Anthony Kay

P Chicago White Sox

Age 32 LHP 6'0" / 225 lbs MLB

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	27	MIX4 levels	14	4	23	5.40	4.77	24.3%	12.1%	-0.1	K 18.9% · BB 16.5% · FIP 7.22
2023	28	MIX2 levels	48	1	55	4.39	3.23	28.9%	13.0%	0.9	K 25.5% · BB 12.1% · FIP 3.44
2026	31	MLBCWS	33	31	158	4.44	4.24	18.2%	7.7%	2.2
2027PROJ	32	MLBCWS	19	19	113	4.53	4.50	19.0%	7.7%	1.2
2028PROJ95% MLB	33	MLBCWS	11	11	65	4.68	4.78	18.1%	8.1%	0.5
2029PROJ90% MLB	34	MLBCWS	6	6	37	4.92	5.08	17.2%	8.6%	0.1

Last 3 seasons WAR 3.0 · Next 3 projected WAR 1.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo70

xwOBA vs24

K%23

Form6.23 ERA (proj 4.53) · K 17.2% (proj 19.0%) · BB 7.4% (proj 7.7%) · last 60d · 26 IP through Oct 27

CompsEverett Teaford (age 31) · Ryan Verdugo (age 30) · Santiago Gutierrez (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 105113vR 121

ERA4.53

FIP4.50

K%19.0%

BB%7.7%

K-BB%11.3%

Proj IP113

Value2027 · WAR

Runs saved vs league avg · 113 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p7095.9

Whiff%

p3723.4%

p2318.2%

xwOBA vs

p240.342

Contract

No contract data on file. Pre-MLB players and minor-league free agents do not yet have salary projections — entries are added at first 40-man roster placement.

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 WAR & MLE are computed

Stats are park-neutral MLB equivalents. The "TEAM" column shows current org affiliation only — we do NOT project at that team's park.
Rates (K%, BB%, HR-BF) are park-stripped; MiLB stat lines are translated to their MLB-equivalent via per-level MLE factors.
WAR is computed from projected runs prevented vs a replacement pitcher (the marginal arm a team would call up if this pitcher were unavailable) — calibrated to the standard WAR scale.

Year	Age	Lvl	Team	G	GS	IP	BF	K	BB	HR	GS%	IP/G	K%	BB%	K-BB%	HR%	ERA	FIP	WAR
▸ Career — actual stats, one row per year (as recorded, no adjustments)
▸ Career — adjusted (each season translated to a park/league-neutral MLB-equivalent line; levels combined per year)
▸ Model inputs — neutral MLE (past 3 seasons + 2027 so far)
2018	23	MIX MLE	2 levels	23	23	123	531	123	49	7	100%	5.3	17.4%	10.7%	6.7%	1.7%	4.26	3.94	—
2018	23	MIX RAW	2 levels	23	23	123	531	123	49	7	100%	5.3	23.2%	9.2%	13.9%	1.3%	4.26	3.03	—
2019	24	MIX MLE	3 levels	29	28	148	624	148	60	12	97%	5.1	20.3%	10.2%	10.1%	2.1%	3.23	3.86	+2.7
2019	24	MIX RAW	3 levels	29	28	148	624	148	60	12	97%	5.1	23.7%	9.6%	14.1%	1.9%	3.23	3.37	+3.7
2020	25	MLB MLE	Toronto Blue Jays	13	0	21	98	22	13	3	0%	1.6	22.4%	13.3%	9.2%	3.1%	5.14	4.56	-0.0
2020	25	MLB RAW	Toronto Blue Jays	13	0	21	98	22	13	3	0%	1.6	22.4%	13.3%	9.2%	3.1%	5.14	4.72	-0.0
2021	26	MIX MLE	2 levels	19	13	60	282	68	31	12	68%	3.2	22.9%	11.2%	11.7%	4.3%	7.05	4.94	+0.3
2021	26	MIX RAW	2 levels	19	13	60	282	68	31	12	68%	3.2	24.1%	11.0%	13.1%	4.3%	7.05	4.98	+0.3
2022	27	MIX MLE	4 levels	14	4	23	107	26	13	4	29%	1.7	18.9%	16.5%	2.4%	6.6%	5.40	7.22	-0.7
2022	27	MIX RAW	4 levels	14	4	23	107	26	13	4	29%	1.7	24.3%	12.1%	12.1%	3.7%	5.40	4.77	-0.1
2023	28	MIX MLE	2 levels	48	1	55	239	69	31	4	2%	1.2	25.5%	12.1%	13.4%	1.8%	4.39	3.44	+0.7
2023	28	MIX RAW	2 levels	48	1	55	239	69	31	4	2%	1.2	28.9%	13.0%	15.9%	1.7%	4.39	3.23	+0.9
2026	31	MLB MLE	Chicago White Sox	33	31	158	710	129	55	21	94%	4.8	18.2%	7.7%	10.4%	2.9%	4.44	4.14	+2.4
2026	31	MLB MLE	Chicago White Sox	33	31	158	710	129	55	21	94%	4.8	18.2%	7.7%	10.4%	2.9%	4.44	4.14	+2.4
2026	31	MLB RAW	Chicago White Sox	33	31	158	710	129	55	21	94%	4.8	18.2%	7.7%	10.4%	3.0%	4.44	4.24	+2.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			77	38	243	1103	217	101	33	49%	3.2	19.7%	9.2%	10.5%	3.0%	4.85	4.32	+0.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	CWS	19	19	113	477	91	37	14	100%	5.9	19.0%	7.7%	11.3%	3.0%	4.53	4.50	+1.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	CWS	11	11	69	290	52	24	9	100%	6.2	18.1%	8.1%	10.0%	3.3%	4.68	4.78	+0.5
2029	34	MLB MLE	CWS	7	7	41	174	30	15	6	100%	5.9	17.2%	8.6%	8.6%	3.6%	4.92	5.08	+0.1
2028	33	MLB CTX	CWS	11	11	65	274	50	22	9	100%	5.9	18.1%	8.1%	10.0%	3.3%	4.68	4.78	+0.5
2029	34	MLB CTX	CWS	6	6	37	156	27	13	6	100%	6.2	17.2%	8.6%	8.6%	3.6%	4.92	5.08	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		94	55	346	1536	294	137	48	59%	3.7	19.1%	8.9%	10.2%	3.1%	4.82	4.32	+4.4
/ 200 IP	—	RAW		54	32	200	888	170	79	28	59%	3.7	19.1%	8.9%	10.2%	3.1%	4.82	4.32	+2.5
Career	—	MLE		179	100	588	2591	516	267	70	56%	3.3	19.9%	10.3%	9.6%	2.7%	4.42	4.20	+3.7
/ 200 IP	—	MLE		61	34	200	881	175	91	24	56%	3.3	19.9%	10.3%	9.6%	2.7%	4.42	4.20	+2.1

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.

2023 AAASyracuse Mets · 41 IPFIP 2.51 → 2.81 (+0.30)K% 33.5% → 28.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.53%	—	×0.860	28.83%
BB% (unintentional) /BF	12.72%	—	×0.900	11.45%
HR / BF /BF	1.16%	÷1.003	×1.100	1.27%

Factors used: pitcher AAA level factors (Triple-A 2023+ robo-zone set: walks improve on promotion) — K ×0.86, BB ×0.90, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 101).

Result: FIP 2.51 → 2.81, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2022 AAABuffalo Bisons · 14 IPFIP 6.42 → 7.22 (+0.81)K% 21.4% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.43%	—	×0.880	18.86%
BB% (unintentional) /BF	15.71%	—	×1.050	16.50%
HR / BF /BF	5.71%	÷0.951	×1.100	6.61%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 90).

Result: FIP 6.42 → 7.22, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2021 AAABuffalo Bisons · 26 IPFIP 4.64 → 4.98 (+0.34)K% 23.0% → 20.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.02%	—	×0.880	20.25%
BB% (unintentional) /BF	10.32%	—	×1.050	10.83%
HR / BF /BF	3.97%	÷1.081	×1.100	4.04%

Result: FIP 4.64 → 4.98, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2019 AAABuffalo Bisons · 67 IPFIP 4.46 → 4.93 (+0.47)K% 21.7% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.74%	—	×0.880	19.13%
BB% (unintentional) /BF	10.70%	—	×1.050	11.24%
HR / BF /BF	3.34%	÷1.000	×1.100	3.68%

Result: FIP 4.46 → 4.93, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2019 AABinghamton Rumble Ponies · 66 IPFIP 2.37 → 2.99 (+0.62)K% 26.7% → 21.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.72%	—	×0.810	21.64%
BB% (unintentional) /BF	8.78%	—	×1.100	9.66%
HR / BF /BF	0.76%	÷1.012	×1.200	0.91%

Factors used: pitcher AA level factors — K ×0.81, BB ×1.10, HR ×1.20. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 102).

Result: FIP 2.37 → 2.99, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2018 AColumbia Fireflies · 69 IPFIP 2.93 → 4.03 (+1.10)K% 26.0% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.00%	—	×0.740	19.24%
BB% (unintentional) /BF	7.33%	—	×1.180	8.65%
HR / BF /BF	2.00%	÷0.976	×1.300	2.66%

Factors used: pitcher A level factors — K ×0.74, BB ×1.18, HR ×1.30. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 95).

Result: FIP 2.93 → 4.03, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2018 A+St. Lucie Mets · 53 IPFIP 3.17 → 3.81 (+0.64)K% 19.5% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.48%	—	×0.770	15.00%
BB% (unintentional) /BF	11.69%	—	×1.150	13.44%
HR / BF /BF	0.43%	÷1.074	×1.250	0.50%

Factors used: pitcher A+ level factors — K ×0.77, BB ×1.15, HR ×1.25. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 115).

Result: FIP 3.17 → 3.81, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

Career Path Comps

What happened to similar pitchers from this age · Y-axis: ERA+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

			Profile at Match Age					Next 3 Yrs				Career
Comp	Age	Role	FIP	K%	BB%	HR/BF	BABIP	FIP	K%	K-BB%	IP	ΔFIP	Low FIP	IP	Match
Anthony Kay (OGILVIE)	—	—	—	—	—	3.0%	—	4.89	17.8%	9.5%	110	+0.39	—	—	—
Everett Teaford L 2015 · 4.42 FIP	31	SP-	4.42	13.9%	7.6%	2.8%	.324	—	—	—	—	—	4.42	208	61
Ryan Verdugo L 2017 · 3.36 FIP	30	SP-	3.36	22.7%	5.4%	2.7%	.333	—	—	—	—	—	3.36	153	60
Santiago Gutierrez L 2017 · 3.95 FIP	31	SP-	3.95	15.0%	8.2%	2.0%	.366	6.54	17.1%	3.7%	46	+2.59	3.90	341	58
Orlando Lara L 2017 · 4.39 FIP	32	SP	4.39	14.7%	6.5%	3.1%	.346	4.09	22.0%	14.2%	104	-0.30	3.85	426	54
Arturo Lopez L 2015 · 4.80 FIP	32	SP	4.80	13.7%	6.2%	3.8%	.301	4.80	10.9%	4.2%	217	+0.00	4.34	445	53
Jorge Castillo L 2015 · 4.50 FIP	33	SP	4.50	16.8%	9.2%	3.0%	.292	4.95	12.4%	7.2%	186	+0.45	4.50	408	53
Tomas Solis L 2015 · 4.20 FIP	32	SP	4.20	15.0%	6.2%	2.9%	.264	5.09	12.0%	3.7%	159	+0.89	4.20	327	52
Greg Smith L 2015 · 3.37 FIP	31	SP-	3.37	11.8%	5.3%	1.1%	.284	—	—	—	—	—	3.37	349	52
Matt Dermody L 2022 · 4.22 FIP	32	SP-	4.22	17.9%	5.5%	3.5%	.302	3.87	20.7%	16.1%	49	-0.35	2.38	348	51
Alejandro Astorga L 2017 · 4.01 FIP	30	SP	4.01	14.4%	8.2%	2.0%	.306	—	—	—	—	—	3.72	311	49
Oscar Rivera L 2015 · 3.68 FIP	34	SP	3.68	14.2%	6.9%	1.7%	.298	4.66	10.4%	3.0%	129	+0.98	3.68	237	49
Sean Nolin L 2021 · 4.54 FIP	31	SP-	4.54	20.4%	8.9%	3.7%	.316	5.87	19.3%	12.9%	23	+1.33	3.79	309	49
Luke Westphal L 2021 · 4.70 FIP	32	SP-	4.70	22.7%	13.1%	3.4%	.321	4.58	21.9%	7.6%	95	-0.12	2.97	294	48
Travis Blackley L 2015 · 4.91 FIP	32	SP-	4.91	15.4%	6.4%	4.2%	.324	4.45	10.5%	0.0%	137	-0.46	3.85	409	48
Edgar Osuna L 2019 · 5.09 FIP	31	SW	5.09	10.0%	7.2%	3.5%	.373	—	—	—	—	—	5.05	175	48
Roy Merritt L 2017 · 3.95 FIP	31	SP	3.95	16.2%	5.8%	2.7%	.339	—	—	—	—	—	3.93	129	48
Eric Stults L 2012 · 3.71 FIP	32	SP-	3.71	13.3%	6.5%	1.7%	.262	4.01	14.8%	9.6%	517	+0.30	3.50	773	46
Yusei Kikuchi L 2023 · 3.90 FIP	32	SP	3.90	25.9%	6.9%	3.9%	.311	3.72	24.7%	16.8%	422	-0.18	3.23	1,056	46
Mark Hendrickson L 2006 · 4.33 FIP	32	SP-	4.33	13.8%	8.6%	2.4%	.288	4.28	14.8%	8.8%	361	-0.05	3.04	1,169	45
Jose De Paula L 2019 · 3.31 FIP	31	SP	3.31	19.0%	7.6%	1.6%	.394	—	—	—	—	—	3.31	118	43

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 historical, 1901-2023), also matched on career-to-date at the same age. * Historical (Lahman) careers: rates era-adjusted to 2001-24 league levels; WAR is an OGILVIE proxy.

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	2.3	78	19.1%	8.7%	1.19	4.75
Adam Conley ('21)	2.2	87	19.8%	9.4%	1.16	4.71
Rich Folkers ('70-'77, -0 WAR*)	2.1	85	19.1%*	8.8%*	1.35*	4.91*
John Montague ('73-'80, -2 WAR*)	2.7	91	17.0%*	9.3%*	1.23*	4.98*
Odell Jones ('75-'88, 2 WAR*)	2.7	78	20.8%*	8.8%*	1.18*	4.62*
Brian Matusz ('16)	2.6	76	19.8%	8.7%	1.34	4.92
Brad Lincoln ('14)	1.1	56	17.4%	7.9%	1.30	4.74