Andrew Bash

P Las Vegas Aviators

Age 30 RHP 6'0" / 190 lbs AAA

Overview

AAAPROSPECT

ETA2029MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	28	16	80	2.91	3.14	23.0%	10.4%	—	K 18.8% · BB 9.5% · FIP 3.46
2025	28	AAATOR	40	5	84	2.57	3.29	19.7%	9.9%	—	K 17.0% · BB 8.9% · FIP 3.57
2026	29	AAAOAK	35	7	68	5.66	5.25	18.8%	11.6%	—	K 16.2% · BB 10.5% · FIP 5.22
2027PROJ	30	MLBOAK	7	0	7	5.07	5.07	15.6%	10.3%	-0.0
2028PROJ37% MLB	31	MLBOAK	17	0	18	5.12	5.20	16.0%	10.5%	-0.1
2029PROJ55% MLB	32	MLBOAK	20	0	21	5.24	5.36	16.1%	10.8%	-0.2

Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control50Command45

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

CompsRodolfo Aguirre (age 30) · Felipe Arredondo (age 30) · Willie Eyre (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 129121vR 113

ERA5.07

FIP5.07

K%15.6%

BB%10.3%

K-BB%5.4%

Proj IP68

Value2027 · WAR

Runs saved vs league avg · 68 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL5050

CMD4545

K†3040

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)
2019	22	ROK MLE	AZL Angels	14	0	16	68	18	5	1	0%	1.1	18.0%	9.2%	8.8%	2.1%	2.81	3.87	—
2019	22	ROK RAW	AZL Angels	14	0	16	68	18	5	1	0%	1.1	26.5%	7.4%	19.1%	1.5%	2.81	2.60	—
2021	24	MIX MLE	3 levels	16	4	56	242	50	21	6	25%	3.5	15.5%	10.4%	5.0%	3.6%	5.50	5.09	—
2021	24	MIX RAW	3 levels	16	4	56	242	50	21	6	25%	3.5	20.7%	8.7%	12.0%	2.5%	5.50	3.84	—
2022	25	MIX MLE	2 levels	34	5	96	405	72	37	4	15%	2.8	14.6%	9.9%	4.7%	1.1%	4.23	3.75	—
2022	25	MIX RAW	2 levels	34	5	96	405	72	37	4	15%	2.8	17.8%	9.1%	8.6%	1.0%	4.23	3.30	—
2023	26	MIX MLE	2 levels	36	11	89	372	80	47	8	31%	2.5	17.9%	12.7%	5.3%	2.6%	2.52	4.61	—
2023	26	MIX RAW	2 levels	36	11	89	372	80	47	8	31%	2.5	21.5%	12.6%	8.9%	2.2%	2.52	4.05	—
2024	27	MIX MLE	2 levels	28	16	80	335	77	35	4	57%	2.9	18.8%	9.5%	9.2%	1.3%	2.91	3.46	—
2024	27	MIX MLE	2 levels	28	16	80	335	77	35	4	57%	2.9	18.8%	9.5%	9.2%	1.3%	2.91	3.46	—
2024	27	MIX RAW	2 levels	28	16	80	335	77	35	4	57%	2.9	23.0%	10.4%	12.5%	1.2%	2.91	3.14	—
2025	28	AAA MLE	Buffalo Bisons	40	5	84	365	72	36	4	12%	2.1	17.0%	8.9%	8.1%	1.4%	2.57	3.57	—
2025	28	AAA MLE	Buffalo Bisons	40	5	84	365	72	36	4	12%	2.1	17.0%	8.9%	8.1%	1.4%	2.57	3.57	—
2025	28	AAA RAW	Buffalo Bisons	40	5	84	365	72	36	4	12%	2.1	19.7%	9.9%	9.9%	1.1%	2.57	3.29	—
2026	29	AAA MLE	Las Vegas Aviators	35	7	68	335	63	39	12	20%	2.0	16.2%	10.5%	5.7%	3.9%	5.66	5.22	—
2026	29	AAA MLE	Las Vegas Aviators	35	7	68	335	63	39	12	20%	2.0	16.2%	10.5%	5.7%	3.9%	5.66	5.22	—
2026	29	AAA RAW	Las Vegas Aviators	35	7	68	335	63	39	12	20%	2.0	18.8%	11.6%	7.2%	3.6%	5.66	5.25	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	OAK	7	0	7	30	5	3	1	0%	1.0	15.6%	10.3%	5.4%	2.9%	5.07	5.07	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	OAK	46	0	48	202	32	21	6	0%	1.0	16.0%	10.5%	5.5%	3.2%	5.12	5.20	-0.3
2029	32	MLB MLE	OAK	36	0	38	161	26	17	5	0%	1.1	16.1%	10.8%	5.3%	3.4%	5.24	5.36	-0.3
2028	31	MLB CTX	OAK	17	0	18	76	12	8	2	0%	1.1	16.0%	10.5%	5.5%	3.2%	5.12	5.20	-0.1
2029	32	MLB CTX	OAK	20	0	21	89	14	10	3	0%	1.1	16.1%	10.8%	5.3%	3.4%	5.24	5.36	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		37	0	39	163	26	17	5	0%	1.0	16.1%	10.7%	5.4%	3.3%	5.19	4.91	-0.2
/ 200 IP	—	RAW		190	0	200	844	135	88	26	0%	1.1	16.1%	10.7%	5.4%	3.3%	5.19	4.91	-0.8
Career	—	MLE		203	48	489	2122	355	218	47	24%	2.4	16.7%	10.3%	6.4%	2.2%	3.72	4.21	-0.7
/ 200 IP	—	MLE		83	20	200	867	145	89	19	24%	2.4	16.7%	10.3%	6.4%	2.2%	3.72	4.21	-1.7

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.

2026 AAALas Vegas Aviators · 68 IPFIP 4.95 → 5.22 (+0.27)K% 18.8% → 16.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.81%	—	×0.860	16.17%
BB% (unintentional) /BF	11.64%	—	×0.900	10.48%
HR / BF /BF	3.58%	÷1.000	×1.100	3.94%

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 4.95 → 5.22, 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).

2025 AAABuffalo Bisons · 84 IPFIP 3.29 → 3.57 (+0.29)K% 19.7% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.73%	—	×0.860	16.96%
BB% (unintentional) /BF	9.86%	—	×0.900	8.88%
HR / BF /BF	1.10%	÷0.847	×1.100	1.42%

Result: FIP 3.29 → 3.57, 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 AAABuffalo Bisons · 79 IPFIP 3.27 → 3.46 (+0.20)K% 21.8% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.82%	—	×0.860	18.76%
BB% (unintentional) /BF	10.61%	—	×0.900	9.55%
HR / BF /BF	1.21%	÷0.990	×1.100	1.35%

Result: FIP 3.27 → 3.46, 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).

2023 AAABuffalo Bisons · 49 IPFIP 4.68 → 5.11 (+0.43)K% 20.0% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.860	17.20%
BB% (unintentional) /BF	12.11%	—	×0.900	10.89%
HR / BF /BF	3.16%	÷0.916	×1.100	3.79%

Result: FIP 4.68 → 5.11, 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 AANew Hampshire Fisher Cats · 41 IPFIP 3.42 → 4.08 (+0.66)K% 23.1% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.810	18.69%
BB% (unintentional) /BF	13.19%	—	×1.100	14.51%
HR / BF /BF	1.10%	÷1.000	×1.200	1.32%

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 3.42 → 4.08, 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 AANew Hampshire Fisher Cats · 76 IPFIP 2.78 → 3.22 (+0.44)K% 18.6% → 15.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.61%	—	×0.810	15.08%
BB% (unintentional) /BF	8.52%	—	×1.100	9.37%
HR / BF /BF	0.32%	÷1.027	×1.200	0.37%

Result: FIP 2.78 → 3.22, 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).

2022 AAABuffalo Bisons · 20 IPFIP 5.16 → 5.68 (+0.51)K% 14.8% → 13.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.77%	—	×0.880	13.00%
BB% (unintentional) /BF	11.36%	—	×1.050	11.93%
HR / BF /BF	3.41%	÷0.951	×1.100	3.94%

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 5.16 → 5.68, 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 ADunedin Blue Jays · 28 IPFIP 3.33 → 4.19 (+0.87)K% 19.8% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.85%	—	×0.740	14.69%
BB% (unintentional) /BF	8.40%	—	×1.180	9.91%
HR / BF /BF	1.53%	÷1.010	×1.300	1.97%

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 102).

Result: FIP 3.33 → 4.19, 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
Andrew Bash (OGILVIE)	—	—	5.07	15.6%	10.3%	2.9%	—	5.27	16.1%	5.4%	86	+0.20	—	—	—
Rodolfo Aguirre R 2015 · 4.29 FIP	30	SW	4.29	12.4%	6.9%	2.5%	.288	4.81	11.4%	1.3%	125	+0.52	3.39	212	86
Felipe Arredondo R 2017 · 4.76 FIP	30	SW	4.76	14.8%	7.3%	3.6%	.311	4.65	16.2%	9.1%	64	-0.11	3.92	337	82
Willie Eyre R 2007 · 4.53 FIP	29	SU	4.53	13.7%	9.1%	2.6%	.306	2.87	11.1%	5.5%	18	-1.66	2.87	164	82
Eder Llamas R 2016 · 4.12 FIP	30	SW	4.12	11.4%	6.8%	2.0%	.301	3.23	11.3%	4.6%	64	-0.89	3.23	171	81
Chris Jakubauskas R 2009 · 4.97 FIP	30	SW	4.97	12.1%	6.2%	3.9%	.250	4.42	15.7%	7.8%	72	-0.55	4.42	165	80
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	80
Murphy Smith R 2018 · 4.57 FIP	30	SW	4.57	13.6%	9.3%	2.6%	.273	—	—	—	—	—	3.16	300	80
Marco Carrillo R 2017 · 5.33 FIP	30	SW	5.33	11.1%	7.4%	4.1%	.278	6.08	9.9%	0.8%	104	+0.75	5.33	194	79
Fredy Quintero R 2017 · 4.45 FIP	29	SW	4.45	14.0%	8.7%	2.6%	.335	4.62	17.2%	3.5%	43	+0.17	4.29	241	79
Grant Black R 2023 · 5.49 FIP	29	SU	5.49	15.9%	11.3%	4.2%	.352	—	—	—	—	—	4.46	215	78
Bradin Hagens R 2019 · 5.46 FIP	30	SW	5.46	13.2%	12.6%	3.4%	.303	—	—	—	—	—	3.79	254	75
Drew Hayes R 2016 · 3.99 FIP	28	SU	3.99	13.8%	10.1%	1.4%	.302	—	—	—	—	—	3.35	117	75
David Goforth R 2018 · 4.07 FIP	29	SU	4.07	14.1%	8.6%	2.0%	.272	—	—	—	—	—	3.98	256	75
Beck Wheeler R 2017 · 5.40 FIP	28	SU	5.40	15.3%	12.2%	3.7%	.347	—	—	—	—	—	3.46	173	73
Cody Satterwhite R 2017 · 4.22 FIP	30	SU	4.22	17.0%	7.1%	3.0%	.310	—	—	—	—	—	3.69	147	73
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	73
Alfonso Sanchez R 2017 · 4.51 FIP	29	SW	4.51	12.5%	9.8%	2.2%	.346	7.58	8.6%	1.4%	39	+3.07	4.51	224	72
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	72
Mike Broadway R 2017 · 4.73 FIP	30	SU	4.73	18.3%	10.2%	3.4%	.245	4.65	23.0%	12.4%	49	-0.08	1.74	195	72
Ivan Zavala R 2017 · 5.02 FIP	30	SU	5.02	12.8%	8.0%	3.6%	.286	5.15	12.7%	5.3%	61	+0.13	4.27	209	72

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	0.8	51	15.9%	10.5%	1.21	5.13
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Rodney Myers ('04)	1.2	60	15.0%	10.3%	1.05	5.07
Tom Martin ('07)	1.6	53	15.8%	10.1%	1.02	4.92
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*