Joe Adametz

P Hub City Spartanburgers

Age 27 LHP 6'5" / 190 lbs A+

Overview

A+PROSPECT

ETA2029MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	MIX2 levels	22	19	97	2.50	2.90	20.7%	7.8%	—	K 15.6% · BB 9.1% · FIP 3.66
2025	25	MIX2 levels	37	0	60	4.62	4.16	18.2%	8.7%	—	K 14.2% · BB 9.7% · FIP 5.39
2026	26	MIX2 levels	18	4	72	7.96	4.01	18.2%	8.5%	—	K 14.3% · BB 9.3% · FIP 4.34
2027PROJ	27	MLBTEX	—	—	0	5.31	5.31	13.1%	10.6%	—
2028PROJ37% MLB	28	MLBTEX	17	0	18	5.26	5.29	14.0%	10.6%	-0.1
2029PROJ55% MLB	29	MLBTEX	22	0	23	5.29	5.35	14.5%	10.8%	-0.2

Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control50Command35

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsJordan Carr (age 27) · Eric Jokisch (age 27) · Brian Holmes (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 118126vR 134

ERA5.31

FIP5.31

K%13.1%

BB%10.6%

K-BB%2.5%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL5050

CMD3535

K†3030

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)
2023	23	MIX MLE	2 levels	10	5	35	136	35	13	4	50%	3.5	19.0%	15.0%	4.0%	4.5%	2.34	5.89	—
2023	23	MIX RAW	2 levels	10	5	35	136	35	13	4	50%	3.5	25.7%	9.6%	16.2%	2.9%	2.34	3.71	—
2024	24	MIX MLE	2 levels	22	19	97	396	82	31	4	86%	4.4	15.6%	9.1%	6.5%	1.3%	2.50	3.66	—
2024	24	MIX MLE	2 levels	22	19	97	396	82	31	4	86%	4.4	15.6%	9.1%	6.5%	1.3%	2.50	3.66	—
2024	24	MIX RAW	2 levels	22	19	97	396	82	31	4	86%	4.4	20.7%	7.8%	12.9%	1.0%	2.50	2.90	—
2025	25	MIX MLE	2 levels	37	0	60	264	48	23	7	0%	1.6	14.2%	9.7%	4.5%	4.1%	4.62	5.39	—
2025	25	MIX MLE	2 levels	37	0	60	264	48	23	7	0%	1.6	14.2%	9.7%	4.5%	4.1%	4.62	5.39	—
2025	25	MIX RAW	2 levels	37	0	60	264	48	23	7	0%	1.6	18.2%	8.7%	9.5%	2.7%	4.62	4.16	—
2026	26	MIX MLE	2 levels	18	4	72	352	64	30	8	22%	4.0	14.3%	9.3%	5.1%	2.3%	7.96	4.34	—
2026	26	MIX MLE	2 levels	18	4	72	352	64	30	8	22%	4.0	14.3%	9.3%	5.1%	2.3%	7.96	4.34	—
2026	26	MIX RAW	2 levels	18	4	72	352	64	30	8	22%	4.0	18.2%	8.5%	9.7%	2.3%	7.96	4.01	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	TEX	—	—	0	—	—	—	—	—	—	13.1%	10.6%	2.5%	2.9%	5.31	5.31	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	TEX	47	0	50	209	29	22	6	0%	1.1	14.0%	10.6%	3.4%	3.0%	5.26	5.29	-0.4
2029	29	MLB MLE	TEX	39	0	41	173	25	19	5	0%	1.0	14.5%	10.8%	3.7%	3.2%	5.29	5.35	-0.4
2028	28	MLB CTX	TEX	17	0	18	76	11	8	2	0%	1.1	14.0%	10.6%	3.4%	3.0%	5.26	5.29	-0.1
2029	29	MLB CTX	TEX	22	0	23	97	14	10	3	0%	1.0	14.5%	10.8%	3.7%	3.2%	5.29	5.35	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		39	0	41	172	25	18	5	0%	1.0	14.3%	10.7%	3.6%	3.1%	5.28	4.95	-0.2
/ 200 IP	—	RAW		190	0	200	844	123	89	25	0%	1.1	14.3%	10.7%	3.6%	3.1%	5.28	4.95	-0.9
Career	—	MLE		87	28	265	1148	176	115	30	32%	3.0	15.3%	10.0%	5.3%	2.7%	4.45	4.53	-0.8
/ 200 IP	—	MLE		66	21	200	868	133	87	23	32%	3.0	15.3%	10.0%	5.3%	2.7%	4.45	4.53	-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.

2026 A+Hub City Spartanburgers · 68 IPFIP 3.57 → 4.34 (+0.77)K% 18.6% → 14.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.63%	—	×0.770	14.35%
BB% (unintentional) /BF	8.07%	—	×1.150	9.29%
HR / BF /BF	1.86%	÷1.000	×1.250	2.33%

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 100).

Result: FIP 3.57 → 4.34, 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).

2026 AAARound Rock Express · 4 IPFIP 7.32 → 7.68 (+0.35)K% 13.3% → 11.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.33%	—	×0.860	11.47%
BB% (unintentional) /BF	13.33%	—	×0.900	12.00%
HR / BF /BF	6.67%	÷1.000	×1.100	7.33%

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 7.32 → 7.68, 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).

2025 A+West Michigan Whitecaps · 58 IPFIP 4.15 → 5.39 (+1.24)K% 18.4% → 14.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.40%	—	×0.770	14.17%
BB% (unintentional) /BF	8.40%	—	×1.150	9.66%
HR / BF /BF	2.80%	÷0.850	×1.250	4.12%

Result: FIP 4.15 → 5.39, 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).

2024 A+West Michigan Whitecaps · 47 IPFIP 3.14 → 3.87 (+0.73)K% 18.2% → 14.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.18%	—	×0.770	14.00%
BB% (unintentional) /BF	8.08%	—	×1.150	9.29%
HR / BF /BF	1.01%	÷0.889	×1.250	1.42%

Result: FIP 3.14 → 3.87, 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 ALakeland Flying Tigers · 50 IPFIP 2.65 → 3.44 (+0.78)K% 23.2% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.23%	—	×0.740	17.19%
BB% (unintentional) /BF	7.58%	—	×1.180	8.94%
HR / BF /BF	1.01%	÷1.099	×1.300	1.20%

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 120).

Result: FIP 2.65 → 3.44, 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 ROKFCL Tigers · 25 IPFIP 3.90 → 5.89 (+1.98)K% 28.0% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.00%	—	×0.680	19.04%
BB% (unintentional) /BF	12.00%	—	×1.250	15.00%
HR / BF /BF	3.00%	÷0.924	×1.400	4.54%

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 85).

Result: FIP 3.90 → 5.89, 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 ALakeland Flying Tigers · 10 IPFIP 3.33 → 3.93 (+0.60)K% 19.4% → 14.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.44%	—	×0.740	14.39%
BB% (unintentional) /BF	2.78%	—	×1.180	3.28%
HR / BF /BF	2.78%	÷1.216	×1.300	2.97%

Result: FIP 3.33 → 3.93, 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
Joe Adametz (OGILVIE)	—	—	5.31	13.1%	10.6%	2.9%	—	5.32	14.2%	3.5%	90	+0.01	—	—	—
Jordan Carr L 2024 · 4.42 FIP	27	SW	4.42	13.1%	8.8%	2.4%	.295	6.61	11.8%	-1.7%	47	+2.19	3.49	269	80
Eric Jokisch L 2016 · 4.64 FIP	27	SW	4.64	12.4%	9.6%	2.5%	.330	3.93	15.2%	7.6%	283	-0.71	3.78	427	79
Brian Holmes L 2017 · 5.91 FIP	26	SW	5.91	15.5%	11.7%	4.8%	.354	—	—	—	—	—	3.60	205	77
Dan Meyer L 2008 · 5.66 FIP	27	SW	5.66	15.2%	10.6%	4.5%	.315	3.73	23.1%	15.2%	58	-1.93	3.73	112	77
Pat Misch L 2009 · 5.15 FIP	27	SW	5.15	8.5%	7.4%	3.3%	.271	3.50	14.5%	12.6%	38	-1.65	3.50	265	76
Greg Nappo L 2016 · 5.09 FIP	27	SU	5.09	17.2%	10.3%	3.9%	.285	6.26	12.3%	-0.3%	11	+1.17	3.37	144	75
Kyle Hunter L 2016 · 4.48 FIP	27	SU	4.48	11.2%	9.9%	1.9%	.295	4.50	14.0%	7.9%	72	+0.02	4.32	188	74
Stephen Peterson L 2015 · 4.59 FIP	27	SU	4.59	13.0%	9.5%	2.5%	.284	3.04	17.3%	6.3%	55	-1.55	3.04	120	73
Chris Reed L 2016 · 4.67 FIP	26	SW	4.67	16.4%	9.8%	3.1%	.238	—	—	—	—	—	4.67	137	73
Aaron Rozek L 2023 · 4.87 FIP	27	SP-	4.87	17.4%	8.8%	3.9%	.311	4.34	16.7%	9.5%	356	-0.53	3.68	579	72
Matt Whitehouse L 2018 · 4.55 FIP	27	SW	4.55	17.0%	12.8%	2.3%	.308	4.07	20.1%	9.2%	81	-0.48	3.37	353	72
Enrique Lechuga L 2015 · 4.70 FIP	29	SP-	4.70	10.0%	10.5%	2.0%	.354	3.78	10.5%	4.4%	59	-0.92	3.78	137	72
Phil Dumatrait L 2008 · 4.39 FIP	27	SP-	4.39	14.8%	11.4%	2.0%	.298	5.73	13.9%	2.0%	54	+1.34	4.39	151	71
Jack Snodgrass L 2015 · 4.66 FIP	27	SP-	4.66	12.6%	10.7%	2.3%	.278	5.01	15.7%	5.6%	45	+0.35	4.66	118	71
Ryan Kellogg L 2021 · 4.33 FIP	27	SW	4.33	12.3%	5.2%	2.9%	.305	—	—	—	—	—	3.65	446	70
Matt Stalcup L 2016 · 6.20 FIP	26	SW	6.20	11.5%	12.7%	4.5%	.337	—	—	—	—	—	3.62	145	70
Demetrio Gutierrez L 2017 · 5.46 FIP	27	SW	5.46	11.4%	9.6%	3.8%	.381	3.68	17.1%	11.8%	49	-1.78	3.68	322	70
John Rheinecker L 2006 · 4.14 FIP	27	SP-	4.14	8.7%	5.9%	1.9%	.364	5.13	16.7%	5.8%	50	+0.99	4.14	121	69
Jose Molina L 2016 · 4.17 FIP	25	SW	4.17	14.4%	8.9%	2.1%	.347	—	—	—	—	—	3.65	144	69
Mitch Stallings L 2021 · 5.48 FIP	26	SW	5.48	16.8%	11.5%	4.3%	.328	—	—	—	—	—	2.18	108	68

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	53	13.7%	10.7%	1.16	5.29
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Rodney Myers ('04)	1.2	60	15.0%	10.3%	1.05	5.07
Luther Hackman ('03)	1.1	71	13.3%	10.9%	1.10	5.09
Greg Booker ('83-'90, -1 WAR*)	1.3	53	13.3%*	10.2%*	1.07*	4.51*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*