Calvin Faucher

P Miami Marlins

Age 31 RHP 6'1" / 190 lbs MLB peak 0.5 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	28	MIX2 levels	57	60	3.30	2.28	25.7%	9.2%	1.6	K 26.8% · BB 9.8% · FIP 2.08
2025	29	MLBMIA	65	60	3.28	4.06	23.1%	9.4%	0.3
2026	30	MLBMIA	69	68	3.56	2.73	24.8%	12.2%	1.5
2027PROJ	31	MLBMIA	50	53	3.80	3.85	25.0%	11.3%	0.4
2028PROJ95% MLB	32	MLBMIA	32	34	3.98	4.10	24.2%	11.8%	0.2
2029PROJ95% MLB	33	MLBMIA	22	23	4.22	4.38	23.4%	12.2%	0.0

Last 3 seasons WAR 3.5 · Next 3 projected WAR 0.7Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo77

xwOBA vs67

K%64

Form1.57 ERA (proj 3.80) · K 29.3% (proj 25.0%) · BB 7.6% (proj 11.3%) ▲▲ last 90d · 23 IP through Oct 27

CompsJose Veras (age 31) · Pedro Báez (age 31) · Tom Wilhelmsen (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10294vR 86

ERA3.80

FIP3.85

K%25.0%

BB%11.3%

K-BB%13.7%

Proj IP53

Value2027 · WAR

Runs saved vs league avg · 53 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL4040

CMD5050

K†6060

Statcast Percentiles

FB Velo

p7796.4

Whiff%

p5526.0%

p6424.8%

xwOBA vs

p670.295

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)
2017	21	ROK MLE	Elizabethton Twins	5	0	7	30	13	3	1	0%	1.5	43.3%	10.0%	33.3%	3.3%	1.23	2.54	—
2017	21	ROK RAW	Elizabethton Twins	5	0	7	30	13	3	1	0%	1.5	43.3%	10.0%	33.3%	3.3%	1.23	2.55	—
2018	22	MIX MLE	2 levels	36	0	66	293	62	34	5	0%	1.8	15.7%	13.7%	2.1%	1.9%	4.09	4.55	—
2018	22	MIX RAW	2 levels	36	0	66	293	62	34	5	0%	1.8	21.2%	11.6%	9.6%	1.7%	4.09	3.75	—
2019	23	A+ MLE	Fort Myers Miracle	34	0	55	240	61	22	2	0%	1.6	19.6%	10.5%	9.0%	0.8%	4.42	3.20	—
2019	23	A+ RAW	Fort Myers Miracle	34	0	55	240	61	22	2	0%	1.6	25.4%	9.2%	16.2%	0.8%	4.42	2.55	—
2021	25	MIX MLE	2 levels	32	3	56	247	72	31	7	9%	1.7	24.3%	13.7%	10.7%	3.5%	4.53	4.71	—
2021	25	MIX RAW	2 levels	32	3	56	247	72	31	7	9%	1.7	29.1%	12.6%	16.6%	2.8%	4.53	3.82	—
2022	26	MIX MLE	2 levels	56	4	64	293	73	30	11	7%	1.1	22.8%	10.6%	12.2%	3.9%	4.20	4.68	-0.1
2022	26	MIX RAW	2 levels	56	4	64	293	73	30	11	7%	1.1	24.9%	10.2%	14.7%	3.8%	4.20	4.45	+0.1
2023	27	MIX MLE	3 levels	26	5	35	166	38	19	4	19%	1.4	20.8%	10.0%	10.8%	3.4%	5.35	4.49	+0.0
2023	27	MIX RAW	3 levels	26	5	35	166	38	19	4	19%	1.4	22.9%	11.4%	11.4%	2.4%	5.35	4.03	+0.2
2024	28	MIX MLE	2 levels	57	0	60	261	67	24	1	0%	1.1	26.8%	9.8%	17.0%	0.0%	3.30	2.08	+1.8
2024	28	MIX MLE	2 levels	57	0	60	261	67	24	1	0%	1.1	26.8%	9.8%	17.0%	0.0%	3.30	2.08	+1.8
2024	28	MIX RAW	2 levels	57	0	60	261	67	24	1	0%	1.1	25.7%	9.2%	16.5%	0.4%	3.30	2.28	+1.6
2025	29	MLB MLE	Miami Marlins	65	0	60	255	59	24	8	0%	0.9	23.1%	9.4%	13.7%	3.3%	3.28	4.15	+0.3
2025	29	MLB MLE	Miami Marlins	65	0	60	255	59	24	8	0%	0.9	23.1%	9.4%	13.7%	3.3%	3.28	4.15	+0.3
2025	29	MLB RAW	Miami Marlins	65	0	60	255	59	24	8	0%	0.9	23.1%	9.4%	13.7%	3.1%	3.28	4.06	+0.3
2026	30	MLB MLE	Miami Marlins	69	0	68	294	73	36	1	0%	1.0	24.8%	12.2%	12.6%	0.4%	3.56	2.75	+1.5
2026	30	MLB MLE	Miami Marlins	69	0	68	294	73	36	1	0%	1.0	24.8%	12.2%	12.6%	0.4%	3.56	2.75	+1.5
2026	30	MLB RAW	Miami Marlins	69	0	68	294	73	36	1	0%	1.0	24.8%	12.2%	12.6%	0.3%	3.56	2.73	+1.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			226	4	229	1005	241	105	17	2%	1.0	24.0%	10.4%	13.5%	1.7%	3.96	3.34	+3.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	MIA	50	0	53	224	56	25	4	0%	1.1	25.0%	11.3%	13.7%	1.9%	3.80	3.85	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	MIA	35	0	36	153	37	18	3	0%	1.0	24.2%	11.8%	12.5%	2.1%	3.98	4.10	+0.2
2029	33	MLB MLE	MIA	23	0	24	101	24	12	2	0%	1.0	23.4%	12.2%	11.2%	2.4%	4.22	4.38	+0.0
2028	32	MLB CTX	MIA	32	0	34	144	35	17	3	0%	1.1	24.2%	11.8%	12.5%	2.1%	3.98	4.10	+0.2
2029	33	MLB CTX	MIA	22	0	23	97	23	12	2	0%	1.0	23.4%	12.2%	11.2%	2.4%	4.22	4.38	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		281	4	287	1247	299	134	22	1%	1.0	24.0%	10.7%	13.2%	1.8%	3.99	3.43	+3.8
/ 200 IP	—	RAW		196	3	200	870	209	94	15	1%	1.0	24.0%	10.7%	13.2%	1.8%	3.99	3.43	+2.7
Career	—	MLE		380	12	472	2079	470	235	44	3%	1.2	22.6%	11.3%	11.3%	2.1%	3.96	3.78	+3.6
/ 200 IP	—	MLE		161	5	200	880	199	100	19	3%	1.2	22.6%	11.3%	11.3%	2.1%	3.96	3.78	+2.5

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.

2024 AAAJacksonville Jumbo Shrimp · 6 IPFIP 4.40 → 4.93 (+0.53)K% 15.4% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.38%	—	×0.860	13.23%
BB% (unintentional) /BF	3.85%	—	×0.900	3.46%
HR / BF /BF	3.85%	÷0.925	×1.100	4.57%

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 85).

Result: FIP 4.40 → 4.93, 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 AAADurham Bulls · 9 IPFIP 2.23 → 2.43 (+0.20)K% 33.3% → 28.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.860	28.67%
BB% (unintentional) /BF	15.38%	—	×0.900	13.85%
HR / BF /BF	0.00%	÷1.137	×1.100	0.00%

Result: FIP 2.23 → 2.43, 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).

2022 AAADurham Bulls · 43 IPFIP 4.13 → 4.60 (+0.47)K% 27.1% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.08%	—	×0.880	23.83%
BB% (unintentional) /BF	10.42%	—	×1.050	10.94%
HR / BF /BF	3.65%	÷1.034	×1.100	3.88%

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 107).

Result: FIP 4.13 → 4.60, 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 AAMontgomery Biscuits · 35 IPFIP 4.56 → 5.73 (+1.17)K% 27.4% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.38%	—	×0.810	22.18%
BB% (unintentional) /BF	14.29%	—	×1.100	15.71%
HR / BF /BF	3.57%	÷0.938	×1.200	4.57%

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 88).

Result: FIP 4.56 → 5.73, 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).

2021 AAADurham Bulls · 20 IPFIP 2.14 → 2.55 (+0.42)K% 32.9% → 29.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.91%	—	×0.880	28.96%
BB% (unintentional) /BF	8.86%	—	×1.050	9.30%
HR / BF /BF	1.27%	÷1.059	×1.100	1.32%

Result: FIP 2.14 → 2.55, 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).

2019 A+Fort Myers Miracle · 55 IPFIP 2.57 → 3.20 (+0.63)K% 25.4% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.42%	—	×0.770	19.57%
BB% (unintentional) /BF	9.17%	—	×1.150	10.54%
HR / BF /BF	0.83%	÷1.362	×1.250	0.77%

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 172).

Result: FIP 2.57 → 3.20, 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).

2018 ACedar Rapids Kernels · 54 IPFIP 3.96 → 4.91 (+0.95)K% 23.3% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.31%	—	×0.740	17.25%
BB% (unintentional) /BF	13.14%	—	×1.180	15.50%
HR / BF /BF	2.12%	÷1.163	×1.300	2.37%

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 133).

Result: FIP 3.96 → 4.91, 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).

2018 A+Fort Myers Miracle · 12 IPFIP 2.73 → 3.07 (+0.34)K% 12.3% → 9.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.28%	—	×0.770	9.46%
BB% (unintentional) /BF	5.26%	—	×1.150	6.05%
HR / BF /BF	0.00%	÷1.059	×1.250	0.00%

Result: FIP 2.73 → 3.07, 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
Calvin Faucher (OGILVIE)	—	—	3.85	25.0%	11.3%	1.9%	—	4.21	23.9%	11.9%	60	+0.36	—	—	—
Jose Veras R 2012 · 3.39 FIP	31	SU	3.39	26.3%	13.0%	1.6%	.316	3.90	22.7%	12.7%	128	+0.51	3.37	422	72
Pedro Báez R 2019 · 3.14 FIP	31	SU	3.14	25.0%	8.0%	2.1%	.207	4.30	18.6%	8.6%	17	+1.16	2.29	356	72
Tom Wilhelmsen R 2015 · 3.07 FIP	31	SU	3.07	22.5%	9.7%	1.1%	.298	5.78	13.8%	4.1%	86	+2.71	2.72	398	70
Kiko Calero R 2006 · 2.77 FIP	31	SU	2.77	27.8%	8.7%	1.7%	.309	2.92	24.0%	13.4%	101	+0.15	2.27	298	70
Brad Brach R 2017 · 3.36 FIP	31	SU	3.36	25.5%	9.1%	2.3%	.254	3.68	22.8%	11.1%	129	+0.32	2.69	570	69
Fernando Rodriguez Jr. R 2015 · 3.34 FIP	31	SU	3.34	26.5%	9.6%	2.3%	.241	3.89	23.3%	13.2%	105	+0.55	3.34	335	69
Santiago Casilla R 2011 · 3.02 FIP	31	SU	3.02	21.3%	11.4%	0.5%	.227	3.42	19.8%	12.7%	172	+0.40	2.76	647	68
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	68
Matt Bush R 2017 · 3.60 FIP	31	SU	3.60	24.2%	7.9%	2.8%	.321	4.72	17.6%	4.6%	23	+1.12	2.87	249	67
Jeff Fulchino R 2011 · 4.44 FIP	31	SU	4.44	20.4%	11.1%	3.0%	.302	—	—	—	—	—	3.36	178	67
Brian Schlitter R 2016 · 3.28 FIP	30	SU	3.28	20.6%	10.8%	1.0%	.333	3.81	14.4%	6.6%	110	+0.53	3.27	300	67
Manny Acosta R 2012 · 4.49 FIP	31	SU	4.49	21.3%	11.1%	3.2%	.295	—	—	—	—	—	3.08	350	67
Mike DeJean R 2002 · 3.80 FIP	31	SU	3.80	19.9%	9.5%	2.1%	.265	3.66	19.6%	10.5%	206	-0.14	2.82	622	67
Fernando Rodney R 2008 · 3.46 FIP	31	SU	3.46	26.1%	13.3%	1.6%	.279	4.09	17.8%	5.3%	176	+0.63	1.85	933	67
Brian Sanches R 2010 · 4.24 FIP	31	SU	4.24	21.3%	10.6%	2.9%	.217	4.35	19.6%	8.5%	62	+0.11	3.39	229	67
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	66
Grant Balfour R 2009 · 3.67 FIP	31	SU	3.67	23.9%	11.4%	2.1%	.293	3.20	24.8%	16.8%	192	-0.47	2.04	533	66
J.J. Putz R 2008 · 3.46 FIP	31	SU	3.46	26.5%	12.3%	1.9%	.336	2.67	25.2%	18.5%	141	-0.79	1.43	563	66
Guillermo Mota R 2004 · 3.39 FIP	31	SU	3.39	21.6%	7.9%	2.0%	.249	4.11	19.3%	11.6%	182	+0.72	2.68	857	66
Chris Hatcher R 2016 · 4.61 FIP	31	SU	4.61	23.8%	9.4%	4.2%	.283	4.69	22.0%	13.8%	96	+0.08	2.51	246	66

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	1.7	43	24.1%	11.1%	0.70	3.96
Marc Rzepczynski ('18)	2.2	48	21.6%	10.8%	0.75	3.89
Chaz Roe ('21)	1.1	43	26.4%	11.1%	0.79	3.89
Daniel Bard ('23)	2.3	57	24.2%	12.3%	0.85	3.74
Ray Searage ('81-'90, 4 WAR*)	1.4	41	21.0%*	10.8%*	0.84*	3.70*
Dave Geisel ('78-'85, 2 WAR*)	1.0	42	23.5%*	10.6%*	0.84*	4.12*
Mike Fetters ('89-'04, 6 WAR*)	3.6	55	20.3%*	10.4%*	0.83*	3.70*