Blane Abeyta

P Columbus Clingstones

Age 28 RHP 6'3" / 220 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	27	20	111	4.95	4.39	17.6%	4.6%	—	K 14.0% · BB 5.1% · FIP 5.10
2025	26	AAATL	43	0	51	2.29	3.14	32.9%	9.7%	—	K 26.6% · BB 10.6% · FIP 4.24
2026	27	AAATL	42	0	49	5.55	6.22	25.1%	12.3%	—	K 20.3% · BB 13.6% · FIP 7.16
2027PROJ	28	MLBATL	3	0	3	5.13	5.13	23.4%	10.2%	-0.0
2028PROJ23% MLB	29	MLBATL	26	0	27	5.12	5.17	23.0%	10.1%	-0.2
2029PROJ39% MLB	30	MLBATL	37	0	39	5.19	5.28	22.6%	10.2%	-0.3

Next 3 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.0 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsJose Pina (age 29) · Asher Wojciechowski (age 28) · Seth Simmons (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 131122vR 114

ERA5.13

FIP5.13

K%23.4%

BB%10.2%

K-BB%13.2%

Proj IP147

Value2027 · WAR

Runs saved vs league avg · 147 IP

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	22	MIX MLE	2 levels	17	10	55	249	71	35	4	59%	3.3	21.1%	18.2%	2.9%	1.9%	5.37	4.66	—
2021	22	MIX RAW	2 levels	17	10	55	249	71	35	4	59%	3.3	28.5%	14.1%	14.5%	1.6%	5.37	3.37	—
2022	23	A+ MLE	Hudson Valley Renegades	23	20	105	472	88	52	6	87%	4.6	14.4%	12.7%	1.7%	1.6%	4.47	4.35	—
2022	23	A+ RAW	Hudson Valley Renegades	23	20	105	472	88	52	6	87%	4.6	18.6%	11.0%	7.6%	1.3%	4.47	3.65	—
2023	24	AA MLE	Somerset Patriots	25	23	127	565	126	51	18	92%	5.1	18.1%	9.9%	8.1%	3.7%	5.67	4.86	—
2023	24	AA RAW	Somerset Patriots	25	23	127	565	126	51	18	92%	5.1	22.3%	9.0%	13.3%	3.2%	5.67	4.16	—
2024	25	MIX MLE	2 levels	27	20	111	483	85	22	19	74%	4.1	14.0%	5.1%	8.9%	4.6%	4.95	5.10	—
2024	25	MIX MLE	2 levels	27	20	111	483	85	22	19	74%	4.1	14.0%	5.1%	8.9%	4.6%	4.95	5.10	—
2024	25	MIX RAW	2 levels	27	20	111	483	85	22	19	74%	4.1	17.6%	4.6%	13.0%	3.9%	4.95	4.39	—
2025	26	AA MLE	Columbus Clingstones	43	0	51	207	68	20	6	0%	1.2	26.6%	10.6%	16.0%	3.7%	2.29	4.24	—
2025	26	AA MLE	Columbus Clingstones	43	0	51	207	68	20	6	0%	1.2	26.6%	10.6%	16.0%	3.7%	2.29	4.24	—
2025	26	AA RAW	Columbus Clingstones	43	0	51	207	68	20	6	0%	1.2	32.9%	9.7%	23.2%	2.9%	2.29	3.14	—
2026	27	AA MLE	Columbus Clingstones	42	0	49	227	57	28	14	0%	1.2	20.3%	13.6%	6.8%	7.4%	5.55	7.16	—
2026	27	AA MLE	Columbus Clingstones	42	0	49	227	57	28	14	0%	1.2	20.3%	13.6%	6.8%	7.4%	5.55	7.16	—
2026	27	AA RAW	Columbus Clingstones	42	0	49	227	57	28	14	0%	1.2	25.1%	12.3%	12.8%	6.2%	5.55	6.22	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	ATL	3	0	3	13	3	1	1	0%	1.0	23.4%	10.2%	13.2%	4.3%	5.13	5.13	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	ATL	111	0	117	493	113	50	21	0%	1.1	23.0%	10.1%	12.9%	4.3%	5.12	5.17	-0.8
2029	30	MLB MLE	ATL	95	0	99	419	95	43	18	0%	1.0	22.6%	10.2%	12.3%	4.4%	5.19	5.28	-0.8
2028	29	MLB CTX	ATL	26	0	27	114	26	12	5	0%	1.0	23.0%	10.1%	12.9%	4.3%	5.12	5.17	-0.2
2029	30	MLB CTX	ATL	37	0	39	165	37	17	7	0%	1.1	22.6%	10.2%	12.3%	4.4%	5.19	5.28	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		62	0	65	276	63	28	12	0%	1.1	22.8%	10.2%	12.6%	4.3%	5.16	4.86	-0.2
/ 200 IP	—	RAW		190	0	200	844	193	86	37	0%	1.1	22.8%	10.2%	12.6%	4.3%	5.16	4.86	-0.7
Career	—	MLE		177	73	498	2203	391	239	80	41%	2.8	17.8%	10.8%	6.9%	3.6%	4.86	4.96	-1.7
/ 200 IP	—	MLE		71	29	200	885	157	96	32	41%	2.8	17.8%	10.8%	6.9%	3.6%	4.86	4.96	-1.5

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 AAColumbus Clingstones · 49 IPFIP 5.93 → 7.16 (+1.24)K% 25.1% → 20.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.11%	—	×0.810	20.34%
BB% (unintentional) /BF	12.33%	—	×1.100	13.57%
HR / BF /BF	6.17%	÷1.000	×1.200	7.40%

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 5.93 → 7.16, 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 AAColumbus Clingstones · 51 IPFIP 3.14 → 4.24 (+1.10)K% 32.9% → 26.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.85%	—	×0.810	26.61%
BB% (unintentional) /BF	9.66%	—	×1.100	10.63%
HR / BF /BF	2.90%	÷0.934	×1.200	3.72%

Result: FIP 3.14 → 4.24, 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).

2024 AASomerset Patriots · 67 IPFIP 5.25 → 6.09 (+0.84)K% 17.6% → 14.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.61%	—	×0.810	14.26%
BB% (unintentional) /BF	5.65%	—	×1.100	6.21%
HR / BF /BF	5.32%	÷1.027	×1.200	6.21%

Result: FIP 5.25 → 6.09, 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 A+Hudson Valley Renegades · 44 IPFIP 2.87 → 3.45 (+0.58)K% 17.6% → 13.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.58%	—	×0.770	13.54%
BB% (unintentional) /BF	2.75%	—	×1.150	3.16%
HR / BF /BF	1.65%	÷1.032	×1.250	2.00%

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 106).

Result: FIP 2.87 → 3.45, 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 AASomerset Patriots · 127 IPFIP 4.11 → 4.86 (+0.76)K% 22.3% → 18.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.30%	—	×0.810	18.06%
BB% (unintentional) /BF	9.03%	—	×1.100	9.93%
HR / BF /BF	3.19%	÷1.033	×1.200	3.70%

Result: FIP 4.11 → 4.86, 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+Hudson Valley Renegades · 105 IPFIP 3.62 → 4.35 (+0.73)K% 18.6% → 14.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.64%	—	×0.770	14.36%
BB% (unintentional) /BF	11.02%	—	×1.150	12.67%
HR / BF /BF	1.27%	÷1.014	×1.250	1.57%

Result: FIP 3.62 → 4.35, 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).

2021 ATampa Tarpons · 46 IPFIP 3.45 → 4.66 (+1.22)K% 28.5% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.50%	—	×0.740	21.09%
BB% (unintentional) /BF	15.46%	—	×1.180	18.24%
HR / BF /BF	1.45%	÷1.000	×1.300	1.88%

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 100).

Result: FIP 3.45 → 4.66, 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 ROKFCL Yankees · 9 IPFIP 2.90 → 4.44 (+1.54)K% 28.6% → 19.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.57%	—	×0.680	19.43%
BB% (unintentional) /BF	7.14%	—	×1.250	8.93%
HR / BF /BF	2.38%	÷0.989	×1.400	3.37%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 98).

Result: FIP 2.90 → 4.44, 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
Blane Abeyta (OGILVIE)	—	—	—	—	—	4.3%	—	5.22	22.8%	12.6%	216	+0.09	—	—	—
Jose Pina R 2015 · 4.90 FIP	29	SW	4.90	16.9%	9.2%	3.8%	.231	3.66	13.6%	6.9%	246	-1.24	3.63	424	76
Asher Wojciechowski R 2017 · 3.99 FIP	28	SW	3.99	23.4%	6.5%	3.7%	.299	5.06	21.5%	13.1%	323	+1.07	3.15	678	69
Seth Simmons R 2016 · 4.27 FIP	28	SW	4.27	18.1%	8.1%	3.0%	.262	6.20	13.3%	2.4%	54	+1.93	3.07	251	67
Josh A. Smith R 2016 · 4.68 FIP	28	SW	4.68	18.3%	8.7%	3.7%	.280	3.84	20.9%	14.5%	259	-0.84	2.91	598	66
Emmanuel Chapman R 2024 · 4.08 FIP	25	SW	4.08	19.7%	10.6%	2.4%	.256	4.52	17.8%	1.3%	117	+0.44	3.81	198	66
Lisalverto Bonilla R 2017 · 4.61 FIP	27	SW	4.61	18.2%	10.5%	3.1%	.304	4.70	15.8%	3.2%	11	+0.09	3.22	242	65
Jesse Scholtens R 2022 · 4.18 FIP	28	SW	4.18	22.4%	8.4%	3.5%	.303	4.35	18.8%	11.9%	193	+0.17	3.34	883	65
Jim Brower R 2001 · 4.60 FIP	28	SW	4.60	16.8%	9.8%	3.0%	.260	3.85	16.0%	7.3%	273	-0.75	3.67	571	65
Drew VerHagen R 2019 · 4.11 FIP	28	SW	4.11	19.5%	7.3%	3.2%	.344	6.00	17.0%	4.7%	22	+1.89	2.80	487	64
Josh Roeder R 2019 · 4.71 FIP	26	SW	4.71	15.1%	8.7%	3.3%	.264	—	—	—	—	—	4.71	175	63
Riley Thompson R 2024 · 4.48 FIP	28	SW	4.48	17.6%	8.9%	3.2%	.340	—	—	—	—	—	4.48	340	62
Todd Wellemeyer R 2007 · 4.74 FIP	28	SW	4.74	17.0%	10.8%	3.1%	.270	4.86	15.5%	6.4%	373	+0.12	3.35	615	62
Luke Farrell R 2018 · 4.25 FIP	27	SW	4.25	24.9%	11.7%	3.2%	.269	4.62	22.1%	10.6%	25	+0.37	3.69	584	61
Hisashi Iwakuma R 2012 · 4.28 FIP	31	SP-	4.28	19.5%	7.7%	3.4%	.277	3.45	21.5%	17.8%	528	-0.83	3.19	884	61
Luis Santos R 2019 · 4.31 FIP	28	SU	4.31	22.9%	10.0%	3.4%	.312	—	—	—	—	—	3.53	472	61
Joel De La Cruz R 2016 · 4.61 FIP	27	SW	4.61	14.4%	8.6%	3.0%	.291	—	—	—	—	—	4.19	205	61
Kaleb Roper R 2022 · 5.67 FIP	26	SW	5.67	17.3%	11.8%	4.6%	.398	—	—	—	—	—	5.67	146	61
Cory Lidle R 2000 · 4.32 FIP	28	SW	4.32	14.6%	6.1%	3.1%	.313	4.06	14.2%	8.7%	573	-0.26	3.48	1,318	61
Adrian Sampson R 2019 · 5.09 FIP	27	SW	5.09	17.9%	6.2%	5.0%	.319	4.95	16.1%	9.0%	250	-0.14	3.23	1,012	61
Casey Sadler R 2018 · 3.95 FIP	28	SW	3.95	16.0%	7.8%	2.2%	.298	3.35	23.2%	16.5%	145	-0.60	2.21	385	61

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	1.8	121	23.0%	10.2%	1.67	5.14
Matt Beech ('98)	1.5	98	20.2%	10.0%	1.59	5.37
Kevin Foster ('01)	2.5	127	18.9%	10.0%	1.55	4.86
Jack Armstrong ('88-'94, 2 WAR*)	3.9	131	19.2%*	9.2%*	1.59*	4.89*
Dan Straily ('19)	4.0	115	19.8%	9.1%	1.60	4.56
Joe Cowley ('82-'87, 3 WAR*)	2.3	117	22.7%*	11.2%*	1.55*	4.37*
Chris Knapp ('75-'80, -1 WAR*)	3.0	121	21.3%*	9.3%*	1.41*	5.48*