Thomas Pannone

P Nashville Sounds

Age 33 LHP 6'0" / 205 lbs AAA

Overview

AAASP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	29	MIX2 levels	12	9	56	2.89	3.08	23.5%	6.1%	1.6	K 19.9% · BB 5.4% · FIP 3.65
2024	30	AAAScranton/Wilk…	30	30	152	3.54	3.77	21.2%	5.9%	—	K 18.2% · BB 5.3% · FIP 4.04
2026	32	MIX2 levels	24	22	103	4.73	4.08	20.0%	7.1%	1.6	K 17.4% · BB 6.2% · FIP 4.28
2027PROJ	33	MLBMIL	26	26	154	4.57	4.68	16.9%	6.4%	1.3
2028PROJ89% MLB	34	MLBMIL	17	17	104	4.82	4.98	16.0%	6.9%	0.5
2029PROJ85% MLB	35	MLBMIL	12	12	75	5.12	5.32	15.0%	7.5%	0.1

Last 3 seasons WAR 3.2 · Next 3 projected WAR 1.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2019

K%43

xwOBA vs22

FB Velo10

CompsTsuyoshi Wada (age 33) · Sean Nolin (age 33) · Enrique Lechuga (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 108116vR 124

ERA4.57

FIP4.68

K%16.9%

BB%6.4%

K-BB%10.4%

Proj IP165

Value2027 · WAR

Runs saved vs league avg · 165 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1089.7

Whiff%

p5125.5%

p4321.2%

xwOBA vs

p220.345

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)
2015	21	A MLE	Lake County Captains	27	20	116	473	120	37	12	74%	4.3	18.8%	9.2%	9.5%	2.8%	4.02	4.23	—
2015	21	A RAW	Lake County Captains	27	20	116	473	120	37	12	74%	4.3	25.4%	7.8%	17.5%	2.5%	4.02	3.33	—
2016	22	MIX MLE	2 levels	25	24	133	540	122	40	8	96%	5.3	16.9%	8.7%	8.3%	1.6%	2.57	3.63	—
2016	22	MIX RAW	2 levels	25	24	133	540	122	40	8	96%	5.3	22.6%	7.4%	15.2%	1.5%	2.57	2.95	—
2017	23	MIX MLE	2 levels	25	25	145	572	149	35	14	100%	5.8	20.8%	6.8%	14.0%	2.5%	2.36	3.59	—
2017	23	MIX RAW	2 levels	25	25	145	572	149	35	14	100%	5.8	26.0%	6.1%	19.9%	2.4%	2.36	3.02	—
2018	24	MIX MLE	4 levels	21	15	93	399	82	28	17	71%	4.4	19.2%	6.7%	12.5%	4.5%	4.82	4.81	+0.6
2018	24	MIX RAW	4 levels	21	15	93	399	82	28	17	71%	4.4	20.6%	7.0%	13.5%	4.3%	4.82	4.61	+0.9
2019	25	MIX MLE	2 levels	45	13	107	467	110	45	17	29%	2.4	22.5%	9.8%	12.7%	3.7%	5.23	4.49	+0.1
2019	25	MIX RAW	2 levels	45	13	107	467	110	45	17	29%	2.4	23.6%	9.6%	13.9%	3.6%	5.23	4.38	+0.2
2021	27	AAA MLE	Salt Lake Bees	24	21	118	548	82	40	24	88%	4.9	13.2%	7.7%	5.5%	5.3%	7.07	5.88	—
2021	27	AAA RAW	Salt Lake Bees	24	21	118	548	82	40	24	88%	4.9	15.0%	7.3%	7.7%	4.4%	7.07	5.36	—
2022	28	AAA MLE	Worcester Red Sox	14	12	63	262	70	8	7	86%	4.5	23.5%	3.2%	20.3%	3.1%	4.57	3.24	—
2022	28	AAA RAW	Worcester Red Sox	14	12	63	262	70	8	7	86%	4.5	26.7%	3.1%	23.7%	2.7%	4.57	2.70	—
2023	29	MIX MLE	2 levels	12	9	56	230	54	14	5	75%	4.7	19.9%	5.4%	14.5%	2.8%	2.89	3.65	+1.2
2023	29	MIX RAW	2 levels	12	9	56	230	54	14	5	75%	4.7	23.5%	6.1%	17.4%	2.2%	2.89	3.08	+1.6
2024	30	AAA MLE	Scranton/Wilkes-Barre RailRiders	30	30	152	642	136	38	20	100%	5.1	18.2%	5.3%	12.9%	3.3%	3.54	4.04	—
2024	30	AAA MLE	Scranton/Wilkes-Barre RailRiders	30	30	152	642	136	38	20	100%	5.1	18.2%	5.3%	12.9%	3.3%	3.54	4.04	—
2024	30	AAA RAW	Scranton/Wilkes-Barre RailRiders	30	30	152	642	136	38	20	100%	5.1	21.2%	5.9%	15.3%	3.1%	3.54	3.77	—
2026	32	MIX MLE	2 levels	24	22	103	435	87	31	14	92%	4.3	17.4%	6.2%	11.2%	3.4%	4.73	4.28	+1.3
2026	32	MIX MLE	2 levels	24	22	103	435	87	31	14	92%	4.3	17.4%	6.2%	11.2%	3.4%	4.73	4.28	+1.3
2026	32	MIX RAW	2 levels	24	22	103	435	87	31	14	92%	4.3	20.0%	7.1%	12.9%	3.2%	4.73	4.08	+1.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			51	14	122	534	104	48	21	27%	2.4	19.5%	9.0%	10.5%	3.9%	5.47	4.82	-0.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	MIL	26	26	154	650	110	42	21	100%	5.9	16.9%	6.4%	10.4%	3.3%	4.57	4.68	+1.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	MIL	19	19	117	493	79	34	18	100%	6.1	16.0%	6.9%	9.0%	3.6%	4.82	4.98	+0.6
2029	35	MLB MLE	MIL	15	15	89	375	56	28	15	100%	5.9	15.0%	7.5%	7.5%	3.9%	5.12	5.32	+0.1
2028	34	MLB CTX	MIL	17	17	104	439	70	30	16	100%	6.1	16.0%	6.9%	9.0%	3.6%	4.82	4.98	+0.5
2029	35	MLB CTX	MIL	12	12	75	317	47	24	12	100%	6.2	15.0%	7.5%	7.5%	3.9%	5.12	5.32	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		81	44	301	1290	222	102	49	54%	3.7	17.2%	7.9%	9.3%	3.8%	5.16	4.75	+2.3
/ 200 IP	—	RAW		54	29	200	858	148	68	33	54%	3.7	17.2%	7.9%	9.3%	3.8%	5.16	4.75	+1.5
Career	—	MLE		247	191	1086	4568	853	326	151	77%	4.4	18.7%	7.1%	11.5%	3.3%	4.12	4.24	+1.5
/ 200 IP	—	MLE		45	35	200	841	157	60	28	77%	4.4	18.7%	7.1%	11.5%	3.3%	4.12	4.24	+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.

2026 AAANashville Sounds · 100 IPFIP 3.96 → 4.28 (+0.32)K% 20.2% → 17.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.19%	—	×0.860	17.36%
BB% (unintentional) /BF	6.89%	—	×0.900	6.20%
HR / BF /BF	3.09%	÷1.000	×1.100	3.40%

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 3.96 → 4.28, 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 AAAScranton/Wilkes-Barre RailRiders · 152 IPFIP 3.77 → 4.04 (+0.27)K% 21.2% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.18%	—	×0.860	18.22%
BB% (unintentional) /BF	5.92%	—	×0.900	5.33%
HR / BF /BF	3.12%	÷1.045	×1.100	3.28%

Result: FIP 3.77 → 4.04, 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 AAANashville Sounds · 53 IPFIP 3.18 → 3.65 (+0.47)K% 23.1% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.15%	—	×0.860	19.91%
BB% (unintentional) /BF	6.02%	—	×0.900	5.42%
HR / BF /BF	2.31%	÷0.905	×1.100	2.81%

Result: FIP 3.18 → 3.65, 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 AAAWorcester Red Sox · 63 IPFIP 2.70 → 3.24 (+0.54)K% 26.7% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.72%	—	×0.880	23.51%
BB% (unintentional) /BF	3.05%	—	×1.050	3.21%
HR / BF /BF	2.67%	÷0.939	×1.100	3.13%

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 88).

Result: FIP 2.70 → 3.24, 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 AAASalt Lake Bees · 118 IPFIP 5.16 → 5.88 (+0.71)K% 15.0% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.96%	—	×0.880	13.17%
BB% (unintentional) /BF	7.30%	—	×1.050	7.66%
HR / BF /BF	4.38%	÷0.907	×1.100	5.31%

Result: FIP 5.16 → 5.88, 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).

2019 AAABuffalo Bisons · 34 IPFIP 3.55 → 4.06 (+0.51)K% 28.9% → 25.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.87%	—	×0.880	25.41%
BB% (unintentional) /BF	10.56%	—	×1.050	11.09%
HR / BF /BF	2.82%	÷1.000	×1.100	3.10%

Result: FIP 3.55 → 4.06, 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 AAABuffalo Bisons · 37 IPFIP 4.33 → 4.68 (+0.35)K% 26.0% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.97%	—	×0.880	22.86%
BB% (unintentional) /BF	4.55%	—	×1.050	4.77%
HR / BF /BF	5.19%	÷1.080	×1.100	5.29%

Result: FIP 4.33 → 4.68, 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 AANew Hampshire Fisher Cats · 9 IPFIP 3.51 → 4.50 (+0.99)K% 29.3% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.27%	—	×0.810	23.71%
BB% (unintentional) /BF	12.20%	—	×1.100	13.41%
HR / BF /BF	2.44%	÷0.945	×1.200	3.10%

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 89).

Result: FIP 3.51 → 4.50, 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
Thomas Pannone (OGILVIE)	—	—	—	—	—	3.3%	—	5.13	15.5%	8.4%	206	+0.45	—	—	—
Tsuyoshi Wada L 2014 · 3.60 FIP	33	SP	3.60	19.7%	6.2%	2.5%	.290	3.66	16.8%	9.7%	119	+0.06	3.60	188	68
Sean Nolin L 2023 · 5.87 FIP	33	SP	5.87	19.3%	6.4%	6.5%	.286	—	—	—	—	—	3.79	309	58
Enrique Lechuga L 2017 · 3.78 FIP	31	SP	3.78	10.5%	6.1%	1.5%	.390	—	—	—	—	—	3.78	137	56
Kwang Hyun Kim L 2021 · 4.21 FIP	33	SP-	4.21	17.7%	8.2%	2.9%	.266	—	—	—	—	—	3.76	146	55
Matt Dermody L 2023 · 3.87 FIP	33	SP	3.87	20.7%	4.6%	3.5%	.336	—	—	—	—	—	2.38	348	55
Jorge Castillo L 2015 · 4.50 FIP	33	SP	4.50	16.8%	9.2%	3.0%	.292	4.95	12.4%	7.2%	186	+0.45	4.50	408	53
Orlando Lara L 2017 · 4.39 FIP	32	SP	4.39	14.7%	6.5%	3.1%	.346	4.09	22.0%	14.2%	104	-0.30	3.85	426	53
Tomas Solis L 2016 · 4.86 FIP	33	SP	4.86	12.4%	8.5%	3.1%	.273	5.95	10.1%	2.4%	117	+1.09	4.20	327	52
Paul Oseguera L 2016 · 5.62 FIP	32	SP	5.62	5.6%	12.5%	2.6%	.320	—	—	—	—	—	3.83	162	50
Pat Misch L 2015 · 3.94 FIP	33	SP-	3.94	11.6%	7.9%	1.5%	.257	—	—	—	—	—	3.50	265	50
Oscar Rivera L 2015 · 3.68 FIP	34	SP	3.68	14.2%	6.9%	1.7%	.298	4.66	10.4%	3.0%	129	+0.98	3.68	237	50
Everett Teaford L 2015 · 4.42 FIP	31	SP-	4.42	13.9%	7.6%	2.8%	.324	—	—	—	—	—	4.42	208	49
Arturo Lopez L 2016 · 5.26 FIP	33	SP	5.26	11.5%	7.9%	3.9%	.341	4.92	11.3%	5.2%	224	-0.34	4.34	445	48
Mauricio Lara L 2015 · 3.62 FIP	36	SP	3.62	13.9%	6.9%	1.5%	.310	3.69	12.1%	5.1%	220	+0.07	3.62	444	47
Yohan Flande L 2019 · 4.21 FIP	33	SP-	4.21	10.0%	11.9%	0.8%	.386	—	—	—	—	—	3.18	394	47
Roy Merritt L 2017 · 3.95 FIP	31	SP	3.95	16.2%	5.8%	2.7%	.339	—	—	—	—	—	3.93	129	45
Daniel Rodriguez L 2017 · 3.87 FIP	32	SP	3.87	13.1%	9.7%	1.2%	.335	4.77	20.8%	13.0%	112	+0.90	2.89	391	41
Luke Westphal L 2022 · 4.35 FIP	33	SW	4.35	24.2%	13.4%	2.9%	.302	5.19	15.7%	-0.7%	26	+0.84	2.97	294	39
Carlos Teller L 2019 · 4.90 FIP	32	SP-	4.90	13.1%	14.2%	2.0%	.365	—	—	—	—	—	3.75	333	37
Edgar Osuna L 2019 · 5.09 FIP	31	SW	5.09	10.0%	7.2%	3.5%	.373	—	—	—	—	—	5.05	175	36

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	2.5	98	17.0%	7.4%	1.41	4.95
Allen Ripley ('78-'82, 1 WAR*)	2.3	93	17.2%*	7.5%*	1.41*	5.06*
Philip Humber ('13)	1.9	93	16.7%	7.9%	1.29	5.31
Mark Bomback ('78-'82, 0 WAR*)	1.6	105	13.7%*	8.1%*	1.45*	4.95*
Chris Flexen ('25)	3.5	115	16.1%	8.5%	1.38	4.83
Boof Bonser ('10)	2.1	104	18.2%	7.2%	1.36	5.18
Roy Smith ('84-'91, 3 WAR*)	3.1	103	16.2%*	7.3%*	1.49*	4.73*