Donny Troconis

P Stockton Ports

Age 21 RHP 6'4" / 180 lbs A peak 0.7 · 2031

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	19	AOAK	11	9	51	1.24	2.57	19.9%	8.7%	—	K 14.7% · BB 10.2% · FIP 3.15
2026	20	AOAK	23	16	87	6.21	4.89	20.5%	12.6%	—	K 15.2% · BB 14.9% · FIP 5.99
2027PROJ	21	MLBOAK	—	—	0	5.90	5.90	13.9%	15.0%	—
2028PROJ49% MLB	22	MLBOAK	5	5	30	5.56	5.45	16.3%	13.4%	-0.0
2029PROJ73% MLB	23	MLBOAK	8	8	44	5.29	5.16	17.7%	12.2%	0.1

Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control45Command35

Career WAR0.0 WAR median (P10 -0.1 / P90 1.0, comp-based) · star 1% · didn't stick 92%

CompsLuis Mateo (age 22) · Danny Flatt (age 20) · Nolberto Henriquez (age 21)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 145137vR 129

ERA5.90

FIP5.90

K%13.9%

BB%15.0%

K-BB%-1.1%

Proj IP61

Value2027 · WAR

Runs saved vs league avg · 61 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL4545

CMD3535

K†3050

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	17	ROK MLE	DSL Athletics	12	8	44	187	44	14	6	67%	3.7	16.0%	9.4%	6.6%	4.3%	4.09	5.31	—
2023	17	ROK RAW	DSL Athletics	12	8	44	187	44	14	6	67%	3.7	23.5%	7.5%	16.0%	3.2%	4.09	3.83	—
2024	18	ROK MLE	ACL Athletics	12	8	42	212	45	19	5	67%	3.5	14.4%	11.2%	3.2%	3.9%	6.80	5.43	—
2024	18	ROK MLE	ACL Athletics	12	8	42	212	45	19	5	67%	3.5	14.4%	11.2%	3.2%	3.9%	6.80	5.43	—
2024	18	ROK RAW	ACL Athletics	12	8	42	212	45	19	5	67%	3.5	21.2%	9.0%	12.3%	2.4%	6.80	3.86	—
2025	19	A MLE	Stockton Ports	11	9	51	196	39	17	0	82%	4.6	14.7%	10.2%	4.5%	0.0%	1.24	3.15	—
2025	19	A MLE	Stockton Ports	11	9	51	196	39	17	0	82%	4.6	14.7%	10.2%	4.5%	0.0%	1.24	3.15	—
2025	19	A RAW	Stockton Ports	11	9	51	196	39	17	0	82%	4.6	19.9%	8.7%	11.2%	0.0%	1.24	2.57	—
2026	20	A MLE	Stockton Ports	23	16	87	405	83	51	13	70%	3.8	15.2%	14.9%	0.3%	4.2%	6.21	5.99	—
2026	20	A MLE	Stockton Ports	23	16	87	405	83	51	13	70%	3.8	15.2%	14.9%	0.3%	4.2%	6.21	5.99	—
2026	20	A RAW	Stockton Ports	23	16	87	405	83	51	13	70%	3.8	20.5%	12.6%	7.9%	3.2%	6.21	4.89	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	21	MLB	OAK	—	—	0	—	—	—	—	—	—	13.9%	15.0%	-1.1%	3.1%	5.90	5.90	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	22	MLB MLE	OAK	11	11	61	257	42	34	8	100%	5.5	16.3%	13.4%	3.0%	3.0%	5.56	5.45	-0.0
2029	23	MLB MLE	OAK	11	11	61	257	46	31	8	100%	5.5	17.7%	12.2%	5.5%	3.0%	5.29	5.16	+0.2
2030	24	MLB MLE	OAK	11	11	61	257	48	30	8	100%	5.5	18.5%	11.6%	6.9%	2.9%	5.10	5.00	+0.3
2031	25	MLB MLE	OAK	9	9	54	226	43	25	7	100%	6.0	18.9%	11.2%	7.7%	2.9%	4.98	4.91	+0.3
2032	26	MLB MLE	OAK	9	9	54	226	43	25	7	100%	6.0	19.1%	11.2%	8.0%	2.9%	4.92	4.89	+0.3
2033	27	MLB MLE	OAK	9	9	52	221	42	25	7	100%	5.8	19.1%	11.2%	7.9%	3.0%	4.92	4.92	+0.3
2034	28	MLB MLE	OAK	8	8	50	211	40	24	7	100%	6.2	19.0%	11.4%	7.6%	3.1%	4.97	5.01	+0.2
2035	29	MLB MLE	OAK	8	8	47	198	37	23	6	100%	5.8	18.8%	11.6%	7.1%	3.2%	5.07	5.14	+0.1
2036	30	MLB MLE	OAK	8	8	45	191	39	21	7	100%	5.7	20.4%	11.1%	9.3%	3.4%	5.06	5.05	+0.2
2028	22	MLB CTX	OAK	5	5	30	127	21	17	4	100%	6.0	16.3%	13.4%	3.0%	3.0%	5.56	5.45	-0.0
2029	23	MLB CTX	OAK	8	8	44	186	33	23	6	100%	5.5	17.7%	12.2%	5.5%	3.0%	5.29	5.16	+0.1
2030	24	MLB CTX	OAK	9	9	50	211	39	24	6	100%	5.6	18.5%	11.6%	6.9%	2.9%	5.10	5.00	+0.2
2031	25	MLB CTX	OAK	8	8	47	198	38	22	6	100%	5.9	18.9%	11.2%	7.7%	2.9%	4.98	4.91	+0.3
2032	26	MLB CTX	OAK	8	8	49	207	40	23	6	100%	6.1	19.1%	11.2%	8.0%	2.9%	4.92	4.89	+0.3
2033	27	MLB CTX	OAK	8	8	48	203	39	23	6	100%	6.0	19.1%	11.2%	7.9%	3.0%	4.92	4.92	+0.3
2034	28	MLB CTX	OAK	8	8	47	198	38	23	6	100%	5.9	19.0%	11.4%	7.6%	3.1%	4.97	5.01	+0.2
2035	29	MLB CTX	OAK	7	7	44	186	35	22	6	100%	6.3	18.8%	11.6%	7.1%	3.2%	5.07	5.14	+0.1
2036	30	MLB CTX	OAK	7	7	43	182	37	20	6	100%	6.1	20.4%	11.1%	9.3%	3.4%	5.06	5.05	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		69	69	404	1705	320	197	52	100%	5.9	18.7%	11.6%	7.2%	3.1%	5.07	4.66	+3.5
/ 200 IP	—	RAW		34	34	200	844	158	98	26	100%	5.8	18.7%	11.6%	7.2%	3.1%	5.07	4.66	+1.7
Career	—	MLE		58	41	224	1000	151	121	33	71%	3.9	15.1%	12.1%	2.9%	3.3%	4.78	5.19	+1.9
/ 200 IP	—	MLE		52	37	200	893	135	108	30	71%	3.9	15.1%	12.1%	2.9%	3.3%	4.78	5.19	+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.

2026 AStockton Ports · 87 IPFIP 4.73 → 5.99 (+1.27)K% 20.5% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.49%	—	×0.740	15.17%
BB% (unintentional) /BF	12.59%	—	×1.180	14.86%
HR / BF /BF	3.21%	÷1.000	×1.300	4.17%

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 100).

Result: FIP 4.73 → 5.99, 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 AStockton Ports · 51 IPFIP 2.52 → 3.15 (+0.63)K% 19.9% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.90%	—	×0.740	14.72%
BB% (unintentional) /BF	8.67%	—	×1.180	10.23%
HR / BF /BF	0.00%	÷1.113	×1.300	0.00%

Result: FIP 2.52 → 3.15, 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 ROKACL Athletics · 42 IPFIP 3.74 → 5.43 (+1.69)K% 21.2% → 14.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.23%	—	×0.680	14.43%
BB% (unintentional) /BF	8.96%	—	×1.250	11.20%
HR / BF /BF	2.36%	÷0.852	×1.400	3.88%

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 70).

Result: FIP 3.74 → 5.43, 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 ROKDSL Athletics · 44 IPFIP 3.82 → 5.31 (+1.48)K% 23.5% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.53%	—	×0.680	16.00%
BB% (unintentional) /BF	7.49%	—	×1.250	9.36%
HR / BF /BF	3.21%	÷1.039	×1.400	4.32%

Result: FIP 3.82 → 5.31, 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
Donny Troconis (OGILVIE)	—	—	5.90	13.9%	15.0%	3.1%	—	5.20	17.5%	5.1%	183	-0.70	—	—	—
Luis Mateo R 2015 · 5.17 FIP	22	SP-	5.17	11.4%	14.7%	2.1%	.315	5.67	15.0%	-1.3%	55	+0.50	4.52	112	89
Danny Flatt R 2024 · 6.12 FIP	20	SP-	6.12	14.5%	15.7%	4.1%	.304	5.81	13.0%	-1.9%	76	-0.31	5.37	122	88
Nolberto Henriquez R 2021 · 4.99 FIP	21	SP-	4.99	16.0%	13.4%	2.8%	.305	5.60	11.3%	-3.1%	52	+0.61	4.99	108	87
Luis Hernandez R 2022 · 4.94 FIP	21	SP	4.94	16.7%	14.0%	2.7%	.311	5.62	21.4%	4.1%	64	+0.68	4.09	109	86
Abel Brito R 2022 · 4.79 FIP	21	SP-	4.79	15.7%	12.6%	2.6%	.310	5.66	13.2%	-8.6%	70	+0.87	4.13	147	85
Jacob Meador R 2024 · 5.34 FIP	23	SP-	5.34	15.6%	14.0%	3.2%	.301	6.73	14.7%	-6.6%	50	+1.39	5.34	139	85
Will Childers R 2023 · 5.41 FIP	22	SP-	5.41	11.8%	12.1%	3.2%	.305	4.43	19.5%	8.9%	150	-0.98	3.60	209	84
Kyle Larsen R 2024 · 5.54 FIP	21	SP-	5.54	15.8%	17.9%	2.8%	.274	4.95	19.9%	6.2%	83	-0.59	4.83	143	84
Carlos Marmol R 2006 · 5.89 FIP	23	SP-	5.89	16.6%	16.0%	3.9%	.252	3.03	31.5%	18.0%	231	-2.86	1.59	608	84
Camilo Sanchez R 2024 · 5.26 FIP	21	SP-	5.26	15.2%	14.0%	3.1%	.289	7.17	13.8%	-0.2%	19	+1.91	3.57	117	84
Jason Savacool R 2024 · 4.83 FIP	22	SP-	4.83	14.9%	14.1%	2.2%	.275	4.88	17.2%	4.6%	128	+0.05	4.26	225	83
Luis Martinez-Gomez R 2024 · 5.22 FIP	21	SP-	5.22	13.9%	15.4%	2.5%	.237	4.69	20.8%	6.1%	105	-0.53	3.76	133	83
Juan Gomez R 2017 · 5.39 FIP	20	SP-	5.39	10.9%	12.6%	2.9%	.345	3.58	11.2%	-0.1%	61	-1.81	3.58	113	83
Aaron Hernandez R 2019 · 4.83 FIP	22	SP-	4.83	18.6%	15.7%	2.4%	.340	4.81	20.2%	6.4%	111	-0.02	4.65	194	83
Kolton Curtis R 2024 · 4.91 FIP	20	SP-	4.91	17.2%	14.4%	2.6%	.236	4.41	19.9%	2.5%	66	-0.50	4.41	148	83
Rafael Martinez R 2021 · 5.68 FIP	21	SP-	5.68	15.3%	14.3%	3.8%	.366	2.50	19.4%	11.2%	18	-3.18	2.50	104	83
Trey Riley R 2019 · 5.78 FIP	21	SP-	5.78	10.6%	19.0%	2.1%	.344	5.78	17.4%	5.2%	74	-0.00	4.35	227	82
Stiven Cruz R 2023 · 6.36 FIP	21	SP-	6.36	13.6%	14.8%	4.6%	.312	4.91	17.3%	6.4%	192	-1.45	2.84	426	82
Cobi Johnson R 2019 · 5.52 FIP	23	SP-	5.52	16.0%	14.8%	3.5%	.257	4.54	19.9%	1.4%	41	-0.98	4.54	140	82
Ramon Santos R 2016 · 5.00 FIP	21	SP-	5.00	12.7%	10.6%	3.0%	.323	4.18	15.6%	5.5%	199	-0.82	3.74	355	82

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	2.7	55	18.0%	12.1%	1.18	5.20
Jesus Colome ('10)	2.1	53	17.3%	11.7%	1.03	4.69
C.J. Nitkowski ('05)	2.4	68	15.8%	11.9%	1.07	5.37
Mike Mohler ('01)	2.1	60	15.0%	12.4%	0.97	4.99
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*