John Rooney

P Durham Bulls

Age 30 LHP 6'5" / 215 lbs AAA

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	AAAOklahoma City…	53	60	4.33	3.80	26.1%	11.4%	—	K 22.4% · BB 10.3% · FIP 4.24
2025	28	MIX2 levels	44	40	2.70	3.02	34.1%	14.4%	0.7	K 29.4% · BB 12.9% · FIP 3.03
2026	29	MIX2 levels	25	28	3.86	4.92	25.8%	16.9%	—	K 20.0% · BB 16.9% · FIP 5.71
2027PROJ	30	MLBTB	2	2	4.82	4.82	23.6%	13.4%	-0.0
2028PROJ37% MLB	31	MLBTB	6	6	4.89	4.97	23.2%	13.3%	-0.0

Last 3 seasons WAR 0.7 · Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.0 / P90 0.1, comp-based) · star 0% · didn't stick 98%

CompsRaul Valdes (age 32) · Andrew Barbosa (age 29) · Ryan O'Rourke (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 108117vR 125

ERA4.82

FIP4.82

K%23.6%

BB%13.4%

K-BB%10.2%

Proj IP19

Value2027 · WAR

Runs saved vs league avg · 19 IP

Grades · Contract

Scouting Grades

K†5555

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	21	MIX MLE	2 levels	8	8	20	76	21	8	0	100%	2.5	17.3%	13.8%	3.5%	0.0%	1.80	3.39	—
2018	21	MIX RAW	2 levels	8	8	20	76	21	8	0	100%	2.5	27.6%	10.5%	17.1%	0.0%	1.80	2.20	—
2019	22	MIX MLE	2 levels	20	20	105	426	89	39	7	100%	5.2	15.8%	10.7%	5.1%	2.1%	2.84	4.28	—
2019	22	MIX RAW	2 levels	20	20	105	426	89	39	7	100%	5.2	20.9%	9.2%	11.7%	1.6%	2.84	3.39	—
2021	24	AA MLE	Tulsa Drillers	8	5	29	133	42	21	3	62%	3.6	25.6%	17.4%	8.2%	2.9%	4.08	4.73	—
2021	24	AA RAW	Tulsa Drillers	8	5	29	133	42	21	3	62%	3.6	31.6%	15.8%	15.8%	2.3%	4.08	3.73	—
2022	25	AA MLE	Tulsa Drillers	24	17	98	440	99	48	19	71%	4.1	18.2%	12.0%	6.2%	5.2%	6.15	5.94	—
2022	25	AA RAW	Tulsa Drillers	24	17	98	440	99	48	19	71%	4.1	22.5%	10.9%	11.6%	4.3%	6.15	5.07	—
2023	26	MIX MLE	2 levels	53	1	69	282	69	22	7	2%	1.3	20.4%	7.7%	12.7%	2.7%	2.86	3.85	—
2023	26	MIX RAW	2 levels	53	1	69	282	69	22	7	2%	1.3	24.5%	7.8%	16.7%	2.5%	2.86	3.37	—
2024	27	AAA MLE	Oklahoma City Baseball Club	53	0	60	272	71	31	7	0%	1.1	22.4%	10.3%	12.2%	3.2%	4.33	4.24	—
2024	27	AAA MLE	Oklahoma City Baseball Club	53	0	60	272	71	31	7	0%	1.1	22.4%	10.3%	12.2%	3.2%	4.33	4.24	—
2024	27	AAA RAW	Oklahoma City Baseball Club	53	0	60	272	71	31	7	0%	1.1	26.1%	11.4%	14.7%	2.6%	4.33	3.80	—
2025	28	MIX MLE	2 levels	44	0	40	167	57	24	3	0%	0.9	29.4%	12.9%	16.5%	1.4%	2.70	3.03	+0.7
2025	28	MIX MLE	2 levels	44	0	40	167	57	24	3	0%	0.9	29.4%	12.9%	16.5%	1.4%	2.70	3.03	+0.7
2025	28	MIX RAW	2 levels	44	0	40	167	57	24	3	0%	0.9	34.1%	14.4%	19.8%	1.8%	2.70	3.02	+0.7
2026	29	MIX MLE	2 levels	25	0	28	124	32	21	4	0%	1.1	20.0%	16.9%	3.1%	3.9%	3.86	5.71	—
2026	29	MIX MLE	2 levels	25	0	28	124	32	21	4	0%	1.1	20.0%	16.9%	3.1%	3.9%	3.86	5.71	—
2026	29	MIX RAW	2 levels	25	0	28	124	32	21	4	0%	1.1	25.8%	16.9%	8.9%	3.2%	3.86	4.92	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			1	0	1	6	2	1	1	0%	1.3	33.3%	16.7%	16.7%	16.7%	6.75	12.10	-0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	TB	2	0	2	8	2	1	0	0%	1.0	23.6%	13.4%	10.2%	3.0%	4.82	4.82	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	TB	16	0	17	72	17	10	2	0%	1.1	23.2%	13.3%	9.8%	3.2%	4.89	4.97	-0.1
2028	31	MLB CTX	TB	6	0	6	25	6	3	1	0%	1.0	23.2%	13.3%	9.8%	3.2%	4.89	4.97	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		7	0	8	32	8	5	2	0%	1.1	25.1%	14.0%	11.1%	5.7%	5.22	5.88	-0.1
/ 200 IP	—	RAW		183	0	200	854	211	132	53	0%	1.1	25.1%	14.0%	11.1%	5.7%	5.22	5.88	-3.1
Career	—	MLE		235	51	449	1920	387	224	59	22%	1.9	20.2%	11.7%	8.5%	3.1%	3.85	4.57	-0.2
/ 200 IP	—	MLE		105	23	200	855	172	100	26	22%	1.9	20.2%	11.7%	8.5%	3.1%	3.85	4.57	-2.2

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 AAADurham Bulls · 25 IPFIP 5.47 → 5.71 (+0.23)K% 23.2% → 20.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.21%	—	×0.860	19.96%
BB% (unintentional) /BF	18.75%	—	×0.900	16.88%
HR / BF /BF	3.57%	÷1.000	×1.100	3.93%

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 5.47 → 5.71, 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 AAASugar Land Space Cowboys · 39 IPFIP 2.71 → 3.03 (+0.32)K% 34.2% → 29.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.16%	—	×0.860	29.38%
BB% (unintentional) /BF	14.29%	—	×0.900	12.86%
HR / BF /BF	1.24%	÷0.961	×1.100	1.42%

Result: FIP 2.71 → 3.03, 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 AAAOklahoma City Baseball Club · 60 IPFIP 3.75 → 4.24 (+0.49)K% 26.1% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.10%	—	×0.860	22.45%
BB% (unintentional) /BF	11.40%	—	×0.900	10.26%
HR / BF /BF	2.57%	÷0.896	×1.100	3.16%

Result: FIP 3.75 → 4.24, 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).

2023 AAAOklahoma City Dodgers · 35 IPFIP 3.91 → 4.21 (+0.30)K% 22.7% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.70%	—	×0.860	19.52%
BB% (unintentional) /BF	9.22%	—	×0.900	8.30%
HR / BF /BF	2.84%	÷1.006	×1.100	3.10%

Result: FIP 3.91 → 4.21, 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 AATulsa Drillers · 34 IPFIP 2.86 → 3.49 (+0.63)K% 26.2% → 21.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.24%	—	×0.810	21.26%
BB% (unintentional) /BF	6.38%	—	×1.100	7.02%
HR / BF /BF	2.13%	÷1.083	×1.200	2.36%

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 117).

Result: FIP 2.86 → 3.49, 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 AATulsa Drillers · 98 IPFIP 4.95 → 5.94 (+0.99)K% 22.5% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.50%	—	×0.810	18.23%
BB% (unintentional) /BF	10.91%	—	×1.100	12.00%
HR / BF /BF	4.32%	÷0.993	×1.200	5.22%

Result: FIP 4.95 → 5.94, 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 AATulsa Drillers · 29 IPFIP 3.67 → 4.73 (+1.06)K% 31.6% → 25.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.58%	—	×0.810	25.58%
BB% (unintentional) /BF	15.79%	—	×1.100	17.37%
HR / BF /BF	2.26%	÷0.935	×1.200	2.90%

Result: FIP 3.67 → 4.73, 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 AGreat Lakes Loons · 55 IPFIP 3.35 → 4.19 (+0.84)K% 20.1% → 14.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.09%	—	×0.740	14.87%
BB% (unintentional) /BF	11.42%	—	×1.180	13.47%
HR / BF /BF	0.91%	÷1.018	×1.300	1.17%

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 104).

Result: FIP 3.35 → 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).

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
John Rooney (OGILVIE)	—	—	4.82	23.6%	13.4%	3.0%	—	4.97	23.2%	9.8%	17	+0.15	—	—	—
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	78
Andrew Barbosa L 2017 · 4.67 FIP	29	SU	4.67	20.2%	9.6%	3.8%	.301	—	—	—	—	—	2.70	175	74
Ryan O'Rourke L 2019 · 4.08 FIP	31	SU	4.08	22.1%	14.3%	1.9%	.290	—	—	—	—	—	3.05	145	73
Keith Hessler L 2018 · 4.96 FIP	29	SU	4.96	19.8%	13.3%	3.4%	.348	—	—	—	—	—	3.31	228	70
Juan Pablo Perez L 2007 · 5.32 FIP	28	SU	5.32	17.5%	14.0%	3.5%	.324	—	—	—	—	—	1.75	104	70
Clay Rapada L 2011 · 4.34 FIP	30	SU	4.34	26.1%	10.1%	3.9%	.268	3.00	24.5%	14.2%	38	-1.34	3.00	120	69
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	69
Tommy Phelps L 2004 · 4.80 FIP	30	SW	4.80	19.4%	8.3%	4.2%	.286	3.98	13.2%	5.7%	23	-0.82	3.39	120	68
Aaron Brown L 2022 · 5.38 FIP	30	SU	5.38	21.3%	12.5%	4.5%	.253	—	—	—	—	—	4.04	269	68
John Rheinecker L 2007 · 5.13 FIP	28	SW	5.13	16.7%	10.9%	3.8%	.317	—	—	—	—	—	4.14	121	67
Buddy Baumann L 2018 · 4.87 FIP	30	SU	4.87	20.5%	11.9%	3.6%	.258	—	—	—	—	—	2.92	155	67
Nick Hagadone L 2015 · 3.65 FIP	29	SU	3.65	22.6%	8.9%	2.4%	.329	3.74	22.6%	13.3%	33	+0.09	2.97	141	67
Jose Meraz L 2017 · 4.34 FIP	29	SU	4.34	16.4%	10.3%	2.4%	.282	3.80	10.5%	-2.0%	30	-0.54	3.78	110	67
Anthony Gose L 2021 · 4.69 FIP	30	SU	4.69	29.9%	19.7%	2.9%	.250	4.08	27.7%	15.5%	66	-0.61	3.78	233	66
Cory Luebke L 2016 · 3.88 FIP	31	SU	3.88	26.4%	9.1%	3.4%	.354	—	—	—	—	—	2.80	216	66
Armando Almanza L 2003 · 4.95 FIP	30	SU	4.95	21.3%	10.0%	4.3%	.331	5.29	24.1%	14.8%	12	+0.34	2.90	211	65
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	65
James Pazos L 2021 · 4.41 FIP	30	SU	4.41	26.0%	12.0%	3.6%	.350	—	—	—	—	—	2.55	261	65
Doug Creek L 2000 · 4.57 FIP	31	SU	4.57	27.5%	13.6%	3.8%	.267	4.75	21.9%	7.8%	132	+0.18	4.48	277	65
Jack Taschner L 2008 · 4.09 FIP	30	SU	4.09	17.2%	9.7%	2.2%	.323	4.73	15.2%	3.0%	49	+0.64	3.14	189	65