Anderson Bido

P Corpus Christi Hooks

Age 28 RHP 6'3" / 205 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	24	A+COL	35	0	53	5.60	3.76	22.1%	4.8%	—	K 17.0% · BB 5.5% · FIP 4.63
2024	25	MIX2 levels	25	1	38	3.29	2.32	24.0%	3.9%	—	K 19.2% · BB 4.4% · FIP 2.90
2025	26	MIX2 levels	42	1	68	4.87	5.84	13.0%	12.0%	—	K 10.8% · BB 13.2% · FIP 6.36
2026	27	No MLB games played
2027PROJ	28	MLBHOU	1	0	1	6.14	6.14	10.9%	14.3%	-0.0
2028PROJ31% MLB	29	MLBHOU	14	0	15	6.03	6.09	11.9%	14.0%	-0.2
2029PROJ51% MLB	30	MLBHOU	19	0	20	6.03	6.13	12.4%	14.0%	-0.3

Next 3 projected WAR -0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff30Control40Command25

CompsKevin Gryboski (age 28) · Fernando Villalobos (age 30) · Oscar Verdugo (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 150142vR 134

ERA6.14

FIP6.14

K%10.9%

BB%14.3%

K-BB%-3.4%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Grades · Contract

Scouting Grades

STUF3030

CTRL4040

CMD2525

K†3030

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)
2017	18	ROK MLE	DSL Rockies	10	10	41	172	39	9	2	100%	4.1	15.4%	6.5%	8.9%	1.6%	2.85	3.52	—
2017	18	ROK RAW	DSL Rockies	10	10	41	172	39	9	2	100%	4.1	22.7%	5.2%	17.4%	1.2%	2.85	2.49	—
2018	19	ROK MLE	DSL Colorado	2	2	10	41	10	2	0	100%	5.2	24.4%	4.9%	19.5%	0.0%	3.48	1.66	—
2018	19	ROK RAW	DSL Colorado	2	2	10	41	10	2	0	100%	5.2	24.4%	4.9%	19.5%	0.0%	3.48	1.75	—
2021	22	A MLE	Fresno Grizzlies	34	0	48	209	32	23	5	0%	1.4	11.3%	13.0%	-1.7%	2.6%	3.97	5.19	—
2021	22	A RAW	Fresno Grizzlies	34	0	48	209	32	23	5	0%	1.4	15.3%	11.0%	4.3%	2.4%	3.97	4.57	—
2022	23	A+ MLE	Spokane Indians	38	0	46	198	49	12	6	0%	1.2	19.1%	7.0%	12.1%	2.9%	4.50	3.95	—
2022	23	A+ RAW	Spokane Indians	38	0	46	198	49	12	6	0%	1.2	24.7%	6.1%	18.7%	3.0%	4.50	3.45	—
2023	24	A+ MLE	Spokane Indians	35	0	53	231	51	11	8	0%	1.5	17.0%	5.5%	11.5%	4.1%	5.60	4.63	—
2023	24	A+ RAW	Spokane Indians	35	0	53	231	51	11	8	0%	1.5	22.1%	4.8%	17.3%	3.5%	5.60	3.76	—
2024	25	MIX MLE	2 levels	25	1	38	154	37	6	2	4%	1.5	19.2%	4.4%	14.9%	1.6%	3.29	2.90	—
2024	25	MIX MLE	2 levels	25	1	38	154	37	6	2	4%	1.5	19.2%	4.4%	14.9%	1.6%	3.29	2.90	—
2024	25	MIX RAW	2 levels	25	1	38	154	37	6	2	4%	1.5	24.0%	3.9%	20.1%	1.3%	3.29	2.32	—
2025	26	MIX MLE	2 levels	42	1	68	308	40	37	12	2%	1.6	10.8%	13.2%	-2.4%	4.6%	4.87	6.36	—
2025	26	MIX MLE	2 levels	42	1	68	308	40	37	12	2%	1.6	10.8%	13.2%	-2.4%	4.6%	4.87	6.36	—
2025	26	MIX RAW	2 levels	42	1	68	308	40	37	12	2%	1.6	13.0%	12.0%	1.0%	3.9%	4.87	5.84	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	HOU	1	0	1	4	0	1	0	0%	1.0	10.9%	14.3%	-3.4%	3.2%	6.14	6.14	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	HOU	46	0	48	203	24	28	7	0%	1.0	11.9%	14.0%	-2.1%	3.3%	6.03	6.09	-0.8
2029	30	MLB MLE	HOU	37	0	39	164	20	23	6	0%	1.0	12.4%	14.0%	-1.6%	3.5%	6.03	6.13	-0.7
2028	29	MLB CTX	HOU	14	0	15	63	8	9	2	0%	1.1	11.9%	14.0%	-2.1%	3.3%	6.03	6.09	-0.2
2029	30	MLB CTX	HOU	19	0	20	84	10	12	3	0%	1.1	12.4%	14.0%	-1.6%	3.5%	6.03	6.13	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		33	0	35	148	18	21	5	0%	1.1	12.2%	14.0%	-1.8%	3.4%	6.03	5.73	-0.5
/ 200 IP	—	RAW		190	0	200	844	103	120	29	0%	1.1	12.2%	14.0%	-1.8%	3.4%	6.03	5.73	-2.8
Career	—	MLE		186	14	305	1313	200	114	40	8%	1.6	15.2%	8.7%	6.5%	3.0%	4.28	4.58	-1.6
/ 200 IP	—	MLE		122	9	200	862	131	75	26	8%	1.6	15.2%	8.7%	6.5%	3.0%	4.28	4.58	-3.6

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 AACorpus Christi Hooks · 66 IPFIP 5.70 → 6.36 (+0.67)K% 13.4% → 10.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.38%	—	×0.810	10.84%
BB% (unintentional) /BF	12.04%	—	×1.100	13.24%
HR / BF /BF	4.01%	÷1.057	×1.200	4.56%

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 111).

Result: FIP 5.70 → 6.36, 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 AAHartford Yard Goats · 22 IPFIP 1.63 → 2.38 (+0.75)K% 31.5% → 25.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.46%	—	×0.810	25.48%
BB% (unintentional) /BF	4.49%	—	×1.100	4.94%
HR / BF /BF	1.12%	÷0.916	×1.200	1.47%

Result: FIP 1.63 → 2.38, 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+Spokane Indians · 16 IPFIP 3.16 → 3.62 (+0.45)K% 13.8% → 10.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.85%	—	×0.770	10.66%
BB% (unintentional) /BF	3.08%	—	×1.150	3.54%
HR / BF /BF	1.54%	÷1.086	×1.250	1.77%

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 117).

Result: FIP 3.16 → 3.62, 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+Spokane Indians · 53 IPFIP 3.74 → 4.63 (+0.89)K% 22.1% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.08%	—	×0.770	17.00%
BB% (unintentional) /BF	4.76%	—	×1.150	5.48%
HR / BF /BF	3.46%	÷1.047	×1.250	4.14%

Result: FIP 3.74 → 4.63, 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+Spokane Indians · 46 IPFIP 3.44 → 3.95 (+0.51)K% 24.7% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.75%	—	×0.770	19.06%
BB% (unintentional) /BF	6.06%	—	×1.150	6.97%
HR / BF /BF	3.03%	÷1.316	×1.250	2.88%

Result: FIP 3.44 → 3.95, 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 AFresno Grizzlies · 48 IPFIP 4.51 → 5.19 (+0.68)K% 15.3% → 11.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.31%	—	×0.740	11.33%
BB% (unintentional) /BF	11.00%	—	×1.180	12.99%
HR / BF /BF	2.39%	÷1.218	×1.300	2.55%

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 144).

Result: FIP 4.51 → 5.19, 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).

2018 ROKDSL Colorado · 10 IPFIP 1.66 → 2.47 (+0.81)K% 24.4% → 16.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.39%	—	×0.680	16.59%
BB% (unintentional) /BF	4.88%	—	×1.250	6.10%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

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 100).

Result: FIP 1.66 → 2.47, 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).

2017 ROKDSL Rockies · 41 IPFIP 2.49 → 3.52 (+1.03)K% 22.7% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.67%	—	×0.680	15.42%
BB% (unintentional) /BF	5.23%	—	×1.250	6.54%
HR / BF /BF	1.16%	÷1.000	×1.400	1.63%

Result: FIP 2.49 → 3.52, 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
Anderson Bido (OGILVIE)	—	—	6.14	10.9%	14.3%	3.2%	—	6.11	12.1%	-1.9%	87	-0.03	—	—	—
Kevin Gryboski R 2002 · 5.02 FIP	28	SU	5.02	13.9%	13.4%	2.5%	.263	3.83	12.0%	2.9%	126	-1.19	3.67	178	83
Fernando Villalobos R 2015 · 5.33 FIP	30	SU	5.33	8.3%	13.1%	2.3%	.365	4.36	11.4%	3.1%	109	-0.97	4.00	152	82
Oscar Verdugo R 2017 · 6.31 FIP	27	SU	6.31	10.3%	13.8%	4.2%	.277	—	—	—	—	—	5.01	144	80
Mike Hepple R 2016 · 5.75 FIP	26	SU	5.75	11.1%	18.5%	2.3%	.271	—	—	—	—	—	4.46	116	80
Beck Wheeler R 2017 · 5.40 FIP	28	SU	5.40	15.3%	12.2%	3.7%	.347	—	—	—	—	—	3.46	173	79
Trey Haley R 2016 · 4.98 FIP	26	SU	4.98	14.0%	16.5%	1.8%	.282	—	—	—	—	—	3.14	111	78
Alex Caldera R 2015 · 5.57 FIP	29	SW	5.57	10.4%	13.1%	3.1%	.333	4.54	11.9%	0.8%	84	-1.03	4.54	120	78
Kevin Kopps R 2024 · 5.03 FIP	27	SU	5.03	11.6%	14.0%	2.1%	.308	4.97	15.7%	3.2%	61	-0.06	3.45	237	77
Grant Black R 2022 · 5.20 FIP	28	SU	5.20	14.0%	11.0%	3.5%	.250	5.49	15.9%	4.6%	79	+0.29	4.46	215	77
David Goforth R 2017 · 5.09 FIP	28	SU	5.09	13.6%	10.2%	3.4%	.282	4.07	14.1%	5.5%	68	-1.02	3.98	256	77
Roman Phansalkar R 2024 · 5.39 FIP	26	SU	5.39	15.8%	13.2%	3.6%	.294	4.33	18.2%	3.7%	31	-1.06	4.33	164	76
Tyler Mizenko R 2016 · 5.15 FIP	26	SU	5.15	13.3%	10.2%	3.5%	.303	—	—	—	—	—	3.66	104	76
Chris Jefferson R 2024 · 5.65 FIP	27	SU	5.65	16.4%	13.6%	4.0%	.308	—	—	—	—	—	3.53	140	75
Carlos Frías R 2017 · 6.07 FIP	27	SU	6.07	10.4%	13.0%	4.0%	.299	4.42	16.9%	5.8%	31	-1.65	3.40	236	75
Jake Haberer R 2023 · 5.10 FIP	28	SU	5.10	16.4%	14.7%	2.8%	.262	5.03	16.2%	-1.4%	15	-0.07	3.46	183	75
Jesus Barraza R 2019 · 5.96 FIP	28	SU	5.96	8.7%	13.5%	3.4%	.328	—	—	—	—	—	3.24	164	74
Tony Fiore R 2000 · 5.61 FIP	28	SU	5.61	10.8%	9.5%	4.0%	.321	4.76	14.3%	3.5%	127	-0.85	4.60	142	74
Matt Eckelman R 2022 · 5.72 FIP	28	SU	5.72	12.4%	13.2%	3.6%	.289	6.65	6.6%	-15.4%	27	+0.93	4.07	386	74
Thad Weber R 2013 · 5.18 FIP	28	SU	5.18	16.4%	13.1%	3.3%	.244	4.52	12.2%	6.0%	308	-0.66	4.40	378	73
Brandon Puffer R 2004 · 5.23 FIP	28	SU	5.23	13.5%	11.2%	3.4%	.328	—	—	—	—	—	3.55	108	73

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	52	11.6%	14.1%	1.29	6.08
Matt Perisho ('05)	1.4	69	15.2%	12.2%	1.37	6.39
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Mike Mohler ('01)	2.1	60	15.0%	12.4%	0.97	4.99
Darrel Akerfelds ('86-'91, -3 WAR*)	1.2	78	15.8%*	11.9%*	1.61*	5.40*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*