Tyler Holton

P Detroit Tigers

Age 31 LHP 6'2" / 200 lbs MLB peak 0.1 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR
2024	28	MLBDET	66	9	94	2.19	2.94	21.8%	4.5%	1.8
2025	29	MLBDET	70	6	79	3.66	4.56	20.5%	5.1%	-0.0
2026	30	MLBDET	67	3	72	2.75	3.81	18.3%	6.3%	0.6
2027PROJ	31	MLBDET	57	0	60	3.94	4.38	18.9%	5.7%	0.1
2028PROJ95% MLB	32	MLBDET	37	0	39	4.36	4.64	18.1%	6.1%	-0.0
2029PROJ95% MLB	33	MLBDET	24	0	25	4.69	4.92	17.2%	6.6%	-0.1

Last 3 seasons WAR 2.4 · Next 3 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs62

K%23

FB Velo10

Form2.19 ERA (proj 3.94) · K 18.0% (proj 18.9%) · BB 8.0% (proj 5.7%) ▼ last 90d · 25 IP through Oct 27

CompsTony Watson (age 31) · Brian Fuentes (age 31) · Pedro Feliciano (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 93102vR 110

ERA3.94

FIP4.38

K%18.9%

BB%5.7%

K-BB%13.2%

Proj IP60

Value2027 · WAR

Runs saved vs league avg · 60 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL6565

CMD5555

K†4545

Statcast Percentiles

FB Velo

p1091.5

Whiff%

p3723.4%

p2318.3%

xwOBA vs

p620.300

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)
2019	23	ROK MLE	ACL D-backs	4	2	5	21	5	4	0	50%	1.3	23.8%	19.0%	4.8%	0.0%	3.38	3.50	—
2019	23	ROK RAW	ACL D-backs	4	2	5	21	5	4	0	50%	1.3	23.8%	19.0%	4.8%	0.0%	3.38	3.48	—
2021	25	MIX MLE	2 levels	26	11	64	294	78	18	7	42%	2.5	22.0%	6.6%	15.4%	2.3%	6.72	3.35	—
2021	25	MIX RAW	2 levels	26	11	64	294	78	18	7	42%	2.5	26.5%	6.1%	20.4%	2.4%	6.72	2.93	—
2022	26	MIX MLE	2 levels	34	2	54	222	49	19	6	6%	1.6	20.7%	9.8%	10.9%	3.1%	4.19	4.30	+0.2
2022	26	MIX RAW	2 levels	34	2	54	222	49	19	6	6%	1.6	22.1%	8.6%	13.5%	2.7%	4.19	3.79	+0.5
2023	27	MIX MLE	2 levels	63	1	93	357	81	20	13	2%	1.5	22.8%	5.2%	17.6%	2.9%	2.52	3.43	+1.2
2023	27	MIX RAW	2 levels	63	1	93	357	81	20	13	2%	1.5	22.7%	5.6%	17.1%	3.6%	2.52	3.82	+0.8
2024	28	MLB MLE	Detroit Tigers	66	9	94	354	77	16	7	14%	1.4	21.8%	4.5%	17.2%	2.1%	2.19	2.97	+1.8
2024	28	MLB MLE	Detroit Tigers	66	9	94	354	77	16	7	14%	1.4	21.8%	4.5%	17.2%	2.1%	2.19	2.97	+1.8
2024	28	MLB RAW	Detroit Tigers	66	9	94	354	77	16	7	14%	1.4	21.8%	4.5%	17.2%	2.0%	2.19	2.94	+1.8
2025	29	MLB MLE	Detroit Tigers	70	6	79	312	64	16	15	9%	1.1	20.5%	5.1%	15.4%	5.0%	3.66	4.77	-0.2
2025	29	MLB MLE	Detroit Tigers	70	6	79	312	64	16	15	9%	1.1	20.5%	5.1%	15.4%	5.0%	3.66	4.77	-0.2
2025	29	MLB RAW	Detroit Tigers	70	6	79	312	64	16	15	9%	1.1	20.5%	5.1%	15.4%	4.8%	3.66	4.56	-0.0
2026	30	MLB MLE	Detroit Tigers	67	3	72	301	55	19	8	4%	1.1	18.3%	6.3%	12.0%	2.8%	2.75	3.88	+0.6
2026	30	MLB MLE	Detroit Tigers	67	3	72	301	55	19	8	4%	1.1	18.3%	6.3%	12.0%	2.8%	2.75	3.88	+0.6
2026	30	MLB RAW	Detroit Tigers	67	3	72	301	55	19	8	4%	1.1	18.3%	6.3%	12.0%	2.7%	2.75	3.81	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			272	19	339	1330	276	70	40	7%	1.2	20.8%	5.3%	15.5%	3.0%	2.65	3.62	+3.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	DET	57	0	60	253	48	15	8	0%	1.1	18.9%	5.7%	13.2%	3.2%	3.94	4.38	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	DET	39	0	41	171	31	11	6	0%	1.0	18.1%	6.1%	11.9%	3.5%	4.36	4.64	-0.0
2029	33	MLB MLE	DET	25	0	27	112	19	7	4	0%	1.1	17.2%	6.6%	10.7%	3.7%	4.69	4.92	-0.1
2028	32	MLB CTX	DET	37	0	39	165	30	10	6	0%	1.1	18.1%	6.1%	11.9%	3.5%	4.36	4.64	-0.0
2029	33	MLB CTX	DET	24	0	25	106	18	7	4	0%	1.0	17.2%	6.6%	10.7%	3.7%	4.69	4.92	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		333	19	403	1600	324	87	50	6%	1.2	20.2%	5.4%	14.8%	3.1%	2.94	3.78	+3.7
/ 200 IP	—	RAW		165	9	200	793	161	43	25	6%	1.2	20.2%	5.4%	14.8%	3.1%	2.94	3.78	+1.8
Career	—	MLE		330	34	461	1861	393	115	55	10%	1.4	21.1%	6.2%	15.0%	3.0%	3.47	3.73	+3.6
/ 200 IP	—	MLE		143	15	200	807	170	50	24	10%	1.4	21.1%	6.2%	15.0%	3.0%	3.47	3.73	+1.8

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.

2023 AAAToledo Mud Hens · 8 IPFIP 9.11 → 10.72 (+1.60)K% 21.2% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.21%	—	×0.860	18.24%
BB% (unintentional) /BF	9.09%	—	×0.900	8.18%
HR / BF /BF	12.12%	÷0.901	×1.100	14.80%

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 80).

Result: FIP 9.11 → 10.72, 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 AAAReno Aces · 45 IPFIP 3.79 → 4.30 (+0.51)K% 23.5% → 20.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.50%	—	×0.880	20.68%
BB% (unintentional) /BF	9.29%	—	×1.050	9.75%
HR / BF /BF	2.73%	÷0.965	×1.100	3.12%

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 93).

Result: FIP 3.79 → 4.30, 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 AAAmarillo Sod Poodles · 48 IPFIP 3.14 → 3.54 (+0.41)K% 26.2% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.17%	—	×0.810	21.20%
BB% (unintentional) /BF	5.61%	—	×1.100	6.17%
HR / BF /BF	2.80%	÷1.271	×1.200	2.65%

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 154).

Result: FIP 3.14 → 3.54, 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).

2021 AAAReno Aces · 16 IPFIP 2.41 → 2.84 (+0.43)K% 27.5% → 24.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.50%	—	×0.880	24.20%
BB% (unintentional) /BF	7.50%	—	×1.050	7.88%
HR / BF /BF	1.25%	÷0.958	×1.100	1.44%

Result: FIP 2.41 → 2.84, 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).

2019 ROKACL D-backs · 5 IPFIP 3.50 → 4.75 (+1.25)K% 23.8% → 16.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.81%	—	×0.680	16.19%
BB% (unintentional) /BF	19.05%	—	×1.250	23.81%
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 3.50 → 4.75, 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
Tyler Holton (OGILVIE)	—	—	4.38	18.9%	5.7%	3.2%	—	4.75	17.7%	11.4%	67	+0.37	—	—	—
Tony Watson L 2016 · 4.37 FIP	31	SU	4.37	21.3%	7.0%	4.0%	.227	3.43	21.4%	16.9%	187	-0.94	2.21	648	74
Brian Fuentes L 2007 · 3.68 FIP	31	SU	3.68	22.0%	9.0%	2.4%	.235	3.19	25.4%	16.4%	166	-0.49	2.08	602	72
Pedro Feliciano L 2008 · 3.90 FIP	31	SU	3.90	21.1%	7.6%	2.9%	.309	3.02	22.1%	14.9%	122	-0.88	2.69	378	72
Brian Duensing L 2014 · 4.31 FIP	31	SU	4.31	14.4%	7.9%	2.6%	.267	3.49	19.1%	12.4%	148	-0.82	2.57	799	70
Phil Coke L 2013 · 3.64 FIP	31	SU	3.64	16.9%	7.9%	1.8%	.308	3.47	17.4%	10.1%	159	-0.17	1.31	500	69
Jeremy Bleich L 2018 · 3.69 FIP	31	SU	3.69	20.3%	6.6%	2.7%	.296	4.41	20.1%	13.1%	33	+0.72	3.20	241	68
Adam Liberatore L 2018 · 4.28 FIP	31	SU	4.28	18.6%	9.1%	2.9%	.354	—	—	—	—	—	2.38	124	67
Aaron Fultz L 2005 · 3.59 FIP	31	SU	3.59	18.9%	7.3%	2.1%	.200	3.50	19.0%	11.4%	108	-0.09	3.46	480	67
Damaso Marte L 2006 · 3.33 FIP	31	SU	3.33	24.7%	9.8%	2.0%	.284	3.05	26.2%	17.3%	124	-0.28	2.41	495	67
Colt Hynes L 2016 · 3.55 FIP	31	SU	3.55	22.3%	4.8%	3.1%	.353	3.75	14.1%	9.5%	56	+0.20	3.42	169	67
Vic Darensbourg L 2002 · 5.46 FIP	31	SU	5.46	14.2%	9.4%	4.3%	.304	4.11	9.4%	4.2%	22	-1.35	2.94	287	67
Raul Valdes L 2010 · 4.02 FIP	32	SU	4.02	21.4%	9.9%	2.7%	.301	3.14	27.4%	22.5%	78	-0.88	2.29	160	67
Randy Flores L 2006 · 4.00 FIP	31	SU	4.00	20.4%	9.7%	2.5%	.333	3.30	18.1%	10.5%	93	-0.70	2.51	250	66
Tommy Layne L 2016 · 3.43 FIP	31	SU	3.43	20.3%	9.6%	1.5%	.266	4.25	19.4%	10.0%	90	+0.82	0.55	218	65
George Sherrill L 2008 · 3.86 FIP	31	SU	3.86	24.3%	11.3%	2.5%	.277	3.38	20.6%	12.4%	141	-0.48	2.74	323	65
Nick Ramirez L 2021 · 3.63 FIP	31	SU	3.63	20.2%	8.0%	2.2%	.305	3.17	17.7%	11.9%	169	-0.46	2.91	478	65
Andrew Barbosa L 2017 · 4.67 FIP	29	SU	4.67	20.2%	9.6%	3.8%	.301	—	—	—	—	—	2.70	175	64
Tommy Phelps L 2005 · 3.98 FIP	31	SU	3.98	13.2%	7.5%	1.9%	.280	—	—	—	—	—	3.39	120	64
Nick Hagadone L 2017 · 3.74 FIP	31	SU	3.74	22.6%	9.3%	2.5%	.267	—	—	—	—	—	2.97	141	63
Darin Downs L 2015 · 4.06 FIP	30	SU	4.06	12.9%	4.2%	2.8%	.288	—	—	—	—	—	2.83	107	63

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	2.3	67	20.0%	5.6%	1.21	3.08
Matt Capps ('12)	2.2	63	17.5%	4.6%	1.08	3.52
Keith Foulke ('08)	3.9	72	22.4%	6.1%	1.08	3.33
Addison Reed ('18)	2.3	66	24.5%	6.2%	1.04	3.53
Tim Crews ('87-'92, 3 WAR*)	2.1	71	20.8%*	6.2%*	1.09*	4.11*
Tim Burke ('85-'92, 10 WAR*)	3.5	87	19.7%*	7.4%*	0.93*	3.14*
Rawly Eastwick ('74-'81, 6 WAR*)	2.6	75	19.8%*	6.9%*	1.06*	3.80*