Bryce Conley

P Binghamton Rumble Ponies

Age 32 RHP 6'3" / 200 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	28	MIX2 levels	7	1	11	5.91	5.16	21.2%	11.5%	—	K 21.2% · BB 11.5% · FIP 4.89
2025	30	MIX2 levels	23	22	119	5.01	4.77	21.3%	8.4%	—	K 18.0% · BB 8.2% · FIP 5.44
2026	31	MIX2 levels	29	18	112	5.48	4.65	23.6%	10.7%	—	K 19.2% · BB 11.1% · FIP 5.43
2027PROJ	32	MLBNYM	1	1	1	5.39	5.39	17.9%	9.8%	0.0
2028PROJ31% MLB	33	MLBNYM	3	3	18	5.43	5.53	18.0%	10.2%	-0.0
2029PROJ27% MLB	34	MLBNYM	2	2	13	5.57	5.72	17.8%	10.7%	-0.0

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

Stuff45Control55Command50

Career WAR0.0 WAR median (P10 -0.1 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsElian Leyva (age 30) · Marco Quevedo (age 32) · Austin Bibens-Dirkx (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 136127vR 119

ERA5.39

FIP5.39

K%17.9%

BB%9.8%

K-BB%8.1%

Proj IP73

Value2027 · WAR

Runs saved vs league avg · 73 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL5555

CMD5050

K†4040

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	23	A MLE	Beloit Snappers	20	16	85	359	98	37	8	80%	4.2	20.2%	12.2%	8.0%	3.2%	4.46	4.71	—
2018	23	A RAW	Beloit Snappers	20	16	85	359	98	37	8	80%	4.2	27.3%	10.3%	17.0%	2.2%	4.46	3.32	—
2019	24	MIX MLE	2 levels	25	19	102	432	98	59	11	76%	4.1	17.0%	16.0%	1.0%	3.1%	3.43	5.40	—
2019	24	MIX RAW	2 levels	25	19	102	432	98	59	11	76%	4.1	22.7%	13.7%	9.0%	2.5%	3.43	4.31	—
2021	26	AA MLE	Midland RockHounds	29	14	94	398	88	44	6	48%	3.3	17.9%	12.2%	5.7%	2.2%	4.39	4.31	—
2021	26	AA RAW	Midland RockHounds	29	14	94	398	88	44	6	48%	3.3	22.1%	11.1%	11.1%	1.5%	4.39	3.46	—
2022	27	MIX MLE	2 levels	41	0	55	261	55	28	6	0%	1.3	16.4%	11.1%	5.3%	2.0%	4.88	4.22	—
2022	27	MIX RAW	2 levels	41	0	55	261	55	28	6	0%	1.3	21.1%	10.7%	10.3%	2.3%	4.88	4.04	—
2023	28	MIX MLE	2 levels	7	1	11	52	11	6	2	14%	1.5	21.2%	11.5%	9.6%	3.8%	5.91	4.89	—
2023	28	MIX RAW	2 levels	7	1	11	52	11	6	2	14%	1.5	21.2%	11.5%	9.6%	3.8%	5.91	5.16	—
2025	30	MIX MLE	2 levels	23	22	119	502	107	42	22	96%	5.2	18.0%	8.2%	9.7%	5.1%	5.01	5.44	—
2025	30	MIX MLE	2 levels	23	22	119	502	107	42	22	96%	5.2	18.0%	8.2%	9.7%	5.1%	5.01	5.44	—
2025	30	MIX RAW	2 levels	23	22	119	502	107	42	22	96%	5.2	21.3%	8.4%	12.9%	4.4%	5.01	4.77	—
2026	31	MIX MLE	2 levels	29	18	112	487	115	52	19	62%	3.9	19.2%	11.1%	8.1%	4.6%	5.48	5.43	—
2026	31	MIX MLE	2 levels	29	18	112	487	115	52	19	62%	3.9	19.2%	11.1%	8.1%	4.6%	5.48	5.43	—
2026	31	MIX RAW	2 levels	29	18	112	487	115	52	19	62%	3.9	23.6%	10.7%	12.9%	3.9%	5.48	4.65	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	NYM	1	1	1	4	1	0	0	100%	1.0	17.9%	9.8%	8.1%	4.0%	5.39	5.39	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	NYM	9	9	58	245	44	25	10	100%	6.4	18.0%	10.2%	7.8%	4.1%	5.43	5.53	-0.1
2029	34	MLB MLE	NYM	7	7	47	198	35	21	9	100%	6.7	17.8%	10.7%	7.2%	4.4%	5.57	5.72	-0.2
2028	33	MLB CTX	NYM	3	3	18	76	14	8	3	100%	6.0	18.0%	10.2%	7.8%	4.1%	5.43	5.53	-0.0
2029	34	MLB CTX	NYM	2	2	13	55	10	6	2	100%	6.5	17.8%	10.7%	7.2%	4.4%	5.57	5.72	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		5	5	31	130	23	13	5	100%	6.1	17.9%	10.4%	7.5%	4.2%	5.49	5.23	+0.1
/ 200 IP	—	RAW		31	31	200	844	150	85	33	100%	6.4	17.9%	10.4%	7.5%	4.2%	5.49	5.23	+0.4
Career	—	MLE		174	90	578	2491	455	292	89	52%	3.3	18.3%	11.7%	6.6%	3.6%	4.64	5.01	-0.3
/ 200 IP	—	MLE		60	31	200	862	157	101	31	52%	3.3	18.3%	11.7%	6.6%	3.6%	4.64	5.01	-0.5

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 AABinghamton Rumble Ponies · 93 IPFIP 4.39 → 5.38 (+0.99)K% 25.7% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.68%	—	×0.810	20.80%
BB% (unintentional) /BF	9.14%	—	×1.100	10.05%
HR / BF /BF	4.20%	÷1.000	×1.200	5.04%

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 4.39 → 5.38, 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 AAASyracuse Mets · 19 IPFIP 5.62 → 5.68 (+0.06)K% 13.4% → 11.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.41%	—	×0.860	11.54%
BB% (unintentional) /BF	18.29%	—	×0.900	16.46%
HR / BF /BF	2.44%	÷1.000	×1.100	2.68%

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 5.62 → 5.68, 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 AAARochester Red Wings · 74 IPFIP 5.20 → 5.79 (+0.59)K% 21.8% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.77%	—	×0.860	18.72%
BB% (unintentional) /BF	7.89%	—	×0.900	7.10%
HR / BF /BF	5.36%	÷0.960	×1.100	6.15%

Result: FIP 5.20 → 5.79, 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 AAHarrisburg Senators · 45 IPFIP 4.01 → 4.82 (+0.81)K% 20.5% → 16.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.54%	—	×0.810	16.64%
BB% (unintentional) /BF	9.19%	—	×1.100	10.11%
HR / BF /BF	2.70%	÷0.963	×1.200	3.37%

Result: FIP 4.01 → 4.82, 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 AAALas Vegas Aviators · 10 IPFIP 4.81 → 5.19 (+0.39)K% 23.4% → 20.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.40%	—	×0.860	20.13%
BB% (unintentional) /BF	10.64%	—	×0.900	9.57%
HR / BF /BF	4.26%	÷0.996	×1.100	4.70%

Result: FIP 4.81 → 5.19, 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).

2022 AAMidland RockHounds · 48 IPFIP 3.40 → 4.22 (+0.83)K% 20.3% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.26%	—	×0.810	16.41%
BB% (unintentional) /BF	10.13%	—	×1.100	11.15%
HR / BF /BF	1.32%	÷0.793	×1.200	2.00%

Result: FIP 3.40 → 4.22, 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 AAALas Vegas Aviators · 7 IPFIP 7.57 → 8.04 (+0.47)K% 26.5% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.47%	—	×0.880	23.29%
BB% (unintentional) /BF	14.71%	—	×1.050	15.44%
HR / BF /BF	8.82%	÷1.075	×1.100	9.03%

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 115).

Result: FIP 7.57 → 8.04, 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).

2021 AAMidland RockHounds · 94 IPFIP 3.46 → 4.31 (+0.85)K% 22.1% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.11%	—	×0.810	17.91%
BB% (unintentional) /BF	11.06%	—	×1.100	12.16%
HR / BF /BF	1.51%	÷0.838	×1.200	2.16%

Result: FIP 3.46 → 4.31, 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
Bryce Conley (OGILVIE)	—	—	5.39	17.9%	9.8%	4.0%	—	5.61	17.9%	7.5%	105	+0.22	—	—	—
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	81
Marco Quevedo R 2019 · 5.17 FIP	32	SP-	5.17	13.6%	11.4%	3.2%	.344	—	—	—	—	—	4.13	300	79
Austin Bibens-Dirkx R 2017 · 5.03 FIP	32	SW	5.03	14.0%	6.6%	4.2%	.268	5.28	17.5%	9.7%	166	+0.25	3.97	567	71
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	71
Juan Omar Espinoza R 2016 · 4.84 FIP	32	SP-	4.84	8.4%	9.2%	2.4%	.348	—	—	—	—	—	4.81	104	70
Jason Berken R 2016 · 4.54 FIP	32	SW	4.54	11.5%	8.3%	2.5%	.308	—	—	—	—	—	3.37	468	67
Bradin Hagens R 2019 · 5.46 FIP	30	SW	5.46	13.2%	12.6%	3.4%	.303	—	—	—	—	—	3.79	254	67
Rodolfo Aguirre R 2017 · 5.96 FIP	32	SW	5.96	10.0%	13.0%	3.8%	.316	4.50	21.3%	16.2%	15	-1.46	3.39	212	67
Seth Simmons R 2018 · 6.20 FIP	30	SW	6.20	13.3%	10.9%	5.2%	.242	—	—	—	—	—	3.07	251	67
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	66
Marco Antonio Duarte R 2019 · 5.03 FIP	32	SW	5.03	12.2%	9.1%	3.3%	.420	—	—	—	—	—	4.07	203	65
Angel Sánchez R 2023 · 4.90 FIP	33	SW	4.90	19.0%	10.5%	3.8%	.333	3.77	11.8%	6.8%	27	-1.13	3.77	284	65
Osvaldo Fernandez R 2001 · 4.53 FIP	32	SP-	4.53	9.6%	8.2%	2.2%	.324	—	—	—	—	—	4.25	387	65
Hector Galvan R 2019 · 4.84 FIP	31	SP-	4.84	14.3%	12.2%	2.6%	.357	—	—	—	—	—	3.59	406	63
Thad Weber R 2017 · 5.25 FIP	32	SP-	5.25	13.2%	4.4%	4.9%	.398	—	—	—	—	—	4.40	378	63
Miguel Ruiz R 2017 · 5.60 FIP	31	SP	5.60	10.6%	11.0%	3.6%	.279	—	—	—	—	—	5.60	117	63
Chris Jakubauskas R 2011 · 4.42 FIP	32	SW	4.42	15.7%	7.9%	3.0%	.339	—	—	—	—	—	4.42	165	63
Ivan Maldonado R 2015 · 4.60 FIP	35	SW	4.60	12.8%	8.7%	2.7%	.269	5.41	6.4%	-3.3%	104	+0.81	4.60	172	63
Pete Walker R 2002 · 4.59 FIP	33	SP-	4.59	13.4%	7.7%	3.0%	.279	5.16	12.0%	2.8%	139	+0.57	4.45	327	61
Junior Guerra R 2017 · 5.24 FIP	32	SP-	5.24	19.4%	12.8%	3.9%	.255	3.99	22.2%	12.5%	248	-1.25	3.18	646	61

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	0.9	59	17.9%	10.2%	1.60	5.45
Scott Proctor ('11)	1.7	57	19.0%	10.9%	1.52	4.78
Josh Osich ('21)	1.1	55	20.7%	9.0%	1.84	5.02
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Phil Hennigan ('69-'73, -0 WAR*)	1.4	70	20.9%*	10.4%*	1.50*	4.95*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Darrel Akerfelds ('86-'91, -3 WAR*)	1.2	78	15.8%*	11.9%*	1.61*	5.40*