Tyler Wells

P Tampa Bay Rays

Age 32 RHP 6'8" / 270 lbs MLB peak 0.4 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MLBBAL	3	3	15	5.87	4.53	19.4%	4.5%	0.2
2025	30	MIX3 levels	10	10	47	2.68	3.76	23.1%	4.4%	0.9	K 21.5% · BB 4.2% · FIP 4.10
2026	31	MIX2 levels	58	0	73	2.33	3.20	26.1%	6.0%	1.2	K 26.0% · BB 6.1% · FIP 3.31
2027PROJ	32	MLBTB	57	0	60	3.77	3.91	24.4%	5.8%	0.5
2028PROJ	33	MLBTB	45	0	47	4.02	4.19	23.6%	6.3%	0.2
2029PROJ	34	MLBTB	33	0	35	4.30	4.49	22.7%	6.8%	0.0

Last 3 seasons WAR 2.3 · Next 3 projected WAR 0.7Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs90

K%71

FB Velo34

Form1.42 ERA (proj 3.77) · K 27.5% (proj 24.4%) · BB 7.2% (proj 5.8%) · last 90d · 19 IP through Oct 27

CompsMiguel Socolovich (age 32) · Spencer Bivens (age 30) · Mitch Lively (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9688vR 80

ERA3.77

FIP3.91

K%24.4%

BB%5.8%

K-BB%18.6%

Proj IP60

Value2027 · WAR

Runs saved vs league avg · 60 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL7070

CMD5555

K†6060

Statcast Percentiles

FB Velo

p3493.4

Whiff%

p8430.6%

p7126.0%

xwOBA vs

p900.266

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)
2016	21	ROK MLE	Elizabethton Twins	10	10	47	202	59	17	0	100%	4.7	19.9%	10.5%	9.3%	0.0%	3.23	2.76	—
2016	21	ROK RAW	Elizabethton Twins	10	10	47	202	59	17	0	100%	4.7	29.2%	8.4%	20.8%	0.0%	3.23	1.68	—
2017	22	MIX MLE	2 levels	18	15	89	368	108	27	6	83%	4.9	21.5%	8.8%	12.7%	2.2%	3.03	3.58	—
2017	22	MIX RAW	2 levels	18	15	89	368	108	27	6	83%	4.9	29.3%	7.3%	22.0%	1.6%	3.03	2.46	—
2018	23	MIX MLE	2 levels	22	21	119	460	121	31	7	95%	5.4	20.6%	7.6%	13.0%	1.8%	2.49	3.31	—
2018	23	MIX RAW	2 levels	22	21	119	460	121	31	7	95%	5.4	26.3%	6.7%	19.6%	1.5%	2.49	2.61	—
2021	26	MLB MLE	Baltimore Orioles	44	0	57	224	65	12	9	0%	1.3	29.0%	5.4%	23.7%	3.6%	4.11	3.32	+0.8
2021	26	MLB RAW	Baltimore Orioles	44	0	57	224	65	12	9	0%	1.3	29.0%	5.4%	23.7%	4.0%	4.11	3.50	+0.7
2022	27	MIX MLE	2 levels	24	24	106	431	79	28	16	100%	4.4	18.0%	6.6%	11.3%	3.8%	4.25	4.51	+1.1
2022	27	MIX RAW	2 levels	24	24	106	431	79	28	16	100%	4.4	18.3%	6.5%	11.8%	3.7%	4.25	4.36	+1.3
2023	28	MIX MLE	3 levels	35	23	133	534	131	41	28	66%	3.8	24.9%	7.2%	17.7%	5.4%	3.85	4.86	+0.8
2023	28	MIX RAW	3 levels	35	23	133	534	131	41	28	66%	3.8	24.5%	7.7%	16.9%	5.2%	3.85	4.79	+0.9
2024	29	MLB MLE	Baltimore Orioles	3	3	15	67	13	3	3	100%	5.1	19.4%	4.5%	14.9%	4.5%	5.87	4.50	+0.2
2024	29	MLB MLE	Baltimore Orioles	3	3	15	67	13	3	3	100%	5.1	19.4%	4.5%	14.9%	4.5%	5.87	4.50	+0.2
2024	29	MLB RAW	Baltimore Orioles	3	3	15	67	13	3	3	100%	5.1	19.4%	4.5%	14.9%	4.5%	5.87	4.53	+0.2
2025	30	MIX MLE	3 levels	10	10	47	182	42	8	7	100%	4.7	21.5%	4.2%	17.3%	4.2%	2.68	4.10	+0.7
2025	30	MIX MLE	3 levels	10	10	47	182	42	8	7	100%	4.7	21.5%	4.2%	17.3%	4.2%	2.68	4.10	+0.7
2025	30	MIX RAW	3 levels	10	10	47	182	42	8	7	100%	4.7	23.1%	4.4%	18.7%	3.8%	2.68	3.76	+0.9
2026	31	MIX MLE	2 levels	58	0	73	284	74	17	8	0%	1.3	26.0%	6.1%	19.9%	3.0%	2.33	3.31	+1.1
2026	31	MIX MLE	2 levels	58	0	73	284	74	17	8	0%	1.3	26.0%	6.1%	19.9%	3.0%	2.33	3.31	+1.1
2026	31	MIX RAW	2 levels	58	0	73	284	74	17	8	0%	1.3	26.1%	6.0%	20.1%	2.8%	2.33	3.20	+1.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			156	50	388	1543	361	96	65	32%	2.5	23.4%	6.2%	17.2%	4.2%	3.68	4.16	+1.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	TB	57	0	60	253	62	15	8	0%	1.1	24.4%	5.8%	18.6%	3.2%	3.77	3.91	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	TB	45	0	47	198	47	12	7	0%	1.0	23.6%	6.3%	17.3%	3.5%	4.02	4.19	+0.2
2029	34	MLB MLE	TB	33	0	35	147	33	10	6	0%	1.1	22.7%	6.8%	15.9%	3.8%	4.30	4.49	+0.0
2028	33	MLB CTX	TB	45	0	47	198	47	12	7	0%	1.0	23.6%	6.3%	17.3%	3.5%	4.02	4.19	+0.2
2029	34	MLB CTX	TB	33	0	35	148	34	10	6	0%	1.1	22.7%	6.8%	15.9%	3.8%	4.30	4.49	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		234	50	470	1888	441	118	77	21%	2.0	23.4%	6.3%	17.1%	4.1%	3.76	4.17	+2.1
/ 200 IP	—	RAW		99	21	200	803	188	50	33	21%	2.0	23.4%	6.3%	17.1%	4.1%	3.76	4.17	+0.9
Career	—	MLE		224	106	688	2752	615	196	88	47%	3.1	22.3%	7.1%	15.2%	3.2%	3.35	3.88	+2.0
/ 200 IP	—	MLE		65	31	200	800	179	57	26	47%	3.1	22.3%	7.1%	15.2%	3.2%	3.35	3.88	+0.9

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.

2025 AAANorfolk Tides · 23 IPFIP 3.59 → 4.09 (+0.50)K% 24.5% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.47%	—	×0.860	21.04%
BB% (unintentional) /BF	6.38%	—	×0.900	5.74%
HR / BF /BF	3.19%	÷0.945	×1.100	3.71%

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 89).

Result: FIP 3.59 → 4.09, 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 AABowie Baysox · 9 IPFIP 5.63 → 6.04 (+0.41)K% 20.0% → 16.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.810	16.20%
BB% (unintentional) /BF	8.57%	—	×1.100	9.43%
HR / BF /BF	5.71%	÷1.208	×1.200	5.68%

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 142).

Result: FIP 5.63 → 6.04, 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).

2023 AAANorfolk Tides · 6 IPFIP 4.70 → 5.01 (+0.31)K% 24.1% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.14%	—	×0.860	20.76%
BB% (unintentional) /BF	13.79%	—	×0.900	12.41%
HR / BF /BF	3.45%	÷0.995	×1.100	3.81%

Result: FIP 4.70 → 5.01, 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).

2018 A+Fort Myers Miracle · 87 IPFIP 2.66 → 3.41 (+0.75)K% 24.6% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.62%	—	×0.770	18.96%
BB% (unintentional) /BF	5.11%	—	×1.150	5.87%
HR / BF /BF	1.80%	÷1.059	×1.250	2.13%

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 112).

Result: FIP 2.66 → 3.41, 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 AAChattanooga Lookouts · 33 IPFIP 2.34 → 3.07 (+0.73)K% 30.7% → 24.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.71%	—	×0.810	24.87%
BB% (unintentional) /BF	11.02%	—	×1.100	12.13%
HR / BF /BF	0.79%	÷0.975	×1.200	0.97%

Result: FIP 2.34 → 3.07, 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).

2017 ACedar Rapids Kernels · 75 IPFIP 2.56 → 3.71 (+1.15)K% 29.6% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.58%	—	×0.740	21.89%
BB% (unintentional) /BF	7.07%	—	×1.180	8.35%
HR / BF /BF	1.93%	÷0.984	×1.300	2.55%

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 97).

Result: FIP 2.56 → 3.71, 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).

2017 ROKGCL Twins · 14 IPFIP 1.84 → 2.88 (+1.04)K% 28.1% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.07%	—	×0.680	19.09%
BB% (unintentional) /BF	8.77%	—	×1.250	10.96%
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 1.84 → 2.88, 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).

2016 ROKElizabethton Twins · 47 IPFIP 1.70 → 2.76 (+1.06)K% 29.2% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.21%	—	×0.680	19.86%
BB% (unintentional) /BF	8.42%	—	×1.250	10.52%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Result: FIP 1.70 → 2.76, 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 Wells (OGILVIE)	—	—	3.91	24.4%	5.8%	3.2%	—	4.32	23.2%	16.7%	82	+0.41	—	—	—
Miguel Socolovich R 2018 · 3.55 FIP	32	SU	3.55	20.8%	5.6%	2.7%	.338	3.55	18.4%	13.7%	42	+0.00	2.65	299	61
Spencer Bivens R 2024 · 4.07 FIP	30	SU	4.07	18.0%	5.8%	3.2%	.265	3.88	18.2%	10.9%	157	-0.19	3.52	391	57
Mitch Lively R 2017 · 3.47 FIP	31	SP-	3.47	17.0%	6.4%	1.8%	.304	—	—	—	—	—	2.39	158	57
Nick Martinez R 2023 · 3.62 FIP	32	SU	3.62	23.0%	8.5%	2.5%	.286	3.71	17.3%	13.0%	488	+0.09	2.94	1,288	57
Radhames Liz R 2015 · 2.81 FIP	31	SW	2.81	24.8%	9.2%	1.2%	.283	4.45	21.8%	7.9%	23	+1.64	2.81	219	56
Chris Jakubauskas R 2011 · 4.42 FIP	32	SW	4.42	15.7%	7.9%	3.0%	.339	—	—	—	—	—	4.42	165	56
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	55
Todd Redmond R 2015 · 3.86 FIP	30	SW	3.86	15.4%	7.1%	2.1%	.311	—	—	—	—	—	3.21	247	55
Jim Miller R 2015 · 3.95 FIP	33	SU	3.95	18.8%	4.1%	3.5%	.275	5.43	20.4%	6.3%	17	+1.48	3.95	140	55
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	54
Dale Thayer R 2013 · 3.62 FIP	32	SU	3.62	23.7%	7.4%	2.9%	.287	3.85	20.6%	15.0%	103	+0.23	2.75	239	54
Austin Bibens-Dirkx R 2017 · 5.03 FIP	32	SW	5.03	14.0%	6.6%	4.2%	.268	5.28	17.5%	9.7%	166	+0.25	3.97	567	54
George Kontos R 2017 · 3.71 FIP	32	SU	3.71	25.2%	6.5%	3.5%	.287	4.41	14.7%	8.6%	97	+0.70	2.56	421	53
Chris Hatcher R 2017 · 4.31 FIP	32	SU	4.31	24.5%	7.4%	4.3%	.291	5.32	18.0%	8.4%	36	+1.01	2.51	246	53
Cody Satterwhite R 2017 · 4.22 FIP	30	SU	4.22	17.0%	7.1%	3.0%	.310	—	—	—	—	—	3.69	147	53
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	53
Tony Barnette R 2016 · 3.05 FIP	32	SU	3.05	19.9%	6.1%	1.6%	.281	3.26	23.4%	17.0%	84	+0.21	2.61	144	53
Gregory Infante R 2018 · 4.07 FIP	31	SU	4.07	22.0%	4.6%	4.1%	.291	—	—	—	—	—	2.97	230	52
Spencer Patton R 2021 · 3.04 FIP	33	SU	3.04	27.9%	8.7%	2.2%	.305	4.97	21.2%	10.4%	88	+1.93	2.79	239	52
Jared Burton R 2013 · 3.20 FIP	32	SU	3.20	21.7%	6.0%	2.1%	.279	3.92	18.4%	10.0%	78	+0.72	3.09	367	52

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	2.6	66	23.5%	6.3%	1.55	3.76
Luis DeLeon ('81-'89, 4 WAR*)	1.7	67	25.0%*	5.7%*	1.69*	3.69*
Bob Lacey ('77-'84, 2 WAR*)	2.3	75	20.5%*	7.3%*	1.35*	4.11*
Mark Huismann ('83-'91, 1 WAR*)	1.5	74	23.8%*	6.5%*	1.30*	4.49*
Tyler Duffey ('24)	2.4	61	23.1%	7.0%	1.24	4.57
Tyler Lyons ('20)	1.4	57	24.3%	7.6%	1.27	4.30
Yusmeiro Petit ('21)	4.5	70	20.7%	5.5%	1.36	3.93