Javier Osorio

SS Lakeland Flying Tigers

Age 22 R/R 6'0" / 165 lbs A HR -8% Svc 0.0 · Ctrl thru 2037

Overview

APROSPECTMiLBFA 2038

OGV OFP35OGV rank#1123ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	19	ROKDSL Tigers 2	198	.304/.434/.503	3	19	62	—	.175/.288/.269
2025	20	ROKDET	146	.304/.389/.488	5	20	72	—	.215/.292/.346
2026	21	ADET	287	.251/.330/.414	9	29	59	—	.201/.266/.324
2027PROJMLE	22	MLBDET	397	.206/.268/.335	10	11	69	0.1
2028PROJ34% MLB	23	MLBDET	73	.207/.269/.338	2	2	74	0.0
2029PROJ46% MLB	24	MLBDET	136	.210/.274/.346	4	4	77	0.1

Next 3 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2037Service0.0First FA2038

2027MiLB2028MiLB2029MiLB2030MiLB2031MiLB2032Pre-Arb$0.9M2033Pre-Arb$0.9M2034Pre-Arb$1.0M+3

Skills · percentileMiLB Statcast 2026 A

Max EV72

Speed67

K%52

Z-Con%40

Whiff%33

BB%26

Career WAR0.0 WAR median (P10 0.0 / P90 1.4, comp-based) · star 2% · didn't stick 91%

CompsCooper Bowman (age 22) · Juan Mora (age 22) · Tim Tawa (age 23)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 172 proj PA

wRC+†69

AVG/OBP/SLG.204 / .265 / .332

PA172

HR4

SB5

K%25

BB%6

ISO129

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$6M ctrl surplus

Tools · ContractCON 35 / POW 50

Toolsscout grade

CONTACT35

scouting grade only

POWER50

scouting grade only

EYE46

scouting grade only

SPEED70

scouting grade only

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

Status MiLB

MLB Debut 2032

Service 0 yrs (est)

Team Control Through 2037

First FA Year 2038

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2032
2028	MiLB	still in minors · estimated debut 2032
2029	MiLB	still in minors · estimated debut 2032
2030	MiLB	still in minors · estimated debut 2032
2031	MiLB	still in minors · estimated debut 2032
2032	Pre-Arb	$0.9M	+0.3	$0.8M	+$0.3M
2033	Pre-Arb	$0.9M	+0.2	$0.5M	+$0.0M
2034	Pre-Arb	$1.0M	+0.1	$0.2M	+$0.0M (cut)
2035	Arb-1	$0.4M	—	—	—
2036	Ext	beyond projection horizon · no WAR estimate
2037	Ext	beyond projection horizon · no WAR estimate
Totals		$2M		$1M	+$0.3M

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)
2022	17	ROK	DSL Tigers 1	—	178	154	27	5	0	1	16	68	7	15	3	175	282	227	510	52	302	38	9	246	-10	—	—	—	—	—	—
2023	18	ROK	DSL Tigers 2	—	117	103	28	6	2	5	11	40	3	11	2	272	359	515	874	243	397	34	9	383	30	—	—	—	—	—	—
2024	19	ROK	DSL Tigers 2	—	198	161	49	15	4	3	30	44	7	19	6	304	434	503	937	199	404	22	15	417	62	—	—	—	—	—	—
2025	20	ROK	FCL Tigers	—	146	125	38	8	0	5	11	34	7	20	4	304	389	488	877	184	375	23	8	384	72	—	—	—	—	—	—
2026	21	A	Lakeland Flying Tigers	—	287	251	63	14	0	9	25	67	5	29	7	251	330	414	744	163	300	23	9	328	59	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2022	17	ROK MLE	DSL Tigers 1	—	178	159	16	3	0	0	11	84	7	15	3	101	192	119	312	19	203	47	6	154	-10	—	—	—	—	—	—
2023	18	ROK MLE	DSL Tigers 2	—	117	106	15	3	1	2	8	50	3	11	2	142	222	245	468	104	244	43	7	213	30	—	—	—	—	—	—
2024	19	ROK MLE	DSL Tigers 2	—	198	171	30	9	2	1	20	54	7	19	6	175	288	269	557	94	251	27	10	260	62	—	—	—	—	—	—
2025	20	ROK MLE	FCL Tigers	—	146	130	28	5	0	4	7	49	7	20	4	215	292	346	638	131	287	34	5	274	72	—	—	—	—	—	—
2026	21	A MLE	Lakeland Flying Tigers	—	287	259	52	11	0	7	18	91	5	29	7	201	266	324	590	124	260	32	6	256	59	—	—	—	—	—	—
2022	17	ROK MLE	DSL Tigers 1	—	178	159	16	3	0	0	11	84	7	15	3	101	192	119	312	19	211	47	6	154	-10	—	—	—	—	—	—
2022	17	ROK RAW	DSL Tigers 1	—	178	154	27	5	0	1	16	68	7	15	3	175	282	227	510	52	302	38	9	246	-10	—	—	—	—	—	—
2023	18	ROK MLE	DSL Tigers 2	—	117	106	15	3	1	2	8	50	3	11	2	142	222	245	468	104	241	43	7	213	30	—	—	—	—	—	—
2023	18	ROK RAW	DSL Tigers 2	—	117	103	28	6	2	5	11	40	3	11	2	272	359	515	874	243	397	34	9	383	30	—	—	—	—	—	—
2024	19	ROK MLE	DSL Tigers 2	—	198	171	30	9	2	1	20	54	7	19	6	175	288	269	557	94	250	27	10	260	62	—	—	—	—	—	—
2024	19	ROK RAW	DSL Tigers 2	—	198	161	49	15	4	3	30	44	7	19	6	304	434	503	937	199	404	22	15	417	62	—	—	—	—	—	—
2025	20	ROK MLE	FCL Tigers	—	146	130	28	5	0	4	7	49	7	20	4	215	292	346	638	131	304	34	5	274	72	—	—	—	—	—	—
2025	20	ROK RAW	FCL Tigers	—	146	125	38	8	0	5	11	34	7	20	4	304	389	488	877	184	375	23	8	384	72	—	—	—	—	—	—
2026	21	A MLE	Lakeland Flying Tigers	—	287	259	52	11	0	7	18	91	5	29	7	201	266	324	590	124	271	32	6	256	59	—	—	—	—	—	—
2026	21	A RAW	Lakeland Flying Tigers	—	287	251	63	14	0	9	25	67	5	29	7	251	330	414	744	163	300	23	9	328	59	—	—	—	—	—	—
2022	17	ROK MLE	DSL Tigers 1	—	178	158	16	3	0	0	11	84	7	15	3	101	192	120	312	19	203	47	6	154	-10	—	—	—	—	—	—
2023	18	ROK MLE	DSL Tigers 2	—	117	105	15	3	1	2	8	50	3	11	2	143	222	248	470	105	244	43	7	213	30	—	—	—	—	—	—
2024	19	ROK MLE	DSL Tigers 2	—	198	169	30	9	2	1	20	54	7	19	6	178	288	272	560	95	251	27	10	260	62	—	—	—	—	—	—
2025	20	ROK MLE	FCL Tigers	—	146	131	28	5	0	4	7	49	7	20	4	214	292	344	635	130	287	34	5	274	72	—	—	—	—	—	—
2026	21	A MLE	Lakeland Flying Tigers	—	287	262	52	11	0	7	18	91	5	29	7	198	266	321	587	122	260	32	6	256	59	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	19	ROK MLE	DSL Tigers 2	—	198	169	30	9	2	1	20	54	7	19	6	178	288	272	560	95	251	27	10	260	62	—	—	—	—	—	—
2025	20	ROK MLE	FCL Tigers	—	146	131	28	5	0	4	7	49	7	20	4	214	292	344	635	130	287	34	5	274	72	—	—	—	—	—	—
2026	21	A MLE	Lakeland Flying Tigers	—	287	262	52	11	0	7	18	91	5	29	7	198	266	321	587	122	260	32	6	256	59	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	DET	0%	397	364	76	15	2	10	25	99	5	11	3	206	268	335	602	129	254	25	6	270	69	-15	+1	+0	+4	+9	0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	DET	34%	212	193	41	8	1	6	14	52	3	6	1	211	273	346	619	136	256	25	7	277	74	-7	+1	+0	+2	+5	0.1
2029	24	MLB MLE	DET	46%	295	269	57	11	1	8	20	72	4	8	2	214	277	355	632	141	259	24	7	282	77	-8	+1	+0	+3	+6	0.2
2030	25	MLB MLE	DET	52%	349	317	68	13	1	10	24	85	5	10	2	216	280	360	640	144	261	24	7	286	80	-8	+1	+0	+4	+8	0.4
2031	26	MLB MLE	DET	54%	379	345	75	14	2	11	26	92	5	10	3	218	282	363	645	145	262	24	7	288	81	-9	+1	+0	+4	+8	0.5
2032	27	MLB MLE	DET	54%	391	356	78	15	2	11	27	95	5	10	3	218	283	363	646	144	263	24	7	288	81	-9	+1	+0	+4	+8	0.5
2033	28	MLB MLE	DET	54%	393	358	78	15	2	11	27	96	5	9	2	217	281	358	640	142	263	24	7	286	80	-10	+1	-1	+4	+9	0.4
2034	29	MLB MLE	DET	53%	386	351	74	14	1	10	27	96	5	7	2	214	279	353	631	138	261	25	7	282	77	-10	+1	-1	+4	+8	0.1
2035	30	MLB MLE	DET	52%	376	343	73	14	1	10	26	94	4	5	2	212	275	345	621	134	260	25	7	278	74	-11	+0	-2	+4	+8	-0.1
2028	23	MLB CTX	DET	34%	73	67	14	3	0	2	5	18	1	2	1	207	269	338	607	131	252	25	7	272	74	-2	+0	+0	+1	+2	0.0
2029	24	MLB CTX	DET	46%	136	124	27	5	1	4	9	33	2	4	1	210	274	346	619	136	255	24	7	277	77	-4	+0	+0	+1	+3	0.1
2030	25	MLB CTX	DET	52%	180	164	36	7	1	5	12	44	2	5	1	212	276	351	627	139	257	24	7	281	80	-4	+1	+0	+2	+4	0.2
2031	26	MLB CTX	DET	54%	205	186	41	8	1	6	14	50	3	6	1	214	279	354	632	140	258	24	7	283	81	-5	+1	+0	+2	+4	0.3
2032	27	MLB CTX	DET	54%	212	192	42	8	1	6	15	51	3	6	1	214	280	354	633	139	259	24	7	283	81	-5	+1	+0	+2	+5	0.3
2033	28	MLB CTX	DET	54%	213	193	42	8	1	6	15	52	3	5	1	213	278	349	627	137	258	24	7	281	80	-5	+1	-0	+2	+5	0.2
2034	29	MLB CTX	DET	53%	205	187	40	8	1	5	14	51	2	4	1	210	275	344	619	133	257	25	7	277	77	-6	+0	-1	+2	+4	0.1
2035	30	MLB CTX	DET	52%	197	180	38	7	1	5	13	49	2	3	1	208	272	337	609	129	256	25	7	273	74	-6	+0	-1	+2	+4	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1421	1293	280	54	7	39	97	348	18	35	8	217	281	360	640	143	264	24	7	279	70	-36	+4	-2	+15	+31	1.1
/ 162G	—	A+C		—	650	591	128	25	3	18	44	159	8	16	4	217	280	360	640	144	264	24	7	279	70	-17	+2	-1	+7	+14	0.5
Career	—	MLE		—	3879	3514	717	141	15	95	266	1053	67	164	40	204	273	334	607	130	260	27	7	272	70	-78	+7	-4	+32	+64	2.0
/ 162G	—	MLE		—	650	589	121	24	3	16	45	176	11	27	7	205	275	338	613	132	262	27	7	272	70	-17	+1	-1	+7	+14	0.5

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.

2026 ALakeland Flying Tigers · 287 PAwOBA .325 → .256 (−69)K% 23.3% → 31.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.34%	÷1.000	×1.360	—	—	31.75%
BB% (unintentional) /PA	8.71%	÷1.000	×0.690	—	×1.015	6.10%
HBP% /PA	1.74%	—	×0.780	—	×1.015	1.38%
Singles /BIP	21.74%	÷1.000	×0.920	×0.961	×1.015	19.51%
Doubles /BIP	7.61%	÷1.000	×0.830	×0.961	×1.015	6.16%
Triples /BIP	0.00%	÷1.000	×0.910	×0.961	×1.015	0.00%
Home runs /BIP	4.89%	÷1.000	×0.800	—	×1.015	3.97%

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 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 ×0.961.

Result: wOBA .325 → .256; ISO .163 → .126; BABIP .300 → .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).

2025 ROKFCL Tigers · 146 PAwOBA .379 → .274 (−105)K% 23.3% → 33.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.29%	÷1.001	×1.440	—	—	33.50%
BB% (unintentional) /PA	7.53%	÷0.996	×0.620	—	×0.995	4.67%
HBP% /PA	4.79%	—	×0.720	—	×0.995	3.43%
Singles /BIP	27.47%	÷0.974	×0.820	×0.954	×0.995	21.96%
Doubles /BIP	8.79%	÷0.992	×0.720	×0.954	×0.995	6.06%
Triples /BIP	0.00%	÷0.900	×0.720	×0.954	×0.995	0.00%
Home runs /BIP	5.49%	÷0.880	×0.780	—	×0.995	4.85%

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 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 ×0.954.

Result: wOBA .379 → .274; ISO .184 → .140; BABIP .375 → .287. 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 · 198 PAwOBA .404 → .260 (−144)K% 22.2% → 27.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.22%	÷0.986	×1.220	—	—	27.49%
BB% (unintentional) /PA	14.14%	÷0.973	×0.700	—	×0.995	10.12%
HBP% /PA	3.54%	—	×0.700	—	×0.995	2.46%
Singles /BIP	23.08%	÷0.995	×0.680	×0.971	×0.995	15.24%
Doubles /BIP	12.82%	÷0.951	×0.600	×0.971	×0.995	7.81%
Triples /BIP	3.42%	÷1.135	×0.600	×0.971	×0.995	1.75%
Home runs /BIP	2.56%	÷0.995	×0.470	—	×0.995	1.21%

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 19 vs a level average of 18.5 → −0.5% on BB/HBP/hit rates (0.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.971.

Result: wOBA .404 → .260; ISO .199 → .110; BABIP .404 → .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).

2023 DSLDSL Tigers 2 · 117 PAwOBA .373 → .213 (−160)K% 34.2% → 42.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	34.19%	÷0.983	×1.220	—	—	42.44%
BB% (unintentional) /PA	9.40%	÷0.997	×0.700	—	×1.008	6.65%
HBP% /PA	2.56%	—	×0.700	—	×1.008	1.81%
Singles /BIP	23.81%	÷1.012	×0.680	×1.009	×1.008	16.27%
Doubles /BIP	9.52%	÷1.101	×0.600	×1.009	×1.008	5.27%
Triples /BIP	3.17%	÷1.009	×0.600	×1.009	×1.008	1.92%
Home runs /BIP	7.94%	÷1.009	×0.470	—	×1.008	3.72%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 102, 1B 102, 2B 120, 3B 102, K 97, BB 99 — 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 ×1.009.

Result: wOBA .373 → .213; ISO .243 → .113; BABIP .397 → .244. 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).

2022 DSLDSL Tigers 1 · 178 PAwOBA .242 → .154 (−88)K% 38.2% → 47.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	38.20%	÷0.992	×1.220	—	—	46.97%
BB% (unintentional) /PA	8.99%	÷1.028	×0.700	—	×1.022	6.26%
HBP% /PA	3.93%	—	×0.700	—	×1.022	2.81%
Singles /BIP	24.42%	÷1.033	×0.680	×1.027	×1.022	16.88%
Doubles /BIP	5.81%	÷1.019	×0.600	×1.027	×1.022	3.59%
Triples /BIP	0.00%	÷1.150	×0.600	×1.027	×1.022	0.00%
Home runs /BIP	1.16%	÷0.996	×0.470	—	×1.022	0.56%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 99, 1B 107, 2B 104, 3B 130, K 98, BB 106 — 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 ×1.027.

Result: wOBA .242 → .154; ISO .052 → .027; BABIP .302 → .203. 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
#1Danny Espinosalast yr '17 career totals — 8 seasons, 3,267 PA	4.9	3,267	98	64	221	297	378	+16	+36	11.0	11.4
/162	664	20	13	+3.2	+7.3	2.2	pk7: 12
#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
#3Mike Tyson'72-'81 * career totals — 9 seasons, 3,200 PA	4.8	3,200	27	23	236*	281*	354*	+20	+24	1.9	3.3
/162	664	6	5	+4.1	+4.9	0.4	pk7: 5
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 5 projected seasons	2.4	1,594	43	39	215	276	356	+17	+15	2.2	2.1
/162	664	18	16	+7.1	+6.2	0.9	pk7: 2
#4Ryan 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
#5Pete Mackanin'73-'81 * career totals — 6 seasons, 1,686 PA	2.5	1,686	30	27	222*	261*	370*	+6	+23	0.6	1.6
/162	664	12	11	+2.4	+8.9	0.2	pk7: 3
#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
Javier Osorio (OGILVIE)	22	30→35	45→50	65→70	46	204/265/332	127	254	4	5	25%	6%	69	-0.3	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Cooper Bowman 2022 · A	22	44	45	56→60	41	214/289/346	132	303	12	19	32%	7%	81	-0.1	204/281/321	117	287	12	34	31%	8%	72	-0.7	210/283/330	120	279	11	40	27%	8%	72	-0.5
✕Juan Mora 2022 · A	22	44	42→45	55	47	215/295/325	110	284	9	14	26%	8%	78	-0.3	222/280/325	103	297	9	9	27%	6%	72	-0.7	218/275/319	102	286	9	8	26%	5%	67	-0.5
✕Tim Tawa 2022 · A	23	45	47→55	58→50	45	221/289/359	138	303	14	18	30%	8%	83	+0.1	213/278/339	126	273	14	11	26%	8%	74	-0.5	223/286/391	168	267	21	13	25%	7%	88	+0.3
✕Trey Sweeney 2023 · AA	23	38→45	48→50	57→55	45	200/273/344	144	263	16	19	30%	8%	74	-0.5	218/289/354	136	286	15	17	28%	8%	82	+0.0	219/291/353	133	286	15	17	27%	8%	81	-0.1
✕Brayan Buelvas 2024 · AA	22	37→45	46→50	55	41	190/252/319	129	260	13	18	32%	7%	61	-1.5	204/265/326	122	293	11	16	32%	7%	66	-1.1	205/266/334	130	290	12	14	32%	7%	66	-0.8
✕Ceddanne Rafaela 2022 · A	21	43→53	46→55	59→55	39	215/259/351	136	270	13	15	26%	4%	70	-0.9	243/280/401	158	309	17	22	26%	4%	89	+0.5	250/287/402	152	300	17	19	22%	4%	93	+0.8
✕Sean Coyle 2014 · A	22	38	49→50	54→50	37	197/258/345	148	285	17	14	36%	6%	69	-0.9	206/268/346	140	308	16	13	36%	7%	73	-0.6	188/254/312	124	285	15	12	37%	7%	57	-1.0
✕Max Wagner 2024 · AA	22	41→38	46→50	55→50	42	204/275/332	128	291	13	18	33%	8%	72	-0.7	195/261/317	122	302	13	12	37%	7%	63	-1.3	190/255/330	140	291	17	7	39%	7%	61	-0.9
✕Cayden Wallace 2023 · A	21	46→49	42→50	57→50	43	224/279/341	116	300	8	15	27%	6%	74	-0.5	220/277/337	117	289	10	12	26%	6%	73	-0.6	232/281/372	140	285	16	15	24%	5%	80	-0.1
✕Mario Lisson 2006 · A	22	46→49	43→50	57→55	50	221/307/345	123	302	9	19	28%	10%	86	+0.3	220/283/335	115	289	10	21	26%	7%	75	-0.5	222/292/345	123	288	15	8	27%	7%	80	-0.1
✕Jared Serna 2024 · A	22	45→48	45	53→50	45	226/284/352	126	276	13	18	23%	7%	79	-0.2	214/271/321	107	261	11	15	22%	6%	68	-1.0	202/265/300	97	245	10	16	21%	6%	58	-1.4
✕Jase Bowen 2023 · A	22	39→42	44→50	55	35	195/250/303	109	296	12	14	37%	5%	56	-1.9	203/253/327	124	287	14	19	33%	5%	62	-1.4	209/260/343	134	298	14	23	33%	6%	66	-0.7
✕Clay Fuller 2009 · A	22	46	42→45	59→55	44	214/295/330	116	316	8	20	32%	8%	79	-0.2	209/279/321	112	294	11	18	31%	8%	71	-0.8	203/269/311	107	279	12	18	30%	7%	62	-1.0
✕Michael Guldberg 2022 · A	23	45	44→45	55	44	222/290/341	119	280	12	16	24%	7%	80	-0.2	214/272/298	84	283	6	12	25%	6%	62	-1.4	205/259/264	60	274	3	10	25%	6%	47	-0.7
✕Evan Van Hoosier 2015 · A	21	47	44→50	56→50	44	229/282/358	129	287	10	10	23%	6%	80	-0.2	230/274/338	108	308	6	9	26%	5%	72	-0.7	232/275/343	110	324	5	10	28%	4%	70	-0.3
✕Johan Lopez 2022 · A	22	44	44→45	56→55	44	210/292/329	119	303	11	16	32%	8%	78	-0.3	197/269/298	101	299	9	12	35%	8%	62	-1.4	173/246/259	86	259	8	12	34%	7%	43	-1.0
✕John Rhodes 2023 · AA	22	43→37	41→45	58→50	47	208/286/313	105	274	8	16	26%	8%	72	-0.7	190/258/293	103	266	10	9	31%	7%	57	-1.8	173/241/264	91	242	10	7	31%	7%	41	-2.2
✕Eric Brown Jr. 2023 · A	22	45→33	44→40	59→55	46	221/296/340	119	291	10	27	26%	8%	82	-0.0	195/262/276	81	252	7	28	24%	7%	55	-2.0	172/239/236	65	221	6	29	24%	7%	34	-1.6
✕Mason Auer 2023 · A	22	47	47→45	63→60	43	230/292/371	140	304	13	29	28%	7%	86	+0.3	190/249/304	114	290	10	31	36%	6%	55	-1.9	163/223/268	105	258	9	37	39%	6%	35	-2.4
✕Noel Cuevas 2014 · A	22	47→52	43→45	56→55	41	231/276/347	116	293	10	24	24%	5%	75	-0.5	229/266/325	96	296	7	17	24%	4%	65	-1.2	254/287/363	108	316	8	12	22%	3%	80	-0.1

Javier Osorio

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps