321 → .289. 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).

2013 A+Palm Beach Cardinals · 523 PAwOBA .369 → .300 (−69)K% 19.3% → 28.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.31%	÷0.974	×1.420	—	—	28.17%
BB% (unintentional) /PA	11.28%	÷1.026	×0.750	—	×0.988	8.15%
HBP% /PA	1.15%	—	×0.930	—	×0.988	1.05%
Singles /BIP	21.47%	÷1.024	×0.920	×1.002	×0.988	19.08%
Doubles /BIP	9.60%	÷1.015	×0.960	×1.002	×0.988	8.99%
Triples /BIP	0.28%	÷0.964	×0.810	×1.002	×0.988	0.23%
Home runs /BIP	5.08%	÷0.972	×0.880	—	×0.988	4.55%

Factors used: league row FSL. Park (home-season share, regressed): HR 94, 1B 105, 2B 103, 3B 93, K 95, BB 105 — applied at half strength. Age: age 24 vs a level average of 22.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.002.

Result: wOBA .369 → .300; ISO .198 → .166; BABIP .328 → .295. 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 — .