Troy Taylor

P Tacoma Rainiers

Age 25 RHP 6'0" / 205 lbs AAA

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	22	MIX3 levels	61	62	2.03	2.70	28.7%	8.6%	1.4	K 25.4% · BB 8.6% · FIP 3.18
2025	23	MIX2 levels	58	51	7.54	5.07	22.9%	13.1%	-0.3	K 22.3% · BB 12.5% · FIP 4.49
2026	24	MIX2 levels	56	60	5.25	4.07	23.4%	13.3%	0.3	K 20.6% · BB 12.0% · FIP 3.99
2027PROJ	25	MLBSEA	47	49	4.53	4.75	21.6%	12.7%	-0.1
2028PROJ83% MLB	26	MLBSEA	41	43	4.61	4.69	21.9%	12.3%	-0.1
2029PROJ87% MLB	27	MLBSEA	38	40	4.65	4.70	22.1%	12.1%	-0.1

Last 3 seasons WAR 1.4 · Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff50Control35Command45

Career WAR0.0 WAR median (P10 -0.4 / P90 1.5, comp-based) · star 0% · didn't stick 94%

CompsDan Kolb (age 26) · Francisco Del Rosario (age 25) · Michael Wuertz (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123115vR 107

ERA4.53

FIP4.75

K%21.6%

BB%12.7%

K-BB%8.9%

Proj IP67

Value2027 · WAR

Runs saved vs league avg · 67 IP

Grades · Contract

Scouting Grades

STUF5050

CTRL3535

CMD4545

K†5055

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)
2023	21	MIX MLE	2 levels	40	0	45	200	62	21	1	0%	1.1	23.4%	13.9%	9.5%	0.9%	3.38	3.39	—
2023	21	MIX RAW	2 levels	40	0	45	200	62	21	1	0%	1.1	31.0%	10.5%	20.5%	0.5%	3.38	2.04	—
2024	22	MIX MLE	3 levels	61	0	62	244	70	21	4	0%	1.0	25.4%	8.6%	16.9%	2.1%	2.03	3.18	+1.0
2024	22	MIX MLE	3 levels	61	0	62	244	70	21	4	0%	1.0	25.4%	8.6%	16.9%	2.1%	2.03	3.18	+1.0
2024	22	MIX RAW	3 levels	61	0	62	244	70	21	4	0%	1.0	28.7%	8.6%	20.1%	1.6%	2.03	2.70	+1.4
2025	23	MIX MLE	2 levels	58	0	51	245	56	32	9	0%	0.9	22.3%	12.5%	9.8%	3.1%	7.54	4.49	+0.0
2025	23	MIX MLE	2 levels	58	0	51	245	56	32	9	0%	0.9	22.3%	12.5%	9.8%	3.1%	7.54	4.49	+0.0
2025	23	MIX RAW	2 levels	58	0	51	245	56	32	9	0%	0.9	22.9%	13.1%	9.8%	3.7%	7.54	5.07	-0.3
2026	24	MIX MLE	2 levels	56	0	60	286	67	38	6	0%	1.1	20.6%	12.0%	8.7%	2.0%	5.25	3.99	+0.4
2026	24	MIX MLE	2 levels	56	0	60	286	67	38	6	0%	1.1	20.6%	12.0%	8.7%	2.0%	5.25	3.99	+0.4
2026	24	MIX RAW	2 levels	56	0	60	286	67	38	6	0%	1.1	23.4%	13.3%	10.1%	2.1%	5.25	4.07	+0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			31	0	29	133	29	12	7	0%	0.9	21.8%	9.0%	12.8%	5.3%	6.21	5.48	-0.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	SEA	47	0	49	207	45	26	6	0%	1.0	21.6%	12.7%	8.9%	2.7%	4.53	4.75	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	SEA	49	0	52	219	48	27	6	0%	1.1	21.9%	12.3%	9.7%	2.7%	4.61	4.69	-0.1
2029	27	MLB MLE	SEA	43	0	46	192	42	23	5	0%	1.1	22.1%	12.1%	9.9%	2.8%	4.65	4.70	-0.1
2030	28	MLB MLE	SEA	40	0	42	176	39	21	5	0%	1.0	22.0%	12.1%	9.9%	2.9%	4.71	4.76	-0.1
2028	26	MLB CTX	SEA	41	0	43	182	40	22	5	0%	1.0	21.9%	12.3%	9.7%	2.7%	4.61	4.69	-0.1
2029	27	MLB CTX	SEA	38	0	40	169	37	20	5	0%	1.1	22.1%	12.1%	9.9%	2.8%	4.65	4.70	-0.1
2030	28	MLB CTX	SEA	36	0	38	160	35	19	5	0%	1.1	22.0%	12.1%	9.9%	2.9%	4.71	4.76	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		146	0	149	641	141	74	21	0%	1.0	22.0%	11.5%	10.4%	3.3%	4.96	4.53	+0.0
/ 200 IP	—	RAW		195	0	200	859	189	99	28	0%	1.0	22.0%	11.5%	10.4%	3.3%	4.96	4.53	+0.0
Career	—	MLE		215	0	219	975	223	114	20	0%	1.0	22.8%	11.7%	11.2%	2.1%	4.49	3.79	-0.6
/ 200 IP	—	MLE		197	0	200	892	204	104	19	0%	1.0	22.8%	11.7%	11.2%	2.1%	4.49	3.79	-0.7

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 AAATacoma Rainiers · 57 IPFIP 3.77 → 3.99 (+0.22)K% 24.0% → 20.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.99%	—	×0.860	20.63%
BB% (unintentional) /BF	13.28%	—	×0.900	11.96%
HR / BF /BF	1.85%	÷1.000	×1.100	2.03%

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 3.77 → 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).

2025 AAATacoma Rainiers · 45 IPFIP 4.52 → 4.49 (−0.03)K% 26.0% → 22.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.96%	—	×0.860	22.33%
BB% (unintentional) /BF	13.94%	—	×0.900	12.55%
HR / BF /BF	3.37%	÷1.204	×1.100	3.07%

Result: FIP 4.52 → 4.49, 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 AAArkansas Travelers · 31 IPFIP 1.83 → 2.35 (+0.53)K% 26.7% → 21.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.72%	—	×0.810	21.65%
BB% (unintentional) /BF	7.76%	—	×1.100	8.53%
HR / BF /BF	0.00%	÷0.820	×1.200	0.00%

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 64).

Result: FIP 1.83 → 2.35, 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).

2024 A+Everett AquaSox · 12 IPFIP 1.93 → 2.71 (+0.78)K% 29.8% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.79%	—	×0.770	22.94%
BB% (unintentional) /BF	10.64%	—	×1.150	12.23%
HR / BF /BF	0.00%	÷1.175	×1.250	0.00%

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 135).

Result: FIP 1.93 → 2.71, 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).

2023 AModesto Nuts · 35 IPFIP 2.26 → 3.39 (+1.13)K% 31.7% → 23.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.68%	—	×0.740	23.44%
BB% (unintentional) /BF	11.80%	—	×1.180	13.93%
HR / BF /BF	0.62%	÷0.883	×1.300	0.91%

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 77).

Result: FIP 2.26 → 3.39, 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+Everett AquaSox · 10 IPFIP 1.37 → 2.01 (+0.65)K% 28.2% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.21%	—	×0.770	21.72%
BB% (unintentional) /BF	5.13%	—	×1.150	5.90%
HR / BF /BF	0.00%	÷1.012	×1.250	0.00%

Result: FIP 1.37 → 2.01, 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
Troy Taylor (OGILVIE)	—	—	4.75	21.6%	12.7%	2.7%	—	4.71	22.0%	9.8%	139	-0.04	—	—	—
Dan Kolb R 2001 · 4.49 FIP	26	SU	4.49	21.4%	12.9%	2.9%	.295	3.61	14.3%	5.5%	131	-0.88	3.00	283	81
Francisco Del Rosario R 2006 · 5.13 FIP	25	SU	5.13	19.4%	13.0%	3.7%	.290	3.93	19.7%	10.3%	26	-1.20	3.93	194	80
Michael Wuertz R 2004 · 4.46 FIP	25	SU	4.46	24.2%	12.9%	3.2%	.243	3.39	26.1%	16.6%	189	-1.07	2.27	414	80
Maikel Cleto R 2014 · 4.24 FIP	25	SU	4.24	23.2%	15.2%	2.1%	.256	3.45	25.4%	14.5%	106	-0.79	2.59	185	80
Josh Zeid R 2013 · 4.00 FIP	26	SU	4.00	20.3%	9.3%	2.6%	.287	4.75	16.2%	4.8%	183	+0.75	4.00	313	79
Pat Light R 2016 · 4.10 FIP	25	SU	4.10	21.1%	13.1%	2.1%	.276	4.63	11.8%	-2.3%	55	+0.53	4.10	172	79
Chad Smith R 2019 · 4.32 FIP	24	SU	4.32	19.8%	13.5%	2.1%	.274	3.93	25.2%	12.6%	86	-0.39	3.31	258	79
Jason Foley R 2021 · 4.79 FIP	25	SU	4.79	20.7%	12.4%	3.4%	.309	2.88	18.4%	13.1%	189	-1.91	1.66	340	79
Brandon Cunniff R 2015 · 4.28 FIP	26	SU	4.28	24.5%	13.2%	2.9%	.256	4.32	20.3%	9.0%	115	+0.04	3.89	180	78
Tyler Mitzel R 2021 · 4.03 FIP	25	SU	4.03	20.8%	12.0%	2.1%	.323	4.14	23.4%	17.9%	58	+0.11	4.03	142	78
Tayron Guerrero R 2016 · 3.77 FIP	25	SU	3.77	19.9%	11.3%	1.7%	.291	4.94	22.0%	7.3%	135	+1.17	2.12	376	78
Luis Vizcaino R 2000 · 4.11 FIP	25	SU	4.11	18.8%	11.5%	2.1%	.354	4.31	22.7%	14.9%	180	+0.20	3.07	564	78
Jordan Weems R 2018 · 3.90 FIP	25	SU	3.90	19.0%	12.0%	1.6%	.333	4.58	22.7%	9.6%	98	+0.68	3.05	473	78
Guillermo Moscoso R 2009 · 3.56 FIP	25	SU	3.56	18.8%	9.4%	1.6%	.311	4.33	15.8%	8.5%	178	+0.77	3.56	486	78
Manny Acosta R 2007 · 4.05 FIP	26	SU	4.05	23.7%	14.0%	2.1%	.196	4.23	19.0%	9.1%	130	+0.18	3.08	350	77
Shawn Tolleson R 2012 · 3.86 FIP	24	SU	3.86	24.4%	11.9%	2.4%	.265	3.47	24.4%	18.5%	144	-0.39	3.05	218	77
Cameron Gann R 2017 · 4.22 FIP	24	SU	4.22	21.4%	12.4%	2.5%	.296	5.36	21.1%	6.8%	23	+1.14	3.58	146	77
Casey Fien R 2009 · 5.17 FIP	25	SU	5.17	17.0%	11.3%	3.8%	.306	2.79	22.7%	19.2%	35	-2.38	2.79	308	77
Dylan Hall R 2023 · 3.98 FIP	25	SU	3.98	21.0%	13.2%	1.8%	.305	7.24	15.1%	2.4%	58	+3.26	3.47	153	77
Brandan Bidois R 2024 · 4.20 FIP	23	SU	4.20	26.1%	14.5%	2.7%	.246	4.15	23.7%	9.6%	84	-0.05	2.73	136	77

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	1.2	59	21.9%	11.9%	1.20	4.81
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Tyler Yates ('09)	1.2	62	19.7%	12.0%	0.94	5.12
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*
David Aardsma ('15)	1.7	48	23.1%	12.4%	1.09	4.27