Kevin McGonigle

3B Detroit Tigers

Age 22 L/R 5'9" / 187 lbs MLB HR -8% Svc 1.000 · Ctrl thru 2034

Overview

MLB40-MANExtFA 2035

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	19	A+/ADET	328	.309/.411/.452	5	22	104	—	.274/.348/.382
2025	20	AA/A+/A/INTL2 orgs	487	.315/.430/.605	24	13	148	—	.263/.344/.495
2026	21	MLBDET	707	.278/.378/.430	18	12	134	4.7
2027PROJ	22	MLBDET	614	.274/.371/.430	16	12	131	3.9
2028PROJ	23	MLBDET	614	.279/.376/.449	18	12	138	4.4
2029PROJ	24	MLBDET	614	.283/.380/.462	20	12	143	4.7

Last 3 seasons WAR 4.7 · Next 3 projected WAR 12.9Projected rows: MLB playing time only, park and league context applied.

ContractCONFIRMED

Control thru2034Service1.000First FA2035

2027Ext$3M2028Ext$9M2029Ext$18M2030Ext$23M2031Ext$24M2032Ext$25M2033Ext$25M2034Ext$25M

Skills · percentileStatcast 2026

xwOBA90

Speed68

Bat Spd52

Barrel%43

Avg EV33

Form.275/.371/.448 · rolling true talent (45d window) · proj .278/.372/.440

CompsJoe Mauer (age 23) · Adrian Beltré (age 22) · Grady Sizemore (age 23)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 116131vR 136

AVG/OBP/SLG.274 / .371 / .430

PA614

HR16

SB12

K%14

BB%13

BABIP301

ISO155

MLB%100%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$141M ctrl surplus

Tools · Recent Form · Splits · Contract

ToolsStatcast %ile · 2026

CONTACT

xAVG

660.264

POWER

Barrel%

437.3

Avg EV

3387.8

Bat Spd

5271.5

SPEED

Sprint

6828.2

Recent Formrolling true talent ⓘ

K%16%▼18% over 62 PA (45d) · proj 15%

BB%13%·13% over 122 PA (60d) · proj 13%

ISO.173▲.190 over 105 AB (60d) · proj .161

HR/BB4.1%·4.6% over 87 BBE (60d) · proj 3.8%

BABIP.306·.313 over 83 BIP (60d) · proj .306

SLASH.275/.371/.448·proj .278/.372/.440

Platoon Splits2026 · 113 PA

vs LHP

vs RHP

Edge

—

wRC+

131

164

▶▶R

wOBA

362

411

▶R

ISO

046

213

▶▶R

BABIP

368

371

—

11.5%

13.8%

◀◀L

BB%

11.5%

13.8%

▶▶R

Contract CONFIRMED · hand-curated extension

Status Pre-Arb

MLB Debut 2026

Service 1.000 yrs.days

Team Control Through 2034

First FA Year 2035

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$3M	+4.4	$52M	+$49M
2028	Ext	$9M	+4.4	$48M	+$40M
2029	Ext	$18M	+4.7	$48M	+$34M
2030	Ext	$23M	+4.9	$47M	+$30M
2031	Ext	$24M	+4.9	$43M	+$28M
2032	Ext	$25M	+4.7	$39M	+$24M
2033	Ext	$25M	+4.4	$33M	+$20M
2034	Ext	$25M	+4.0	$26M	+$14M
Totals		$150M		$336M	+$239M

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)
2023	18	A	Lakeland Flying Tigers	—	48	40	14	2	0	1	7	5	0	2	2	350	447	475	922	125	371	10	15	406	129	—	—	—	—	—	—
2023	18	ROK	FCL Tigers	—	45	33	9	2	0	0	11	5	1	6	3	273	467	333	800	61	321	11	24	385	78	—	—	—	—	—	—
2024	19	A+	West Michigan Whitecaps	—	57	42	9	1	1	1	11	4	1	2	0	214	389	357	746	143	200	7	19	330	99	—	—	—	—	—	—
2024	19	A	Lakeland Flying Tigers	—	271	230	75	15	3	4	35	24	0	20	2	326	415	470	885	143	343	9	13	387	105	—	—	—	—	—	—
2025	20	AA	Erie SeaWolves	—	206	169	43	10	2	12	33	26	0	7	2	254	376	550	927	296	230	13	16	394	112	—	—	—	—	—	—
2025	20	A+	West Michigan Whitecaps	—	171	145	54	19	0	7	23	19	2	3	5	372	465	648	1.113	276	392	11	13	478	156	—	—	—	—	—	—
2025	20	A	Lakeland Flying Tigers	—	20	17	4	2	0	0	3	1	0	0	0	235	350	353	703	118	250	5	15	324	68	—	—	—	—	—	—
2025	20	INTL	Scottsdale Scorpions	—	90	69	25	5	2	5	19	12	1	3	1	362	506	710	1.216	348	377	13	21	509	231	—	—	—	—	—	—
2026	21	MLB	Detroit Tigers	—	707	605	168	28	5	18	95	100	3	12	4	278	378	430	808	152	305	14	13	362	134	+29	+1	-2	+3	+15	4.7
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	707	605	168	28	5	18	95	100	3	12	4	278	378	430	808	152	305	14	13	362	131	+26	+1	-2	+3	+15	4.4
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2023	18	A MLE	Lakeland Flying Tigers	—	48	42	14	2	0	1	5	7	0	2	2	333	404	452	857	119	360	15	10	359	129	—	—	—	—	—	—
2023	18	ROK MLE	FCL Tigers	—	45	37	8	2	0	0	7	7	1	6	3	216	356	270	626	54	260	16	16	283	78	—	—	—	—	—	—
2024	19	A+ MLE	West Michigan Whitecaps	—	57	45	9	1	1	1	8	5	1	2	0	200	333	333	667	133	193	9	14	314	99	—	—	—	—	—	—
2024	19	A MLE	Lakeland Flying Tigers	—	271	242	70	10	3	3	23	32	0	20	2	289	351	393	744	103	304	12	8	324	105	—	—	—	—	—	—
2025	20	AA MLE	Erie SeaWolves	—	206	178	40	8	2	10	24	31	0	7	2	225	317	461	778	236	208	15	12	334	112	—	—	—	—	—	—
2025	20	A+ MLE	West Michigan Whitecaps	—	171	153	48	16	0	7	15	25	2	3	5	314	382	556	938	242	335	15	9	399	156	—	—	—	—	—	—
2025	20	A MLE	Lakeland Flying Tigers	—	20	18	4	2	0	0	2	1	0	0	0	222	300	333	633	111	219	5	10	268	68	—	—	—	—	—	—
2026	21	MLB MLE	Detroit Tigers	—	707	606	171	29	5	19	94	100	3	12	4	282	381	441	822	158	305	14	13	366	134	+29	+1	-2	+3	+15	4.7
2023	18	A MLE	2 teams	—	93	79	22	3	0	1	12	14	1	8	5	278	380	354	735	76	323	15	13	322	104	—	—	—	—	—	—
2023	18	A RAW	2 teams	—	93	73	23	4	0	1	18	10	1	8	5	315	457	411	867	96	349	11	19	396	104	—	—	—	—	—	—
2024	19	A MLE	2 teams	—	328	287	79	11	4	4	31	37	1	22	2	275	348	383	731	108	295	11	9	322	104	—	—	—	—	—	—
2024	19	A RAW	2 teams	—	328	272	84	16	4	5	46	28	1	22	2	309	411	452	863	143	320	9	14	377	104	—	—	—	—	—	—
2025	20	AA MLE	4 teams	—	487	427	112	32	2	21	51	70	3	13	8	262	345	494	839	232	266	14	10	359	129	—	—	—	—	—	—
2025	20	AA RAW	4 teams	—	487	400	126	36	4	24	78	58	3	13	8	315	430	605	1.035	290	315	12	16	442	129	—	—	—	—	—	—
2026	21	MLB MLE	Detroit Tigers	—	707	606	171	29	5	19	94	100	3	12	4	282	381	441	822	158	310	14	13	366	134	+29	+1	-2	+3	+15	4.7
2026	21	MLB RAW	Detroit Tigers	—	707	605	168	28	5	18	95	100	3	12	4	278	378	430	808	152	305	14	13	362	134	+29	+1	-2	+3	+15	4.7
2023	18	A MLE	2 teams	—	93	80	22	3	0	1	12	14	1	8	5	275	380	350	730	75	312	15	13	322	104	—	—	—	—	—	—
2024	19	A MLE	2 teams	—	328	293	79	11	4	4	31	37	1	22	2	270	348	375	723	106	285	11	9	322	104	—	—	—	—	—	—
2025	20	AA MLE	4 teams	—	487	430	112	32	2	21	51	70	3	13	8	260	345	491	836	230	263	14	10	359	129	—	—	—	—	—	—
2026	21	MLB MLE	Detroit Tigers	—	707	604	171	29	5	19	94	100	3	12	4	283	381	442	823	159	305	14	13	366	134	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	19	A MLE	2 teams	—	328	293	79	11	4	4	31	37	1	22	2	270	348	375	723	106	285	11	9	322	104	—	—	—	—	—	—
2025	20	AA MLE	4 teams	—	487	430	112	32	2	21	51	70	3	13	8	260	345	491	836	230	263	14	10	359	129	—	—	—	—	—	—
2026	21	MLB MLE	Detroit Tigers	—	707	604	171	29	5	19	94	100	3	12	4	283	381	442	823	159	305	14	13	366	134	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	DET	100%	636	547	152	27	5	17	81	92	3	12	3	279	375	440	815	161	306	14	13	363	131	+24	+1	-2	+2	+14	4.4
▸ 2027 — real world (MLB)
2027	22	MLB CTX	DET	100%	614	528	145	26	4	16	78	89	3	12	3	274	371	430	800	156	301	14	13	357	131	+23	+1	-2	+2	+13	3.9
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	DET	100%	614	527	150	26	5	19	79	87	3	12	3	284	381	460	841	176	307	14	13	372	138	+28	+1	-2	+2	+13	4.4
2029	24	MLB MLE	DET	100%	614	527	152	26	5	21	79	85	3	12	3	288	384	474	858	186	308	14	13	379	143	+31	+1	-2	+2	+13	4.7
2030	25	MLB MLE	DET	100%	614	526	153	26	5	22	80	85	3	12	3	290	386	481	868	192	308	14	13	382	145	+33	+1	-2	+2	+13	4.9
2031	26	MLB MLE	DET	100%	614	526	152	26	4	22	80	85	3	12	3	290	387	481	868	191	308	14	13	382	145	+33	+1	-2	+2	+13	4.9
2032	27	MLB MLE	DET	100%	606	519	149	26	4	21	79	85	3	11	3	289	386	479	864	190	308	14	13	381	144	+32	+1	-2	+2	+13	4.7
2033	28	MLB MLE	DET	100%	592	507	145	25	4	20	77	84	3	9	2	287	384	474	857	187	307	14	13	378	142	+30	+1	-2	+2	+13	4.4
2034	29	MLB MLE	DET	100%	571	489	139	24	4	19	74	83	3	6	2	284	381	467	848	183	306	15	13	375	140	+27	+0	-3	+2	+12	4.0
2035	30	MLB MLE	DET	100%	555	477	134	23	4	18	71	82	2	4	1	281	377	459	837	178	304	15	13	370	137	+24	+0	-4	+2	+12	3.6
2036	31	MLB MLE	DET	100%	536	461	128	22	3	17	68	81	2	0	1	277	372	449	821	172	301	15	13	364	133	+21	-0	-4	+2	+12	3.0
2037	32	MLB MLE	DET	100%	513	441	119	20	3	15	65	80	2	0	1	270	366	434	800	164	297	16	13	356	127	+17	-0	-5	+2	+11	2.5
2038	33	MLB MLE	DET	100%	476	412	108	17	3	14	60	77	1	0	0	263	358	417	775	154	292	16	13	346	120	+12	+0	-6	+2	+10	1.8
2039	34	MLB MLE	DET	96%	419	363	91	14	2	11	52	71	1	0	0	253	347	396	743	143	284	17	12	334	112	+6	+0	-6	+1	+9	1.1
2040	35	MLB MLE	DET	91%	351	306	74	11	2	8	42	62	0	0	0	242	336	373	709	130	276	18	12	320	103	+1	+0	-7	+1	+8	0.3
2041	36	MLB MLE	DET	82%	274	240	56	8	1	6	32	51	0	0	0	232	324	349	673	117	269	19	12	306	93	-2	+0	-7	+1	+6	-0.3
2028	23	MLB CTX	DET	100%	614	527	147	26	4	18	79	87	3	12	3	279	376	449	825	170	302	14	13	366	138	+28	+1	-2	+2	+13	4.4
2029	24	MLB CTX	DET	100%	614	527	149	26	4	20	79	85	3	12	3	283	380	462	842	179	303	14	13	373	143	+31	+1	-2	+2	+13	4.7
2030	25	MLB CTX	DET	100%	614	526	150	26	4	21	80	85	3	12	3	285	382	469	851	185	303	14	13	376	145	+33	+1	-2	+2	+13	4.9
2031	26	MLB CTX	DET	100%	614	526	150	26	4	21	80	85	3	12	3	284	382	469	851	185	303	14	13	376	145	+33	+1	-2	+2	+13	4.9
2032	27	MLB CTX	DET	100%	606	519	146	25	4	20	79	85	3	11	3	283	381	467	848	183	302	14	13	375	144	+32	+1	-2	+2	+13	4.7
2033	28	MLB CTX	DET	100%	592	507	143	24	4	20	77	84	3	9	2	282	379	462	841	180	302	14	13	372	142	+30	+1	-2	+2	+13	4.4
2034	29	MLB CTX	DET	100%	571	489	136	23	4	18	74	83	3	6	2	279	376	456	832	177	301	15	13	369	140	+27	+0	-3	+2	+12	4.0
2035	30	MLB CTX	DET	100%	555	477	131	22	4	17	71	82	2	4	1	276	373	448	821	172	299	15	13	364	137	+24	+0	-4	+2	+12	3.6
2036	31	MLB CTX	DET	100%	536	461	124	21	3	16	68	81	2	0	1	272	368	438	806	166	296	15	13	358	133	+21	-0	-4	+2	+12	3.0
2037	32	MLB CTX	DET	100%	513	441	117	19	3	15	65	80	2	0	1	266	362	424	785	158	292	16	13	350	127	+17	-0	-5	+2	+11	2.5
2038	33	MLB CTX	DET	100%	476	412	107	17	3	13	60	77	1	0	0	258	353	407	761	149	287	16	13	341	120	+12	+0	-6	+2	+10	1.8
2039	34	MLB CTX	DET	96%	400	347	86	13	2	10	49	68	1	0	0	249	343	387	730	138	280	17	12	328	112	+6	+0	-6	+1	+9	1.0
2040	35	MLB CTX	DET	91%	319	277	67	10	2	7	39	57	0	0	0	238	332	364	696	126	272	18	12	315	103	+1	+0	-6	+1	+7	0.3
2041	36	MLB CTX	DET	82%	225	196	45	6	1	5	27	42	0	0	0	228	320	341	662	113	265	19	12	301	93	-2	+0	-6	+1	+5	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	7956	6837	1866	312	51	239	1022	1181	32	90	26	273	370	438	808	165	298	15	13	360	132	+317	+8	-53	+28	+172	48.2
/ 162G	—	A+C		—	650	559	152	25	4	20	83	96	3	7	2	272	369	438	807	166	296	15	13	360	132	+26	+1	-4	+2	+14	3.9
Career	—	MLE		—	9578	8248	2282	395	65	295	1204	1408	40	145	44	277	371	448	819	171	301	15	13	363	132	+340	+9	-57	+31	+188	52.1
/ 162G	—	MLE		—	650	560	155	27	4	20	82	96	3	10	3	277	373	446	819	170	301	15	13	363	132	+26	+1	-4	+2	+14	3.9

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 AAErie SeaWolves · 206 PAwOBA .392 → .334 (−58)K% 12.6% → 14.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.62%	÷1.035	×1.220	—	—	14.87%
BB% (unintentional) /PA	16.02%	÷0.996	×0.700	—	×1.050	11.82%
HBP% /PA	0.00%	—	×0.850	—	×1.050	0.00%
Singles /BIP	13.29%	÷0.981	×0.970	×0.955	×1.050	13.17%
Doubles /BIP	6.99%	÷1.075	×0.860	×0.955	×1.050	5.61%
Triples /BIP	1.40%	÷1.115	×0.950	×0.955	×1.050	1.20%
Home runs /BIP	8.39%	÷1.056	×0.780	—	×1.050	6.51%

Factors used: league row EL. Park (home-season share, regressed): HR 111, 1B 96, 2B 115, 3B 123, K 107, BB 99 — applied at half strength. Age: age 21 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.955.

Result: wOBA .392 → .334; ISO .296 → .246; BABIP .230 → .208. 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 A+West Michigan Whitecaps · 171 PAwOBA .468 → .399 (−70)K% 11.1% → 14.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.11%	÷0.960	×1.270	—	—	14.70%
BB% (unintentional) /PA	13.45%	÷1.106	×0.710	—	×1.027	8.87%
HBP% /PA	1.17%	—	×0.790	—	×1.027	0.95%
Singles /BIP	22.22%	÷1.027	×0.920	×0.950	×1.027	19.42%
Doubles /BIP	15.08%	÷0.948	×0.810	×0.950	×1.027	12.58%
Triples /BIP	0.00%	÷0.900	×0.850	×0.950	×1.027	0.00%
Home runs /BIP	5.56%	÷0.850	×0.800	—	×1.027	5.37%

Factors used: league row Midwest League. Park (home-season share, regressed): HR 70, 1B 105, 2B 90, 3B 80, K 92, BB 121 — applied at half strength. Age: age 21 vs a level average of 22.8 → +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 .468 → .399; ISO .276 → .255; BABIP .392 → .335. 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 ALakeland Flying Tigers · 20 PAwOBA .316 → .268 (−48)K% 5.0% → 6.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	5.00%	÷0.998	×1.360	—	—	6.81%
BB% (unintentional) /PA	15.00%	÷0.945	×0.690	—	×1.015	11.12%
HBP% /PA	0.00%	—	×0.780	—	×1.015	0.00%
Singles /BIP	12.50%	÷1.051	×0.920	—	×1.015	11.10%
Doubles /BIP	12.50%	÷0.971	×0.830	—	×1.015	10.84%
Triples /BIP	0.00%	÷1.150	×0.910	—	×1.015	0.00%
Home runs /BIP	0.00%	÷0.864	×0.800	—	×1.015	0.00%

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 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average).

Result: wOBA .316 → .268; ISO .118 → .105; BABIP .250 → .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).

2024 ALakeland Flying Tigers · 271 PAwOBA .384 → .324 (−60)K% 8.9% → 11.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.86%	÷1.028	×1.360	—	—	11.72%
BB% (unintentional) /PA	12.92%	÷1.061	×0.690	—	×1.030	8.65%
HBP% /PA	0.00%	—	×0.780	—	×1.030	0.00%
Singles /BIP	25.73%	÷0.980	×0.920	×0.997	×1.030	24.82%
Doubles /BIP	7.28%	÷1.351	×0.830	×0.997	×1.030	4.59%
Triples /BIP	1.46%	÷1.106	×0.910	×0.997	×1.030	1.23%
Home runs /BIP	1.94%	÷1.099	×0.800	—	×1.030	1.46%

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 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 ×0.997.

Result: wOBA .384 → .324; ISO .143 → .107; BABIP .343 → .304. 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 A+West Michigan Whitecaps · 57 PAwOBA .341 → .314 (−27)K% 7.0% → 9.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	7.02%	÷0.957	×1.270	—	—	9.32%
BB% (unintentional) /PA	19.30%	÷1.026	×0.710	—	×1.042	13.92%
HBP% /PA	1.75%	—	×0.790	—	×1.042	1.44%
Singles /BIP	15.79%	÷1.021	×0.920	×1.012	×1.042	15.01%
Doubles /BIP	2.63%	÷0.892	×0.810	×1.012	×1.042	2.52%
Triples /BIP	2.63%	÷0.900	×0.850	×1.012	×1.042	2.62%
Home runs /BIP	2.63%	÷0.889	×0.800	—	×1.042	2.47%

Factors used: league row Midwest League. Park (home-season share, regressed): HR 78, 1B 104, 2B 78, 3B 80, K 91, BB 105 — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.012.

Result: wOBA .341 → .314; ISO .143 → .155; BABIP .200 → .193. 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 ALakeland Flying Tigers · 48 PAwOBA .404 → .359 (−45)K% 10.4% → 14.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.42%	÷0.975	×1.360	—	—	14.53%
BB% (unintentional) /PA	14.58%	÷1.089	×0.690	—	×1.045	9.66%
HBP% /PA	0.00%	—	×0.780	—	×1.045	0.00%
Singles /BIP	31.43%	÷0.957	×0.920	—	×1.045	31.58%
Doubles /BIP	5.71%	÷1.056	×0.830	—	×1.045	4.69%
Triples /BIP	0.00%	÷1.020	×0.910	—	×1.045	0.00%
Home runs /BIP	2.86%	÷1.216	×0.800	—	×1.045	1.96%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 143, 1B 91, 2B 111, 3B 104, K 95, BB 118 — 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).

Result: wOBA .404 → .359; ISO .125 → .096; BABIP .371 → .360. 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 Tigers · 45 PAwOBA .377 → .283 (−94)K% 11.1% → 16.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.11%	÷0.972	×1.440	—	—	16.46%
BB% (unintentional) /PA	24.44%	÷0.987	×0.620	—	×1.008	15.47%
HBP% /PA	2.22%	—	×0.720	—	×1.008	1.61%
Singles /BIP	25.00%	÷0.987	×0.820	—	×1.008	20.92%
Doubles /BIP	7.14%	÷1.014	×0.720	—	×1.008	5.11%
Triples /BIP	0.00%	÷1.150	×0.720	—	×1.008	0.00%
Home runs /BIP	0.00%	÷0.924	×0.780	—	×1.008	0.00%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 85, 1B 97, 2B 103, 3B 130, K 94, BB 97 — 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).

Result: wOBA .377 → .283; ISO .061 → .046; BABIP .321 → .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).

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

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Joe Morgan'63-'84 * career totals — 19 seasons, 11,329 PA	17.1	11,329	268	689	268*	390*	461*	+39	-69	90.6	69.9
/162	664	16	40	+2.3	-4.1	5.3	pk7: 49
#2Cal Ripken'81-'01 * career totals — 20 seasons, 12,883 PA	19.4	12,883	431	36	269*	334*	456*	+114	+12	76.5	62.5
/162	664	22	2	+5.8	+0.6	3.9	pk7: 48
#3Robinson Canólast yr '22 AS×8GG×2SS×5 career totals — 17 seasons, 9,550 PA	14.4	9,550	335	51	301	351	488	+34	+8	70.1	58.3
/162	664	23	4	+2.4	+0.6	4.9	pk7: 47
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 16 projected seasons	12.9	8,570	267	103	279	371	451	+76	-22	67.2	53.2
/162	664	21	8	+5.9	-1.7	5.2	pk7: 39
#4David Wrightlast yr '16 AS×7GG×2SS×2 career totals — 13 seasons, 6,869 PA	10.3	6,869	242	196	296	376	491	+25	-8	58.2	52.5
/162	664	23	19	+2.4	-0.8	5.6	pk7: 47
#5Lou Whitaker'77-'95 * career totals — 18 seasons, 9,967 PA	15.0	9,967	244	143	272*	361*	446*	+32	+27	62.5	47.1
/162	664	16	10	+2.1	+1.8	4.2	pk7: 32
#6Ryan Zimmermanlast yr '21 career totals — 16 seasons, 7,402 PA	11.1	7,402	284	43	277	341	475	-25	+13	44.4	40.7
/162	664	25	4	-2.2	+1.2	4.0	pk7: 37

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
Kevin McGonigle (OGILVIE)	22	—	—	—	—	276/372/436	160	306	17	12	15%	13%	131	+3.7	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
★Joe Mauer 2006 · MLB	23	57→67	46→50	54→50	56	280/344/415	135	301	13	13	12%	9%	116	+2.5	304/373/441	137	327	11	8	10%	10%	132	+3.6	328/400/484	156	345	15	2	9%	10%	152	+5.2
★Adrian Beltré 2001 · MLB	22	55→62	53→65	48→50	56	279/347/459	180	297	21	12	14%	9%	127	+3.3	259/309/424	165	282	19	10	16%	6%	105	+1.7	298/336/528	230	297	31	1	12%	5%	140	+4.3
★Grady Sizemore 2006 · MLB	23	55→58	53→60	54→55	49	277/338/462	185	318	18	16	19%	8%	124	+3.1	277/360/487	210	322	21	21	20%	10%	138	+4.1	273/366/489	216	313	23	25	20%	11%	142	+5.5
●Jason Heyward 2012 · MLB	22	50→59	53→55	50	57	255/346/432	177	292	20	11	20%	11%	120	+2.8	259/337/437	178	299	21	14	20%	10%	119	+2.7	264/342/431	167	302	19	15	19%	10%	120	+2.7
★Buster Posey 2010 · MLB	23	55→65	51→60	48→45	52	274/342/437	163	314	18	6	19%	8%	120	+2.8	299/361/478	179	334	20	4	16%	8%	137	+4.0	311/375/498	187	332	22	1	13%	9%	148	+4.8
●Jeremy Hermida 2006 · MLB	22	52→59	54→55	56→50	61	262/368/456	193	314	21	19	22%	14%	135	+3.8	260/339/424	164	319	17	9	22%	10%	116	+2.5	263/338/427	163	319	19	5	22%	9%	118	+2.2
★Francisco Lindor 2017 · MLB	23	58→63	46→65	52→55	50	282/335/415	133	317	13	17	15%	7%	112	+2.2	275/332/484	209	286	25	16	14%	8%	128	+3.3	270/347/485	215	296	27	26	19%	9%	135	+4.5
●Austin Kearns 2003 · MLB	23	60→64	52→60	48→45	57	294/381/473	178	343	18	9	19%	11%	142	+4.4	264/351/459	195	316	23	7	23%	11%	129	+3.4	258/346/445	187	301	20	4	20%	10%	125	+3.2
★Corey Seager 2016 · MLB	22	53→62	53→65	50→45	44	270/316/454	184	321	19	6	22%	6%	115	+2.4	291/349/475	184	344	20	5	20%	8%	132	+3.6	281/349/508	228	296	29	2	16%	9%	141	+3.8
●Wander Franco 2023 · MLB	22	56→60	48→55	53→55	53	275/330/432	157	294	13	11	12%	7%	114	+2.4	268/328/444	176	289	19	24	14%	8%	117	+2.6	274/336/469	195	291	21	37	14%	8%	126	+2.7
★Brandon Belt 2011 · AAA	23	58→61	55→65	53→50	54	287/364/494	207	347	20	14	22%	10%	141	+4.3	272/351/449	177	343	17	12	24%	10%	126	+3.2	269/370/482	213	337	21	4	24%	13%	141	+4.0
★Nick Markakis 2008 · MLB	24	57→62	51→55	48→50	51	287/344/458	171	319	18	10	16%	8%	126	+3.2	293/362/459	166	329	16	8	15%	10%	132	+3.7	293/366/449	157	328	14	7	14%	10%	132	+4.3
●Carlos Correa 2017 · MLB	22	54→61	54→60	54→55	53	273/345/463	190	316	21	17	20%	10%	128	+3.3	269/344/470	201	314	25	7	22%	10%	129	+3.4	263/344/444	182	303	22	0	20%	10%	124	+3.1
★Ryan Zimmerman 2007 · MLB	22	58→59	52→65	42→45	49	288/339/467	179	328	17	8	18%	7%	126	+3.2	275/332/462	187	307	20	5	17%	8%	122	+3.0	289/358/487	198	317	24	3	17%	9%	139	+4.0
●Ozzie Albies 2020 · MLB	23	55→62	53→60	55	48	276/324/464	188	307	19	14	17%	6%	120	+2.8	265/314/467	202	295	23	14	18%	6%	118	+2.6	262/315/476	214	281	26	13	18%	6%	121	+2.6
●Brian McCann 2007 · MLB	23	56→62	56→60	44→45	51	291/343/490	199	299	24	4	13%	7%	133	+3.7	281/337/480	199	294	22	4	13%	7%	128	+3.4	278/355/480	202	295	24	5	14%	10%	136	+3.7
★Mookie Betts 2016 · MLB	23	57→63	50→65	57→55	53	283/342/449	166	307	15	22	14%	8%	122	+3.0	288/349/493	205	299	23	22	12%	8%	136	+3.9	282/374/532	250	295	30	11	16%	11%	157	+5.7
●Kelly Johnson 2006 · MLB	24	50→58	52→55	53→50	56	254/337/433	179	291	19	10	20%	11%	118	+2.6	270/350/443	173	318	16	10	19%	11%	124	+3.1	264/337/440	177	307	17	11	19%	10%	120	+2.6
★Troy Tulowitzki 2008 · MLB	23	54→57	51→65	44→50	49	271/334/437	166	313	18	7	19%	7%	118	+2.6	278/345/471	193	307	22	10	17%	9%	130	+3.5	286/356/514	228	301	28	14	15%	9%	145	+4.5
★Gunnar Henderson 2023 · MLB	22	51→56	50→60	56→55	49	244/328/411	167	344	17	15	32%	10%	109	+2.0	260/336/467	207	319	24	16	25%	10%	125	+3.2	263/338/474	211	310	25	18	23%	9%	129	+3.8

Kevin McGonigle

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps