Ben Joyce

P Los Angeles Angels

Age 26 RHP 6'5" / 225 lbs MLB peak 0.6 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	MIX2 levels	49	1	54	2.85	2.73	30.3%	11.3%	1.2	K 27.4% · BB 11.8% · FIP 3.14
2025	24	MLBLAA	5	0	4	6.23	6.33	5.0%	5.0%	-0.1
2026	25	MIX4 levels	28	0	26	4.50	3.14	26.1%	13.9%	0.4	K 29.5% · BB 13.1% · FIP 3.15
2027PROJ	26	MLBLAA	49	0	51	3.83	3.81	32.2%	12.5%	0.5
2028PROJ86% MLB	27	MLBLAA	47	0	49	3.90	3.90	31.3%	12.2%	0.4
2029PROJ90% MLB	28	MLBLAA	45	0	47	3.98	4.02	30.6%	12.2%	0.3

Last 3 seasons WAR 1.5 · Next 3 projected WAR 1.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo90

K%90

xwOBA vs61

Form4.11 ERA (proj 3.83) · K 29.5% (proj 32.2%) · BB 14.8% (proj 12.5%) ▼ last 90d · 15 IP through Oct 27

CompsTrey Wingenter (age 25) · Jon Edwards (age 27) · Félix Bautista (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10697vR 89

ERA3.83

FIP3.81

K%32.2%

BB%12.5%

K-BB%19.7%

Proj IP63

Value2027 · WAR

Runs saved vs league avg · 63 IP

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL4040

CMD4545

K†7070

Statcast Percentiles

FB Velo

p90101.0

Whiff%

p9031.5%

p9029.5%

xwOBA vs

p610.301

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)
2022	21	AA MLE	Rocket City Trash Pandas	13	0	13	57	20	4	0	0%	1.0	28.4%	7.7%	20.7%	0.0%	2.08	1.68	—
2022	21	AA RAW	Rocket City Trash Pandas	13	0	13	57	20	4	0	0%	1.0	35.1%	7.0%	28.1%	0.0%	2.08	0.95	—
2023	22	MIX MLE	3 levels	28	0	28	125	36	23	2	0%	1.0	27.8%	20.4%	7.3%	1.8%	4.55	4.31	+0.1
2023	22	MIX RAW	3 levels	28	0	28	125	36	23	2	0%	1.0	28.8%	18.4%	10.4%	1.6%	4.55	3.93	+0.2
2024	23	MIX MLE	2 levels	49	1	54	221	67	25	3	2%	1.1	27.4%	11.8%	15.6%	1.6%	2.85	3.14	+0.9
2024	23	MIX MLE	2 levels	49	1	54	221	67	25	3	2%	1.1	27.4%	11.8%	15.6%	1.6%	2.85	3.14	+0.9
2024	23	MIX RAW	2 levels	49	1	54	221	67	25	3	2%	1.1	30.3%	11.3%	19.0%	1.4%	2.85	2.73	+1.2
2025	24	MLB MLE	Los Angeles Angels	5	0	4	20	1	1	1	0%	0.9	5.0%	5.0%	0.0%	5.0%	6.23	6.06	-0.1
2025	24	MLB MLE	Los Angeles Angels	5	0	4	20	1	1	1	0%	0.9	5.0%	5.0%	0.0%	5.0%	6.23	6.06	-0.1
2025	24	MLB RAW	Los Angeles Angels	5	0	4	20	1	1	1	0%	0.9	5.0%	5.0%	0.0%	5.0%	6.23	6.33	-0.1
2026	25	MIX MLE	4 levels	28	0	26	115	30	16	1	0%	0.9	29.5%	13.1%	16.4%	1.6%	4.50	3.15	+0.4
2026	25	MIX MLE	4 levels	28	0	26	115	30	16	1	0%	0.9	29.5%	13.1%	16.4%	1.6%	4.50	3.15	+0.4
2026	25	MIX RAW	4 levels	28	0	26	115	30	16	1	0%	0.9	26.1%	13.9%	12.2%	0.9%	4.50	3.14	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			64	1	64	271	62	32	4	2%	1.0	22.9%	11.8%	11.1%	1.5%	3.36	3.47	+0.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	LAA	49	0	51	215	69	27	6	0%	1.0	32.2%	12.5%	19.7%	2.7%	3.83	3.81	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	LAA	54	0	57	239	75	29	7	0%	1.1	31.3%	12.2%	19.1%	2.8%	3.90	3.90	+0.4
2029	28	MLB MLE	LAA	50	0	52	220	67	27	6	0%	1.0	30.6%	12.2%	18.4%	2.9%	3.98	4.02	+0.3
2028	27	MLB CTX	LAA	47	0	49	207	65	25	6	0%	1.0	31.3%	12.2%	19.1%	2.8%	3.90	3.90	+0.4
2029	28	MLB CTX	LAA	45	0	47	198	61	24	6	0%	1.0	30.6%	12.2%	18.4%	2.9%	3.98	4.02	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		155	1	160	674	187	81	15	1%	1.0	27.7%	12.0%	15.7%	2.3%	3.70	3.54	+1.9
/ 200 IP	—	RAW		194	1	200	844	234	101	19	1%	1.0	27.7%	12.0%	15.7%	2.3%	3.70	3.54	+2.4
Career	—	MLE		123	1	125	538	146	72	8	1%	1.0	27.2%	13.4%	13.8%	1.6%	3.61	3.37	+1.6
/ 200 IP	—	MLE		197	2	200	863	235	116	14	1%	1.0	27.2%	13.4%	13.8%	1.6%	3.61	3.37	+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 ARancho Cucamonga Quakes · 4 IPFIP 2.90 → 3.75 (+0.85)K% 23.8% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.81%	—	×0.740	17.62%
BB% (unintentional) /BF	14.29%	—	×1.180	16.86%
HR / BF /BF	0.00%	÷1.000	×1.300	0.00%

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 2.90 → 3.75, 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 AARocket City Trash Pandas · 19 IPFIP 2.62 → 3.81 (+1.19)K% 43.0% → 34.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	43.04%	—	×0.810	34.86%
BB% (unintentional) /BF	13.92%	—	×1.100	15.32%
HR / BF /BF	2.53%	÷0.976	×1.200	3.11%

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 95).

Result: FIP 2.62 → 3.81, 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 AARocket City Trash Pandas · 16 IPFIP 3.34 → 4.31 (+0.97)K% 34.3% → 27.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.29%	—	×0.810	27.77%
BB% (unintentional) /BF	18.57%	—	×1.100	20.43%
HR / BF /BF	1.43%	÷0.970	×1.200	1.77%

Result: FIP 3.34 → 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).

2022 AARocket City Trash Pandas · 13 IPFIP 1.03 → 1.68 (+0.65)K% 35.1% → 28.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.09%	—	×0.810	28.42%
BB% (unintentional) /BF	7.02%	—	×1.100	7.72%
HR / BF /BF	0.00%	÷1.131	×1.200	0.00%

Result: FIP 1.03 → 1.68, 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).

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
Ben Joyce (OGILVIE)	—	—	3.81	32.2%	12.5%	2.7%	—	3.96	30.9%	18.7%	109	+0.15	—	—	—
Trey Wingenter R 2019 · 3.17 FIP	25	SU	3.17	33.0%	12.8%	2.2%	.257	—	—	—	—	—	2.81	293	71
Jon Edwards R 2015 · 3.40 FIP	27	SU	3.40	31.7%	13.1%	2.4%	.264	2.40	30.3%	22.6%	30	-1.00	2.40	132	71
Félix Bautista R 2021 · 3.16 FIP	26	SU	3.16	32.5%	17.0%	1.2%	.212	2.17	40.4%	30.6%	127	-0.99	1.50	334	68
Kyle Keller R 2019 · 3.83 FIP	26	SU	3.83	28.7%	9.4%	3.6%	.293	4.88	28.0%	17.8%	52	+1.05	2.72	296	68
Ty Buttrey R 2019 · 3.14 FIP	26	SU	3.14	27.2%	7.4%	2.5%	.314	4.33	15.9%	5.2%	63	+1.19	2.43	522	68
Pierce Johnson R 2017 · 3.09 FIP	26	SU	3.09	27.8%	11.7%	1.6%	.374	3.71	25.0%	13.7%	86	+0.62	2.75	598	68
Alex Lange R 2022 · 3.00 FIP	26	SU	3.00	30.3%	11.1%	1.9%	.273	3.86	26.3%	10.9%	108	+0.86	3.00	511	68
Ben Heller R 2017 · 2.86 FIP	25	SU	2.86	32.4%	9.4%	2.4%	.243	—	—	—	—	—	2.49	246	67
Tucker Healy R 2016 · 2.82 FIP	26	SU	2.82	30.4%	10.5%	1.8%	.294	4.64	16.9%	5.8%	67	+1.82	2.82	174	67
Brian Ellington R 2017 · 4.75 FIP	26	SU	4.75	25.5%	14.9%	3.5%	.283	5.61	22.4%	5.3%	29	+0.86	2.75	233	67
Ryne Stanek R 2017 · 3.05 FIP	26	SU	3.05	30.4%	10.0%	2.3%	.311	3.83	28.9%	18.4%	143	+0.78	2.96	771	67
Lou Trivino R 2018 · 3.54 FIP	26	SU	3.54	27.4%	9.0%	2.9%	.247	3.90	22.4%	11.8%	157	+0.36	2.39	595	67
Dovydas Neverauskas R 2019 · 4.33 FIP	26	SU	4.33	26.7%	9.7%	4.1%	.352	5.67	25.8%	14.6%	19	+1.34	2.74	353	66
Reyes Moronta R 2019 · 3.31 FIP	26	SU	3.31	28.5%	13.0%	1.8%	.264	5.16	21.5%	5.3%	56	+1.85	3.06	361	66
Tanner Rainey R 2019 · 3.59 FIP	26	SU	3.59	34.5%	16.4%	2.4%	.304	4.29	31.6%	19.7%	82	+0.70	2.63	563	66
Trevor Megill R 2019 · 3.29 FIP	25	SU	3.29	28.4%	9.1%	2.6%	.408	3.87	25.8%	17.6%	83	+0.58	1.54	391	66
Brooks Kriske R 2019 · 3.47 FIP	25	SU	3.47	26.1%	12.2%	1.9%	.245	4.95	28.6%	16.5%	41	+1.48	3.09	246	66
Kiko Calero R 2003 · 3.54 FIP	28	SU	3.54	31.5%	11.1%	3.1%	.273	3.11	26.1%	18.9%	159	-0.43	2.27	298	66
Josh James R 2019 · 3.71 FIP	26	SU	3.71	37.6%	13.2%	3.9%	.298	4.56	24.0%	9.4%	62	+0.85	1.99	571	66
Cody Carroll R 2018 · 3.73 FIP	25	SU	3.73	24.2%	12.7%	2.0%	.282	6.46	24.3%	12.3%	24	+2.73	3.67	311	65

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	1.2	59	29.1%	12.3%	0.94	3.75
Antonio Bastardo ('17)	2.0	56	28.0%	11.4%	1.01	4.01
Chad Fox ('09)	1.1	57	25.8%	13.2%	0.87	3.79
Kyle Barraclough ('23)	1.4	56	28.2%	13.9%	0.99	3.86
Rod Scurry ('80-'88, 5 WAR*)	2.3	58	29.6%*	13.6%*	0.91*	3.67*
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*