Jonathan Mejía

SS Palm Beach Cardinals

Age 22 S/R 6'0" / 185 lbs A HR -14%BB -5% Svc 0.0 · Ctrl thru 2037

Overview

APROSPECTMiLBFA 2038

OGV OFP35OGV rank#2419ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	19	ROKSTL	205	.299/.399/.425	3	18	59	—	.207/.281/.283
2025	20	ASTL	324	.183/.305/.308	6	18	36	—	.146/.237/.240
2026	21	ASTL	321	.220/.372/.424	12	9	70	—	.172/.287/.322
2027PROJMLE	22	MLBSTL	431	.165/.265/.283	9	10	57	-0.2
2028PROJ34% MLB	23	MLBSTL	84	.171/.269/.291	2	2	62	-0.1
2029PROJ46% MLB	24	MLBSTL	150	.176/.274/.301	3	3	66	-0.1

Next 3 projected WAR -0.4Projected 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

BB%82

Speed68

Chase%66

Max EV59

Whiff%45

K%37

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 96%

CompsHayden Cantrelle (age 23) · Nerwilian Cedeño (age 22) · Yasel Antuna (age 23)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 208 proj PA

wRC+†57

AVG/OBP/SLG.164 / .262 / .280

PA208

HR4

SB5

K%35

BB%11

ISO118

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$3M ctrl surplus

Tools · ContractCON 20 / POW 35

Toolsscout grade

CONTACT20

scouting grade only

POWER35

scouting grade only

EYE55

scouting grade only

SPEED55

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	—	—	—
2033	Pre-Arb	$0.9M	—	—	—
2034	Pre-Arb	$1.0M	—	—	—
2035	Ext	beyond projection horizon · no WAR estimate
2036	Ext	beyond projection horizon · no WAR estimate
2037	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$-0.7M	+$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)
2022	17	ROK	DSL Cardinals	—	208	165	44	14	3	5	33	48	10	3	2	267	418	479	897	212	348	23	16	401	59	—	—	—	—	—	—
2023	18	A	Palm Beach Cardinals	—	33	28	3	1	0	0	4	10	1	1	0	107	242	143	385	36	167	30	12	201	-13	—	—	—	—	—	—
2023	18	ROK	FCL Cardinals	—	131	104	18	0	3	2	24	37	1	7	1	173	331	288	619	115	242	28	18	292	18	—	—	—	—	—	—
2024	19	ROK	FCL Cardinals	—	205	174	52	9	2	3	25	52	4	18	4	299	399	425	824	126	405	25	12	370	59	—	—	—	—	—	—
2025	20	A	Palm Beach Cardinals	—	324	273	50	4	6	6	46	106	2	18	4	183	305	308	613	125	270	33	14	283	36	—	—	—	—	—	—
2026	21	A	Palm Beach Cardinals	—	321	255	56	10	3	12	59	88	3	9	6	220	372	424	796	204	277	27	18	355	70	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2022	17	ROK MLE	DSL Cardinals	—	208	174	28	9	2	2	24	59	10	3	2	161	298	270	568	109	219	28	12	255	59	—	—	—	—	—	—
2023	18	A MLE	Palm Beach Cardinals	—	33	29	3	1	0	0	3	14	1	1	0	103	212	138	350	34	156	42	9	149	-13	—	—	—	—	—	—
2023	18	ROK MLE	FCL Cardinals	—	131	114	13	0	2	1	15	53	1	7	1	114	223	175	399	61	187	40	11	195	18	—	—	—	—	—	—
2024	19	ROK MLE	FCL Cardinals	—	205	184	38	6	1	2	15	74	4	18	4	207	281	283	563	76	319	36	7	255	59	—	—	—	—	—	—
2025	20	A MLE	Palm Beach Cardinals	—	324	287	42	3	6	4	32	144	2	18	4	146	237	240	477	94	268	44	10	222	36	—	—	—	—	—	—
2026	21	A MLE	Palm Beach Cardinals	—	321	273	47	8	3	9	41	120	3	9	6	172	287	322	609	150	243	37	13	271	70	—	—	—	—	—	—
2022	17	ROK MLE	DSL Cardinals	—	208	174	28	9	2	2	24	59	10	3	2	161	298	270	568	109	230	28	12	255	59	—	—	—	—	—	—
2022	17	ROK RAW	DSL Cardinals	—	208	165	44	14	3	5	33	48	10	3	2	267	418	479	897	212	348	23	16	401	59	—	—	—	—	—	—
2023	18	ROK MLE	2 teams	—	164	143	15	1	2	1	18	68	2	8	1	105	215	161	376	56	187	41	11	186	12	—	—	—	—	—	—
2023	18	ROK RAW	2 teams	—	164	132	21	1	3	2	28	47	2	8	1	159	313	258	570	98	226	29	17	274	12	—	—	—	—	—	—
2024	19	ROK MLE	FCL Cardinals	—	205	184	38	6	1	2	15	74	4	18	4	207	281	283	563	76	327	36	7	255	59	—	—	—	—	—	—
2024	19	ROK RAW	FCL Cardinals	—	205	174	52	9	2	3	25	52	4	18	4	299	399	425	824	126	405	25	12	370	59	—	—	—	—	—	—
2025	20	A MLE	Palm Beach Cardinals	—	324	287	42	3	6	4	32	144	2	18	4	146	237	240	477	94	270	44	10	222	36	—	—	—	—	—	—
2025	20	A RAW	Palm Beach Cardinals	—	324	273	50	4	6	6	46	106	2	18	4	183	305	308	613	125	270	33	14	283	36	—	—	—	—	—	—
2026	21	A MLE	Palm Beach Cardinals	—	321	273	47	8	3	9	41	120	3	9	6	172	287	322	609	150	257	37	13	271	70	—	—	—	—	—	—
2026	21	A RAW	Palm Beach Cardinals	—	321	255	56	10	3	12	59	88	3	9	6	220	372	424	796	204	277	27	18	355	70	—	—	—	—	—	—
2022	17	ROK MLE	DSL Cardinals	—	208	172	28	9	2	2	24	59	10	3	2	163	298	273	571	110	219	28	12	255	59	—	—	—	—	—	—
2023	18	ROK MLE	2 teams	—	164	143	15	1	2	1	18	68	2	8	1	105	215	161	376	56	181	41	11	186	12	—	—	—	—	—	—
2024	19	ROK MLE	FCL Cardinals	—	205	184	38	6	1	2	15	74	4	18	4	207	281	283	563	76	319	36	7	255	59	—	—	—	—	—	—
2025	20	A MLE	Palm Beach Cardinals	—	324	287	42	3	6	4	32	144	2	18	4	146	237	240	477	94	268	44	10	222	36	—	—	—	—	—	—
2026	21	A MLE	Palm Beach Cardinals	—	321	274	47	8	3	9	41	120	3	9	6	172	287	321	608	150	243	37	13	271	70	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	19	ROK MLE	FCL Cardinals	—	205	184	38	6	1	2	15	74	4	18	4	207	281	283	563	76	319	36	7	255	59	—	—	—	—	—	—
2025	20	A MLE	Palm Beach Cardinals	—	324	287	42	3	6	4	32	144	2	18	4	146	237	240	477	94	268	44	10	222	36	—	—	—	—	—	—
2026	21	A MLE	Palm Beach Cardinals	—	321	274	47	8	3	9	41	120	3	9	6	172	287	321	608	150	243	37	13	271	70	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	STL	0%	431	377	63	10	4	9	48	151	3	10	3	165	265	283	547	118	241	35	11	253	57	-22	+1	+0	+5	+9	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	STL	34%	244	213	37	6	2	6	27	83	2	6	2	171	270	296	566	124	245	34	11	260	62	-11	+0	+0	+3	+5	-0.3
2029	24	MLB MLE	STL	46%	326	284	51	8	3	8	36	109	3	7	3	177	274	306	580	129	249	33	11	266	66	-13	+0	+0	+3	+7	-0.3
2030	25	MLB MLE	STL	52%	372	325	59	10	3	9	41	122	3	8	3	181	278	313	590	132	252	33	11	270	69	-14	+0	+0	+4	+8	-0.2
2031	26	MLB MLE	STL	54%	399	350	65	11	3	10	43	128	3	9	3	184	280	317	597	133	254	32	11	272	70	-14	+1	+0	+4	+9	-0.1
2032	27	MLB MLE	STL	54%	411	361	67	11	3	10	44	131	3	9	3	186	281	320	600	133	255	32	11	273	71	-14	+1	+0	+4	+9	-0.0
2033	28	MLB MLE	STL	54%	411	361	66	11	3	10	44	132	3	7	3	184	279	315	594	131	255	32	11	271	70	-15	+0	-1	+4	+9	-0.2
2034	29	MLB MLE	STL	58%	403	354	64	11	3	9	43	130	3	6	3	182	276	309	586	127	253	32	11	267	67	-16	+0	-1	+4	+9	-0.4
2028	23	MLB CTX	STL	34%	84	74	13	2	1	2	9	29	1	2	1	171	269	291	560	120	246	35	11	258	62	-4	+0	+0	+1	+2	-0.1
2029	24	MLB CTX	STL	46%	150	132	23	4	1	3	16	50	1	3	1	176	274	301	574	124	250	33	11	263	66	-6	+0	+0	+2	+3	-0.1
2030	25	MLB CTX	STL	52%	192	167	30	5	2	4	21	63	2	4	2	180	277	307	584	127	253	33	11	267	69	-7	+0	+0	+2	+4	-0.1
2031	26	MLB CTX	STL	54%	216	189	35	6	2	5	23	70	2	5	2	183	279	312	591	129	255	32	11	270	70	-8	+0	+0	+2	+5	-0.0
2032	27	MLB CTX	STL	54%	223	195	36	6	2	5	24	71	2	5	2	186	280	314	595	129	257	32	11	271	71	-8	+0	+0	+2	+5	-0.0
2033	28	MLB CTX	STL	54%	223	195	36	6	2	5	24	71	2	4	2	184	278	310	589	126	256	32	11	269	70	-8	+0	-0	+2	+5	-0.1
2034	29	MLB CTX	STL	58%	232	203	37	6	2	5	25	75	2	3	1	182	276	304	580	123	255	32	11	266	67	-9	+0	-1	+2	+5	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1320	1155	210	35	12	29	142	429	12	26	11	182	278	308	586	126	257	32	11	267	62	-49	+1	-1	+14	+29	-0.7
/ 162G	—	A+C		—	650	569	103	17	6	14	70	211	6	13	5	181	278	306	583	125	256	32	11	267	62	-24	+0	-1	+7	+14	-0.4
Career	—	MLE		—	3996	3490	609	100	36	84	431	1373	43	113	39	174	273	296	569	121	255	34	11	260	62	-108	+3	-2	+30	+60	-1.8
/ 162G	—	MLE		—	650	568	99	16	6	14	70	223	7	18	6	174	273	298	570	123	254	34	11	260	62	-25	+1	-0	+7	+14	-0.4

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 APalm Beach Cardinals · 321 PAwOBA .351 → .271 (−80)K% 27.4% → 37.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.41%	÷1.000	×1.360	—	—	37.28%
BB% (unintentional) /PA	18.38%	÷1.000	×0.690	—	×1.015	12.87%
HBP% /PA	0.93%	—	×0.780	—	×1.015	0.74%
Singles /BIP	18.56%	÷1.000	×0.920	×0.979	×1.015	16.97%
Doubles /BIP	5.99%	÷1.000	×0.830	×0.979	×1.015	4.94%
Triples /BIP	1.80%	÷1.000	×0.910	×0.979	×1.015	1.62%
Home runs /BIP	7.19%	÷1.000	×0.800	—	×1.015	5.83%

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 ×0.979.

Result: wOBA .351 → .271; ISO .204 → .159; BABIP .277 → .243. 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 APalm Beach Cardinals · 324 PAwOBA .277 → .222 (−54)K% 32.7% → 44.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	32.72%	÷1.000	×1.360	—	—	44.52%
BB% (unintentional) /PA	13.89%	÷0.988	×0.690	—	×1.030	9.99%
HBP% /PA	0.62%	—	×0.780	—	×1.030	0.50%
Singles /BIP	20.36%	÷0.995	×0.920	×1.037	×1.030	20.11%
Doubles /BIP	2.40%	÷0.896	×0.830	×1.037	×1.030	2.37%
Triples /BIP	3.59%	÷0.900	×0.910	×1.037	×1.030	3.88%
Home runs /BIP	3.59%	÷0.973	×0.800	—	×1.030	3.04%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 95, 1B 99, 2B 79, 3B 80, K 100, BB 98 — 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 ×1.037.

Result: wOBA .277 → .222; ISO .125 → .103; BABIP .270 → .268. 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 Cardinals · 205 PAwOBA .364 → .255 (−109)K% 25.4% → 35.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.37%	÷1.018	×1.440	—	—	35.89%
BB% (unintentional) /PA	12.20%	÷1.043	×0.620	—	×1.008	7.31%
HBP% /PA	1.95%	—	×0.720	—	×1.008	1.42%
Singles /BIP	31.15%	÷0.998	×0.820	×0.984	×1.008	25.37%
Doubles /BIP	7.38%	÷1.016	×0.720	×0.984	×1.008	5.19%
Triples /BIP	1.64%	÷0.935	×0.720	×0.984	×1.008	1.25%
Home runs /BIP	2.46%	÷0.975	×0.780	—	×1.008	1.98%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 95, 1B 100, 2B 103, 3B 87, K 104, BB 109 — 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 ×0.984.

Result: wOBA .364 → .255; ISO .126 → .089; BABIP .405 → .319. 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 ROKFCL Cardinals · 131 PAwOBA .288 → .195 (−92)K% 28.2% → 40.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.24%	÷1.000	×1.440	—	—	40.67%
BB% (unintentional) /PA	18.32%	÷1.000	×0.620	—	×1.022	11.61%
HBP% /PA	0.76%	—	×0.720	—	×1.022	0.56%
Singles /BIP	19.40%	÷1.000	×0.820	×0.950	×1.022	15.46%
Doubles /BIP	0.00%	÷1.000	×0.720	×0.950	×1.022	0.00%
Triples /BIP	4.48%	÷1.000	×0.720	×0.950	×1.022	3.13%
Home runs /BIP	2.99%	÷1.000	×0.780	—	×1.022	2.38%

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 18 vs a level average of 19.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .288 → .195; ISO .115 → .080; BABIP .242 → .187. 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 APalm Beach Cardinals · 33 PAwOBA .197 → .149 (−48)K% 30.3% → 43.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.30%	÷0.950	×1.360	—	—	43.38%
BB% (unintentional) /PA	12.12%	÷1.000	×0.690	—	×1.050	8.78%
HBP% /PA	3.03%	—	×0.780	—	×1.050	2.48%
Singles /BIP	11.11%	÷0.998	×0.920	—	×1.050	10.75%
Doubles /BIP	5.56%	÷1.007	×0.830	—	×1.050	4.81%
Triples /BIP	0.00%	÷1.023	×0.910	—	×1.050	0.00%
Home runs /BIP	0.00%	÷1.010	×0.800	—	×1.050	0.00%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 102, 1B 100, 2B 101, 3B 105, K 90, BB 100 — applied at half strength. Age: age 18 vs a level average of 22.0 → +5.0% on BB/HBP/hit rates (4.0 yr younger than average).

Result: wOBA .197 → .149; ISO .036 → .026; BABIP .167 → .156. 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 Cardinals · 208 PAwOBA .392 → .255 (−137)K% 23.1% → 28.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.08%	÷0.988	×1.220	—	—	28.50%
BB% (unintentional) /PA	15.87%	÷0.972	×0.700	—	×1.022	11.69%
HBP% /PA	4.81%	—	×0.700	—	×1.022	3.44%
Singles /BIP	18.80%	÷1.003	×0.680	×0.951	×1.022	12.39%
Doubles /BIP	11.97%	÷0.910	×0.600	×0.951	×1.022	7.67%
Triples /BIP	2.56%	÷1.093	×0.600	×0.951	×1.022	1.37%
Home runs /BIP	4.27%	÷1.039	×0.470	—	×1.022	1.98%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 108, 1B 101, 2B 82, 3B 119, K 98, BB 94 — 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 ×0.951.

Result: wOBA .392 → .255; ISO .212 → .116; BABIP .348 → .219. 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
#1Tim 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
#2Ryan 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 5 projected seasons	2.3	1,529	36	31	181	274	310	+16	+15	0.0	0.2
/162	664	16	13	+7.1	+6.5	0.0	pk7: 0
#3Abraham Torolast yr '25 career totals — 6 seasons, 1,561 PA	2.4	1,561	39	16	220	282	351	-1	-8	-0.5	-0.5
/162	664	17	7	-0.2	-3.2	-0.2	pk7: -0
#4David Howard'91-'99 * career totals — 8 seasons, 1,795 PA	2.7	1,795	11	23	220*	280*	301*	+10	+23	-1.6	-0.8
/162	664	4	9	+3.7	+8.5	-0.6	pk7: -0
#5Hector Torres'68-'77 * career totals — 9 seasons, 1,889 PA	2.8	1,889	18	7	215*	262*	312*	+16	+3	-2.1	-0.9
/162	664	6	2	+5.7	+1.2	-0.7	pk7: 0
#6Alexi Amaristalast yr '17 career totals — 7 seasons, 1,901 PA	2.9	1,901	21	39	231	275	323	+14	-6	-1.1	-1.1
/162	664	7	14	+4.9	-2.1	-0.4	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
Jonathan Mejía (OGILVIE)	22	20	35	55	55	164/262/280	116	241	4	5	35%	11%	57	-0.6	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Hayden Cantrelle 2022 · AA	23	34	41→40	54→60	55	164/295/261	97	258	8	24	35%	14%	66	-1.1	191/307/295	104	295	8	20	33%	12%	77	-0.3	192/310/298	105	297	8	21	33%	12%	77	-0.2
✕Nerwilian Cedeño 2024 · A	22	40→34	44→45	48→50	42	197/268/314	117	296	11	13	35%	8%	65	-1.2	196/253/295	99	282	9	11	32%	6%	55	-2.0	185/239/274	90	262	7	11	31%	6%	42	-1.6
✕Yasel Antuna 2023 · AA	23	37→35	43→45	48→50	48	187/265/295	108	254	11	14	30%	9%	60	-1.6	188/267/285	97	271	9	13	31%	9%	59	-1.7	142/231/221	79	208	7	12	33%	9%	30	-1.5
✕Kaden Polcovich 2022 · AA	23	39→41	46→45	54→55	46	195/283/323	128	276	13	17	32%	9%	74	-0.6	200/283/317	117	274	11	17	29%	9%	72	-0.7	190/277/301	111	259	10	19	29%	9%	64	-0.7
✕Loidel Chapelli 2024 · A	22	39→36	43→45	56→55	46	196/271/312	116	271	10	18	30%	8%	65	-1.2	196/259/284	88	300	7	17	34%	7%	54	-2.0	176/233/238	63	279	4	20	36%	6%	31	-2.0
✕Jose Acosta 2023 · A	23	39	45	49→55	37	194/253/316	122	299	13	16	38%	6%	60	-1.6	193/246/301	108	278	10	17	33%	6%	53	-2.1	169/217/263	95	233	9	22	31%	5%	31	-1.0
✕Iverson Leonardo 2023 · A	21	37	44→45	49→50	40	186/254/299	114	273	12	9	35%	7%	57	-1.8	197/278/292	95	346	7	8	41%	8%	64	-1.3	149/272/225	76	351	3	4	50%	12%	46	-0.6
✕Luis García 2023 · AA	22	36→38	43→40	46→45	46	182/267/289	108	262	11	10	33%	10%	60	-1.6	190/281/284	94	303	9	10	36%	10%	64	-1.3	134/262/190	56	240	7	10	41%	13%	36	-0.9
✕C.J. Beatty 2010 · A	21	40	41→45	52→40	41	198/252/295	98	278	9	9	31%	6%	54	-2.0	210/271/325	115	299	9	5	31%	7%	68	-1.0	202/267/333	131	282	11	2	30%	8%	65	-0.7
✕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
✕Jacob Wetzel 2023 · A	23	39→34	43→45	50	47	194/280/301	107	268	12	10	30%	9%	68	-1.0	192/268/302	110	281	9	13	32%	9%	63	-1.4	180/256/297	117	269	7	16	33%	9%	55	-1.0
✕Chris Roller 2019 · A	22	39	41→45	51→55	42	190/265/292	102	283	8	14	34%	8%	59	-1.6	204/267/311	107	290	7	12	30%	6%	63	-1.3	179/266/281	102	259	10	19	32%	8%	57	-1.0
✕Eduardo Lopez 2024 · A	22	41	40	50	42	196/263/286	90	295	8	12	34%	8%	57	-1.8	189/252/307	118	273	12	10	33%	7%	57	-1.8	151/219/283	132	204	15	8	33%	8%	37	-1.0
✕Marcus Littlewood 2014 · A	22	41	40→45	48→45	47	197/272/295	98	284	7	4	31%	9%	62	-1.4	207/273/319	112	272	10	5	26%	8%	68	-1.0	207/274/317	110	265	10	4	25%	8%	65	-0.6
✕Kay-Lan Nicasia 2024 · A	22	37	41→40	53→55	41	178/255/278	100	300	8	17	40%	9%	52	-2.2	166/251/267	101	307	9	19	44%	9%	49	-2.4	117/220/216	99	221	9	21	47%	10%	25	-1.3
✕Michael Papierski 2019 · A	23	37→45	39→40	47→40	54	180/284/263	83	241	7	6	26%	11%	61	-1.5	193/282/279	86	272	8	4	29%	10%	63	-1.3	203/293/298	95	263	9	0	25%	10%	70	-0.5
✕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
✕Frank Rodriguez 2024 · A	22	35	42→45	47→30	38	180/236/279	99	250	10	4	32%	5%	45	-2.7	188/246/274	86	257	8	4	29%	6%	47	-2.5	183/244/267	84	241	9	1	27%	6%	43	-0.9
✕Max George 2018 · A	22	39	42→45	50→55	45	195/270/303	109	255	9	15	27%	7%	64	-1.3	188/271/296	108	261	10	20	30%	7%	63	-1.4	145/250/272	127	214	15	25	38%	9%	49	-1.2
✕Cole Roederer 2021 · A	21	39→33	43→45	51→50	42	193/261/303	109	286	10	12	34%	8%	60	-1.6	207/272/319	112	304	11	12	33%	7%	68	-1.0	183/257/295	112	268	12	11	34%	8%	56	-1.1

Jonathan Mejía

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps