Chris Roycroft

P Athletics

Age 30 RHP 6'8" / 230 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	63	80	3.04	3.24	22.2%	9.7%	1.3	K 20.4% · BB 9.2% · FIP 3.38
2025	28	MIX2 levels	55	67	5.75	3.98	19.9%	11.3%	0.5	K 17.8% · BB 10.5% · FIP 4.20
2026	29	MIX2 levels	54	67	5.91	4.94	16.4%	8.8%	-0.3	K 15.4% · BB 8.6% · FIP 4.85
2027PROJ	30	MLBOAK	31	33	5.25	5.18	16.8%	11.0%	-0.2
2028PROJ90% MLB	31	MLBOAK	19	20	5.26	5.33	16.7%	11.2%	-0.2
2029PROJ91% MLB	32	MLBOAK	11	12	5.38	5.51	16.4%	11.4%	-0.1

Last 3 seasons WAR 1.4 · Next 3 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo58

K%10

xwOBA vs10

Form3.29 ERA (proj 5.25) · K 17.2% (proj 16.8%) · BB 14.1% (proj 11.0%) ▼ last 60d · 14 IP through Oct 27

CompsWirfin Obispo (age 30) · Esteban Haro (age 30) · Jim Miller (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 137129vR 121

ERA5.25

FIP5.18

K%16.8%

BB%11.0%

K-BB%5.8%

Proj IP38

Value2027 · WAR

Runs saved vs league avg · 38 IP

Grades · Statcast · Contract

Scouting Grades

STUF4040

CTRL3535

CMD3535

K†4040

Statcast Percentiles

FB Velo

p5895.1

Whiff%

p1017.3%

p1015.3%

xwOBA vs

p100.375

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	25	A+ MLE	Peoria Chiefs	19	0	32	157	40	16	2	0%	1.7	19.6%	11.7%	7.9%	1.4%	4.50	3.71	—
2022	25	A+ RAW	Peoria Chiefs	19	0	32	157	40	16	2	0%	1.7	25.5%	10.2%	15.3%	1.3%	4.50	2.91	—
2023	26	MIX MLE	3 levels	46	0	63	294	64	40	3	0%	1.4	16.5%	14.7%	1.8%	1.4%	5.86	4.31	—
2023	26	MIX RAW	3 levels	46	0	63	294	64	40	3	0%	1.4	21.8%	13.6%	8.2%	1.0%	5.86	3.59	—
2024	27	MIX MLE	2 levels	63	0	80	351	78	34	5	0%	1.3	20.4%	9.2%	11.2%	1.5%	3.04	3.38	+1.1
2024	27	MIX MLE	2 levels	63	0	80	351	78	34	5	0%	1.3	20.4%	9.2%	11.2%	1.5%	3.04	3.38	+1.1
2024	27	MIX RAW	2 levels	63	0	80	351	78	34	5	0%	1.3	22.2%	9.7%	12.5%	1.4%	3.04	3.24	+1.3
2025	28	MIX MLE	2 levels	55	0	67	311	62	35	6	0%	1.2	17.8%	10.5%	7.3%	2.3%	5.75	4.20	+0.3
2025	28	MIX MLE	2 levels	55	0	67	311	62	35	6	0%	1.2	17.8%	10.5%	7.3%	2.3%	5.75	4.20	+0.3
2025	28	MIX RAW	2 levels	55	0	67	311	62	35	6	0%	1.2	19.9%	11.3%	8.7%	1.9%	5.75	3.98	+0.5
2026	29	MIX MLE	2 levels	54	0	67	317	52	28	11	0%	1.2	15.4%	8.6%	6.8%	3.6%	5.91	4.85	-0.2
2026	29	MIX MLE	2 levels	54	0	67	317	52	28	11	0%	1.2	15.4%	8.6%	6.8%	3.6%	5.91	4.85	-0.2
2026	29	MIX RAW	2 levels	54	0	67	317	52	28	11	0%	1.2	16.4%	8.8%	7.6%	3.5%	5.91	4.94	-0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			74	0	93	445	77	48	14	0%	1.3	17.3%	10.8%	6.5%	3.1%	5.98	4.94	-0.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	OAK	31	0	33	139	23	15	4	0%	1.1	16.8%	11.0%	5.8%	3.2%	5.25	5.18	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	OAK	21	0	22	93	16	10	3	0%	1.1	16.7%	11.2%	5.5%	3.4%	5.26	5.33	-0.2
2029	32	MLB MLE	OAK	13	0	14	57	9	7	2	0%	1.0	16.4%	11.4%	5.0%	3.6%	5.38	5.51	-0.1
2028	31	MLB CTX	OAK	19	0	20	84	14	9	3	0%	1.1	16.7%	11.2%	5.5%	3.4%	5.26	5.33	-0.2
2029	32	MLB CTX	OAK	11	0	12	51	8	6	2	0%	1.1	16.4%	11.4%	5.0%	3.6%	5.38	5.51	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		105	0	125	581	100	63	19	0%	1.2	17.1%	10.9%	6.2%	3.2%	5.81	4.80	-0.4
/ 200 IP	—	RAW		167	0	200	926	159	100	30	0%	1.2	17.1%	10.9%	6.2%	3.2%	5.81	4.80	-0.6
Career	—	MLE		237	0	309	1430	255	154	30	0%	1.3	17.8%	10.7%	7.1%	2.1%	4.98	4.11	-0.8
/ 200 IP	—	MLE		153	0	200	925	165	99	20	0%	1.3	17.8%	10.7%	7.1%	2.1%	4.98	4.11	-1.2

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 · 29 IPFIP 2.80 → 2.98 (+0.18)K% 18.0% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.97%	—	×0.860	15.45%
BB% (unintentional) /BF	6.25%	—	×0.900	5.62%
HR / BF /BF	0.78%	÷1.000	×1.100	0.86%

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 2.80 → 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).

2025 AAAMemphis Redbirds · 47 IPFIP 3.70 → 4.10 (+0.40)K% 22.4% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.38%	—	×0.860	19.25%
BB% (unintentional) /BF	11.43%	—	×0.900	10.29%
HR / BF /BF	1.90%	÷0.869	×1.100	2.41%

Result: FIP 3.70 → 4.10, 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 AAAMemphis Redbirds · 46 IPFIP 3.10 → 3.33 (+0.23)K% 23.0% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.96%	—	×0.860	19.74%
BB% (unintentional) /BF	8.67%	—	×0.900	7.81%
HR / BF /BF	1.53%	÷1.020	×1.100	1.65%

Result: FIP 3.10 → 3.33, 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 AAAMemphis Redbirds · 32 IPFIP 3.97 → 4.15 (+0.18)K% 23.3% → 20.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.33%	—	×0.860	20.07%
BB% (unintentional) /BF	16.67%	—	×0.900	15.00%
HR / BF /BF	1.33%	÷0.955	×1.100	1.54%

Result: FIP 3.97 → 4.15, 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).

2023 AASpringfield Cardinals · 20 IPFIP 4.10 → 4.55 (+0.45)K% 13.9% → 11.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.86%	—	×0.810	11.23%
BB% (unintentional) /BF	12.87%	—	×1.100	14.16%
HR / BF /BF	0.99%	÷1.080	×1.200	1.10%

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 116).

Result: FIP 4.10 → 4.55, 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 A+Peoria Chiefs · 11 IPFIP 0.74 → 1.51 (+0.77)K% 34.9% → 26.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.88%	—	×0.770	26.86%
BB% (unintentional) /BF	4.65%	—	×1.150	5.35%
HR / BF /BF	0.00%	÷1.093	×1.250	0.00%

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 119).

Result: FIP 0.74 → 1.51, 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+Peoria Chiefs · 32 IPFIP 2.94 → 3.71 (+0.77)K% 25.5% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.48%	—	×0.770	19.62%
BB% (unintentional) /BF	10.19%	—	×1.150	11.72%
HR / BF /BF	1.27%	÷1.114	×1.250	1.43%

Result: FIP 2.94 → 3.71, 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).

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
Chris Roycroft (OGILVIE)	—	—	5.18	16.8%	11.0%	3.2%	—	5.40	16.6%	5.3%	36	+0.22	—	—	—
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	85
Esteban Haro R 2016 · 4.55 FIP	30	SU	4.55	17.1%	10.2%	2.9%	.338	3.83	11.6%	6.3%	75	-0.72	3.76	164	82
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	80
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	80
Carlos Fisher R 2011 · 4.33 FIP	28	SU	4.33	15.5%	9.1%	2.5%	.275	—	—	—	—	—	2.48	245	78
Brandon Puffer R 2004 · 5.23 FIP	28	SU	5.23	13.5%	11.2%	3.4%	.328	—	—	—	—	—	3.55	108	77
Ivan Zavala R 2017 · 5.02 FIP	30	SU	5.02	12.8%	8.0%	3.6%	.286	5.15	12.7%	5.3%	61	+0.13	4.27	209	77
Willie Eyre R 2007 · 4.53 FIP	29	SU	4.53	13.7%	9.1%	2.6%	.306	2.87	11.1%	5.5%	18	-1.66	2.87	164	76
Mike Broadway R 2017 · 4.73 FIP	30	SU	4.73	18.3%	10.2%	3.4%	.245	4.65	23.0%	12.4%	49	-0.08	1.74	195	76
Jeff Gray R 2012 · 5.43 FIP	30	SU	5.43	11.0%	9.3%	3.8%	.274	—	—	—	—	—	3.46	127	75
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	75
Beck Wheeler R 2017 · 5.40 FIP	28	SU	5.40	15.3%	12.2%	3.7%	.347	—	—	—	—	—	3.46	173	75
Drew Hayes R 2016 · 3.99 FIP	28	SU	3.99	13.8%	10.1%	1.4%	.302	—	—	—	—	—	3.35	117	74
Kyle Snyder R 2007 · 4.83 FIP	29	SU	4.83	16.9%	12.4%	2.9%	.232	—	—	—	—	—	3.80	236	74
Ronald Peña R 2021 · 4.49 FIP	29	SU	4.49	16.5%	10.4%	2.7%	.288	—	—	—	—	—	3.72	187	74
Ryan Doolittle R 2016 · 4.38 FIP	28	SU	4.38	13.9%	7.1%	2.8%	.269	—	—	—	—	—	4.03	101	74
Erik Davis R 2017 · 4.25 FIP	30	SU	4.25	22.2%	11.1%	3.0%	.349	3.52	17.4%	8.5%	65	-0.73	3.05	227	73
Ramon Troncoso R 2013 · 4.95 FIP	30	SU	4.95	13.1%	10.9%	2.9%	.260	3.05	17.3%	9.5%	82	-1.90	2.65	310	73
Adrian Garza R 2017 · 4.47 FIP	29	SU	4.47	16.0%	7.0%	3.4%	.351	5.18	9.7%	4.1%	113	+0.71	3.94	229	73
Wil Browning R 2017 · 4.44 FIP	28	SU	4.44	17.9%	13.1%	2.2%	.359	—	—	—	—	—	2.14	162	73

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	0.8	28	17.1%	11.2%	1.24	5.67
Jeff Manship ('16)	1.1	32	16.5%	9.3%	1.05	4.82
Will Cunnane ('04)	1.4	46	18.9%	10.4%	1.25	5.26
Dennis Powell ('85-'93, -2 WAR*)	1.7	49	17.6%*	10.1%*	1.18*	5.31*
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*