Tito Polo

PosCF

B/TR/R

Born1994-08-23

Age (2027)32

No MLB projection yet. Career stats below are historical.

Overview

INTLPROSPECT

MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2022	27	INTLGigantes del …	160	.261/.346/.391	2	16	106	—
2024	29	INTLNavegantes de…	73	.313/.370/.463	2	1	138	—
2025	30	INTLAlgodoneros d…	25	.143/.280/.333	0	0	76	—

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)
2012	17	ROK	DSL Pirates 1	—	165	132	37	7	1	2	16	32	12	17	7	280	406	394	800	114	354	19	10	359	55	—	—	—	—	—	—
2013	18	ROK	DSL Pirates 1	—	184	160	44	3	3	2	15	41	4	22	5	275	352	369	721	94	359	22	8	320	29	—	—	—	—	—	—
2014	19	ROK	GCL Pirates	—	187	158	46	8	6	3	17	34	5	8	4	291	376	475	850	184	350	18	9	364	72	—	—	—	—	—	—
2015	20	A	West Virginia Power	—	414	360	85	20	2	3	28	77	13	46	13	236	314	328	642	92	292	19	7	286	48	—	—	—	—	—	—
2016	21	A+	Tampa Yankees	—	256	222	61	3	0	4	22	47	5	17	7	275	353	342	696	68	329	18	9	313	71	—	—	—	—	—	—
2016	21	A	West Virginia Power	—	251	225	68	14	3	12	13	47	11	20	10	302	369	551	921	249	335	19	5	399	88	—	—	—	—	—	—
2016	21	INTL	Venados de Mazatlan	—	75	66	15	4	0	0	5	19	4	8	1	227	320	288	608	61	319	25	7	287	80	—	—	—	—	—	—
2017	22	AA	Birmingham Barons	—	143	127	41	8	3	1	11	23	4	14	4	323	394	457	851	134	388	16	8	378	114	—	—	—	—	—	—
2017	22	A+	Tampa Yankees	—	259	235	68	10	6	4	16	62	5	20	6	289	348	434	782	145	376	24	6	344	65	—	—	—	—	—	—
2017	22	INTL	Glendale Desert Dogs	—	33	30	8	0	0	0	1	10	1	4	3	267	312	267	579		381	30	3	263	64	—	—	—	—	—	—
2018	23	AA	Birmingham Barons	—	181	163	40	6	3	1	12	34	4	15	4	245	313	337	650	92	305	19	7	293	53	—	—	—	—	—	—
2018	23	ROK	ACL White Sox	—	29	22	7	0	0	3	5	4	1	5	1	318	464	727	1.192	409	250	14	17	486	138	—	—	—	—	—	—
2018	23	INTL	Aguilas del Zulia	—	63	53	14	2	2	0	6	14	2	6	2	264	361	377	738	113	359	22	10	325	106	—	—	—	—	—	—
2019	24	AAA	Rieleros de Aguascalientes	—	123	114	31	6	2	1	6	22	1	6	3	272	314	386	700	114	330	18	5	308	51	—	—	—	—	—	—
2021	26	INTL	Aguilas de Mexicali	—	32	31	6	1	0	0	0	11	1	1	1	194	219	226	445	32	300	34	0	204	25	—	—	—	—	—	—
2022	27	INTL	Gigantes del Cibao	—	160	138	36	6	3	2	14	30	4	16	3	261	346	391	737	130	315	19	9	325	106	—	—	—	—	—	—
2024	29	INTL	Navegantes del Magallanes	—	73	67	21	4	0	2	3	18	3	1	0	313	370	463	833	149	404	25	4	372	138	—	—	—	—	—	—
2025	30	INTL	Algodoneros de Guasave	—	25	21	3	0	2	0	2	7	2	0	1	143	280	333	613	190	214	28	8	280	76	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	17	ROK MLE	DSL Pirates 1	—	165	137	28	5	1	1	11	39	12	17	7	204	319	277	596	73	245	24	7	250	55	—	—	—	—	—	—
2013	18	ROK MLE	DSL Pirates 1	—	184	165	30	2	2	1	10	50	4	22	5	182	246	236	482	55	243	27	5	211	29	—	—	—	—	—	—
2014	19	ROK MLE	GCL Pirates	—	187	166	37	6	4	2	10	49	5	8	4	223	287	343	631	120	284	26	5	274	72	—	—	—	—	—	—
2015	20	A MLE	West Virginia Power	—	414	369	78	17	2	2	19	102	13	46	13	211	274	285	559	73	269	25	5	239	48	—	—	—	—	—	—
2016	21	A+ MLE	Tampa Yankees	—	256	228	56	3	0	4	16	68	5	17	7	246	309	311	621	66	313	27	6	273	71	—	—	—	—	—	—
2016	21	A MLE	West Virginia Power	—	251	230	54	9	3	9	8	62	11	20	10	235	293	417	711	183	275	25	3	298	88	—	—	—	—	—	—
2017	22	AA MLE	Birmingham Barons	—	143	130	40	8	3	1	8	29	4	14	4	308	366	438	805	131	377	20	6	336	114	—	—	—	—	—	—
2017	22	A+ MLE	Tampa Yankees	—	259	240	53	9	4	3	11	93	5	20	6	221	270	329	599	108	338	36	4	264	65	—	—	—	—	—	—
2018	23	AA MLE	Birmingham Barons	—	181	166	36	6	2	1	9	41	4	15	4	217	274	295	569	78	277	23	5	247	53	—	—	—	—	—	—
2018	23	ROK MLE	ACL White Sox	—	29	24	5	0	0	2	3	6	1	5	1	208	321	458	780	250	188	21	10	372	138	—	—	—	—	—	—
2019	24	AAA MLE	Rieleros de Aguascalientes	—	123	117	27	5	2	1	3	28	1	6	3	231	256	333	590	103	284	23	2	244	51	—	—	—	—	—	—
2012	17	ROK MLE	DSL Pirates 1	—	165	137	28	5	1	1	11	39	12	17	7	204	319	277	596	73	276	24	7	250	55	—	—	—	—	—	—
2012	17	ROK RAW	DSL Pirates 1	—	165	132	37	7	1	2	16	32	12	17	7	280	406	394	800	114	354	19	10	359	55	—	—	—	—	—	—
2013	18	ROK MLE	DSL Pirates 1	—	184	165	30	2	2	1	10	50	4	22	5	182	246	236	482	55	254	27	5	211	29	—	—	—	—	—	—
2013	18	ROK RAW	DSL Pirates 1	—	184	160	44	3	3	2	15	41	4	22	5	275	352	369	721	94	359	22	8	320	29	—	—	—	—	—	—
2014	19	ROK MLE	GCL Pirates	—	187	166	37	6	4	2	10	49	5	8	4	223	287	343	631	120	299	26	5	274	72	—	—	—	—	—	—
2014	19	ROK RAW	GCL Pirates	—	187	158	46	8	6	3	17	34	5	8	4	291	376	475	850	184	350	18	9	364	72	—	—	—	—	—	—
2015	20	A MLE	West Virginia Power	—	414	369	78	17	2	2	19	102	13	46	13	211	274	285	559	73	286	25	5	239	48	—	—	—	—	—	—
2015	20	A RAW	West Virginia Power	—	414	360	85	20	2	3	28	77	13	46	13	236	314	328	642	92	292	19	7	286	48	—	—	—	—	—	—
2016	21	A+ MLE	3 teams	—	582	525	126	14	3	15	28	149	20	45	18	240	304	364	667	124	305	26	5	285	79	—	—	—	—	—	—
2016	21	A+ RAW	3 teams	—	582	513	144	21	3	16	40	113	20	45	18	281	356	427	783	146	331	19	7	347	79	—	—	—	—	—	—
2017	22	A+ MLE	3 teams	—	435	400	100	18	7	4	20	131	10	38	13	250	302	360	662	110	360	30	5	290	82	—	—	—	—	—	—
2017	22	A+ RAW	3 teams	—	435	392	117	18	9	5	28	95	10	38	13	298	360	429	789	130	381	22	6	349	82	—	—	—	—	—	—
2018	23	AA MLE	3 teams	—	273	246	54	8	3	4	15	61	7	26	7	220	284	325	609	106	275	22	5	264	65	—	—	—	—	—	—
2018	23	AA RAW	3 teams	—	273	238	61	8	5	4	23	52	7	26	7	256	340	382	722	126	311	19	8	321	65	—	—	—	—	—	—
2019	24	AAA MLE	Rieleros de Aguascalientes	—	123	117	27	5	2	1	3	28	1	6	3	231	256	333	590	103	295	23	2	244	51	—	—	—	—	—	—
2019	24	AAA RAW	Rieleros de Aguascalientes	—	123	114	31	6	2	1	6	22	1	6	3	272	314	386	700	114	330	18	5	308	51	—	—	—	—	—	—
2021	26	INTL MLE	Aguilas de Mexicali	—	32	31	6	1	0	0	0	11	1	1	1	194	219	226	445	32	300	34	0	—	—	—	—	—	—	—	—
2021	26	INTL RAW	Aguilas de Mexicali	—	32	31	6	1	0	0	0	11	1	1	1	194	219	226	445	32	300	34	0	204	25	—	—	—	—	—	—
2022	27	INTL MLE	Gigantes del Cibao	—	160	138	36	6	3	2	14	30	4	16	3	261	346	391	737	130	315	19	9	—	—	—	—	—	—	—	—
2022	27	INTL RAW	Gigantes del Cibao	—	160	138	36	6	3	2	14	30	4	16	3	261	346	391	737	130	315	19	9	325	106	—	—	—	—	—	—
2024	29	INTL MLE	Navegantes del Magallanes	—	73	67	21	4	0	2	3	18	3	1	0	313	370	463	833	149	404	25	4	—	—	—	—	—	—	—	—
2024	29	INTL RAW	Navegantes del Magallanes	—	73	67	21	4	0	2	3	18	3	1	0	313	370	463	833	149	404	25	4	372	138	—	—	—	—	—	—
2025	30	INTL MLE	Algodoneros de Guasave	—	25	21	3	0	2	0	2	7	2	0	1	143	280	333	613	190	214	28	8	—	—	—	—	—	—	—	—
2025	30	INTL RAW	Algodoneros de Guasave	—	25	21	3	0	2	0	2	7	2	0	1	143	280	333	613	190	214	28	8	280	76	—	—	—	—	—	—
2012	17	ROK MLE	DSL Pirates 1	—	165	141	28	5	1	1	11	39	12	17	7	199	319	270	588	71	245	24	7	250	55	—	—	—	—	—	—
2013	18	ROK MLE	DSL Pirates 1	—	184	168	30	2	2	1	10	50	4	22	5	179	246	232	478	54	243	27	5	211	29	—	—	—	—	—	—
2014	19	ROK MLE	GCL Pirates	—	187	170	37	6	4	2	10	49	5	8	4	218	287	335	623	118	284	26	5	274	72	—	—	—	—	—	—
2015	20	A MLE	West Virginia Power	—	414	379	78	17	2	2	19	102	13	46	13	206	274	277	551	71	269	25	5	239	48	—	—	—	—	—	—
2016	21	A+ MLE	3 teams	—	582	529	126	14	3	15	28	149	20	45	18	238	304	361	665	123	294	26	5	285	79	—	—	—	—	—	—
2017	22	A+ MLE	3 teams	—	435	402	100	18	7	4	20	131	10	38	13	249	302	358	661	109	352	30	5	290	82	—	—	—	—	—	—
2018	23	AA MLE	3 teams	—	273	249	54	8	3	4	15	61	7	26	7	217	284	321	605	104	265	22	5	264	65	—	—	—	—	—	—
2019	24	AAA MLE	Rieleros de Aguascalientes	—	123	118	27	5	2	1	3	28	1	6	3	229	256	331	587	102	284	23	2	244	51	—	—	—	—	—	—
▸ Career Totals
Career	—	MLE		—	2653	2382	546	86	29	34	135	675	82	226	75	229	294	332	626	103	304	25	5	235	45	-172	+15	+0	+9	+57	-9.2
/ 162G	—	MLE		—	650	584	133	21	7	8	33	165	20	55	18	228	292	329	621	101	302	25	5	235	45	-42	+4	+0	+2	+14	-2.2

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 AAARieleros de Aguascalientes · 123 PAwOBA .296 → .244 (−53)K% 17.9% → 22.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.89%	÷0.936	×1.200	—	—	22.93%
BB% (unintentional) /PA	4.07%	÷1.051	×0.690	—	×1.033	2.76%
HBP% /PA	0.81%	—	×0.940	—	×1.033	0.79%
Singles /BIP	23.91%	÷1.050	×0.930	×0.950	×1.033	20.78%
Doubles /BIP	6.52%	÷0.954	×0.830	×0.950	×1.033	5.57%
Triples /BIP	2.17%	÷1.065	×0.920	×0.950	×1.033	1.84%
Home runs /BIP	1.09%	÷1.115	×0.700	—	×1.033	0.71%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 123, 1B 110, 2B 91, 3B 113, K 87, BB 110 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .296 → .244; ISO .114 → .090; BABIP .330 → .284. 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 AABirmingham Barons · 181 PAwOBA .286 → .247 (−38)K% 18.8% → 22.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.78%	÷1.006	×1.220	—	—	22.77%
BB% (unintentional) /PA	6.63%	÷0.954	×0.680	—	×1.012	4.78%
HBP% /PA	2.21%	—	×0.840	—	×1.012	1.88%
Singles /BIP	23.26%	÷1.069	×0.920	×1.038	×1.012	21.02%
Doubles /BIP	4.65%	÷0.969	×0.910	×1.038	×1.012	4.59%
Triples /BIP	2.33%	÷1.150	×0.880	×1.038	×1.012	1.87%
Home runs /BIP	0.78%	÷0.949	×0.800	—	×1.012	0.66%

Factors used: league row SL. Park (home-season share, regressed): HR 90, 1B 114, 2B 94, 3B 130, K 101, BB 91 — applied at half strength. Age: age 24 vs a level average of 24.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.038.

Result: wOBA .286 → .247; ISO .092 → .081; BABIP .305 → .277. 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 ROKACL White Sox · 29 PAwOBA .489 → .372 (−118)K% 13.8% → 19.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.79%	÷1.000	×1.440	—	—	19.86%
BB% (unintentional) /PA	17.24%	÷1.000	×0.620	—	×0.955	10.21%
HBP% /PA	3.45%	—	×0.720	—	×0.955	2.37%
Singles /BIP	22.22%	÷1.000	×0.820	—	×0.955	17.40%
Doubles /BIP	0.00%	÷1.000	×0.720	—	×0.955	0.00%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.955	0.00%
Home runs /BIP	16.67%	÷1.000	×0.780	—	×0.955	12.41%

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 24 vs a level average of 19.5 → −4.5% on BB/HBP/hit rates (4.5 yr older than average).

Result: wOBA .489 → .372; ISO .409 → .332; BABIP .250 → .188. 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+Tampa Yankees · 259 PAwOBA .335 → .264 (−71)K% 23.9% → 35.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.94%	÷0.949	×1.420	—	—	35.82%
BB% (unintentional) /PA	5.79%	÷1.007	×0.750	—	×0.998	4.31%
HBP% /PA	1.93%	—	×0.930	—	×0.998	1.79%
Singles /BIP	27.75%	÷1.071	×0.920	×1.039	×0.998	24.72%
Doubles /BIP	5.78%	÷0.995	×0.960	×1.039	×0.998	5.79%
Triples /BIP	3.47%	÷1.031	×0.810	×1.039	×0.998	2.83%
Home runs /BIP	2.31%	÷0.949	×0.880	—	×0.998	2.14%

Factors used: league row FSL. Park (home-season share, regressed): HR 90, 1B 114, 2B 99, 3B 106, K 90, BB 101 — applied at half strength. Age: age 23 vs a level average of 22.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.039.

Result: wOBA .335 → .264; ISO .145 → .114; BABIP .376 → .338. 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 AABirmingham Barons · 143 PAwOBA .368 → .336 (−32)K% 16.1% → 20.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.08%	÷0.980	×1.220	—	—	20.03%
BB% (unintentional) /PA	7.69%	÷1.001	×0.680	—	×1.027	5.37%
HBP% /PA	2.80%	—	×0.840	—	×1.027	2.41%
Singles /BIP	27.88%	÷1.009	×0.920	×1.050	×1.027	27.42%
Doubles /BIP	7.69%	÷1.021	×0.910	×1.050	×1.027	7.39%
Triples /BIP	2.88%	÷1.086	×0.880	×1.050	×1.027	2.52%
Home runs /BIP	0.96%	÷0.894	×0.800	—	×1.027	0.88%

Factors used: league row SL. Park (home-season share, regressed): HR 79, 1B 102, 2B 104, 3B 117, K 96, BB 100 — 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 ×1.050.

Result: wOBA .368 → .336; ISO .134 → .123; BABIP .388 → .377. 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 A+Tampa Yankees · 256 PAwOBA .307 → .273 (−34)K% 18.4% → 26.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.36%	÷0.988	×1.420	—	—	26.38%
BB% (unintentional) /PA	8.59%	÷1.021	×0.750	—	×1.012	6.39%
HBP% /PA	1.95%	—	×0.930	—	×1.012	1.84%
Singles /BIP	30.86%	÷1.022	×0.920	×1.037	×1.012	29.14%
Doubles /BIP	1.71%	÷0.953	×0.960	×1.037	×1.012	1.81%
Triples /BIP	0.00%	÷1.032	×0.810	×1.037	×1.012	0.00%
Home runs /BIP	2.29%	÷0.862	×0.880	—	×1.012	2.36%

Factors used: league row FSL. Park (home-season share, regressed): HR 72, 1B 104, 2B 91, 3B 106, K 98, BB 104 — 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 ×1.037.

Result: wOBA .307 → .273; ISO .068 → .067; BABIP .329 → .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).

2016 AWest Virginia Power · 251 PAwOBA .390 → .298 (−92)K% 18.7% → 24.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.73%	÷1.012	×1.340	—	—	24.79%
BB% (unintentional) /PA	5.18%	÷1.037	×0.660	—	—	3.30%
HBP% /PA	4.38%	—	×0.770	—	—	3.37%
Singles /BIP	21.91%	÷1.028	×0.920	×0.989	—	19.38%
Doubles /BIP	7.87%	÷1.190	×0.820	×0.989	—	5.36%
Triples /BIP	1.69%	÷1.056	×0.940	×0.989	—	1.48%
Home runs /BIP	6.74%	÷1.069	×0.820	—	—	5.17%

Factors used: league row SAL. Park (home-season share, regressed): HR 114, 1B 106, 2B 138, 3B 111, K 102, BB 107 — applied at half strength. Age: age 22 vs a level average of 22.0 → +0.0% on BB/HBP/hit rates (0.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.989.

Result: wOBA .390 → .298; ISO .249 → .182; BABIP .335 → .275. 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 AWest Virginia Power · 414 PAwOBA .280 → .239 (−40)K% 18.6% → 24.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.60%	÷1.009	×1.340	—	—	24.69%
BB% (unintentional) /PA	6.76%	÷1.012	×0.660	—	×1.015	4.48%
HBP% /PA	3.14%	—	×0.770	—	×1.015	2.45%
Singles /BIP	21.20%	÷1.024	×0.920	×1.033	×1.015	19.97%
Doubles /BIP	7.07%	÷0.998	×0.820	×1.033	×1.015	6.09%
Triples /BIP	0.71%	÷0.987	×0.940	×1.033	×1.015	0.71%
Home runs /BIP	1.06%	÷1.137	×0.820	—	×1.015	0.78%

Factors used: league row SAL. Park (home-season share, regressed): HR 127, 1B 105, 2B 100, 3B 97, K 102, BB 102 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.033.

Result: wOBA .280 → .239; ISO .092 → .077; BABIP .292 → .269. 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 — .