Antonio Knowles

P Tulsa Drillers

Age 27 RHP 6'1" / 190 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	AALAD	42	2	55	3.62	3.85	25.8%	13.7%	—	K 20.9% · BB 15.1% · FIP 4.58
2025	25	MIX2 levels	40	0	48	3.54	2.79	28.0%	7.5%	—	K 23.1% · BB 7.4% · FIP 3.24
2026	26	MIX2 levels	24	0	26	4.91	3.29	19.3%	14.3%	—	K 16.4% · BB 12.9% · FIP 3.35
2027PROJ	27	MLBLAD	1	0	1	4.37	4.37	20.9%	9.6%	0.0
2028PROJ38% MLB	28	MLBLAD	17	0	18	4.41	4.45	21.0%	9.7%	0.0
2029PROJ56% MLB	29	MLBLAD	22	0	23	4.50	4.57	21.0%	9.9%	-0.0

Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff55Control55Command60

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 98%

CompsRicky Stone (age 27) · Cody Satterwhite (age 28) · Tyler Walker (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 116108vR 100

ERA4.37

FIP4.37

K%20.9%

BB%9.6%

K-BB%11.3%

Proj IP60

Value2027 · WAR

Runs saved vs league avg · 60 IP

Grades · Contract

Scouting Grades

STUF5555

CTRL5555

CMD6060

K†5050

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)
2021	21	MIX MLE	2 levels	4	0	4	17	11	1	0	0%	1.0	64.7%	5.9%	58.8%	0.0%	2.25	-1.62	—
2021	21	MIX RAW	2 levels	4	0	4	17	11	1	0	0%	1.0	64.7%	5.9%	58.8%	0.0%	2.25	-1.65	—
2022	22	A+ MLE	Great Lakes Loons	36	0	44	213	63	36	2	0%	1.2	22.8%	19.4%	3.3%	1.2%	4.74	4.28	—
2022	22	A+ RAW	Great Lakes Loons	36	0	44	213	63	36	2	0%	1.2	29.6%	16.9%	12.7%	0.9%	4.74	3.28	—
2023	23	MIX MLE	2 levels	47	0	59	244	68	35	7	0%	1.2	22.2%	15.9%	6.2%	3.3%	3.99	5.09	—
2023	23	MIX RAW	2 levels	47	0	59	244	68	35	7	0%	1.2	27.9%	14.3%	13.5%	2.9%	3.99	4.12	—
2024	24	AA MLE	Tulsa Drillers	42	2	55	233	60	32	5	5%	1.3	20.9%	15.1%	5.8%	2.4%	3.62	4.58	—
2024	24	AA MLE	Tulsa Drillers	42	2	55	233	60	32	5	5%	1.3	20.9%	15.1%	5.8%	2.4%	3.62	4.58	—
2024	24	AA RAW	Tulsa Drillers	42	2	55	233	60	32	5	5%	1.3	25.8%	13.7%	12.0%	2.1%	3.62	3.85	—
2025	25	MIX MLE	2 levels	40	0	48	200	56	15	4	0%	1.2	23.1%	7.4%	15.7%	2.1%	3.54	3.24	—
2025	25	MIX MLE	2 levels	40	0	48	200	56	15	4	0%	1.2	23.1%	7.4%	15.7%	2.1%	3.54	3.24	—
2025	25	MIX RAW	2 levels	40	0	48	200	56	15	4	0%	1.2	28.0%	7.5%	20.5%	2.0%	3.54	2.79	—
2026	26	MIX MLE	2 levels	24	0	26	119	23	17	0	0%	1.1	16.4%	12.9%	3.5%	0.0%	4.91	3.35	—
2026	26	MIX MLE	2 levels	24	0	26	119	23	17	0	0%	1.1	16.4%	12.9%	3.5%	0.0%	4.91	3.35	—
2026	26	MIX RAW	2 levels	24	0	26	119	23	17	0	0%	1.1	19.3%	14.3%	5.0%	0.0%	4.91	3.29	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	LAD	1	0	1	4	1	0	0	0%	1.0	20.9%	9.6%	11.3%	2.6%	4.37	4.37	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	LAD	45	0	47	200	42	19	6	0%	1.1	21.0%	9.7%	11.3%	2.8%	4.41	4.45	+0.1
2029	29	MLB MLE	LAD	39	0	41	171	36	17	5	0%	1.0	21.0%	9.9%	11.1%	2.9%	4.50	4.57	-0.0
2028	28	MLB CTX	LAD	17	0	18	76	16	7	2	0%	1.1	21.0%	9.7%	11.3%	2.8%	4.41	4.45	+0.0
2029	29	MLB CTX	LAD	22	0	23	97	20	10	3	0%	1.0	21.0%	9.9%	11.1%	2.9%	4.50	4.57	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		38	0	40	170	36	17	5	0%	1.1	21.0%	9.8%	11.2%	2.8%	4.46	4.13	+0.2
/ 200 IP	—	RAW		190	0	200	844	178	84	25	0%	1.1	21.0%	9.8%	11.2%	2.8%	4.46	4.13	+1.0
Career	—	MLE		193	2	235	1026	228	147	20	1%	1.2	22.2%	14.3%	7.9%	2.0%	4.02	4.13	+0.0
/ 200 IP	—	MLE		164	2	200	873	194	125	17	1%	1.2	22.2%	14.3%	7.9%	2.0%	4.02	4.13	+0.1

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.

2026 AATulsa Drillers · 22 IPFIP 2.88 → 3.35 (+0.47)K% 20.2% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.21%	—	×0.810	16.37%
BB% (unintentional) /BF	11.70%	—	×1.100	12.87%
HR / BF /BF	0.00%	÷1.000	×1.200	0.00%

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 100).

Result: FIP 2.88 → 3.35, 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).

2026 AAAOklahoma City Comets · 4 IPFIP 4.79 → 4.67 (−0.11)K% 16.0% → 13.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.00%	—	×0.860	13.76%
BB% (unintentional) /BF	24.00%	—	×0.900	21.60%
HR / BF /BF	0.00%	÷1.000	×1.100	0.00%

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 100).

Result: FIP 4.79 → 4.67, 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).

2025 AATulsa Drillers · 44 IPFIP 2.46 → 3.24 (+0.78)K% 28.5% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.49%	—	×0.810	23.08%
BB% (unintentional) /BF	6.70%	—	×1.100	7.37%
HR / BF /BF	1.68%	÷0.957	×1.200	2.10%

Result: FIP 2.46 → 3.24, 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).

2025 AAAOklahoma City Comets · 4 IPFIP 5.51 → 6.01 (+0.49)K% 23.8% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.81%	—	×0.860	20.48%
BB% (unintentional) /BF	14.29%	—	×0.900	12.86%
HR / BF /BF	4.76%	÷0.956	×1.100	5.48%

Result: FIP 5.51 → 6.01, 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).

2024 AATulsa Drillers · 55 IPFIP 3.84 → 4.58 (+0.74)K% 25.8% → 20.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.75%	—	×0.810	20.86%
BB% (unintentional) /BF	13.73%	—	×1.100	15.11%
HR / BF /BF	2.15%	÷1.063	×1.200	2.42%

Result: FIP 3.84 → 4.58, 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).

2023 AATulsa Drillers · 41 IPFIP 4.57 → 5.35 (+0.77)K% 25.0% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.810	20.25%
BB% (unintentional) /BF	15.70%	—	×1.100	17.27%
HR / BF /BF	2.91%	÷1.083	×1.200	3.22%

Result: FIP 4.57 → 5.35, 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).

2023 A+Great Lakes Loons · 18 IPFIP 3.10 → 4.46 (+1.36)K% 34.7% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.72%	—	×0.770	26.74%
BB% (unintentional) /BF	11.11%	—	×1.150	12.78%
HR / BF /BF	2.78%	÷0.951	×1.250	3.65%

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 90).

Result: FIP 3.10 → 4.46, 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 A+Great Lakes Loons · 44 IPFIP 3.26 → 4.28 (+1.02)K% 29.6% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.58%	—	×0.770	22.77%
BB% (unintentional) /BF	16.90%	—	×1.150	19.44%
HR / BF /BF	0.94%	÷1.013	×1.250	1.16%

Result: FIP 3.26 → 4.28, 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
Antonio Knowles (OGILVIE)	—	—	4.37	20.9%	9.6%	2.6%	—	4.51	21.0%	11.2%	88	+0.14	—	—	—
Ricky Stone R 2002 · 4.16 FIP	27	SU	4.16	18.8%	9.3%	2.7%	.297	4.96	13.7%	7.4%	165	+0.80	4.16	243	91
Cody Satterwhite R 2015 · 3.71 FIP	28	SU	3.71	20.2%	9.8%	1.9%	.333	4.04	17.7%	10.2%	75	+0.33	3.69	147	90
Tyler Walker R 2004 · 4.28 FIP	28	SU	4.28	17.5%	8.4%	2.9%	.311	3.77	18.5%	10.4%	101	-0.51	2.38	289	89
Fernando Rodriguez Jr. R 2011 · 3.85 FIP	27	SU	3.85	24.7%	10.8%	2.7%	.315	3.90	25.2%	16.5%	70	+0.05	3.34	335	89
C.C. Lee R 2014 · 3.77 FIP	27	SU	3.77	20.5%	8.7%	2.4%	.310	2.80	25.7%	17.6%	96	-0.97	2.59	149	88
Ryan Kelly R 2015 · 3.52 FIP	27	SU	3.52	20.3%	7.5%	2.1%	.241	3.21	20.8%	14.2%	43	-0.31	2.49	131	87
Austin Ross R 2016 · 3.81 FIP	27	SU	3.81	22.9%	8.0%	3.0%	.295	3.67	12.4%	5.2%	127	-0.14	3.16	269	87
Aquilino López R 2003 · 3.42 FIP	28	SU	3.42	20.3%	9.2%	1.6%	.243	4.81	21.2%	11.7%	38	+1.39	3.10	207	87
Jason Frasor R 2005 · 3.90 FIP	27	SU	3.90	20.3%	8.5%	2.6%	.282	3.66	22.9%	13.0%	154	-0.24	2.71	647	87
Cole Sulser R 2017 · 3.52 FIP	27	SU	3.52	22.6%	10.2%	1.9%	.321	2.85	28.2%	18.4%	140	-0.67	2.38	554	87
Jose Veras R 2008 · 3.67 FIP	27	SU	3.67	24.9%	9.1%	2.8%	.281	4.10	23.8%	11.7%	169	+0.43	3.37	422	87
Jason Motte R 2009 · 4.62 FIP	27	SU	4.62	22.1%	9.0%	4.1%	.297	2.84	26.9%	21.0%	192	-1.78	2.22	387	86
Matt Ramsey R 2017 · 3.25 FIP	27	SU	3.25	24.2%	9.6%	1.8%	.330	3.21	23.6%	14.6%	81	-0.04	2.42	125	86
Josh Lueke R 2011 · 3.24 FIP	26	SU	3.24	20.4%	8.5%	1.4%	.323	4.75	18.7%	12.4%	52	+1.51	2.29	191	86
Taylor Williams R 2018 · 3.52 FIP	27	SU	3.52	24.2%	8.9%	2.4%	.309	4.35	22.5%	12.7%	108	+0.83	2.51	309	86
Francisco Rodriguez R 2010 · 4.33 FIP	27	SU	4.33	17.2%	11.0%	2.4%	.283	5.00	11.9%	3.4%	14	+0.67	3.16	334	86
Santiago Casilla R 2007 · 3.58 FIP	27	SU	3.58	23.7%	7.8%	2.7%	.257	3.60	19.8%	10.7%	154	+0.02	2.76	647	86
J.J. Putz R 2004 · 4.57 FIP	27	SU	4.57	17.1%	7.3%	3.6%	.283	2.58	28.5%	23.0%	210	-1.99	1.43	563	86
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	85
Tom Wilhelmsen R 2011 · 3.28 FIP	27	SU	3.28	22.1%	9.6%	1.5%	.253	3.18	22.9%	13.4%	218	-0.10	2.72	398	85

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 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	0.7	49	21.0%	9.7%	1.06	4.42
Kevin Quackenbush ('21)	1.0	52	21.0%	9.2%	1.04	4.41
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Juan Gutierrez ('14)	1.4	57	19.4%	8.4%	1.04	4.49
Gary Wayne ('89-'94, 2 WAR*)	1.2	62	19.9%*	9.4%*	1.05*	3.88*