Tyler Thomas

P Salt Lake Bees

Age 31 LHP 6'1" / 175 lbs AAA

Overview

AAAPROSPECT

MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	26	MIX2 levels	27	0	44	6.14	5.19	26.2%	13.4%	—	K 21.7% · BB 15.1% · FIP 6.20
2023	27	MIX2 levels	24	0	35	2.86	2.23	28.5%	9.0%	—	K 23.4% · BB 8.8% · FIP 2.66
2024	28	AAALAA	31	2	45	5.44	4.26	21.5%	14.4%	—	K 18.5% · BB 12.9% · FIP 4.48
2025	29	No MLB games played
2026	30	No MLB games played
2027PROJ	31	MLBLAA	2	0	2	4.70	4.70	21.0%	10.8%	-0.0
2028PROJ37% MLB	32	MLBLAA	7	0	7	4.79	4.88	20.8%	11.0%	-0.0

Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsRaul Valdes (age 32) · Andrew Barbosa (age 29) · Edward Paredes (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 106114vR 122

ERA4.70

FIP4.70

K%21.0%

BB%10.8%

K-BB%10.2%

Proj IP25

Value2027 · WAR

Runs saved vs league avg · 25 IP

Grades · Contract

Scouting Grades

K†5050

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)
2018	22	MIX MLE	2 levels	22	20	105	416	108	26	7	91%	4.8	19.3%	7.3%	12.0%	1.8%	3.00	3.39	—
2018	22	MIX RAW	2 levels	22	20	105	416	108	26	7	91%	4.8	26.0%	6.2%	19.7%	1.7%	3.00	2.65	—
2019	23	A+ MLE	Down East Wood Ducks	2	2	9	36	7	5	1	100%	4.3	19.4%	13.9%	5.6%	2.8%	5.19	4.74	—
2019	23	A+ RAW	Down East Wood Ducks	2	2	9	36	7	5	1	100%	4.3	19.4%	13.9%	5.6%	2.8%	5.19	4.72	—
2021	25	MIX MLE	3 levels	33	0	59	253	71	22	5	0%	1.8	24.2%	9.6%	14.6%	2.3%	3.66	3.55	—
2021	25	MIX RAW	3 levels	33	0	59	253	71	22	5	0%	1.8	28.1%	8.7%	19.4%	2.0%	3.66	2.91	—
2022	26	MIX MLE	2 levels	27	0	44	202	53	27	9	0%	1.6	21.7%	15.1%	6.7%	5.5%	6.14	6.20	—
2022	26	MIX RAW	2 levels	27	0	44	202	53	27	9	0%	1.6	26.2%	13.4%	12.9%	4.5%	6.14	5.19	—
2023	27	MIX MLE	2 levels	24	0	35	144	41	13	1	0%	1.4	23.4%	8.8%	14.6%	0.8%	2.86	2.66	—
2023	27	MIX RAW	2 levels	24	0	35	144	41	13	1	0%	1.4	28.5%	9.0%	19.4%	0.7%	2.86	2.23	—
2024	28	AAA MLE	Salt Lake Bees	31	2	45	209	45	30	4	6%	1.4	18.5%	12.9%	5.6%	2.4%	5.44	4.48	—
2024	28	AAA MLE	Salt Lake Bees	31	2	45	209	45	30	4	6%	1.4	18.5%	12.9%	5.6%	2.4%	5.44	4.48	—
2024	28	AAA RAW	Salt Lake Bees	31	2	45	209	45	30	4	6%	1.4	21.5%	14.4%	7.2%	1.9%	5.44	4.26	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	LAA	2	0	2	8	2	1	0	0%	1.0	21.0%	10.8%	10.2%	3.0%	4.70	4.70	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	LAA	18	0	19	81	17	9	3	0%	1.1	20.8%	11.0%	9.8%	3.2%	4.79	4.88	-0.1
2028	32	MLB CTX	LAA	7	0	7	30	6	3	1	0%	1.0	20.8%	11.0%	9.8%	3.2%	4.79	4.88	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		7	0	7	30	6	3	1	0%	1.0	20.8%	11.0%	9.8%	3.2%	4.79	4.50	+0.0
/ 200 IP	—	RAW		190	0	200	844	170	85	28	0%	1.1	20.8%	11.0%	9.8%	3.2%	4.79	4.50	+0.1
Career	—	MLE		139	24	296	1260	265	130	32	17%	2.1	21.0%	10.3%	10.7%	2.5%	4.01	4.01	-0.1
/ 200 IP	—	MLE		94	16	200	851	179	88	21	17%	2.1	21.0%	10.3%	10.7%	2.5%	4.01	4.01	-0.8

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.

2024 AAASalt Lake Bees · 45 IPFIP 4.15 → 4.48 (+0.33)K% 21.5% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.53%	—	×0.860	18.52%
BB% (unintentional) /BF	14.35%	—	×0.900	12.92%
HR / BF /BF	1.91%	÷0.886	×1.100	2.38%

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 77).

Result: FIP 4.15 → 4.48, 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).

2023 AABinghamton Rumble Ponies · 23 IPFIP 0.81 → 1.47 (+0.66)K% 36.1% → 29.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.14%	—	×0.810	29.28%
BB% (unintentional) /BF	6.02%	—	×1.100	6.63%
HR / BF /BF	0.00%	÷0.925	×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 85).

Result: FIP 0.81 → 1.47, 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 AAASyracuse Mets · 12 IPFIP 4.14 → 4.27 (+0.13)K% 18.0% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.03%	—	×0.860	15.51%
BB% (unintentional) /BF	13.11%	—	×0.900	11.80%
HR / BF /BF	1.64%	÷1.003	×1.100	1.80%

Result: FIP 4.14 → 4.27, 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 AAFrisco RoughRiders · 41 IPFIP 4.88 → 6.20 (+1.33)K% 26.8% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.84%	—	×0.810	21.74%
BB% (unintentional) /BF	13.68%	—	×1.100	15.05%
HR / BF /BF	4.21%	÷0.915	×1.200	5.52%

Result: FIP 4.88 → 6.20, 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 AAFrisco RoughRiders · 41 IPFIP 3.43 → 4.14 (+0.70)K% 28.8% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.81%	—	×0.810	23.34%
BB% (unintentional) /BF	9.60%	—	×1.100	10.56%
HR / BF /BF	2.82%	÷1.114	×1.200	3.04%

Result: FIP 3.43 → 4.14, 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+Hickory Crawdads · 13 IPFIP 0.83 → 1.62 (+0.79)K% 35.2% → 27.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.19%	—	×0.770	27.09%
BB% (unintentional) /BF	5.56%	—	×1.150	6.39%
HR / BF /BF	0.00%	÷0.881	×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 76).

Result: FIP 0.83 → 1.62, 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 AAARound Rock Express · 5 IPFIP 3.87 → 3.97 (+0.10)K% 4.5% → 4.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	4.55%	—	×0.880	4.00%
BB% (unintentional) /BF	9.09%	—	×1.050	9.55%
HR / BF /BF	0.00%	÷0.958	×1.100	0.00%

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 92).

Result: FIP 3.87 → 3.97, 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 A+Down East Wood Ducks · 9 IPFIP 4.74 → 5.51 (+0.77)K% 19.4% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.44%	—	×0.770	14.97%
BB% (unintentional) /BF	13.89%	—	×1.150	15.97%
HR / BF /BF	2.78%	÷1.152	×1.250	3.02%

Result: FIP 4.74 → 5.51, 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 Thomas (OGILVIE)	—	—	4.70	21.0%	10.8%	3.0%	—	4.88	20.8%	9.8%	19	+0.18	—	—	—
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	83
Andrew Barbosa L 2017 · 4.67 FIP	29	SU	4.67	20.2%	9.6%	3.8%	.301	—	—	—	—	—	2.70	175	79
Edward Paredes L 2018 · 3.81 FIP	31	SU	3.81	22.7%	11.9%	2.0%	.351	5.10	21.5%	14.2%	18	+1.29	2.36	130	76
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	73
Nick Hagadone L 2017 · 3.74 FIP	31	SU	3.74	22.6%	9.3%	2.5%	.267	—	—	—	—	—	2.97	141	72
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	71
Adam Liberatore L 2018 · 4.28 FIP	31	SU	4.28	18.6%	9.1%	2.9%	.354	—	—	—	—	—	2.38	124	71
Jason Gurka L 2019 · 5.13 FIP	31	SW	5.13	15.5%	7.6%	4.3%	.382	—	—	—	—	—	2.82	183	71
Ryan O'Rourke L 2019 · 4.08 FIP	31	SU	4.08	22.1%	14.3%	1.9%	.290	—	—	—	—	—	3.05	145	70
David Purcey L 2013 · 3.79 FIP	31	SU	3.79	20.4%	11.5%	1.7%	.227	—	—	—	—	—	3.60	206	70
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	70
Juan Pablo Perez L 2007 · 5.32 FIP	28	SU	5.32	17.5%	14.0%	3.5%	.324	—	—	—	—	—	1.75	104	68
James Jones L 2019 · 4.28 FIP	30	SU	4.28	21.9%	13.0%	2.5%	.230	4.65	23.9%	8.8%	35	+0.37	3.58	127	68
Brian Shouse L 2002 · 5.54 FIP	33	SU	5.54	15.5%	11.3%	4.2%	.245	3.31	16.3%	10.7%	159	-2.23	2.32	339	68
Justin Marks L 2017 · 3.83 FIP	29	SW	3.83	18.7%	11.0%	1.7%	.317	—	—	—	—	—	3.83	324	67
Buddy Baumann L 2018 · 4.87 FIP	30	SU	4.87	20.5%	11.9%	3.6%	.258	—	—	—	—	—	2.92	155	67
Cory Luebke L 2016 · 3.88 FIP	31	SU	3.88	26.4%	9.1%	3.4%	.354	—	—	—	—	—	2.80	216	67
Tom Martin L 2001 · 5.68 FIP	31	SU	5.68	14.1%	9.4%	4.7%	.311	4.25	19.8%	11.1%	96	-1.43	3.40	303	65
Buddy Boshers L 2019 · 3.73 FIP	31	SU	3.73	25.3%	10.4%	2.6%	.294	—	—	—	—	—	2.76	239	65
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	65