Franyerber Montilla

SS Lakeland Flying Tigers

Age 22 S/R 6'0" / 160 lbs A HR -8% Svc 0.0 · Ctrl thru 2033

Overview

APROSPECTMiLBFA 2034

OGV OFP35OGV rank#776ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2023	18	ROKDSL Tigers 1	127	.280/.394/.439	3	11	45	—	.170/.268/.277
2024	19	A/ROKDET	295	.226/.375/.362	6	30	50	—	.164/.273/.262
2025	20	ADET	299	.271/.369/.395	4	27	65	—	.202/.285/.288
2027PROJMLE	22	MLBDET	409	.204/.289/.314	7	10	72	0.1
2028PROJ34% MLB	23	MLBDET	38	.205/.289/.318	1	1	76	0.1
2029PROJ46% MLB	24	MLBDET	88	.208/.292/.325	2	2	79	0.1

Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2033Service0.0First FA2034

2027MiLB2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Pre-Arb$0.8M2031Arb-1$2M2032Arb-2$4M2033Arb-3$4M

Skills · percentileMiLB Statcast 2025 A

Speed85

Max EV78

BB%55

Whiff%49

K%45

Chase%38

CompsJuan Mora (age 22) · Wilmer Difo (age 22) · Brainer Bonaci (age 21)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 96 proj PA

wRC+†72

AVG/OBP/SLG.203 / .286 / .311

PA96

HR2

K%26

BB%9

ISO109

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$1M ctrl surplus

Contract

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

Status MiLB

MLB Debut 2028

Service 0 yrs (est)

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2028
2028	Pre-Arb	$0.8M	+0.1	$0.4M	+$0.0M (cut)
2029	Pre-Arb	$0.8M	+0.1	$0.3M	+$0.0M (cut)
2030	Pre-Arb	$0.8M	+0.3	$1.0M	+$0.3M
2031	Arb-1	$2M	+0.4	$1M	+$0.0M (cut)
2032	Arb-2	$4M	+0.4	$1M	+$0.0M (cut)
2033	Arb-3	$4M	+0.4	$1M	+$0.0M (cut)
Totals		$0.8M		$5M	+$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	—	216	176	37	8	4	3	38	62	1	11	6	210	353	352	706	142	304	29	18	325	23	—	—	—	—	—	—
2023	18	ROK	DSL Tigers 1	—	127	107	30	6	1	3	17	22	3	11	5	280	394	439	833	159	329	17	13	376	45	—	—	—	—	—	—
2024	19	A	Lakeland Flying Tigers	—	79	63	6	2	0	0	12	25	4	6	1	95	278	127	405	32	158	32	15	222	-6	—	—	—	—	—	—
2024	19	ROK	FCL Tigers	—	216	172	47	12	0	6	38	40	3	24	7	273	411	448	859	174	320	19	18	384	71	—	—	—	—	—	—
2025	20	A	Lakeland Flying Tigers	—	299	258	70	16	2	4	38	74	2	27	7	271	369	395	764	124	365	25	13	346	65	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2022	17	ROK MLE	DSL Tigers 1	—	216	187	22	5	2	1	27	76	1	11	6	118	233	182	414	64	189	35	12	202	23	—	—	—	—	—	—
2023	18	ROK MLE	DSL Tigers 1	—	127	112	19	4	1	2	12	27	3	11	5	170	268	277	545	107	201	21	9	235	45	—	—	—	—	—	—
2024	19	A MLE	Lakeland Flying Tigers	—	79	67	5	1	0	0	8	33	4	6	1	75	215	90	305	15	136	42	10	159	-6	—	—	—	—	—	—
2024	19	ROK MLE	FCL Tigers	—	216	188	37	9	0	5	23	58	3	24	7	197	294	324	619	128	245	27	11	273	71	—	—	—	—	—	—
2025	20	A MLE	Lakeland Flying Tigers	—	299	267	54	12	1	3	29	101	2	27	7	202	285	288	574	86	314	34	10	265	65	—	—	—	—	—	—
2022	17	ROK MLE	DSL Tigers 1	—	216	187	22	5	2	1	27	76	1	11	6	118	233	182	414	64	189	35	12	202	23	—	—	—	—	—	—
2022	17	ROK RAW	DSL Tigers 1	—	216	176	37	8	4	3	38	62	1	11	6	210	353	352	706	142	304	29	18	325	23	—	—	—	—	—	—
2023	18	ROK MLE	DSL Tigers 1	—	127	112	19	4	1	2	12	27	3	11	5	170	268	277	545	107	205	21	9	235	45	—	—	—	—	—	—
2023	18	ROK RAW	DSL Tigers 1	—	127	107	30	6	1	3	17	22	3	11	5	280	394	439	833	159	329	17	13	376	45	—	—	—	—	—	—
2024	19	ROK MLE	2 teams	—	295	255	42	10	0	5	31	91	7	30	8	165	273	263	536	98	230	31	11	242	50	—	—	—	—	—	—
2024	19	ROK RAW	2 teams	—	295	235	53	14	0	6	50	65	7	30	8	226	375	362	737	136	283	22	17	340	50	—	—	—	—	—	—
2025	20	A MLE	Lakeland Flying Tigers	—	299	267	54	12	1	3	29	101	2	27	7	202	285	288	574	86	311	34	10	265	65	—	—	—	—	—	—
2025	20	A RAW	Lakeland Flying Tigers	—	299	258	70	16	2	4	38	74	2	27	7	271	369	395	764	124	365	25	13	346	65	—	—	—	—	—	—
2022	17	ROK MLE	DSL Tigers 1	—	216	186	22	5	2	1	27	76	1	11	6	118	233	183	415	65	189	35	12	202	23	—	—	—	—	—	—
2023	18	ROK MLE	DSL Tigers 1	—	127	111	19	4	1	2	12	27	3	11	5	171	268	279	547	108	201	21	9	235	45	—	—	—	—	—	—
2024	19	ROK MLE	2 teams	—	295	255	42	10	0	5	31	91	7	30	8	165	273	263	536	98	216	31	11	242	50	—	—	—	—	—	—
2025	20	A MLE	Lakeland Flying Tigers	—	299	266	54	12	1	3	29	101	2	27	7	203	285	289	575	86	314	34	10	265	65	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	19	ROK MLE	2 teams	—	295	255	42	10	0	5	31	91	7	30	8	165	273	263	536	98	216	31	11	242	50	—	—	—	—	—	—
2025	20	A MLE	Lakeland Flying Tigers	—	299	266	54	12	1	3	29	101	2	27	7	203	285	289	575	86	314	34	10	265	65	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	DET	0%	409	363	74	15	2	7	39	105	4	10	3	204	289	314	602	109	265	26	10	275	72	-14	+1	+1	+4	+9	0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	DET	34%	110	98	21	4	1	2	10	28	1	3	1	209	293	325	618	116	267	25	9	281	76	-3	+0	+0	+1	+2	0.1
2029	24	MLB MLE	DET	46%	190	168	36	7	1	4	18	48	2	5	1	212	296	333	629	121	269	25	9	285	79	-5	+1	+1	+2	+4	0.3
2030	25	MLB MLE	DET	52%	267	237	51	10	1	6	25	66	3	7	2	214	297	338	636	124	270	25	9	288	81	-6	+1	+2	+3	+6	0.5
2031	26	MLB MLE	DET	54%	329	292	64	13	2	7	31	81	3	8	2	216	299	341	640	126	271	25	9	290	82	-7	+1	+2	+4	+7	0.7
2032	27	MLB MLE	DET	54%	362	321	70	14	2	8	34	90	4	8	2	216	299	342	641	126	272	25	9	290	82	-8	+1	+3	+4	+8	0.8
2033	28	MLB MLE	DET	54%	376	334	72	14	2	8	35	94	4	7	2	215	297	338	635	123	271	25	9	287	81	-9	+1	+2	+4	+8	0.6
2034	29	MLB MLE	DET	53%	377	335	72	14	2	8	35	95	4	6	2	212	294	332	626	120	270	25	9	284	78	-10	+0	+1	+4	+8	0.4
2028	23	MLB CTX	DET	34%	38	34	7	1	0	1	4	10	0	1	0	205	289	318	607	112	263	26	11	277	76	-1	+0	+0	+0	+1	0.1
2029	24	MLB CTX	DET	46%	88	79	16	3	0	2	8	22	1	2	1	208	292	325	618	117	265	25	9	281	79	-2	+0	+0	+1	+2	0.1
2030	25	MLB CTX	DET	52%	138	123	26	5	1	3	13	34	1	3	1	210	294	330	624	120	266	25	9	283	81	-3	+0	+1	+1	+3	0.3
2031	26	MLB CTX	DET	54%	178	157	34	7	1	4	17	44	2	4	1	212	295	333	628	122	267	25	10	285	82	-4	+0	+1	+2	+4	0.4
2032	27	MLB CTX	DET	54%	196	173	37	7	1	4	19	49	2	5	1	212	295	334	630	122	268	25	10	285	82	-4	+1	+1	+2	+4	0.4
2033	28	MLB CTX	DET	54%	204	181	39	8	1	4	19	51	2	4	1	211	293	330	623	119	267	25	9	283	81	-5	+0	+1	+2	+4	0.4
2034	29	MLB CTX	DET	53%	200	177	37	7	1	4	19	50	2	3	1	208	291	324	615	116	266	25	10	280	78	-5	+0	+1	+2	+4	0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1042	924	196	38	5	22	99	260	10	22	6	212	295	335	631	123	269	25	10	283	70	-24	+2	+6	+11	+23	1.8
/ 162G	—	A+C		—	650	576	123	24	3	14	62	162	6	14	4	214	296	339	635	125	270	25	10	283	70	-15	+1	+4	+7	+14	1.1
Career	—	MLE		—	3044	2692	541	111	15	56	296	822	35	125	39	201	288	316	604	115	265	27	10	272	70	-50	+4	+12	+23	+46	3.5
/ 162G	—	MLE		—	650	575	116	24	3	12	63	176	7	27	8	202	288	317	604	115	267	27	10	272	70	-15	+1	+4	+7	+14	1.1

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.

2025 ALakeland Flying Tigers · 299 PAwOBA .339 → .265 (−74)K% 24.7% → 33.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.75%	÷0.998	×1.360	—	—	33.71%
BB% (unintentional) /PA	12.71%	÷0.945	×0.690	—	×1.030	9.56%
HBP% /PA	0.67%	—	×0.780	—	×1.030	0.54%
Singles /BIP	26.09%	÷1.051	×0.920	×0.964	×1.030	22.67%
Doubles /BIP	8.70%	÷0.971	×0.830	×0.964	×1.030	7.38%
Triples /BIP	1.09%	÷1.150	×0.910	×0.964	×1.030	0.85%
Home runs /BIP	2.17%	÷0.864	×0.800	—	×1.030	2.07%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 73, 1B 110, 2B 94, 3B 130, K 100, BB 89 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.964.

Result: wOBA .339 → .265; ISO .124 → .100; BABIP .365 → .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).

2024 ROKFCL Tigers · 216 PAwOBA .378 → .273 (−105)K% 18.5% → 26.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.52%	÷0.991	×1.440	—	—	26.90%
BB% (unintentional) /PA	17.59%	÷1.040	×0.620	—	×1.008	10.57%
HBP% /PA	1.39%	—	×0.720	—	×1.008	1.01%
Singles /BIP	21.97%	÷0.993	×0.820	×0.957	×1.008	17.51%
Doubles /BIP	9.09%	÷0.981	×0.720	×0.957	×1.008	6.44%
Triples /BIP	0.00%	÷0.947	×0.720	×0.957	×1.008	0.00%
Home runs /BIP	4.55%	÷0.952	×0.780	—	×1.008	3.75%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 90, 1B 99, 2B 96, 3B 89, K 98, BB 108 — 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 ×0.957.

Result: wOBA .378 → .273; ISO .174 → .137; BABIP .320 → .245. 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 ALakeland Flying Tigers · 79 PAwOBA .217 → .159 (−59)K% 31.6% → 41.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	31.65%	÷1.028	×1.360	—	—	41.87%
BB% (unintentional) /PA	15.19%	÷1.061	×0.690	—	×1.045	10.32%
HBP% /PA	5.06%	—	×0.780	—	×1.045	4.13%
Singles /BIP	10.53%	÷0.980	×0.920	×0.993	×1.045	10.25%
Doubles /BIP	5.26%	÷1.351	×0.830	×0.993	×1.045	3.35%
Triples /BIP	0.00%	÷1.106	×0.910	×0.993	×1.045	0.00%
Home runs /BIP	0.00%	÷1.099	×0.800	—	×1.045	0.00%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 120, 1B 96, 2B 170, 3B 121, K 106, BB 112 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.993.

Result: wOBA .217 → .159; ISO .032 → .018; BABIP .158 → .136. 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 1 · 127 PAwOBA .367 → .235 (−131)K% 17.3% → 21.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.32%	÷0.995	×1.220	—	—	21.23%
BB% (unintentional) /PA	13.39%	÷1.009	×0.700	—	×1.008	9.35%
HBP% /PA	2.36%	—	×0.700	—	×1.008	1.67%
Singles /BIP	23.53%	÷1.058	×0.680	×0.950	×1.008	14.48%
Doubles /BIP	7.06%	÷0.901	×0.600	×0.950	×1.008	4.50%
Triples /BIP	1.18%	÷0.900	×0.600	×0.950	×1.008	0.75%
Home runs /BIP	3.53%	÷0.862	×0.470	—	×1.008	1.94%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 72, 1B 112, 2B 80, 3B 80, K 99, BB 102 — 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 .367 → .235; ISO .159 → .095; BABIP .329 → .201. 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 · 216 PAwOBA .319 → .202 (−117)K% 28.7% → 35.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.70%	÷0.992	×1.220	—	—	35.29%
BB% (unintentional) /PA	17.59%	÷1.028	×0.700	—	×1.022	12.25%
HBP% /PA	0.46%	—	×0.700	—	×1.022	0.33%
Singles /BIP	19.30%	÷1.033	×0.680	×0.985	×1.022	12.79%
Doubles /BIP	7.02%	÷1.019	×0.600	×0.985	×1.022	4.16%
Triples /BIP	3.51%	÷1.150	×0.600	×0.985	×1.022	1.84%
Home runs /BIP	2.63%	÷0.996	×0.470	—	×1.022	1.27%

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 ×0.985.

Result: wOBA .319 → .202; ISO .142 → .075; BABIP .304 → .189. 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
#3Adam Rosaleslast yr '17 career totals — 9 seasons, 1,756 PA	2.6	1,756	47	16	227	293	367	+6	+8	3.0	3.5
/162	664	18	6	+2.4	+3.0	1.1	pk7: 4
#4Tim Bogar'93-'01 * career totals — 8 seasons, 1,710 PA	2.6	1,710	24	13	217*	284*	324*	+11	+37	2.1	2.9
/162	664	9	5	+4.2	+14.4	0.8	pk7: 4
#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
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 4 projected seasons	1.7	1,138	23	25	214	294	337	+12	+13	1.9	1.9
/162	664	14	15	+7.1	+7.7	1.1	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
Franyerber Montilla (OGILVIE)	22	—	—	—	—	203/286/311	108	265	2	2	26%	9%	72	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕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
✕Wilmer Difo 2014 · A	22	43→53	38→45	53→55	49	207/273/289	82	261	5	18	22%	8%	61	-1.5	251/289/359	108	301	9	24	19%	4%	82	-0.0	258/296/362	104	307	8	28	18%	4%	82	+0.0
✕Brainer Bonaci 2023 · A	21	45→46	40→45	55→50	53	211/302/310	100	290	7	16	27%	11%	77	-0.3	227/287/348	121	312	12	11	29%	8%	80	-0.2	232/274/365	133	311	17	8	30%	5%	76	-0.3
✕Colin Walsh 2012 · A	22	43→52	41→45	50	53	207/286/311	104	254	8	9	21%	10%	71	-0.8	233/303/355	122	292	11	7	23%	9%	87	+0.4	214/321/331	117	302	10	7	29%	13%	87	+0.3
✕Allan Castro 2024 · A	21	42→45	42→45	52→50	47	205/277/316	111	276	7	12	27%	8%	69	-0.9	213/282/329	116	284	11	15	27%	8%	74	-0.6	212/279/324	113	274	12	17	26%	8%	69	-0.7
●Bryan Rincon 2024 · A	20	43→47	43→45	49→55	54	210/307/319	109	268	10	19	24%	11%	82	-0.0	196/286/316	120	277	12	25	31%	10%	73	-0.6	192/290/337	145	263	17	31	32%	11%	77	-0.2
✕Jared Serna 2023 · A	21	40→48	42→45	54→50	51	196/289/300	104	251	9	21	24%	9%	71	-0.8	219/276/335	116	269	11	15	22%	6%	72	-0.7	216/271/322	106	262	11	16	21%	6%	65	-1.1
✕Christian Cairo 2023 · A	22	40→49	39→40	53→60	50	187/295/270	83	292	6	16	34%	11%	67	-1.1	210/302/291	81	303	5	23	29%	10%	73	-0.6	219/314/286	67	298	3	31	25%	10%	75	-0.4
✕Harold Garcia 2009 · A	22	44→54	41→45	55	44	212/285/317	104	260	7	14	20%	6%	73	-0.6	247/297/349	102	331	7	22	26%	4%	83	+0.1	259/308/359	99	353	7	27	27%	4%	88	+0.3
✕Robert Moore 2024 · A	22	41→44	40→45	48→50	44	198/265/297	99	262	7	16	26%	7%	60	-1.6	204/268/313	109	256	10	14	23%	7%	65	-1.2	196/264/316	120	235	12	13	22%	7%	62	-0.9
✕Peyton Wilson 2022 · A	22	43→52	41→45	53→55	41	204/279/310	106	302	7	14	32%	7%	68	-1.0	222/288/343	121	297	11	18	27%	7%	79	-0.2	217/286/336	120	283	12	19	26%	7%	74	-0.4
✕Austin Elkins 2014 · A	23	43→41	40	49→50	53	207/294/304	97	258	7	13	22%	10%	73	-0.6	215/293/305	90	277	7	10	23%	9%	72	-0.7	208/294/273	65	268	4	6	22%	9%	62	-0.6
✕Jeferson Morales 2021 · A	22	42→47	40→45	47→50	52	201/291/303	102	246	6	8	20%	9%	72	-0.7	201/282/330	129	264	13	9	28%	8%	75	-0.5	222/297/349	127	274	11	8	22%	7%	81	-0.0
✕Geraldo Quintero 2023 · A	21	45→47	41→40	56→60	47	216/284/325	109	278	7	20	24%	8%	73	-0.6	213/279/301	88	280	6	26	25%	7%	66	-1.1	202/273/285	83	265	7	32	25%	7%	57	-1.2
✕Victor Scott II 2023 · A	22	44→54	43→40	58→65	50	212/292/336	124	282	9	19	27%	10%	79	-0.2	228/288/323	95	287	7	44	22%	6%	74	-0.5	222/287/310	87	280	7	49	22%	7%	70	-0.8
●Jakob Marsee 2023 · A	22	44→49	42→45	58→60	54	211/313/323	113	290	8	21	28%	12%	85	+0.2	220/320/345	125	277	13	33	24%	11%	93	+0.8	217/321/350	133	273	12	37	23%	11%	92	+0.8
✕Hoy Park 2018 · A	22	44→52	39→45	58→55	46	208/280/301	93	279	6	17	26%	8%	66	-1.1	228/306/313	85	303	5	16	24%	9%	78	-0.3	234/324/332	98	306	8	17	24%	11%	88	+0.3
✕Patrick Bailey 2022 · A	23	43→49	44→45	50→45	43	211/277/328	117	305	11	8	33%	8%	72	-0.7	217/286/343	126	292	13	5	28%	8%	78	-0.3	221/291/343	122	286	14	4	26%	8%	80	-0.1
✕Spencer Nivens 2024 · A	22	41→49	41→45	48→50	52	199/280/294	96	255	8	14	24%	10%	65	-1.2	208/277/334	126	276	13	11	28%	9%	73	-0.6	211/281/333	122	272	12	12	26%	9%	73	-0.5
✕Oliver Dominguez 2011 · A	22	42	41→40	51→45	49	204/274/300	96	258	9	16	24%	8%	64	-1.3	195/265/289	94	278	7	10	30%	8%	58	-1.7	180/250/270	90	260	6	8	31%	8%	46	-1.2

Franyerber Montilla

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps