Alex Faedo

P Salt Lake Bees

Age 31 RHP 6'6" / 225 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	28	MIX2 levels	40	7	60	3.58	4.67	22.4%	12.2%	-0.1	K 22.4% · BB 11.4% · FIP 4.75
2025	29	MIX2 levels	6	1	8	4.32	4.90	21.6%	16.2%	—	K 21.6% · BB 16.2% · FIP 4.81
2026	30	MIX2 levels	21	2	26	3.76	4.13	21.1%	10.5%	—	K 18.0% · BB 9.9% · FIP 3.50
2027PROJ	31	MLBLAA	1	1	6	4.48	4.71	21.2%	11.2%	0.0
2028PROJ37% MLB	32	MLBLAA	2	2	15	4.77	4.96	20.4%	11.6%	0.1
2029PROJ55% MLB	33	MLBLAA	3	3	18	5.05	5.24	19.5%	12.1%	0.0

Last 3 seasons WAR -0.1 · Next 3 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

K%51

FB Velo43

xwOBA vs37

CompsElian Leyva (age 30) · Robert Stock (age 31) · Edgar Alberto Garcia (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 120112vR 104

ERA4.48

FIP4.71

K%21.2%

BB%11.2%

K-BB%10.0%

Proj IP58

Value2027 · WAR

Runs saved vs league avg · 58 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL3535

CMD4040

K†5050

Statcast Percentiles

FB Velo

p4394.0

Whiff%

p8731.1%

p5122.4%

xwOBA vs

p370.327

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	22	MIX MLE	2 levels	24	24	121	500	110	35	18	100%	5.0	17.4%	7.8%	9.6%	3.8%	4.02	4.72	—
2018	22	MIX RAW	2 levels	24	24	121	500	110	35	18	100%	5.0	22.0%	7.0%	15.0%	3.6%	4.02	4.08	—
2019	23	AA MLE	Erie SeaWolves	22	22	115	473	134	25	17	100%	5.2	22.9%	5.8%	17.1%	3.3%	3.90	3.73	—
2019	23	AA RAW	Erie SeaWolves	22	22	115	473	134	25	17	100%	5.2	28.3%	5.3%	23.0%	3.6%	3.90	3.34	—
2022	26	MIX MLE	3 levels	16	14	69	304	64	28	7	88%	4.3	18.0%	10.2%	7.8%	3.0%	4.67	4.52	+0.7
2022	26	MIX RAW	3 levels	16	14	69	304	64	28	7	88%	4.3	21.1%	9.2%	11.8%	2.3%	4.67	3.78	+1.3
2023	27	MIX MLE	3 levels	23	20	96	387	96	27	17	87%	4.2	23.0%	7.0%	16.0%	4.8%	4.20	4.67	+0.8
2023	27	MIX RAW	3 levels	23	20	96	387	96	27	17	87%	4.2	24.8%	7.0%	17.8%	4.4%	4.20	4.24	+1.3
2024	28	MIX MLE	2 levels	40	7	60	263	59	32	9	18%	1.5	22.4%	11.4%	11.0%	3.8%	3.58	4.75	-0.1
2024	28	MIX MLE	2 levels	40	7	60	263	59	32	9	18%	1.5	22.4%	11.4%	11.0%	3.8%	3.58	4.75	-0.1
2024	28	MIX RAW	2 levels	40	7	60	263	59	32	9	18%	1.5	22.4%	12.2%	10.3%	3.4%	3.58	4.67	-0.1
2025	29	MIX MLE	2 levels	6	1	8	37	8	6	1	17%	1.4	21.6%	16.2%	5.4%	2.7%	4.32	4.81	—
2025	29	MIX MLE	2 levels	6	1	8	37	8	6	1	17%	1.4	21.6%	16.2%	5.4%	2.7%	4.32	4.81	—
2025	29	MIX RAW	2 levels	6	1	8	37	8	6	1	17%	1.4	21.6%	16.2%	5.4%	2.7%	4.32	4.90	—
2026	30	MIX MLE	2 levels	21	2	26	114	24	12	3	10%	1.3	18.0%	9.9%	8.1%	1.2%	3.76	3.50	—
2026	30	MIX MLE	2 levels	21	2	26	114	24	12	3	10%	1.3	18.0%	9.9%	8.1%	1.2%	3.76	3.50	—
2026	30	MIX RAW	2 levels	21	2	26	114	24	12	3	10%	1.3	21.1%	10.5%	10.5%	2.6%	3.76	4.13	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			64	30	176	752	157	73	28	47%	2.7	20.9%	9.7%	11.2%	3.7%	4.51	4.63	-0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	LAA	1	1	6	25	5	3	1	100%	6.0	21.2%	11.2%	10.0%	2.9%	4.48	4.71	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	LAA	7	7	42	178	36	21	6	100%	6.0	20.4%	11.6%	8.8%	3.2%	4.77	4.96	+0.2
2029	33	MLB MLE	LAA	6	6	33	139	27	17	5	100%	5.5	19.5%	12.1%	7.4%	3.4%	5.05	5.24	+0.1
2030	34	MLB MLE	LAA	4	4	27	114	21	14	4	100%	6.8	18.6%	12.6%	6.0%	3.7%	5.35	5.55	-0.0
2028	32	MLB CTX	LAA	2	2	15	63	13	7	2	100%	7.5	20.4%	11.6%	8.8%	3.2%	4.77	4.96	+0.1
2029	33	MLB CTX	LAA	3	3	18	76	15	9	3	100%	6.0	19.5%	12.1%	7.4%	3.4%	5.05	5.24	+0.0
2030	34	MLB CTX	LAA	2	2	14	59	11	7	2	100%	7.0	18.6%	12.6%	6.0%	3.7%	5.35	5.55	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		72	38	223	952	196	97	35	53%	3.1	20.6%	10.2%	10.4%	3.7%	4.62	4.66	+1.9
/ 200 IP	—	RAW		64	34	200	854	176	87	31	53%	3.1	20.6%	10.2%	10.4%	3.7%	4.62	4.66	+1.7
Career	—	MLE		152	90	497	2078	427	172	75	59%	3.3	20.5%	8.3%	12.3%	3.6%	4.06	4.39	+1.8
/ 200 IP	—	MLE		61	36	200	836	172	69	30	59%	3.3	20.5%	8.3%	12.3%	3.6%	4.06	4.39	+1.3

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 AAASalt Lake Bees · 21 IPFIP 3.33 → 3.50 (+0.17)K% 20.9% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.88%	—	×0.860	17.96%
BB% (unintentional) /BF	10.99%	—	×0.900	9.89%
HR / BF /BF	1.10%	÷1.000	×1.100	1.21%

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 3.33 → 3.50, 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 ROKACL Angels · 5 IPFIP 7.14 → 9.91 (+2.77)K% 21.7% → 14.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.74%	—	×0.680	14.78%
BB% (unintentional) /BF	8.70%	—	×1.250	10.87%
HR / BF /BF	8.70%	÷1.000	×1.400	12.17%

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 7.14 → 9.91, 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 AAADurham Bulls · 6 IPFIP 5.87 → 5.46 (−0.40)K% 20.7% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.69%	—	×0.860	17.79%
BB% (unintentional) /BF	20.69%	—	×0.900	18.62%
HR / BF /BF	3.45%	÷1.380	×1.100	2.75%

Result: FIP 5.87 → 5.46, 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 AAAToledo Mud Hens · 26 IPFIP 3.51 → 4.26 (+0.75)K% 29.4% → 25.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.41%	—	×0.860	25.29%
BB% (unintentional) /BF	5.88%	—	×0.900	5.29%
HR / BF /BF	3.92%	÷0.901	×1.100	4.79%

Result: FIP 3.51 → 4.26, 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 AAErie SeaWolves · 5 IPFIP 3.10 → 4.04 (+0.94)K% 34.8% → 28.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.78%	—	×0.810	28.17%
BB% (unintentional) /BF	4.35%	—	×1.100	4.78%
HR / BF /BF	4.35%	÷1.055	×1.200	4.95%

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 3.10 → 4.04, 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 ALakeland Flying Tigers · 11 IPFIP 1.59 → 2.38 (+0.79)K% 28.6% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.57%	—	×0.740	21.14%
BB% (unintentional) /BF	7.14%	—	×1.180	8.43%
HR / BF /BF	0.00%	÷1.279	×1.300	0.00%

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 156).

Result: FIP 1.59 → 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).

2019 AAErie SeaWolves · 115 IPFIP 3.35 → 3.73 (+0.38)K% 28.3% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.33%	—	×0.810	22.95%
BB% (unintentional) /BF	5.29%	—	×1.100	5.81%
HR / BF /BF	3.59%	÷1.294	×1.200	3.33%

Result: FIP 3.35 → 3.73, 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 AAErie SeaWolves · 60 IPFIP 5.48 → 6.22 (+0.74)K% 23.2% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.23%	—	×0.810	18.81%
BB% (unintentional) /BF	8.66%	—	×1.100	9.53%
HR / BF /BF	5.91%	÷1.112	×1.200	6.37%

Result: FIP 5.48 → 6.22, 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).

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
Alex Faedo (OGILVIE)	—	—	4.71	21.2%	11.2%	2.9%	—	5.21	19.7%	7.6%	102	+0.50	—	—	—
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	76
Robert Stock R 2021 · 4.18 FIP	31	SW	4.18	23.0%	8.5%	3.5%	.301	7.20	14.3%	0.1%	23	+3.02	2.74	378	70
Edgar Alberto Garcia R 2017 · 4.01 FIP	29	SP-	4.01	17.3%	10.9%	1.8%	.305	—	—	—	—	—	4.01	272	70
Yoanner Negrin R 2015 · 3.79 FIP	31	SW	3.79	15.1%	7.5%	1.9%	.256	3.29	15.0%	8.5%	270	-0.50	3.15	485	67
Josh A. Smith R 2019 · 4.65 FIP	31	SW	4.65	20.8%	6.4%	4.5%	.341	3.67	17.4%	8.6%	59	-0.98	2.91	598	66
Scott Copeland R 2019 · 5.62 FIP	31	SP-	5.62	17.1%	12.4%	4.4%	.311	—	—	—	—	—	3.55	569	66
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	65
Paolo Espino R 2018 · 4.51 FIP	31	SW	4.51	18.7%	9.6%	3.2%	.348	4.42	20.4%	14.7%	202	-0.09	3.42	933	65
Derek Eitel R 2017 · 4.72 FIP	29	SP-	4.72	17.2%	16.0%	1.9%	.273	—	—	—	—	—	3.96	138	65
Jared Fernandez R 2003 · 3.57 FIP	31	SP-	3.57	11.8%	6.2%	1.2%	.269	—	—	—	—	—	3.57	101	64
Angel Sánchez R 2023 · 4.90 FIP	33	SW	4.90	19.0%	10.5%	3.8%	.333	3.77	11.8%	6.8%	27	-1.13	3.77	284	64
Jose A. Flores R 2018 · 4.77 FIP	29	SP-	4.77	13.7%	10.3%	2.8%	.350	—	—	—	—	—	2.94	237	64
Luke Hudson R 2006 · 3.81 FIP	29	SP-	3.81	14.5%	8.4%	1.6%	.307	—	—	—	—	—	3.81	235	64
Todd Redmond R 2015 · 3.86 FIP	30	SW	3.86	15.4%	7.1%	2.1%	.311	—	—	—	—	—	3.21	247	64
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	64
Jorge Martinez R 2016 · 3.53 FIP	31	SP-	3.53	12.9%	5.3%	1.6%	.266	3.71	16.5%	11.5%	154	+0.18	3.53	214	64
Samuel Deduno R 2014 · 3.92 FIP	31	SW	3.92	18.7%	9.9%	2.1%	.287	3.84	19.8%	12.3%	39	-0.08	2.99	327	64
Wes Obermueller R 2007 · 4.83 FIP	30	SW	4.83	12.6%	11.2%	2.5%	.317	—	—	—	—	—	4.72	308	63
Murphy Smith R 2018 · 4.57 FIP	30	SW	4.57	13.6%	9.3%	2.6%	.273	—	—	—	—	—	3.16	300	63
Luke Farrell R 2022 · 4.87 FIP	31	SP-	4.87	17.8%	11.0%	3.4%	.289	4.85	17.3%	7.9%	55	-0.02	3.69	584	62

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	1.7	48	20.6%	10.7%	1.35	4.66
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Josias Manzanillo ('04)	1.7	57	20.0%	10.2%	1.21	4.71
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Bill Pleis ('61-'66, -0 WAR*)	1.4	56	19.7%*	9.8%*	1.15*	4.53*