Ronald Ramirez

SS FCL Tigers

Age 20 R/R 5'10" / 170 lbs ROK HR -8% Svc 0.0 · Ctrl thru 2038

Overview

ROKPROSPECTMiLBFA 2039

OGV OFP35OGV rank#1627ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	17	ROKDSL Tigers 2	175	.343/.462/.429	1	6	71	—	.224/.333/.286
2025	18	ROKDET	145	.242/.347/.282	0	7	26	—	.168/.243/.191
2026	19	A/ROKDET	141	.333/.410/.520	4	11	86	—	.248/.302/.380
2027PROJMLE	20	MLBDET	251	.206/.273/.297	3	5	62	0.0
2028PROJ34% MLB	21	MLBDET	49	.207/.275/.304	1	1	67	-0.0
2029PROJ48% MLB	22	MLBDET	115	.211/.280/.315	2	3	71	0.0

Next 3 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2038Service0.0First FA2039

2027MiLB2028MiLB2029MiLB2030MiLB2031MiLB2032MiLB2033Pre-Arb$0.9M2034Pre-Arb$1.0M+4

Skills · percentileMiLB Statcast 2026 Rk

Speed85

wRC+83

wOBA76

ISO76

Whiff%76

Z-Con%63

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 97%

CompsGeorge Feliz (age 20) · Brian Sanchez (age 20) · Alexander Palma (age 20)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 84 proj PA

wRC+†62

AVG/OBP/SLG.204 / .270 / .294

PA84

HR1

K%27

BB%7

ISO90

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$5M ctrl surplus

Tools · ContractCON 36 / POW 39

Toolsscout grade

CONTACT36

scouting grade only

POWER39

scouting grade only

EYE51

scouting grade only

SPEED60

scouting grade only

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

Status MiLB

MLB Debut 2033

Service 0 yrs (est)

Team Control Through 2038

First FA Year 2039

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2033
2028	MiLB	still in minors · estimated debut 2033
2029	MiLB	still in minors · estimated debut 2033
2030	MiLB	still in minors · estimated debut 2033
2031	MiLB	still in minors · estimated debut 2033
2032	MiLB	still in minors · estimated debut 2033
2033	Pre-Arb	$0.9M	+0.2	$0.5M	+$0.0M
2034	Pre-Arb	$1.0M	+0.2	$0.5M	+$0.0M
2035	Pre-Arb	$1.0M	+0.1	$0.2M	+$0.0M (cut)
2036	Arb-1	$0.6M	—	—	—
2037	Ext	beyond projection horizon · no WAR estimate
2038	Ext	beyond projection horizon · no WAR estimate
Totals		$2M		$1M	+$0.0M

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)
2024	17	ROK	DSL Tigers 2	—	175	140	48	9	0	1	24	29	7	6	7	343	462	429	891	86	412	17	14	400	71	—	—	—	—	—	—
2025	18	ROK	FCL Tigers	—	145	124	30	5	0	0	17	31	3	7	5	242	347	282	629	40	319	21	12	297	26	—	—	—	—	—	—
2026	19	A	Lakeland Flying Tigers	—	36	32	10	2	1	1	4	10	0	1	0	312	389	531	920	219	429	28	11	402	95	—	—	—	—	—	—
2026	19	ROK	FCL Tigers	—	105	91	31	3	2	3	12	24	0	10	0	341	417	516	934	176	424	23	11	405	83	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	17	ROK MLE	DSL Tigers 2	—	175	147	33	6	0	1	17	36	7	6	7	224	333	286	619	61	265	21	10	273	71	—	—	—	—	—	—
2025	18	ROK MLE	FCL Tigers	—	145	131	22	3	0	0	10	45	3	7	5	168	243	191	434	23	251	31	7	206	26	—	—	—	—	—	—
2026	19	A MLE	Lakeland Flying Tigers	—	36	33	9	2	1	1	3	14	0	1	0	273	333	485	818	212	393	39	8	308	95	—	—	—	—	—	—
2026	19	ROK MLE	FCL Tigers	—	105	96	23	2	1	2	7	35	0	10	0	240	291	344	635	104	339	33	7	291	83	—	—	—	—	—	—
2024	17	ROK MLE	DSL Tigers 2	—	175	147	33	6	0	1	17	36	7	6	7	224	333	286	619	61	281	21	10	273	71	—	—	—	—	—	—
2024	17	ROK RAW	DSL Tigers 2	—	175	140	48	9	0	1	24	29	7	6	7	343	462	429	891	86	412	17	14	400	71	—	—	—	—	—	—
2025	18	ROK MLE	FCL Tigers	—	145	131	22	3	0	0	10	45	3	7	5	168	243	191	434	23	253	31	7	206	26	—	—	—	—	—	—
2025	18	ROK RAW	FCL Tigers	—	145	124	30	5	0	0	17	31	3	7	5	242	347	282	629	40	319	21	12	297	26	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	141	129	32	4	2	3	10	48	0	11	0	248	302	380	682	132	362	34	7	295	86	—	—	—	—	—	—
2026	19	ROK RAW	2 teams	—	141	123	41	5	3	4	16	34	0	11	0	333	410	520	930	187	425	24	11	404	86	—	—	—	—	—	—
2024	17	ROK MLE	DSL Tigers 2	—	175	149	33	6	0	1	17	36	7	6	7	221	333	282	615	60	265	21	10	273	71	—	—	—	—	—	—
2025	18	ROK MLE	FCL Tigers	—	145	131	22	3	0	0	10	45	3	7	5	168	243	191	434	23	251	31	7	206	26	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	141	130	32	4	2	3	10	48	0	11	0	246	302	377	679	131	353	34	7	295	86	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	17	ROK MLE	DSL Tigers 2	—	175	149	33	6	0	1	17	36	7	6	7	221	333	282	615	60	265	21	10	273	71	—	—	—	—	—	—
2025	18	ROK MLE	FCL Tigers	—	145	131	22	3	0	0	10	45	3	7	5	168	243	191	434	23	251	31	7	206	26	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	141	130	32	4	2	3	10	48	0	11	0	246	302	377	679	131	353	34	7	295	86	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	20	MLB MLE	DET	0%	251	228	47	8	2	3	18	67	3	5	1	206	273	297	569	90	274	27	7	259	62	-11	+1	+0	+3	+5	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	21	MLB MLE	DET	34%	143	129	28	5	1	2	11	38	2	3	1	211	278	311	589	100	276	27	8	267	67	-6	+0	+0	+2	+3	-0.1
2029	22	MLB MLE	DET	48%	237	214	46	8	1	4	18	61	3	6	1	215	283	322	605	107	278	26	8	274	71	-8	+1	+0	+3	+5	0.0
2030	23	MLB MLE	DET	54%	332	300	65	11	2	6	25	85	4	8	2	218	286	330	617	113	279	26	8	279	75	-10	+1	+0	+4	+7	0.2
2031	24	MLB MLE	DET	55%	396	359	79	14	2	8	30	100	4	10	3	220	289	337	626	117	281	25	8	282	77	-11	+1	+0	+4	+9	0.3
2032	25	MLB MLE	DET	56%	432	391	87	15	3	9	33	109	5	10	3	222	291	341	632	119	282	25	8	285	79	-11	+1	+0	+5	+9	0.4
2033	26	MLB MLE	DET	56%	451	408	91	16	3	9	35	113	5	11	3	222	291	341	632	119	281	25	8	285	79	-11	+1	+0	+5	+10	0.4
2034	27	MLB MLE	DET	55%	458	414	92	16	3	9	36	116	5	11	3	221	290	338	628	118	281	25	8	283	78	-12	+1	+0	+5	+10	0.4
2035	28	MLB MLE	DET	55%	456	413	91	16	3	9	35	116	5	10	3	219	288	334	622	115	280	25	8	281	76	-13	+1	-1	+5	+10	0.2
2036	29	MLB MLE	DET	53%	447	405	88	15	3	8	34	115	5	9	3	217	285	328	614	111	279	26	8	277	74	-14	+1	-1	+5	+10	-0.0
2028	21	MLB CTX	DET	34%	49	44	10	2	0	1	4	13	1	1	0	207	275	304	579	97	272	27	8	263	67	-2	+0	+0	+1	+1	-0.0
2029	22	MLB CTX	DET	48%	115	104	23	4	1	2	9	30	1	3	1	211	280	315	595	104	274	26	8	270	71	-4	+0	+0	+1	+2	0.0
2030	23	MLB CTX	DET	54%	180	162	35	6	1	3	14	46	2	4	1	214	283	323	606	109	275	26	8	274	75	-5	+0	+0	+2	+4	0.1
2031	24	MLB CTX	DET	55%	219	198	42	7	1	4	17	55	2	5	1	217	286	329	615	113	277	25	8	278	77	-6	+1	+0	+2	+5	0.2
2032	25	MLB CTX	DET	56%	242	218	47	8	1	5	19	61	3	6	2	218	288	333	621	115	277	25	8	280	79	-6	+0	+0	+3	+5	0.2
2033	26	MLB CTX	DET	56%	254	229	51	9	2	5	20	64	3	6	2	218	287	333	621	115	277	25	8	280	79	-6	+0	+0	+3	+6	0.2
2034	27	MLB CTX	DET	55%	253	228	50	9	1	5	20	64	3	6	2	217	287	331	617	114	276	25	8	279	78	-7	+0	+0	+3	+5	0.2
2035	28	MLB CTX	DET	55%	250	226	48	8	1	5	19	64	3	5	2	215	285	326	611	111	276	26	8	276	76	-7	+0	-0	+3	+5	0.1
2036	29	MLB CTX	DET	53%	239	217	46	8	1	4	18	62	2	5	2	213	282	321	603	108	275	26	8	273	74	-7	+0	-1	+3	+5	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1801	1626	352	61	9	34	140	459	20	41	13	216	287	328	614	111	279	25	8	277	74	-51	+3	-1	+19	+39	1.0
/ 162G	—	A+C		—	650	587	127	22	3	12	51	166	7	15	5	216	287	325	613	109	279	26	8	277	74	-18	+1	-0	+7	+14	0.3
Career	—	MLE		—	3897	3517	770	132	24	69	300	1004	49	104	34	219	289	329	618	110	284	26	8	278	74	-99	+7	-2	+37	+74	1.7
/ 162G	—	MLE		—	650	587	129	22	4	12	50	167	8	17	6	220	290	332	622	112	284	26	8	278	74	-19	+1	-0	+7	+14	0.3

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 ROKFCL Tigers · 105 PAwOBA .402 → .291 (−111)K% 22.9% → 32.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.86%	÷1.000	×1.440	—	—	32.91%
BB% (unintentional) /PA	11.43%	÷1.000	×0.620	—	×0.995	7.05%
HBP% /PA	0.00%	—	×0.720	—	×0.995	0.00%
Singles /BIP	34.33%	÷1.000	×0.820	×1.013	×0.995	28.39%
Doubles /BIP	4.48%	÷1.000	×0.720	×1.013	×0.995	3.25%
Triples /BIP	2.99%	÷1.000	×0.720	×1.013	×0.995	2.17%
Home runs /BIP	4.48%	÷1.000	×0.780	—	×0.995	3.48%

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 20 vs a level average of 19.5 → −0.5% on BB/HBP/hit rates (0.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.013.

Result: wOBA .402 → .291; ISO .176 → .125; BABIP .424 → .339. 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 ALakeland Flying Tigers · 36 PAwOBA .392 → .308 (−84)K% 27.8% → 37.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.78%	÷1.000	×1.360	—	—	37.78%
BB% (unintentional) /PA	11.11%	÷1.000	×0.690	—	×1.030	7.90%
HBP% /PA	0.00%	—	×0.780	—	×1.030	0.00%
Singles /BIP	27.27%	÷1.000	×0.920	—	×1.030	25.84%
Doubles /BIP	9.09%	÷1.000	×0.830	—	×1.030	7.77%
Triples /BIP	4.55%	÷1.000	×0.910	—	×1.030	4.26%
Home runs /BIP	4.55%	÷1.000	×0.800	—	×1.030	3.75%

Factors used: level-wide A 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 20 vs a level average of 22.0 → +3.0% on BB/HBP/hit rates (2.0 yr younger than average).

Result: wOBA .392 → .308; ISO .219 → .168; BABIP .429 → .393. 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).

2025 ROKFCL Tigers · 145 PAwOBA .290 → .206 (−84)K% 21.4% → 30.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.38%	÷1.001	×1.440	—	—	30.75%
BB% (unintentional) /PA	11.03%	÷0.996	×0.620	—	×1.008	6.92%
HBP% /PA	2.07%	—	×0.720	—	×1.008	1.50%
Singles /BIP	26.88%	÷0.974	×0.820	×0.950	×1.008	21.66%
Doubles /BIP	5.38%	÷0.992	×0.720	×0.950	×1.008	3.74%
Triples /BIP	0.00%	÷0.900	×0.720	×0.950	×1.008	0.00%
Home runs /BIP	0.00%	÷0.880	×0.780	—	×1.008	0.00%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 76, 1B 95, 2B 98, 3B 80, K 100, BB 99 — applied at half strength. Age: age 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .290 → .206; ISO .040 → .027; BABIP .319 → .251. 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).

2024 DSLDSL Tigers 2 · 175 PAwOBA .399 → .273 (−126)K% 16.6% → 20.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.57%	÷0.986	×1.220	—	—	20.50%
BB% (unintentional) /PA	13.71%	÷0.973	×0.700	—	×1.008	9.94%
HBP% /PA	4.00%	—	×0.700	—	×1.008	2.82%
Singles /BIP	34.23%	÷0.995	×0.680	×0.950	×1.008	22.40%
Doubles /BIP	8.11%	÷0.951	×0.600	×0.950	×1.008	4.89%
Triples /BIP	0.00%	÷1.135	×0.600	×0.950	×1.008	0.00%
Home runs /BIP	0.90%	÷0.995	×0.470	—	×1.008	0.43%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 99, 1B 99, 2B 90, 3B 127, K 97, BB 95 — applied at half strength. Age: age 18 vs a level average of 18.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .399 → .273; ISO .086 → .052; BABIP .412 → .265. 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
#1Gene Michael'66-'75 * career totals — 9 seasons, 3,095 PA	4.7	3,095	15	22	233*	291*	316*	+32	+27	4.6	5.8
/162	664	3	5	+6.8	+5.8	1.0	pk7: 7
#2Ronny Cedenolast yr '13 career totals — 9 seasons, 2,783 PA	4.2	2,783	40	39	246	289	354	+28	+19	5.5	5.6
/162	664	10	9	+6.7	+4.5	1.3	pk7: 6
#3Chris Owingslast yr '22 career totals — 9 seasons, 2,420 PA	3.6	2,420	35	78	239	286	365	+13	-0	3.7	4.5
/162	664	10	21	+3.6	-0.1	1.0	pk7: 5
#4Tim Cullen'66-'72 * career totals — 6 seasons, 1,960 PA	3.0	1,960	9	10	229*	288*	313*	+10	+27	2.7	2.7
/162	664	3	3	+3.6	+9.1	0.9	pk7: 3
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	2.8	1,885	36	44	220	285	334	+20	+18	2.3	2.2
/162	664	13	15	+7.1	+6.3	0.8	pk7: 2
#5Ryan Goinslast yr '19 career totals — 7 seasons, 1,680 PA	2.5	1,680	22	6	230	279	335	+9	+21	2.0	2.0
/162	664	9	2	+3.7	+8.5	0.8	pk7: 2
#6Benji Gil'93-'03 * career totals — 7 seasons, 1,767 PA	2.7	1,767	32	24	227*	272*	349*	+10	+30	0.6	1.0
/162	664	12	9	+3.8	+11.3	0.2	pk7: 1

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
Ronald Ramirez (OGILVIE)	20	31→36	34→39	55→60	51	204/270/294	90	274	1	2	27%	7%	62	-0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕George Feliz 2023 · A	20	34	39→45	54→45	38	169/229/251	81	271	6	13	38%	7%	36	-3.4	173/235/269	96	305	10	11	44%	6%	42	-2.9	160/223/268	108	267	13	9	43%	6%	36	-1.2
✕Brian Sanchez 2016 · A	20	35	39→50	47→45	37	173/232/259	86	255	6	7	33%	5%	39	-3.1	185/246/289	104	268	10	4	33%	6%	51	-2.2	177/247/294	117	245	12	0	32%	7%	52	-0.7
✕Alexander Palma 2016 · A	20	40	37→50	51→45	39	195/224/265	70	238	5	9	21%	3%	35	-3.4	219/252/328	109	266	10	8	21%	4%	61	-1.5	240/278/387	146	288	16	7	22%	4%	81	-0.0
●Óscar Mercado 2015 · A	20	37→47	37→50	53→60	42	180/236/248	68	230	5	19	23%	5%	37	-3.3	205/252/275	70	255	4	26	20%	5%	49	-2.4	245/308/380	135	288	13	27	19%	7%	93	+0.7
✕Edwin Gomez 2007 · A	19	40	34→40	52→50	45	188/248/242	54	254	2	16	26%	7%	40	-3.0	204/287/282	78	267	5	13	23%	10%	65	-1.2	191/302/269	79	238	6	17	20%	12%	68	-0.4
✕Athanael Duarte 2024 · A	19	40	38→40	54→45	47	190/248/268	78	225	6	14	19%	6%	47	-2.6	183/258/265	82	267	6	7	31%	8%	51	-2.3	153/243/231	78	239	5	5	35%	9%	36	-1.0
✕Luis Hidalgo 2017 · A	21	34	40→45	47→45	46	171/237/257	86	202	9	12	21%	6%	40	-3.0	218/268/334	116	259	12	8	20%	5%	70	-0.9	255/297/374	119	283	12	8	14%	4%	87	+0.2
✕Conner Capel 2017 · A	20	40→48	36→45	52→55	44	191/238/258	68	240	2	13	21%	5%	40	-3.1	210/265/335	125	281	12	11	28%	7%	68	-1.0	226/297/349	123	283	12	19	23%	8%	80	-0.1
✕Enger Jimenez 2015 · A	20	36	38→40	48→50	41	176/230/258	82	234	5	9	26%	5%	38	-3.2	196/253/274	78	249	4	10	22%	6%	49	-2.4	189/247/262	73	232	3	14	19%	6%	42	-1.5
✕Jose Paniagua 2015 · A	21	35	38→45	50→55	46	171/238/253	82	230	5	12	27%	8%	40	-3.1	191/242/280	89	274	7	8	31%	6%	47	-2.6	177/211/272	96	252	10	2	33%	3%	30	-1.1
✕Moisés Sierra 2008 · A	19	35→45	40→50	49→50	38	177/232/265	88	238	8	10	29%	5%	40	-3.0	223/270/316	93	303	8	8	28%	4%	65	-1.2	252/302/391	139	320	16	11	25%	5%	93	+0.8
✕Carlos Tatis 2017 · A	20	41	36→45	50→45	45	193/248/264	72	246	2	6	22%	6%	45	-2.7	197/248/280	83	261	8	5	26%	5%	49	-2.4	184/236/261	78	241	9	4	27%	5%	40	-1.2
✕Jesus Solorzano 2011 · A	20	38→46	34→45	51→55	37	182/244/237	54	264	2	12	30%	5%	38	-3.2	211/256/301	90	279	6	16	26%	4%	57	-1.8	211/240/307	96	291	8	21	30%	3%	49	-1.4
✕Stanley Martinez 2017 · A	20	37	36→40	48→50	49	177/259/243	66	236	3	10	25%	9%	46	-2.6	201/272/288	87	266	7	7	25%	7%	61	-1.5	191/264/271	80	248	7	5	24%	7%	53	-0.7
✕Ignacio Valdez 2015 · A	20	35	37→45	48→50	44	168/241/248	80	235	4	10	28%	7%	40	-3.1	163/232/272	109	259	11	5	39%	7%	42	-2.9	118/172/221	103	188	14	1	45%	5%	5	-1.3
✕Daniel Montano 2018 · A	19	34→44	39→45	46→50	45	171/236/261	90	223	6	9	25%	7%	40	-3.0	177/222/264	87	248	6	10	30%	5%	35	-3.4	213/289/324	112	322	9	6	34%	9%	73	-0.5
✕Luis Tejada 2014 · A	21	41→44	36→45	52→50	38	195/236/262	67	270	3	13	28%	4%	40	-3.1	210/252/296	86	278	7	9	26%	4%	54	-2.0	216/264/322	106	271	10	7	23%	5%	62	-0.8
✕Israel Mota 2016 · A	20	38	38→40	48→50	39	185/234/260	76	257	5	9	29%	5%	39	-3.1	195/256/287	92	296	7	7	34%	6%	55	-2.0	139/225/243	104	203	11	5	36%	7%	34	-0.7
✕Edwin Ventura 2018 · A	20	40	35→30	51→55	40	191/233/245	54	245	2	9	23%	4%	35	-3.4	184/240/234	50	243	2	16	23%	6%	35	-3.4	150/214/169	19	195	0	27	21%	6%	11	-2.1
✕Francisco Sosa 2010 · A	20	37→46	35→45	47→50	41	179/246/236	57	257	3	14	30%	6%	38	-3.2	179/236/257	78	276	6	11	35%	6%	40	-3.1	193/249/307	115	289	12	14	36%	6%	54	-1.1

Ronald Ramirez

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps