Taylor Floyd

P Chattanooga Lookouts

Age 29 RHP 6'1" / 185 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	27	AASEA	45	0	58	4.53	3.53	25.9%	7.2%	—	K 20.9% · BB 7.9% · FIP 4.84
2026	28	AACIN	34	1	70	4.13	4.32	21.6%	9.3%	—	K 17.5% · BB 10.2% · FIP 5.18
2027PROJ	29	MLBCIN	1	0	1	4.87	4.87	18.7%	8.9%	-0.0
2028PROJ31% MLB	30	MLBCIN	15	0	16	4.92	5.00	18.8%	9.2%	-0.1
2029PROJ51% MLB	31	MLBCIN	21	0	22	5.03	5.15	18.8%	9.5%	-0.1

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

Contract

No contract data on file.

Scouting grades · 20-80

Stuff50Control55Command55

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

CompsAngel Castro (age 32) · Tyler Walker (age 29) · Neil Wagner (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 126118vR 109

ERA4.87

FIP4.87

K%18.7%

BB%8.9%

K-BB%9.8%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Grades · Contract

Scouting Grades

STUF5050

CTRL5555

CMD5555

K†4545

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)
2021	23	MIX MLE	2 levels	40	0	56	227	84	23	4	0%	1.4	27.7%	12.1%	15.6%	2.2%	2.89	3.48	—
2021	23	MIX RAW	2 levels	40	0	56	227	84	23	4	0%	1.4	37.0%	10.1%	26.9%	1.8%	2.89	2.26	—
2022	24	MIX MLE	2 levels	41	0	57	269	67	44	4	0%	1.4	19.6%	18.4%	1.1%	1.9%	5.49	4.84	—
2022	24	MIX RAW	2 levels	41	0	57	269	67	44	4	0%	1.4	24.9%	16.4%	8.6%	1.5%	5.49	3.97	—
2023	25	MIX MLE	2 levels	43	0	61	267	73	26	8	0%	1.4	21.7%	10.8%	10.8%	3.1%	4.84	4.34	—
2023	25	MIX RAW	2 levels	43	0	61	267	73	26	8	0%	1.4	27.3%	9.7%	17.6%	3.0%	4.84	3.69	—
2024	26	AA MLE	Wichita Wind Surge	44	1	65	280	59	26	3	2%	1.5	17.1%	10.2%	6.9%	1.5%	4.04	3.79	—
2024	26	AA MLE	Wichita Wind Surge	44	1	65	280	59	26	3	2%	1.5	17.1%	10.2%	6.9%	1.5%	4.04	3.79	—
2024	26	AA RAW	Wichita Wind Surge	44	1	65	280	59	26	3	2%	1.5	21.1%	9.3%	11.8%	1.1%	4.04	3.08	—
2025	27	AA MLE	Arkansas Travelers	45	0	58	263	68	19	8	0%	1.3	20.9%	7.9%	13.0%	4.6%	4.53	4.84	—
2025	27	AA MLE	Arkansas Travelers	45	0	58	263	68	19	8	0%	1.3	20.9%	7.9%	13.0%	4.6%	4.53	4.84	—
2025	27	AA RAW	Arkansas Travelers	45	0	58	263	68	19	8	0%	1.3	25.9%	7.2%	18.6%	3.0%	4.53	3.53	—
2026	28	AA MLE	Chattanooga Lookouts	34	1	70	291	63	27	10	3%	2.0	17.5%	10.2%	7.3%	4.1%	4.13	5.18	—
2026	28	AA MLE	Chattanooga Lookouts	34	1	70	291	63	27	10	3%	2.0	17.5%	10.2%	7.3%	4.1%	4.13	5.18	—
2026	28	AA RAW	Chattanooga Lookouts	34	1	70	291	63	27	10	3%	2.0	21.6%	9.3%	12.4%	3.4%	4.13	4.32	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	CIN	1	0	1	4	1	0	0	0%	1.0	18.7%	8.9%	9.8%	3.4%	4.87	4.87	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	CIN	49	0	52	219	41	20	8	0%	1.1	18.8%	9.2%	9.6%	3.5%	4.92	5.00	-0.3
2029	31	MLB MLE	CIN	41	0	43	181	34	17	7	0%	1.0	18.8%	9.5%	9.2%	3.7%	5.03	5.15	-0.3
2028	30	MLB CTX	CIN	15	0	16	68	13	6	2	0%	1.1	18.8%	9.2%	9.6%	3.5%	4.92	5.00	-0.1
2029	31	MLB CTX	CIN	21	0	22	93	17	9	3	0%	1.0	18.8%	9.5%	9.2%	3.7%	5.03	5.15	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		36	0	38	161	30	15	6	0%	1.1	18.8%	9.4%	9.4%	3.6%	4.98	4.70	-0.1
/ 200 IP	—	RAW		190	0	200	844	157	78	31	0%	1.1	18.8%	9.4%	9.4%	3.6%	4.98	4.70	-0.4
Career	—	MLE		247	2	367	1597	327	185	47	1%	1.5	20.5%	11.6%	8.9%	2.9%	4.32	4.44	-0.6
/ 200 IP	—	MLE		135	1	200	871	179	101	25	1%	1.5	20.5%	11.6%	8.9%	2.9%	4.32	4.44	-1.2

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 AAChattanooga Lookouts · 70 IPFIP 4.33 → 5.18 (+0.84)K% 21.6% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.65%	—	×0.810	17.54%
BB% (unintentional) /BF	9.28%	—	×1.100	10.21%
HR / BF /BF	3.44%	÷1.000	×1.200	4.12%

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 4.33 → 5.18, 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 AAArkansas Travelers · 58 IPFIP 3.50 → 4.84 (+1.34)K% 25.9% → 20.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.86%	—	×0.810	20.94%
BB% (unintentional) /BF	7.22%	—	×1.100	7.95%
HR / BF /BF	3.04%	÷0.800	×1.200	4.56%

Result: FIP 3.50 → 4.84, 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 AAWichita Wind Surge · 65 IPFIP 3.08 → 3.79 (+0.70)K% 21.1% → 17.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.07%	—	×0.810	17.07%
BB% (unintentional) /BF	9.29%	—	×1.100	10.21%
HR / BF /BF	1.07%	÷0.845	×1.200	1.52%

Result: FIP 3.08 → 3.79, 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 AAWichita Wind Surge · 38 IPFIP 4.38 → 4.84 (+0.47)K% 23.4% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.43%	—	×0.810	18.98%
BB% (unintentional) /BF	10.86%	—	×1.100	11.94%
HR / BF /BF	3.43%	÷1.231	×1.200	3.34%

Result: FIP 4.38 → 4.84, 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+Wisconsin Timber Rattlers · 24 IPFIP 2.32 → 3.39 (+1.07)K% 34.8% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.78%	—	×0.770	26.78%
BB% (unintentional) /BF	7.61%	—	×1.150	8.75%
HR / BF /BF	2.17%	÷1.033	×1.250	2.63%

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 107).

Result: FIP 2.32 → 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).

2022 A+Wisconsin Timber Rattlers · 34 IPFIP 3.41 → 4.54 (+1.13)K% 27.8% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.81%	—	×0.770	21.42%
BB% (unintentional) /BF	15.23%	—	×1.150	17.52%
HR / BF /BF	1.32%	÷0.885	×1.250	1.87%

Result: FIP 3.41 → 4.54, 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 AABiloxi Shuckers · 23 IPFIP 4.50 → 5.23 (+0.74)K% 21.2% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.19%	—	×0.810	17.16%
BB% (unintentional) /BF	17.80%	—	×1.100	19.58%
HR / BF /BF	1.69%	÷1.012	×1.200	2.01%

Result: FIP 4.50 → 5.23, 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 A+Wisconsin Timber Rattlers · 49 IPFIP 2.49 → 3.48 (+0.99)K% 36.0% → 27.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.00%	—	×0.770	27.72%
BB% (unintentional) /BF	10.50%	—	×1.150	12.07%
HR / BF /BF	2.00%	÷1.155	×1.250	2.17%

Result: FIP 2.49 → 3.48, 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
Taylor Floyd (OGILVIE)	—	—	4.87	18.7%	8.9%	3.4%	—	5.07	18.8%	9.4%	95	+0.20	—	—	—
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	88
Tyler Walker R 2005 · 4.19 FIP	29	SU	4.19	19.4%	7.5%	3.2%	.303	3.61	19.7%	11.3%	93	-0.58	2.38	289	86
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	85
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	84
Bo Schultz R 2015 · 4.30 FIP	29	SU	4.30	18.3%	7.9%	3.2%	.218	3.49	15.1%	8.9%	77	-0.81	2.73	141	84
Diego Moreno R 2016 · 3.75 FIP	29	SU	3.75	21.0%	8.2%	2.5%	.347	3.13	17.8%	11.9%	54	-0.62	2.29	187	83
Francisco Mendoza R 2016 · 3.81 FIP	28	SU	3.81	17.9%	7.7%	2.3%	.344	—	—	—	—	—	3.13	120	82
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	82
Brandon Cunniff R 2017 · 4.79 FIP	28	SU	4.79	20.1%	11.6%	3.5%	.275	6.80	13.9%	-1.9%	30	+2.01	3.89	180	82
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	82
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	81
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	81
Tyler Sturdevant R 2015 · 4.37 FIP	29	SU	4.37	21.3%	8.5%	3.6%	.241	3.97	18.5%	11.9%	118	-0.40	3.44	149	81
Gregory Infante R 2016 · 4.47 FIP	29	SU	4.47	19.0%	12.3%	2.6%	.333	3.43	22.5%	15.8%	120	-1.04	2.97	230	80
Coleman Huntley III R 2022 · 4.05 FIP	29	SU	4.05	24.4%	10.9%	3.0%	.311	2.38	20.9%	12.6%	25	-1.67	2.38	160	80
Adrian Garza R 2017 · 4.47 FIP	29	SU	4.47	16.0%	7.0%	3.4%	.351	5.18	9.7%	4.1%	113	+0.71	3.94	229	80
Grant Black R 2023 · 5.49 FIP	29	SU	5.49	15.9%	11.3%	4.2%	.352	—	—	—	—	—	4.46	215	79
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	79
Ryan Doolittle R 2016 · 4.38 FIP	28	SU	4.38	13.9%	7.1%	2.8%	.269	—	—	—	—	—	4.03	101	79
Santiago Casilla R 2009 · 4.44 FIP	29	SU	4.44	15.0%	9.4%	2.6%	.324	3.29	22.1%	13.0%	170	-1.15	2.76	647	79

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	54	18.8%	9.1%	1.36	4.93
J. C. Gutierrez ('07-'14, -0 WAR*)	1.4	57	19.8%*	8.5%*	1.19*	4.72*
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*