Adam Seminaris

P Reading Fightin Phils

Age 28 LHP 6'0" / 191 lbs AA peak 1.3 · 2027

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	26	AASEA	24	22	125	3.02	2.49	20.2%	6.9%	—	K 16.4% · BB 7.6% · FIP 3.00
2026	27	AAPHI	26	26	138	4.03	3.29	28.1%	5.2%	—	K 22.7% · BB 5.7% · FIP 4.19
2027PROJ	28	MLBPHI	1	1	2	4.32	4.32	19.4%	6.7%	0.0
2028PROJ31% MLB	29	MLBPHI	4	4	24	4.39	4.44	19.4%	7.0%	0.3
2029PROJ51% MLB	30	MLBPHI	6	6	39	4.35	4.33	21.3%	6.6%	0.5

Next 3 projected WAR 0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control55Command45

Career WAR0.0 WAR median (P10 -0.6 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsDylan Dodd (age 26) · Matt Tracy (age 28) · Danny Wirchansky (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 99107vR 115

ERA4.32

FIP4.32

K%19.4%

BB%6.7%

K-BB%12.7%

Proj IP89

Value2027 · WAR

Runs saved vs league avg · 89 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL5555

CMD4545

K†4550

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)
2021	22	MIX MLE	2 levels	20	18	83	368	112	26	9	90%	4.2	22.7%	8.3%	14.4%	3.1%	4.86	3.94	—
2021	22	MIX RAW	2 levels	20	18	83	368	112	26	9	90%	4.2	30.4%	7.1%	23.4%	2.4%	4.86	2.75	—
2022	23	MIX MLE	3 levels	24	21	102	439	97	38	7	88%	4.2	17.9%	9.4%	8.5%	2.0%	3.54	3.87	—
2022	23	MIX RAW	3 levels	24	21	102	439	97	38	7	88%	4.2	22.1%	8.7%	13.4%	1.6%	3.54	3.21	—
2023	24	MIX MLE	3 levels	16	16	62	277	64	25	6	100%	3.9	19.6%	9.8%	9.8%	2.4%	5.95	4.01	—
2023	24	MIX RAW	3 levels	16	16	62	277	64	25	6	100%	3.9	23.1%	9.0%	14.1%	2.2%	5.95	3.50	—
2024	25	AA MLE	Biloxi Shuckers	25	10	75	335	73	23	5	40%	3.0	17.7%	7.6%	10.1%	1.5%	6.15	3.39	—
2024	25	AA MLE	Biloxi Shuckers	25	10	75	335	73	23	5	40%	3.0	17.7%	7.6%	10.1%	1.5%	6.15	3.39	—
2024	25	AA RAW	Biloxi Shuckers	25	10	75	335	73	23	5	40%	3.0	21.8%	6.9%	14.9%	1.5%	6.15	2.94	—
2025	26	AA MLE	Arkansas Travelers	24	22	125	519	105	36	2	92%	5.2	16.4%	7.6%	8.8%	0.6%	3.02	3.00	—
2025	26	AA MLE	Arkansas Travelers	24	22	125	519	105	36	2	92%	5.2	16.4%	7.6%	8.8%	0.6%	3.02	3.00	—
2025	26	AA RAW	Arkansas Travelers	24	22	125	519	105	36	2	92%	5.2	20.2%	6.9%	13.3%	0.4%	3.02	2.49	—
2026	27	AA MLE	Reading Fightin Phils	26	26	138	577	162	30	20	100%	5.3	22.7%	5.7%	17.0%	4.2%	4.03	4.19	—
2026	27	AA MLE	Reading Fightin Phils	26	26	138	577	162	30	20	100%	5.3	22.7%	5.7%	17.0%	4.2%	4.03	4.19	—
2026	27	AA RAW	Reading Fightin Phils	26	26	138	577	162	30	20	100%	5.3	28.1%	5.2%	22.9%	3.5%	4.03	3.29	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	PHI	1	1	2	8	2	1	0	100%	2.0	19.4%	6.7%	12.7%	3.0%	4.32	4.32	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	PHI	13	13	78	330	64	23	10	100%	6.0	19.4%	7.0%	12.4%	3.1%	4.39	4.44	+0.9
2029	30	MLB MLE	PHI	13	13	75	318	68	21	11	100%	5.8	21.3%	6.6%	14.7%	3.3%	4.35	4.33	+0.9
2030	31	MLB MLE	PHI	11	11	67	284	60	20	10	100%	6.1	21.0%	7.0%	14.0%	3.5%	4.46	4.54	+0.7
2031	32	MLB MLE	PHI	10	10	59	248	51	19	9	100%	5.9	20.6%	7.5%	13.1%	3.8%	4.63	4.76	+0.4
2032	33	MLB MLE	PHI	8	8	50	212	43	17	9	100%	6.3	20.1%	7.9%	12.2%	4.0%	4.85	5.00	+0.2
2028	29	MLB CTX	PHI	4	4	24	101	20	7	3	100%	6.0	19.4%	7.0%	12.4%	3.1%	4.39	4.44	+0.3
2029	30	MLB CTX	PHI	6	6	39	165	35	11	5	100%	6.5	21.3%	6.6%	14.7%	3.3%	4.35	4.33	+0.5
2030	31	MLB CTX	PHI	7	7	44	186	39	13	7	100%	6.3	21.0%	7.0%	14.0%	3.5%	4.46	4.54	+0.4
2031	32	MLB CTX	PHI	7	7	44	186	38	14	7	100%	6.3	20.6%	7.5%	13.1%	3.8%	4.63	4.76	+0.3
2032	33	MLB CTX	PHI	7	7	41	173	35	14	7	100%	5.9	20.1%	7.9%	12.2%	4.0%	4.85	5.00	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		32	32	191	808	166	58	29	100%	6.0	20.6%	7.2%	13.3%	3.6%	4.55	4.25	+2.6
/ 200 IP	—	RAW		33	33	200	844	174	61	30	100%	6.0	20.6%	7.2%	13.3%	3.6%	4.55	4.25	+2.7
Career	—	MLE		135	113	585	2515	492	197	59	84%	4.3	19.6%	7.8%	11.7%	2.3%	4.32	3.72	+3.2
/ 200 IP	—	MLE		46	39	200	859	168	67	20	84%	4.3	19.6%	7.8%	11.7%	2.3%	4.32	3.72	+1.9

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 AAReading Fightin Phils · 138 IPFIP 3.29 → 4.19 (+0.90)K% 28.1% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.08%	—	×0.810	22.74%
BB% (unintentional) /BF	5.20%	—	×1.100	5.72%
HR / BF /BF	3.47%	÷1.000	×1.200	4.16%

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 100).

Result: FIP 3.29 → 4.19, 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 AAArkansas Travelers · 125 IPFIP 2.48 → 3.00 (+0.52)K% 20.2% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.23%	—	×0.810	16.39%
BB% (unintentional) /BF	6.94%	—	×1.100	7.63%
HR / BF /BF	0.39%	÷0.800	×1.200	0.58%

Result: FIP 2.48 → 3.00, 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 AABiloxi Shuckers · 75 IPFIP 2.95 → 3.39 (+0.44)K% 21.8% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.79%	—	×0.810	17.65%
BB% (unintentional) /BF	6.87%	—	×1.100	7.55%
HR / BF /BF	1.49%	÷1.198	×1.200	1.49%

Result: FIP 2.95 → 3.39, 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).

2023 AABiloxi Shuckers · 54 IPFIP 3.35 → 4.01 (+0.66)K% 24.3% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.26%	—	×0.810	19.65%
BB% (unintentional) /BF	8.94%	—	×1.100	9.83%
HR / BF /BF	2.13%	÷1.055	×1.200	2.42%

Result: FIP 3.35 → 4.01, 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).

2023 ROKACL Brewers · 5 IPFIP 2.04 → 2.98 (+0.94)K% 25.0% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.680	17.00%
BB% (unintentional) /BF	8.33%	—	×1.250	10.42%
HR / BF /BF	0.00%	÷0.898	×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 80).

Result: FIP 2.04 → 2.98, 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 AAASalt Lake Bees · 34 IPFIP 4.70 → 5.16 (+0.46)K% 17.3% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.31%	—	×0.880	15.23%
BB% (unintentional) /BF	10.26%	—	×1.050	10.77%
HR / BF /BF	3.21%	÷0.978	×1.100	3.61%

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 96).

Result: FIP 4.70 → 5.16, 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 A+Tri-City Dust Devils · 37 IPFIP 2.04 → 3.14 (+1.10)K% 30.1% → 23.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.07%	—	×0.770	23.15%
BB% (unintentional) /BF	5.59%	—	×1.150	6.43%
HR / BF /BF	1.40%	÷0.814	×1.250	2.15%

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 63).

Result: FIP 2.04 → 3.14, 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).

2022 AARocket City Trash Pandas · 31 IPFIP 2.74 → 3.17 (+0.44)K% 19.3% → 15.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.29%	—	×0.810	15.62%
BB% (unintentional) /BF	10.00%	—	×1.100	11.00%
HR / BF /BF	0.00%	÷1.131	×1.200	0.00%

Result: FIP 2.74 → 3.17, 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
Adam Seminaris (OGILVIE)	—	—	4.32	19.4%	6.7%	3.0%	—	4.43	20.5%	13.7%	221	+0.11	—	—	—
Dylan Dodd L 2024 · 4.71 FIP	26	SP-	4.71	17.5%	6.0%	4.2%	.338	3.97	26.5%	21.7%	123	-0.74	3.31	475	77
Matt Tracy L 2017 · 4.82 FIP	28	SP-	4.82	16.1%	9.4%	3.5%	.325	3.24	13.9%	3.5%	49	-1.58	3.24	298	77
Danny Wirchansky L 2024 · 4.47 FIP	27	SP-	4.47	16.2%	7.4%	3.3%	.246	5.88	13.0%	0.2%	68	+1.41	4.47	179	77
Ryan Bollinger L 2018 · 3.56 FIP	27	SP	3.56	17.1%	7.5%	1.7%	.290	—	—	—	—	—	3.56	112	76
T.J. Sikkema L 2024 · 3.57 FIP	26	SP-	3.57	18.5%	6.0%	2.3%	.282	4.10	16.1%	7.2%	87	+0.53	3.57	300	75
James Gillheeney L 2015 · 3.79 FIP	27	SP-	3.79	14.4%	8.0%	1.6%	.300	—	—	—	—	—	3.79	129	73
Alejandro Soto L 2015 · 4.41 FIP	29	SP	4.41	12.8%	7.0%	2.7%	.367	4.07	14.6%	9.1%	128	-0.34	3.96	280	73
Chipper Smith L 2015 · 3.81 FIP	25	SP-	3.81	15.6%	9.5%	1.5%	.321	—	—	—	—	—	3.81	109	73
Matt Lujan L 2017 · 4.69 FIP	28	SP-	4.69	14.3%	6.4%	3.6%	.348	—	—	—	—	—	4.06	227	73
Ben Shields L 2024 · 3.23 FIP	25	SP-	3.23	25.3%	8.2%	2.2%	.273	3.02	23.5%	13.3%	43	-0.21	3.02	147	72
Kyle Hald L 2015 · 4.33 FIP	26	SP	4.33	12.1%	7.4%	2.4%	.313	—	—	—	—	—	4.33	124	71
Kramer Sneed L 2016 · 4.21 FIP	27	SP	4.21	13.2%	8.2%	2.2%	.265	—	—	—	—	—	4.21	116	70
Orlando Lara L 2015 · 4.29 FIP	30	SP	4.29	15.2%	10.3%	2.1%	.348	4.08	14.2%	7.2%	230	-0.21	3.85	426	70
Yohan Flande L 2014 · 3.65 FIP	28	SP-	3.65	14.1%	5.8%	1.8%	.266	3.90	14.1%	7.9%	312	+0.25	3.18	394	69
Michael O'Connor L 2006 · 4.93 FIP	25	SP	4.93	13.0%	8.8%	3.3%	.238	—	—	—	—	—	4.93	105	69
John Anderson L 2016 · 4.23 FIP	27	SP-	4.23	14.3%	8.7%	2.2%	.367	—	—	—	—	—	4.12	235	69
Jared Koenig L 2022 · 4.06 FIP	28	SP-	4.06	18.1%	7.4%	2.8%	.308	3.29	23.6%	15.8%	187	-0.77	2.79	475	69
Nick Additon L 2016 · 4.47 FIP	28	SP-	4.47	12.9%	6.8%	2.9%	.303	3.13	19.3%	10.2%	26	-1.34	3.13	217	68
Darin Gorski L 2016 · 4.50 FIP	28	SP	4.50	15.0%	9.8%	2.6%	.299	—	—	—	—	—	4.50	206	68
Misael Siverio L 2017 · 4.32 FIP	28	SP	4.32	17.3%	9.1%	2.8%	.299	—	—	—	—	—	3.89	185	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	2.1	70	20.3%	7.0%	1.31	4.47
Blas Minor ('97)	1.1	75	19.2%	7.3%	1.16	4.40
Rich Monteleone ('87-'96, 2 WAR*)	1.8	71	18.7%*	7.5%*	1.39*	4.03*
Tim Crews ('87-'92, 3 WAR*)	2.1	71	20.8%*	6.2%*	1.09*	4.11*
Matt Wise ('08)	1.6	53	18.1%	7.9%	1.14	4.23
Michael Tonkin ('25)	1.6	55	23.2%	8.1%	1.28	4.23
Cris Carpenter ('88-'96, 2 WAR*)	2.1	69	18.3%*	7.4%*	1.15*	4.29*