Jonathan Rangel

SS ACL Brewers

Age 20 L/R 5'9" / 176 lbs ROK HR +10%K +6% Svc 0.0 · Ctrl thru 2038

Overview

ROKPROSPECTMiLBFA 2039

OGV OFP35OGV rank#1208ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	17	ROKDSL Brewers 2	109	.272/.385/.315	0	10	42	—	.188/.284/.219
2025	18	ROKDSL Brewers G…	159	.288/.451/.500	2	5	70	—	.172/.307/.281
2026	19	ROKMIL	156	.250/.425/.474	5	6	70	—	.171/.301/.318
2027PROJMLE	20	MLBMIL	266	.202/.286/.305	4	4	69	0.0
2028PROJ34% MLB	21	MLBMIL	45	.204/.289/.315	1	1	74	0.0
2029PROJ48% MLB	22	MLBMIL	109	.208/.292/.325	2	2	77	0.1

Next 3 projected WAR 0.1Projected 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

ISO88

Speed84

BB%83

wRC+75

wOBA69

Chase%30

Career WAR0.0 WAR median (P10 0.0 / P90 0.3, comp-based) · star 1% · didn't stick 93%

CompsHoy Park (age 20) · Canaan Smith-Njigba (age 20) · Randy Florentino (age 21)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 81 proj PA

wRC+†69

AVG/OBP/SLG.200 / .284 / .302

PA81

HR1

K%29

BB%9

ISO103

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$10M ctrl surplus

Tools · ContractCON 45 / POW 40

Toolsscout grade

CONTACT45

scouting grade only

POWER40

scouting grade only

EYE60

scouting grade only

SPEED45

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	+0.4	$1M	+$0.5M
2034	Pre-Arb	$1.0M	+0.3	$0.7M	+$0.2M
2035	Pre-Arb	$1.0M	+0.2	$0.4M	+$0.0M
2036	Arb-1	$1M	+0.1	$0.2M	+$0.0M (cut)
2037	Arb-2	$1M	—	—	—
2038	Ext	beyond projection horizon · no WAR estimate
Totals		$3M		$2M	+$0.8M

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 Brewers 2	—	109	92	25	4	0	0	13	15	4	10	2	272	385	315	701	43	325	14	12	332	42	—	—	—	—	—	—
2025	18	ROK	DSL Brewers Gold	—	159	118	34	5	7	2	31	28	4	5	0	288	451	500	951	212	340	18	19	406	70	—	—	—	—	—	—
2026	19	ROK	ACL Brewers	—	156	116	29	7	2	5	32	48	4	6	1	250	425	474	899	224	364	31	21	394	70	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	17	ROK MLE	DSL Brewers 2	—	109	96	18	3	0	0	9	19	4	10	2	188	284	219	503	31	228	17	8	230	42	—	—	—	—	—	—
2025	18	ROK MLE	DSL Brewers Gold	—	159	128	22	3	4	1	21	36	4	5	0	172	307	281	588	109	207	23	13	272	70	—	—	—	—	—	—
2026	19	ROK MLE	ACL Brewers	—	156	129	22	5	1	4	20	69	4	6	1	171	301	318	618	147	279	44	13	271	70	—	—	—	—	—	—
2024	17	ROK MLE	DSL Brewers 2	—	109	96	18	3	0	0	9	19	4	10	2	188	284	219	503	31	234	17	8	230	42	—	—	—	—	—	—
2024	17	ROK RAW	DSL Brewers 2	—	109	92	25	4	0	0	13	15	4	10	2	272	385	315	701	43	325	14	12	332	42	—	—	—	—	—	—
2025	18	ROK MLE	DSL Brewers Gold	—	159	128	22	3	4	1	21	36	4	5	0	172	307	281	588	109	216	23	13	272	70	—	—	—	—	—	—
2025	18	ROK RAW	DSL Brewers Gold	—	159	118	34	5	7	2	31	28	4	5	0	288	451	500	951	212	340	18	19	406	70	—	—	—	—	—	—
2026	19	ROK MLE	ACL Brewers	—	156	129	22	5	1	4	20	69	4	6	1	171	301	318	618	147	305	44	13	271	70	—	—	—	—	—	—
2026	19	ROK RAW	ACL Brewers	—	156	116	29	7	2	5	32	48	4	6	1	250	425	474	899	224	364	31	21	394	70	—	—	—	—	—	—
2024	17	ROK MLE	DSL Brewers 2	—	109	95	18	3	0	0	9	19	4	10	2	189	284	221	505	32	228	17	8	230	42	—	—	—	—	—	—
2025	18	ROK MLE	DSL Brewers Gold	—	159	133	22	3	4	1	21	36	4	5	0	165	307	271	578	105	207	23	13	272	70	—	—	—	—	—	—
2026	19	ROK MLE	ACL Brewers	—	156	131	22	5	1	4	20	69	4	6	1	168	301	313	614	145	279	44	13	271	70	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	17	ROK MLE	DSL Brewers 2	—	109	95	18	3	0	0	9	19	4	10	2	189	284	221	505	32	228	17	8	230	42	—	—	—	—	—	—
2025	18	ROK MLE	DSL Brewers Gold	—	159	133	22	3	4	1	21	36	4	5	0	165	307	271	578	105	207	23	13	272	70	—	—	—	—	—	—
2026	19	ROK MLE	ACL Brewers	—	156	131	22	5	1	4	20	69	4	6	1	168	301	313	614	145	279	44	13	271	70	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	20	MLB MLE	MIL	0%	266	237	47	8	2	4	24	78	3	4	1	202	286	305	591	103	282	29	9	270	69	-10	+0	+0	+3	+6	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	21	MLB MLE	MIL	34%	131	116	24	4	1	2	12	38	2	2	1	207	291	317	608	111	283	29	9	277	74	-4	+0	+0	+1	+3	0.0
2029	22	MLB MLE	MIL	48%	224	198	42	7	2	4	21	64	3	4	1	210	294	327	621	117	284	29	9	282	77	-6	+0	+0	+2	+5	0.2
2030	23	MLB MLE	MIL	54%	319	283	61	11	3	6	29	89	4	5	1	213	297	335	631	121	286	28	9	286	80	-8	+1	+0	+3	+7	0.3
2031	24	MLB MLE	MIL	55%	388	344	74	13	3	8	36	107	5	6	2	216	299	340	639	124	287	28	9	289	82	-8	+0	+0	+4	+8	0.5
2032	25	MLB MLE	MIL	56%	427	379	84	15	4	9	39	117	6	7	2	218	300	344	645	127	287	27	9	291	83	-8	+1	+0	+5	+9	0.6
2033	26	MLB MLE	MIL	56%	448	398	86	15	4	9	41	122	6	7	2	218	300	344	644	127	287	27	9	291	83	-9	+1	+0	+5	+10	0.6
2034	27	MLB MLE	MIL	55%	456	405	87	15	4	9	42	125	6	7	2	217	299	342	641	125	286	27	9	290	82	-10	+1	+0	+5	+10	0.6
2035	28	MLB MLE	MIL	55%	455	404	87	15	4	9	42	126	6	6	2	215	297	337	634	122	286	28	9	287	81	-11	+0	-1	+5	+10	0.4
2036	29	MLB MLE	MIL	53%	447	398	85	15	4	8	41	125	5	6	2	213	295	331	626	119	284	28	9	284	78	-12	+0	-1	+5	+10	0.2
2037	30	MLB MLE	MIL	57%	437	389	81	14	3	8	40	124	5	5	2	210	291	324	615	114	283	28	9	279	75	-13	+0	-2	+5	+9	-0.1
2028	21	MLB CTX	MIL	34%	45	40	8	1	0	1	4	13	1	1	0	204	289	315	603	111	279	29	9	275	74	-1	+0	+0	+0	+1	0.0
2029	22	MLB CTX	MIL	48%	109	97	20	3	1	2	10	31	1	2	0	208	292	325	617	117	280	28	9	280	77	-3	+0	+0	+1	+2	0.1
2030	23	MLB CTX	MIL	54%	173	153	31	5	1	3	16	48	2	3	1	211	295	333	627	121	281	28	9	285	80	-4	+0	+0	+2	+4	0.2
2031	24	MLB CTX	MIL	55%	215	190	41	7	2	4	20	59	3	4	1	214	297	339	635	125	282	27	9	288	82	-5	+0	+0	+2	+5	0.3
2032	25	MLB CTX	MIL	56%	239	212	46	8	2	5	22	65	3	4	1	216	298	343	641	127	283	27	9	290	83	-5	+0	+0	+3	+5	0.3
2033	26	MLB CTX	MIL	56%	252	224	48	8	2	5	23	69	3	4	1	215	298	342	640	127	282	27	9	290	83	-5	+0	+0	+3	+5	0.4
2034	27	MLB CTX	MIL	55%	252	224	48	8	2	5	23	69	3	4	1	214	297	340	637	126	282	27	9	288	82	-5	+0	+0	+3	+5	0.3
2035	28	MLB CTX	MIL	55%	249	221	47	8	2	5	23	69	3	3	1	213	295	335	630	123	281	28	9	286	81	-6	+0	-0	+3	+5	0.2
2036	29	MLB CTX	MIL	53%	239	212	45	7	2	5	22	67	3	3	1	210	293	329	622	119	280	28	9	282	78	-6	+0	-1	+3	+5	0.1
2037	30	MLB CTX	MIL	57%	249	221	47	8	2	5	23	70	3	3	1	207	289	322	611	114	278	28	9	278	75	-7	+0	-1	+3	+5	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2022	1794	381	63	16	40	186	560	25	31	8	212	295	332	627	120	283	28	9	285	78	-48	+3	-2	+22	+44	1.9
/ 162G	—	A+C		—	650	577	122	20	5	13	60	180	8	10	3	211	295	331	626	120	282	28	9	285	78	-15	+1	-1	+7	+14	0.6
Career	—	MLE		—	4237	3740	788	138	38	78	400	1185	61	77	20	211	297	330	628	120	284	28	9	284	78	-91	+4	-4	+41	+83	3.3
/ 162G	—	MLE		—	650	574	121	21	6	12	61	182	9	12	3	211	296	331	627	120	284	28	9	284	78	-16	+1	-1	+7	+14	0.6

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 ROKACL Brewers · 156 PAwOBA .392 → .271 (−121)K% 30.8% → 44.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.77%	÷1.000	×1.440	—	—	44.31%
BB% (unintentional) /PA	20.51%	÷1.000	×0.620	—	×1.008	12.81%
HBP% /PA	2.56%	—	×0.720	—	×1.008	1.86%
Singles /BIP	22.06%	÷1.000	×0.820	×0.990	×1.008	18.05%
Doubles /BIP	10.29%	÷1.000	×0.720	×0.990	×1.008	7.40%
Triples /BIP	2.94%	÷1.000	×0.720	×0.990	×1.008	2.11%
Home runs /BIP	7.35%	÷1.000	×0.780	—	×1.008	5.78%

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 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 ×0.990.

Result: wOBA .392 → .271; ISO .224 → .160; BABIP .364 → .279. 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 DSLDSL Brewers Gold · 159 PAwOBA .412 → .272 (−140)K% 17.6% → 22.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.61%	÷0.947	×1.220	—	—	22.68%
BB% (unintentional) /PA	19.50%	÷1.021	×0.700	—	×1.008	13.47%
HBP% /PA	2.52%	—	×0.700	—	×1.008	1.77%
Singles /BIP	22.22%	÷1.006	×0.680	×0.955	×1.008	14.45%
Doubles /BIP	5.56%	÷0.958	×0.600	×0.955	×1.008	3.35%
Triples /BIP	7.78%	÷1.121	×0.600	×0.955	×1.008	4.01%
Home runs /BIP	2.22%	÷1.040	×0.470	—	×1.008	1.01%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 108, 1B 101, 2B 92, 3B 124, K 89, BB 104 — 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 ×0.955.

Result: wOBA .412 → .272; ISO .212 → .120; BABIP .340 → .207. 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 Brewers 2 · 109 PAwOBA .324 → .230 (−94)K% 13.8% → 17.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.76%	÷0.989	×1.220	—	—	16.97%
BB% (unintentional) /PA	11.93%	÷1.012	×0.700	—	×1.022	8.44%
HBP% /PA	3.67%	—	×0.700	—	×1.022	2.63%
Singles /BIP	27.27%	÷0.989	×0.680	×1.016	×1.022	19.48%
Doubles /BIP	5.19%	÷0.968	×0.600	×1.016	×1.022	3.34%
Triples /BIP	0.00%	÷1.150	×0.600	×1.016	×1.022	0.00%
Home runs /BIP	0.00%	÷0.808	×0.470	—	×1.022	0.00%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 62, 1B 98, 2B 94, 3B 130, K 98, BB 102 — applied at half strength. Age: age 17 vs a level average of 18.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.016.

Result: wOBA .324 → .230; ISO .043 → .028; BABIP .325 → .228. 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
#1Gordon Beckhamlast yr '19 career totals — 10 seasons, 3,764 PA	5.7	3,764	80	34	237	301	368	+13	+19	8.2	8.4
/162	664	14	6	+2.4	+3.4	1.4	pk7: 9
#2Jose Uribe'84-'93 * career totals — 9 seasons, 3,369 PA	5.1	3,369	19	74	240*	300*	338*	+36	+27	7.8	7.7
/162	664	4	15	+7.1	+5.3	1.5	pk7: 8
#3Gene 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
#4Ronny 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
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	3.2	2,104	40	31	215	294	336	+23	+18	3.2	3.0
/162	664	13	10	+7.1	+5.7	1.0	pk7: 3
#5Tim 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
#6Ryan 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

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
Jonathan Rangel (OGILVIE)	20	45	40	45	60	200/284/302	102	282	1	1	29%	9%	69	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Hoy Park 2016 · A	20	40→50	41→45	47→55	46	197/270/297	100	265	8	11	28%	8%	62	-1.4	207/284/295	88	286	5	16	27%	9%	67	-1.1	234/324/332	98	306	8	17	24%	11%	88	+0.3
✕Canaan Smith-Njigba 2019 · A	20	46→51	41→45	46→55	51	218/304/317	98	298	9	7	28%	10%	79	-0.2	237/308/353	116	333	10	11	29%	9%	88	+0.5	242/319/359	118	343	9	15	29%	10%	91	+0.4
✕Randy Florentino 2021 · A	21	42	39→45	42→45	49	199/281/287	88	284	6	6	30%	10%	64	-1.3	180/242/262	82	268	8	5	34%	7%	43	-2.8	183/231/259	76	238	8	4	26%	5%	37	-1.0
✕Angel Ortiz 2022 · A	19	42→45	41→50	46→45	44	206/261/296	90	269	9	9	26%	7%	57	-1.8	207/257/302	95	281	7	7	27%	6%	57	-1.8	227/286/370	143	294	13	8	26%	7%	82	+0.0
✕John Whittleman 2007 · A	20	42→45	40→50	46→45	47	202/267/297	95	265	7	7	26%	8%	60	-1.6	209/290/329	120	288	11	4	28%	10%	77	-0.3	203/292/325	122	277	11	2	29%	11%	76	-0.4
✕Eddys Leonard 2021 · A	20	42→47	39→50	45→50	45	198/273/287	89	286	6	8	31%	8%	61	-1.5	229/297/377	148	305	16	5	29%	7%	91	+0.6	227/295/375	148	296	16	4	28%	6%	86	+0.3
✕Carlos Rodriguez 2023 · A	20	37	39→45	47→45	49	178/272/261	83	262	6	6	32%	10%	55	-1.9	190/264/264	74	295	5	6	34%	9%	52	-2.2	178/256/266	88	258	7	2	31%	9%	47	-1.0
✕Cam Collier 2024 · A	19	46→44	40→45	47→40	46	215/292/308	93	309	8	5	31%	9%	72	-0.7	214/289/325	111	309	11	3	32%	9%	76	-0.4	204/279/320	116	291	12	1	32%	8%	69	-0.8
✕Anthony Seigler 2019 · A	20	45→40	38→45	48→55	50	214/284/293	79	268	6	5	22%	8%	66	-1.1	196/276/274	78	288	5	5	30%	9%	59	-1.7	221/312/347	126	270	10	25	21%	11%	87	+0.2
✕Shed Long Jr. 2016 · A	20	44→50	42→50	44→50	43	216/269/322	106	282	10	6	27%	6%	66	-1.1	235/294/368	133	322	13	11	29%	7%	87	+0.4	238/300/387	148	320	15	11	29%	7%	91	+0.5
✕Imanol Vargas 2018 · A	20	42→43	39→50	43→45	46	195/281/282	87	299	6	7	34%	10%	63	-1.3	194/285/297	103	277	9	8	30%	11%	68	-1.0	198/285/355	157	311	19	2	39%	10%	79	-0.2
✕Izaac Pacheco 2023 · A	20	41→40	42→50	47→45	42	201/260/306	105	290	10	8	33%	7%	59	-1.6	187/250/307	120	297	13	5	39%	7%	57	-1.8	185/263/344	159	294	20	3	41%	9%	69	-0.6
✕Daniel Montesino 2023 · A	19	46	38→40	48→45	50	212/301/299	87	300	5	8	28%	10%	74	-0.5	199/264/269	70	309	2	9	33%	7%	53	-2.1	176/234/225	50	289	0	8	36%	6%	29	-1.1
✕Enmanuel Terrero 2023 · A	20	46	37→45	47→55	56	216/300/287	72	267	3	12	19%	11%	71	-0.8	208/277/303	95	322	9	15	35%	8%	65	-1.2	191/260/285	94	305	11	18	38%	8%	53	-0.8
✕Darrien Miller 2021 · A	20	42	36→45	47→45	43	198/274/269	70	273	3	8	27%	6%	57	-1.8	204/306/321	117	276	13	6	29%	9%	82	+0.0	179/320/285	107	245	9	4	27%	12%	79	-0.1
✕Iverson Leonardo 2022 · A	20	40	43→45	47→50	42	192/272/308	116	291	10	9	35%	8%	65	-1.2	188/265/289	101	308	9	8	38%	8%	59	-1.7	157/243/251	94	257	8	8	39%	8%	41	-0.7
✕Ryan Mount 2007 · A	20	42	42→50	49→50	42	206/265/309	102	291	10	8	32%	7%	62	-1.4	224/270/342	118	294	12	11	27%	6%	72	-0.7	242/286/380	138	297	15	8	23%	5%	85	+0.1
✕Dayan Frias 2022 · A	20	44→43	39→40	48→55	48	210/286/301	91	288	5	7	27%	9%	69	-0.9	209/284/301	92	305	7	6	31%	9%	68	-1.0	201/280/292	91	289	8	6	31%	9%	62	-1.1
✕Josh Johnson 2006 · A	20	43→50	39→45	48→50	50	203/281/298	95	268	5	9	24%	9%	66	-1.1	222/309/292	70	291	3	10	22%	11%	75	-0.5	247/316/346	99	293	8	16	17%	9%	86	+0.2
✕Manuel Pena 2024 · A	20	43→50	39→50	47→50	39	203/254/293	90	301	6	10	33%	6%	54	-2.0	227/266/337	110	316	10	7	30%	5%	69	-0.9	238/273/365	128	316	15	5	29%	4%	76	-0.4

Jonathan Rangel

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps