Tayler Saucedo

P Salt Lake Bees

Age 34 LHP 6'4" / 205 lbs AAA peak 0.2 · 2027

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	31	MIX2 levels	54	0	40	3.40	3.25	23.1%	8.9%	0.6	K 22.9% · BB 9.0% · FIP 3.33
2025	32	MIX2 levels	32	0	33	4.64	4.34	23.7%	10.5%	0.1	K 21.5% · BB 9.9% · FIP 4.27
2026	33	MIX2 levels	62	1	60	4.83	3.77	25.1%	12.0%	0.6	K 22.9% · BB 11.0% · FIP 3.89
2027PROJ	34	MLBLAA	58	0	61	4.23	4.44	22.4%	10.8%	0.1
2028PROJ95% MLB	35	MLBLAA	29	0	30	4.56	4.78	21.5%	11.4%	-0.1
2029PROJ86% MLB	36	MLBLAA	12	0	13	4.91	5.15	20.5%	12.0%	-0.1

Last 3 seasons WAR 1.2 · Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%90

xwOBA vs90

FB Velo23

Form2.00 ERA (proj 4.23) · K 27.8% (proj 22.4%) · BB 9.7% (proj 10.8%) ▲▲ last 90d · 18 IP through Oct 27

CompsJuan Pablo Perez (age 34) · Ryan Buchter (age 34) · Pedro Borbón (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 101109vR 118

ERA4.23

FIP4.44

K%22.4%

BB%10.8%

K-BB%11.6%

Proj IP61

Value2027 · WAR

Runs saved vs league avg · 61 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p2392.6

Whiff%

p9037.2%

p9029.9%

xwOBA vs

p900.256

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)
2015	22	ROK MLE	Bluefield Blue Jays	6	2	22	97	18	4	0	33%	3.7	12.6%	5.2%	7.5%	0.0%	2.42	2.69	—
2015	22	ROK RAW	Bluefield Blue Jays	6	2	22	97	18	4	0	33%	3.7	18.6%	4.1%	14.4%	0.0%	2.42	2.03	—
2016	23	A MLE	Lansing Lugnuts	28	16	120	551	71	41	14	57%	4.3	9.5%	8.8%	0.8%	3.4%	5.91	5.28	—
2016	23	A RAW	Lansing Lugnuts	28	16	120	551	71	41	14	57%	4.3	12.9%	7.4%	5.4%	2.5%	5.91	4.45	—
2017	24	MIX MLE	2 levels	33	13	96	439	85	45	4	39%	2.9	14.7%	11.9%	2.8%	1.3%	4.48	4.10	—
2017	24	MIX RAW	2 levels	33	13	96	439	85	45	4	39%	2.9	19.4%	10.3%	9.1%	0.9%	4.48	3.28	—
2018	25	MIX MLE	2 levels	26	26	148	628	104	36	16	100%	5.7	13.0%	6.4%	6.5%	3.0%	4.14	4.49	—
2018	25	MIX RAW	2 levels	26	26	148	628	104	36	16	100%	5.7	16.6%	5.7%	10.8%	2.5%	4.14	3.83	—
2019	26	MIX MLE	2 levels	36	8	82	366	69	36	6	22%	2.3	16.2%	10.5%	5.6%	1.9%	3.61	4.11	—
2019	26	MIX RAW	2 levels	36	8	82	366	69	36	6	22%	2.3	18.9%	9.8%	9.0%	1.6%	3.61	3.68	—
2021	28	MIX MLE	2 levels	41	0	44	178	44	11	1	0%	1.1	23.0%	6.2%	16.8%	0.6%	3.48	2.25	+1.2
2021	28	MIX RAW	2 levels	41	0	44	178	44	11	1	0%	1.1	24.7%	6.2%	18.5%	0.6%	3.48	2.15	+1.3
2022	29	MIX MLE	3 levels	25	0	23	100	30	11	4	0%	0.9	30.0%	12.8%	17.2%	1.4%	3.57	2.96	+0.4
2022	29	MIX RAW	3 levels	25	0	23	100	30	11	4	0%	0.9	30.0%	11.0%	19.0%	4.0%	3.57	4.20	+0.1
2023	30	MIX MLE	2 levels	57	0	55	233	51	24	2	0%	1.0	20.8%	10.6%	10.1%	1.0%	3.09	3.24	+0.9
2023	30	MIX RAW	2 levels	57	0	55	233	51	24	2	0%	1.0	21.9%	10.3%	11.6%	0.9%	3.09	3.03	+1.0
2024	31	MIX MLE	2 levels	54	0	40	169	39	15	3	0%	0.7	22.9%	9.0%	13.9%	1.9%	3.40	3.33	+0.6
2024	31	MIX MLE	2 levels	54	0	40	169	39	15	3	0%	0.7	22.9%	9.0%	13.9%	1.9%	3.40	3.33	+0.6
2024	31	MIX RAW	2 levels	54	0	40	169	39	15	3	0%	0.7	23.1%	8.9%	14.2%	1.8%	3.40	3.25	+0.6
2025	32	MIX MLE	2 levels	32	0	33	152	36	16	5	0%	1.0	21.5%	9.9%	11.6%	3.2%	4.64	4.27	+0.1
2025	32	MIX MLE	2 levels	32	0	33	152	36	16	5	0%	1.0	21.5%	9.9%	11.6%	3.2%	4.64	4.27	+0.1
2025	32	MIX RAW	2 levels	32	0	33	152	36	16	5	0%	1.0	23.7%	10.5%	13.2%	3.3%	4.64	4.34	+0.1
2026	33	MIX MLE	2 levels	62	1	60	267	67	32	6	2%	1.0	22.9%	11.0%	11.9%	2.4%	4.83	3.89	+0.5
2026	33	MIX MLE	2 levels	62	1	60	267	67	32	6	2%	1.0	22.9%	11.0%	11.9%	2.4%	4.83	3.89	+0.5
2026	33	MIX RAW	2 levels	62	1	60	267	67	32	6	2%	1.0	25.1%	12.0%	13.1%	2.2%	4.83	3.77	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			176	0	149	650	138	61	12	0%	0.8	21.2%	9.4%	11.8%	1.8%	4.10	3.52	+1.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	LAA	58	0	61	258	58	28	7	0%	1.1	22.4%	10.8%	11.6%	2.7%	4.23	4.44	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	LAA	30	0	32	133	29	15	4	0%	1.1	21.5%	11.4%	10.1%	3.0%	4.56	4.78	-0.1
2029	36	MLB MLE	LAA	15	0	16	65	13	8	2	0%	1.0	20.5%	12.0%	8.5%	3.4%	4.91	5.15	-0.1
2030	37	MLB MLE	LAA	7	0	7	30	6	4	1	0%	1.0	19.4%	12.6%	6.8%	3.8%	5.29	5.55	-0.1
2028	35	MLB CTX	LAA	29	0	30	127	27	14	4	0%	1.0	21.5%	11.4%	10.1%	3.0%	4.56	4.78	-0.1
2029	36	MLB CTX	LAA	12	0	13	55	11	7	2	0%	1.1	20.5%	12.0%	8.5%	3.4%	4.91	5.15	-0.1
2030	37	MLB CTX	LAA	6	0	6	25	5	3	1	0%	1.0	19.4%	12.6%	6.8%	3.8%	5.29	5.55	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		223	0	198	856	181	85	19	0%	0.9	21.2%	9.9%	11.2%	2.2%	4.26	3.77	+1.8
/ 200 IP	—	RAW		225	0	200	864	183	86	19	0%	0.9	21.2%	9.9%	11.2%	2.2%	4.26	3.77	+1.9
Career	—	MLE		400	66	723	3180	522	293	70	16%	1.8	16.4%	9.2%	7.2%	2.2%	4.27	4.08	+1.5
/ 200 IP	—	MLE		111	18	200	879	144	81	19	16%	1.8	16.4%	9.2%	7.2%	2.2%	4.27	4.08	+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 AAASalt Lake Bees · 38 IPFIP 4.46 → 4.71 (+0.25)K% 22.8% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.78%	—	×0.860	19.59%
BB% (unintentional) /BF	13.89%	—	×0.900	12.50%
HR / BF /BF	2.78%	÷1.000	×1.100	3.06%

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 4.46 → 4.71, 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 AAATacoma Rainiers · 20 IPFIP 4.13 → 4.15 (+0.02)K% 27.9% → 24.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.91%	—	×0.860	24.00%
BB% (unintentional) /BF	11.63%	—	×0.900	10.47%
HR / BF /BF	3.49%	÷1.204	×1.100	3.19%

Result: FIP 4.13 → 4.15, 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 AAATacoma Rainiers · 8 IPFIP 1.48 → 1.74 (+0.27)K% 30.8% → 26.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.77%	—	×0.860	26.46%
BB% (unintentional) /BF	7.69%	—	×0.900	6.92%
HR / BF /BF	0.00%	÷1.157	×1.100	0.00%

Result: FIP 1.48 → 1.74, 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 · 19 IPFIP 2.43 → 2.96 (+0.53)K% 34.1% → 30.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.15%	—	×0.880	30.05%
BB% (unintentional) /BF	12.20%	—	×1.050	12.80%
HR / BF /BF	1.22%	÷0.951	×1.100	1.41%

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 2.43 → 2.96, 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 AAABuffalo Bisons · 18 IPFIP 0.22 → 0.60 (+0.38)K% 36.2% → 31.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.23%	—	×0.880	31.88%
BB% (unintentional) /BF	1.45%	—	×1.050	1.52%
HR / BF /BF	0.00%	÷1.081	×1.100	0.00%

Result: FIP 0.22 → 0.60, 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 AAABuffalo Bisons · 56 IPFIP 3.65 → 3.99 (+0.34)K% 18.2% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.18%	—	×0.880	16.00%
BB% (unintentional) /BF	7.91%	—	×1.050	8.30%
HR / BF /BF	1.98%	÷1.000	×1.100	2.17%

Result: FIP 3.65 → 3.99, 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 AANew Hampshire Fisher Cats · 27 IPFIP 3.66 → 4.36 (+0.70)K% 20.4% → 16.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.35%	—	×0.810	16.49%
BB% (unintentional) /BF	14.16%	—	×1.100	15.58%
HR / BF /BF	0.88%	÷0.860	×1.200	1.23%

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 72).

Result: FIP 3.66 → 4.36, 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).

2018 A+Dunedin Blue Jays · 85 IPFIP 3.26 → 3.82 (+0.56)K% 18.9% → 14.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.91%	—	×0.770	14.56%
BB% (unintentional) /BF	5.16%	—	×1.150	5.93%
HR / BF /BF	2.01%	÷1.147	×1.250	2.19%

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 129).

Result: FIP 3.26 → 3.82, 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
Tayler Saucedo (OGILVIE)	—	—	—	—	—	2.7%	—	4.90	21.2%	9.6%	47	+0.46	—	—	—
Juan Pablo Perez L 2013 · 3.68 FIP	34	SU	3.68	25.2%	11.5%	2.3%	.250	3.68	26.5%	11.2%	51	-0.00	1.75	104	74
Ryan Buchter L 2021 · 5.24 FIP	34	SU	5.24	22.9%	13.2%	4.4%	.267	—	—	—	—	—	2.37	296	71
Pedro Borbón L 2002 · 4.57 FIP	34	SU	4.57	21.6%	7.3%	4.3%	.277	—	—	—	—	—	2.26	264	68
James Jones L 2023 · 4.67 FIP	34	SU	4.67	13.7%	11.5%	2.3%	.246	—	—	—	—	—	3.58	127	67
Brandon Mann L 2018 · 3.59 FIP	34	SU	3.59	17.8%	11.4%	1.0%	.232	—	—	—	—	—	3.59	190	67
Alejandro Soto L 2019 · 4.03 FIP	33	SW	4.03	17.1%	6.9%	2.7%	.376	—	—	—	—	—	3.96	280	66
Heriberto Ruelas L 2016 · 3.75 FIP	34	SU	3.75	15.0%	8.9%	1.4%	.310	3.42	17.2%	10.5%	49	-0.33	2.95	117	66
Tim Byrdak L 2008 · 5.18 FIP	34	SU	5.18	19.8%	11.4%	4.2%	.229	4.30	22.4%	10.5%	138	-0.88	2.85	320	65
Clay Rapada L 2015 · 3.84 FIP	34	SU	3.84	14.3%	8.0%	1.7%	.299	—	—	—	—	—	3.00	120	65
Tom Martin L 2004 · 4.74 FIP	34	SU	4.74	14.7%	7.8%	3.4%	.278	3.96	14.7%	7.1%	86	-0.78	3.40	303	65
Hideki Okajima L 2010 · 4.27 FIP	34	SU	4.27	15.5%	7.0%	2.9%	.333	—	—	—	—	—	3.05	238	65
Dan Runzler L 2019 · 4.84 FIP	34	SU	4.84	16.0%	13.0%	2.6%	.284	—	—	—	—	—	2.84	187	63
Joey Eischen L 2004 · 3.63 FIP	34	SU	3.63	21.2%	7.5%	2.5%	.255	3.37	19.0%	9.1%	51	-0.26	2.13	294	61
Luke Westphal L 2022 · 4.35 FIP	33	SW	4.35	24.2%	13.4%	2.9%	.302	5.19	15.7%	-0.7%	26	+0.84	2.97	294	60
Scott Rice L 2015 · 3.67 FIP	33	SU	3.67	22.9%	17.2%	0.6%	.266	—	—	—	—	—	3.10	104	59
Hisanori Takahashi L 2010 · 3.50 FIP	35	SW	3.50	22.1%	7.0%	2.5%	.292	3.81	21.1%	15.0%	118	+0.31	3.50	240	58
Doug Creek L 2003 · 5.00 FIP	34	SU	5.00	15.9%	13.0%	2.9%	.255	6.28	17.8%	10.9%	22	+1.28	4.48	277	58
Edwin Escobar L 2024 · 5.12 FIP	32	SU	5.12	19.6%	14.0%	3.5%	.275	—	—	—	—	—	4.28	218	57
Jamie Walker L 2005 · 3.81 FIP	34	SU	3.81	14.4%	4.8%	2.4%	.270	4.46	16.3%	12.2%	147	+0.65	3.48	442	56
Carlos Pulido L 2004 · 4.41 FIP	32	SU	4.41	16.4%	5.5%	3.6%	.341	—	—	—	—	—	2.91	111	55

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	1.3	33	21.4%	10.5%	0.90	4.26
Yorkis Perez ('02)	1.4	40	20.8%	11.8%	0.93	4.44
Ray Searage ('81-'90, 4 WAR*)	1.4	41	21.0%*	10.8%*	0.84*	3.70*
Tony Fossas ('88-'99, 2 WAR*)	2.1	42	21.9%*	9.3%*	0.99*	3.88*
Jason Christiansen ('05)	2.2	43	20.1%	11.4%	0.77	4.30
Will Ohman ('12)	1.8	50	21.8%	10.3%	1.07	4.28
Ed Vosberg ('86-'02, 1 WAR*)	1.2	47	21.0%*	9.6%*	0.86*	4.06*