Kevin Cron

Pos1B

B/TR/R

Born1993-02-17

Age (2027)34

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2023

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2019	26	AAAARI	377	.331/.448/.777	38	1	142	—	.241/.336/.549
2019	26	MLBARI	78	.211/.273/.521	6	0	116	-0.6
2020	27	MLBARI	20	.000/.150/.000	0	0	-40	-0.3
2023	30	AAAOAK	46	.133/.152/.156	0	0	-43	—	.111/.130/.133
2024	31	No MLB games played
2025	32	No MLB games played
2026	33	No MLB games played

Last 3 seasons WAR -1.0

Contract

No contract data on file.

Skills · percentileMiLB Statcast 2023 AAA

Max EV90

Whiff%16

BB%7

K%5

Chase%5

wOBA1

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)
2014	21	ROK	Missoula Osprey	—	150	132	39	10	0	6	10	16	7	0	0	295	376	508	883	212	297	11	7	388	74	—	—	—	—	—	—
2015	22	A+	Visalia Rawhide	—	559	518	141	34	0	27	28	131	6	0	0	272	316	494	811	222	311	23	5	351	72	—	—	—	—	—	—
2016	23	AA	Mobile BayBears	—	510	465	103	20	1	26	33	134	6	3	1	222	282	437	718	215	248	26	6	313	39	—	—	—	—	—	—
2016	23	INTL	Salt River Rafters	—	86	80	15	3	0	3	4	19	1	2	0	188	235	338	573	150	203	22	5	253	57	—	—	—	—	—	—
2017	24	AA	Jackson Generals	—	588	515	146	35	0	25	56	134	8	1	0	283	363	497	860	214	332	23	10	374	94	—	—	—	—	—	—
2018	25	AAA	Reno Aces	—	438	392	121	28	1	22	36	100	4	1	0	309	373	554	926	245	359	23	8	399	86	—	—	—	—	—	—
2019	26	MLB	Arizona Diamondbacks	—	78	71	15	4	0	6	4	28	2	0	1	211	273	521	794	310	237	36	5	339	116	+2	-0	-1	-8	+2	-0.6
2019	26	AAA	Reno Aces	—	377	305	101	20	1	38	61	77	6	1	2	331	448	777	1.225	446	328	20	16	508	142	—	—	—	—	—	—
2020	27	MLB	Arizona Diamondbacks	—	20	17	0	0	0	0	1	7	2	0	0		150		150			35	5	108	-40	-3	+0	-0	-0	+0	-0.3
2023	30	AAA	Las Vegas Aviators	—	46	45	6	1	0	0	1	18	0	0	0	133	152	156	308	22	222	39	2	141	-43	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	98	88	15	4	0	6	5	35	4	0	1	170	247	420	668	250	188	36	5	292	83	-2	-0	-1	-8	+2	-1.0
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2014	21	ROK MLE	Missoula Osprey	—	150	136	29	7	0	4	6	23	7	0	0	213	282	353	635	140	225	15	4	278	74	—	—	—	—	—	—
2015	22	A+ MLE	Visalia Rawhide	—	559	529	112	25	0	24	18	175	6	0	0	212	246	395	641	183	258	31	3	274	72	—	—	—	—	—	—
2016	23	AA MLE	Mobile BayBears	—	510	476	79	15	1	18	22	167	6	3	1	166	212	315	527	149	200	33	4	226	39	—	—	—	—	—	—
2017	24	AA MLE	Jackson Generals	—	588	535	127	30	0	20	36	166	8	1	0	237	295	406	701	168	293	28	6	307	94	—	—	—	—	—	—
2018	25	AAA MLE	Reno Aces	—	438	403	94	19	1	16	25	130	4	1	0	233	285	404	689	171	288	30	6	296	86	—	—	—	—	—	—
2019	26	MLB MLE	Arizona Diamondbacks	—	78	71	15	4	0	6	4	28	2	0	1	211	273	521	794	310	237	36	5	340	116	+2	-0	-1	-8	+2	-0.6
2019	26	AAA MLE	Reno Aces	—	377	328	79	15	1	28	41	103	6	1	2	241	336	549	885	308	254	27	11	378	142	—	—	—	—	—	—
2020	27	MLB MLE	Arizona Diamondbacks	—	20	17	0	0	0	0	1	7	2	0	0		150		150			35	5	108	-40	-3	+0	-0	-0	+0	-0.3
2023	30	AAA MLE	Las Vegas Aviators	—	46	45	5	1	0	0	1	21	0	0	0	111	130	133	264	22	195	46	2	105	-43	—	—	—	—	—	—
2014	21	ROK MLE	Missoula Osprey	—	150	136	29	7	0	4	6	23	7	0	0	213	282	353	635	140	227	15	4	278	74	—	—	—	—	—	—
2014	21	ROK RAW	Missoula Osprey	—	150	132	39	10	0	6	10	16	7	0	0	295	376	508	883	212	297	11	7	388	74	—	—	—	—	—	—
2015	22	A+ MLE	Visalia Rawhide	—	559	529	112	25	0	24	18	175	6	0	0	212	246	395	641	183	262	31	3	274	72	—	—	—	—	—	—
2015	22	A+ RAW	Visalia Rawhide	—	559	518	141	34	0	27	28	131	6	0	0	272	316	494	811	222	311	23	5	351	72	—	—	—	—	—	—
2016	23	AA MLE	2 teams	—	596	556	92	17	1	21	26	195	7	5	1	165	212	313	525	147	205	33	4	226	39	—	—	—	—	—	—
2016	23	AA RAW	2 teams	—	596	545	118	23	1	29	37	153	7	5	1	217	275	422	697	206	241	26	6	304	39	—	—	—	—	—	—
2017	24	AA MLE	Jackson Generals	—	588	535	127	30	0	20	36	166	8	1	0	237	295	406	701	168	299	28	6	307	94	—	—	—	—	—	—
2017	24	AA RAW	Jackson Generals	—	588	515	146	35	0	25	56	134	8	1	0	283	363	497	860	214	332	23	10	374	94	—	—	—	—	—	—
2018	25	AAA MLE	Reno Aces	—	438	403	94	19	1	16	25	130	4	1	0	233	285	404	689	171	297	30	6	296	86	—	—	—	—	—	—
2018	25	AAA RAW	Reno Aces	—	438	392	121	28	1	22	36	100	4	1	0	309	373	554	926	245	359	23	8	399	86	—	—	—	—	—	—
2019	26	AAA MLE	2 teams	—	455	399	94	19	1	34	45	131	8	1	3	236	325	544	869	308	253	29	10	372	138	—	—	—	—	—	—
2019	26	AAA RAW	2 teams	—	455	376	116	24	1	44	65	105	8	1	3	309	418	729	1.147	420	313	23	14	479	138	—	—	—	—	—	—
2020	27	MLB MLE	Arizona Diamondbacks	—	20	17	0	0	0	0	1	7	2	0	0		150		150			35	5	108	-40	-3	+0	-0	-0	+0	-0.3
2020	27	MLB RAW	Arizona Diamondbacks	—	20	17	0	0	0	0	1	7	2	0	0		150		150			35	5	108	-40	-3	+0	-0	-0	+0	-0.3
2023	30	AAA MLE	Las Vegas Aviators	—	46	45	5	1	0	0	1	21	0	0	0	111	130	133	264	22	208	46	2	105	-43	—	—	—	—	—	—
2023	30	AAA RAW	Las Vegas Aviators	—	46	45	6	1	0	0	1	18	0	0	0	133	152	156	308	22	222	39	2	141	-43	—	—	—	—	—	—
2014	21	ROK MLE	Missoula Osprey	—	150	136	29	7	0	4	6	23	7	0	0	213	282	353	635	140	225	15	4	278	74	—	—	—	—	—	—
2015	22	A+ MLE	Visalia Rawhide	—	559	530	112	25	0	24	18	175	6	0	0	211	246	394	640	183	258	31	3	274	72	—	—	—	—	—	—
2016	23	AA MLE	2 teams	—	596	558	92	17	1	21	26	195	7	5	1	165	212	312	524	147	200	33	4	226	39	—	—	—	—	—	—
2017	24	AA MLE	Jackson Generals	—	588	539	127	30	0	20	36	166	8	1	0	236	295	403	698	167	293	28	6	307	94	—	—	—	—	—	—
2018	25	AAA MLE	Reno Aces	—	438	406	94	19	1	16	25	130	4	1	0	232	285	401	686	170	288	30	6	296	86	—	—	—	—	—	—
2019	26	AAA MLE	2 teams	—	455	399	94	19	1	34	45	131	8	1	3	236	325	544	869	308	251	29	10	372	138	—	—	—	—	—	—
2020	27	MLB MLE	Arizona Diamondbacks	—	20	17	0	0	0	0	1	7	2	0	0		150		150			35	5	108	-40	—	—	—	—	—	—
2023	30	AAA MLE	Las Vegas Aviators	—	46	45	5	1	0	0	1	21	0	0	0	111	130	133	264	22	195	46	2	105	-43	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	98	88	15	4	0	6	5	35	4	0	1	170	247	420	668	250	188	36	5	292	80	-2	-0	-1	-8	+2	-1.0
/ 162G	—	A+C		—	650	584	100	27	0	40	33	232	27	0	7	171	249	423	672	252	188	36	5	292	80	-13	-3	-7	-56	+14	-6.6
Career	—	MLE		—	2852	2620	553	118	3	119	158	848	42	8	4	211	267	395	662	184	258	30	6	286	80	-2	-0	-1	-8	+2	-1.0
/ 162G	—	MLE		—	650	597	126	27	1	27	36	193	10	2	1	211	267	395	663	184	258	30	6	286	80	-13	-3	-7	-56	+14	-6.6

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.

2023 AAALas Vegas Aviators · 46 PAwOBA .138 → .105 (−33)K% 39.1% → 46.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	39.13%	÷1.017	×1.200	—	—	46.15%
BB% (unintentional) /PA	2.17%	÷1.055	×0.690	—	×0.972	1.38%
HBP% /PA	0.00%	—	×0.940	—	×0.972	0.00%
Singles /BIP	18.52%	÷0.993	×0.930	—	×0.972	16.86%
Doubles /BIP	3.70%	÷1.124	×0.830	—	×0.972	2.66%
Triples /BIP	0.00%	÷1.133	×0.970	—	×0.972	0.00%
Home runs /BIP	0.00%	÷0.996	×0.700	—	×0.972	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 99, 1B 99, 2B 125, 3B 127, K 103, BB 111 — applied at half strength. Age: age 30 vs a level average of 27.2 → −2.8% on BB/HBP/hit rates (2.8 yr older than average).

Result: wOBA .138 → .105; ISO .022 → .014; BABIP .222 → .195. 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).

2019 AAAReno Aces · 377 PAwOBA .493 → .378 (−116)K% 20.4% → 27.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.42%	÷0.970	×1.290	—	—	27.17%
BB% (unintentional) /PA	14.85%	÷0.986	×0.710	—	×1.018	10.89%
HBP% /PA	1.59%	—	×0.980	—	×1.018	1.59%
Singles /BIP	18.42%	÷1.035	×0.900	×0.950	×1.018	15.49%
Doubles /BIP	8.77%	÷1.025	×0.810	×0.950	×1.018	6.70%
Triples /BIP	0.44%	÷1.150	×0.810	×0.950	×1.018	0.30%
Home runs /BIP	16.67%	÷1.077	×0.780	—	×1.018	12.28%

Factors used: league row PCL. Park (home-season share, regressed): HR 115, 1B 107, 2B 105, 3B 130, K 94, BB 97 — applied at half strength. Age: age 26 vs a level average of 27.2 → +1.8% on BB/HBP/hit rates (1.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .493 → .378; ISO .446 → .329; BABIP .328 → .254. 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).

2018 AAAReno Aces · 438 PAwOBA .393 → .296 (−97)K% 22.8% → 29.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.83%	÷0.991	×1.290	—	—	29.73%
BB% (unintentional) /PA	8.22%	÷1.069	×0.710	—	×1.033	5.64%
HBP% /PA	0.91%	—	×0.980	—	×1.033	0.92%
Singles /BIP	23.97%	÷1.024	×0.900	×0.950	×1.033	20.68%
Doubles /BIP	9.59%	÷1.117	×0.810	×0.950	×1.033	6.82%
Triples /BIP	0.34%	÷1.150	×0.810	×0.950	×1.033	0.24%
Home runs /BIP	7.53%	÷1.044	×0.780	—	×1.033	5.82%

Factors used: league row PCL. Park (home-season share, regressed): HR 109, 1B 105, 2B 123, 3B 130, K 98, BB 114 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .393 → .296; ISO .245 → .176; BABIP .359 → .288. 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).

2017 AAJackson Generals · 588 PAwOBA .367 → .307 (−60)K% 22.8% → 28.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.79%	÷0.983	×1.220	—	—	28.27%
BB% (unintentional) /PA	8.84%	÷0.987	×0.680	—	×1.012	6.17%
HBP% /PA	1.36%	—	×0.840	—	×1.012	1.16%
Singles /BIP	22.57%	÷0.980	×0.920	×0.950	×1.012	20.38%
Doubles /BIP	9.19%	÷1.004	×0.910	×0.950	×1.012	8.00%
Triples /BIP	0.00%	÷1.150	×0.880	×0.950	×1.012	0.00%
Home runs /BIP	6.56%	÷0.985	×0.800	—	×1.012	5.39%

Factors used: league row SL. Park (home-season share, regressed): HR 97, 1B 96, 2B 101, 3B 130, K 97, BB 97 — applied at half strength. Age: age 24 vs a level average of 24.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .367 → .307; ISO .214 → .178; BABIP .332 → .293. 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).

2016 AAMobile BayBears · 510 PAwOBA .306 → .226 (−80)K% 26.3% → 32.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.27%	÷0.977	×1.220	—	—	32.81%
BB% (unintentional) /PA	6.08%	÷0.975	×0.680	—	×1.027	4.35%
HBP% /PA	1.18%	—	×0.840	—	×1.027	1.01%
Singles /BIP	16.92%	÷1.065	×0.920	×0.950	×1.027	14.26%
Doubles /BIP	6.04%	÷1.146	×0.910	×0.950	×1.027	4.68%
Triples /BIP	0.30%	÷0.900	×0.880	×0.950	×1.027	0.29%
Home runs /BIP	7.85%	÷1.160	×0.800	—	×1.027	5.56%

Factors used: league row SL. Park (home-season share, regressed): HR 132, 1B 113, 2B 129, 3B 80, K 95, BB 95 — applied at half strength. Age: age 23 vs a level average of 24.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .306 → .226; ISO .215 → .149; BABIP .248 → .200. 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).

2015 A+Visalia Rawhide · 559 PAwOBA .343 → .274 (−69)K% 23.4% → 31.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.43%	÷1.002	×1.340	—	—	31.32%
BB% (unintentional) /PA	4.65%	÷1.057	×0.710	—	×1.012	3.16%
HBP% /PA	1.07%	—	×0.790	—	×1.012	0.86%
Singles /BIP	20.67%	÷1.058	×0.910	×0.971	×1.012	17.48%
Doubles /BIP	8.79%	÷1.007	×0.820	×0.971	×1.012	7.03%
Triples /BIP	0.00%	÷0.913	×0.760	×0.971	×1.012	0.00%
Home runs /BIP	6.98%	÷0.973	×0.920	—	×1.012	6.67%

Factors used: league row CAL. Park (home-season share, regressed): HR 95, 1B 112, 2B 101, 3B 83, K 100, BB 111 — applied at half strength. Age: age 22 vs a level average of 22.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.971.

Result: wOBA .343 → .274; ISO .222 → .189; BABIP .311 → .258. 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).

2014 ROKMissoula Osprey · 150 PAwOBA .380 → .278 (−102)K% 10.7% → 15.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.67%	÷1.000	×1.440	—	—	15.36%
BB% (unintentional) /PA	6.67%	÷1.000	×0.610	—	×0.985	4.01%
HBP% /PA	4.67%	—	×0.720	—	×0.985	3.31%
Singles /BIP	19.83%	÷1.000	×0.820	×0.985	×0.985	15.77%
Doubles /BIP	8.62%	÷1.000	×0.720	×0.985	×0.985	6.02%
Triples /BIP	0.00%	÷1.000	×0.720	×0.985	×0.985	0.00%
Home runs /BIP	5.17%	÷1.000	×0.750	—	×0.985	3.82%

Factors used: league row PIO. 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 19.5 → −1.5% on BB/HBP/hit rates (1.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.985.

Result: wOBA .380 → .278; ISO .212 → .154; BABIP .297 → .225. 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).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .