Will Kengor

Pos1B

B/TL/R

Born1992-07-24

Age (2027)35

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2019

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2014	22	ROKGCL Tigers	191	.278/.364/.358	0	6	40	—	.200/.261/.247
2015	23	ADET	457	.286/.380/.358	1	4	72	—	.247/.316/.303
2019	27	INTLLeones del Es…	50	.209/.320/.256	0	1	73	—

Contract

No contract data on file.

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	22	ROK	GCL Tigers	—	191	162	45	9	2	0	21	31	1	6	3	278	364	358	722	80	333	16	11	319	40	—	—	—	—	—	—
2015	23	A	West Michigan Whitecaps	—	457	391	112	19	3	1	54	100	5	4	3	286	380	358	738	72	380	22	12	335	72	—	—	—	—	—	—
2019	27	INTL	Leones del Escogido	—	50	43	9	2	0	0	7	13	0	1	0	209	320	256	576	47	300	26	14	276	73	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2014	22	ROK MLE	GCL Tigers	—	191	170	34	6	1	0	13	45	1	6	3	200	261	247	508	47	251	24	7	228	40	—	—	—	—	—	—
2015	23	A MLE	West Michigan Whitecaps	—	457	409	101	16	2	1	36	139	5	4	3	247	316	303	619	56	359	30	8	275	72	—	—	—	—	—	—
2014	22	ROK MLE	GCL Tigers	—	191	170	34	6	1	0	13	45	1	6	3	200	261	247	508	47	264	24	7	228	40	—	—	—	—	—	—
2014	22	ROK RAW	GCL Tigers	—	191	162	45	9	2	0	21	31	1	6	3	278	364	358	722	80	333	16	11	319	40	—	—	—	—	—	—
2015	23	A MLE	West Michigan Whitecaps	—	457	409	101	16	2	1	36	139	5	4	3	247	316	303	619	56	369	30	8	275	72	—	—	—	—	—	—
2015	23	A RAW	West Michigan Whitecaps	—	457	391	112	19	3	1	54	100	5	4	3	286	380	358	738	72	380	22	12	335	72	—	—	—	—	—	—
2019	27	INTL MLE	Leones del Escogido	—	50	43	9	2	0	0	7	13	0	1	0	209	320	256	576	47	300	26	14	—	—	—	—	—	—	—	—
2019	27	INTL RAW	Leones del Escogido	—	50	43	9	2	0	0	7	13	0	1	0	209	320	256	576	47	300	26	14	276	73	—	—	—	—	—	—
2014	22	ROK MLE	GCL Tigers	—	191	175	34	6	1	0	13	45	1	6	3	194	261	240	501	46	251	24	7	228	40	—	—	—	—	—	—
2015	23	A MLE	West Michigan Whitecaps	—	457	413	101	16	2	1	36	139	5	4	3	245	316	300	616	56	359	30	8	275	72	—	—	—	—	—	—
▸ Career Totals
Career	—	MLE		—	698	622	144	24	3	1	56	197	6	11	6	232	301	285	586	53	333	28	8	242	50	-41	-0	+0	-12	+15	-4.0
/ 162G	—	MLE		—	650	579	134	22	3	1	52	183	6	10	6	231	301	285	586	54	332	28	8	242	50	-38	-0	+0	-12	+14	-3.7

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.

2015 AWest Michigan Whitecaps · 457 PAwOBA .328 → .275 (−53)K% 21.9% → 30.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.88%	÷0.977	×1.360	—	—	30.46%
BB% (unintentional) /PA	11.60%	÷1.006	×0.690	—	×0.990	7.88%
HBP% /PA	1.09%	—	×0.780	—	×0.990	0.84%
Singles /BIP	30.58%	÷0.996	×0.920	×1.050	×0.990	29.38%
Doubles /BIP	6.53%	÷0.969	×0.830	×1.050	×0.990	5.81%
Triples /BIP	1.03%	÷1.128	×0.910	×1.050	×0.990	0.86%
Home runs /BIP	0.34%	÷0.954	×0.800	—	×0.990	0.29%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 91, 1B 99, 2B 94, 3B 126, K 95, BB 101 — applied at half strength. Age: age 23 vs a level average of 22.0 → −1.0% on BB/HBP/hit rates (1.0 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .328 → .275; ISO .072 → .060; BABIP .380 → .359. 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 ROKGCL Tigers · 191 PAwOBA .318 → .228 (−90)K% 16.2% → 23.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.23%	÷1.000	×1.440	—	—	23.37%
BB% (unintentional) /PA	10.99%	÷1.000	×0.620	—	×0.975	6.65%
HBP% /PA	0.52%	—	×0.720	—	×0.975	0.37%
Singles /BIP	25.95%	÷1.000	×0.820	×0.969	×0.975	20.11%
Doubles /BIP	6.87%	÷1.000	×0.720	×0.969	×0.975	4.67%
Triples /BIP	1.53%	÷1.000	×0.720	×0.969	×0.975	1.04%
Home runs /BIP	0.00%	÷1.000	×0.780	—	×0.975	0.00%

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 22 vs a level average of 19.5 → −2.5% on BB/HBP/hit rates (2.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.969.

Result: wOBA .318 → .228; ISO .080 → .055; BABIP .333 → .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).

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