Sam Moll

P Cincinnati Reds

Age 35 LHP 5'9" / 190 lbs MLB peak 0.1 · 2027

Overview

MLBRP

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	32	MIX2 levels	57	46	3.91	3.17	24.5%	7.8%	0.8	K 25.0% · BB 7.9% · FIP 2.99
2025	33	MIX2 levels	51	45	5.56	3.98	25.3%	10.3%	0.3	K 23.3% · BB 9.8% · FIP 4.11
2026	34	MLBCIN	65	56	4.79	3.76	21.8%	10.9%	0.5
2027PROJ	35	MLBCIN	46	48	4.30	4.37	22.2%	10.6%	0.1
2028PROJ91% MLB	36	MLBCIN	22	23	4.56	4.74	21.1%	11.2%	-0.1
2029PROJ82% MLB	37	MLBCIN	10	10	4.91	5.14	20.0%	11.9%	-0.1

Last 3 seasons WAR 1.6 · Next 3 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%47

xwOBA vs39

FB Velo23

Form5.93 ERA (proj 4.30) · K 15.4% (proj 22.2%) · BB 9.2% (proj 10.6%) ▼ last 90d · 14 IP through Oct 27

CompsBrian Shouse (age 35) · John Bale (age 35) · Heriberto Ruelas (age 35)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 99107vR 115

ERA4.30

FIP4.37

K%22.2%

BB%10.6%

K-BB%11.5%

Proj IP48

Value2027 · WAR

Runs saved vs league avg · 48 IP

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL4040

CMD5050

K†5555

Statcast Percentiles

FB Velo

p2392.6

Whiff%

p3122.6%

p4721.8%

xwOBA vs

p390.324

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)
2015	23	MIX MLE	2 levels	38	0	68	264	74	16	7	0%	1.8	21.8%	6.9%	14.9%	4.0%	2.63	4.33	—
2015	23	MIX RAW	2 levels	38	0	68	264	74	16	7	0%	1.8	28.0%	6.1%	22.0%	2.7%	2.63	2.97	—
2016	24	MIX MLE	2 levels	44	0	49	215	44	18	5	0%	1.1	16.4%	9.0%	7.4%	2.2%	4.74	4.06	—
2016	24	MIX RAW	2 levels	44	0	49	215	44	18	5	0%	1.1	20.5%	8.4%	12.1%	2.3%	4.74	3.73	—
2017	25	MIX MLE	2 levels	61	0	61	278	54	22	6	0%	1.0	17.0%	8.2%	8.8%	2.1%	4.43	3.85	+0.5
2017	25	MIX RAW	2 levels	61	0	61	278	54	22	6	0%	1.0	19.4%	7.9%	11.5%	2.2%	4.43	3.69	+0.6
2018	26	AAA MLE	Buffalo Bisons	15	0	19	88	19	5	1	0%	1.2	19.0%	6.0%	13.0%	1.2%	5.30	2.89	—
2018	26	AAA RAW	Buffalo Bisons	15	0	19	88	19	5	1	0%	1.2	21.6%	5.7%	15.9%	1.1%	5.30	2.56	—
2019	27	MIX MLE	2 levels	41	0	49	213	54	20	1	0%	1.2	20.2%	11.1%	9.1%	0.0%	2.39	2.80	—
2019	27	MIX RAW	2 levels	41	0	49	213	54	20	1	0%	1.2	25.4%	9.4%	16.0%	0.5%	2.39	2.39	—
2021	29	MIX MLE	2 levels	41	0	46	200	55	25	6	0%	1.1	26.5%	13.5%	13.1%	3.7%	4.34	4.62	-0.0
2021	29	MIX RAW	2 levels	41	0	46	200	55	25	6	0%	1.1	27.5%	12.5%	15.0%	3.0%	4.34	4.04	+0.3
2022	30	MLB MLE	Oakland Athletics	53	0	43	187	46	16	5	0%	0.8	24.6%	8.6%	16.0%	2.9%	2.91	3.72	+0.4
2022	30	MLB RAW	Oakland Athletics	53	0	43	187	46	16	5	0%	0.8	24.6%	8.6%	16.0%	2.7%	2.91	3.58	+0.5
2023	31	MLB MLE	Cincinnati Reds	70	1	62	268	68	22	2	1%	0.9	25.4%	8.2%	17.2%	0.7%	3.03	2.38	+1.6
2023	31	MLB RAW	Cincinnati Reds	70	1	62	268	68	22	2	1%	0.9	25.4%	8.2%	17.2%	0.7%	3.03	2.39	+1.6
2024	32	MIX MLE	2 levels	57	0	46	192	47	15	4	0%	0.8	25.0%	7.9%	17.1%	1.8%	3.91	2.99	+0.9
2024	32	MIX MLE	2 levels	57	0	46	192	47	15	4	0%	0.8	25.0%	7.9%	17.1%	1.8%	3.91	2.99	+0.9
2024	32	MIX RAW	2 levels	57	0	46	192	47	15	4	0%	0.8	24.5%	7.8%	16.7%	2.1%	3.91	3.17	+0.8
2025	33	MIX MLE	2 levels	51	0	45	194	49	20	6	0%	0.9	23.3%	9.8%	13.5%	3.2%	5.56	4.11	+0.2
2025	33	MIX MLE	2 levels	51	0	45	194	49	20	6	0%	0.9	23.3%	9.8%	13.5%	3.2%	5.56	4.11	+0.2
2025	33	MIX RAW	2 levels	51	0	45	194	49	20	6	0%	0.9	25.3%	10.3%	14.9%	3.1%	5.56	3.98	+0.3
2026	34	MLB MLE	Cincinnati Reds	65	0	56	257	56	28	5	0%	0.9	21.8%	10.9%	10.9%	1.8%	4.79	3.63	+0.6
2026	34	MLB MLE	Cincinnati Reds	65	0	56	257	56	28	5	0%	0.9	21.8%	10.9%	10.9%	1.8%	4.79	3.63	+0.6
2026	34	MLB RAW	Cincinnati Reds	65	0	56	257	56	28	5	0%	0.9	21.8%	10.9%	10.9%	1.9%	4.79	3.76	+0.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			278	1	235	1024	245	96	22	0%	0.8	23.9%	9.4%	14.6%	2.1%	3.98	3.46	+3.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	35	MLB	CIN	46	0	48	203	45	22	5	0%	1.0	22.2%	10.6%	11.5%	2.6%	4.30	4.37	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	36	MLB MLE	CIN	24	0	26	108	23	12	3	0%	1.1	21.1%	11.2%	9.9%	2.9%	4.56	4.74	-0.1
2029	37	MLB MLE	CIN	12	0	12	52	10	6	2	0%	1.0	20.0%	11.9%	8.1%	3.4%	4.91	5.14	-0.1
2030	38	MLB MLE	CIN	5	0	5	23	4	3	1	0%	1.1	18.9%	12.6%	6.3%	3.8%	5.31	5.57	-0.1
2028	36	MLB CTX	CIN	22	0	23	97	21	11	3	0%	1.0	21.1%	11.2%	9.9%	2.9%	4.56	4.74	-0.1
2029	37	MLB CTX	CIN	10	0	10	42	8	5	1	0%	1.0	20.0%	11.9%	8.1%	3.4%	4.91	5.14	-0.1
2030	38	MLB CTX	CIN	4	0	4	17	3	2	1	0%	1.0	18.9%	12.6%	6.3%	3.8%	5.31	5.57	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		313	1	272	1180	277	114	27	0%	0.9	23.5%	9.7%	13.8%	2.3%	4.08	3.59	+3.1
/ 200 IP	—	RAW		230	1	200	868	204	84	20	0%	0.9	23.5%	9.7%	13.8%	2.3%	4.08	3.59	+2.3
Career	—	MLE		536	1	545	2356	516	217	51	0%	1.0	21.9%	9.2%	12.7%	2.2%	3.88	3.61	+2.8
/ 200 IP	—	MLE		197	0	200	864	189	79	19	0%	1.0	21.9%	9.2%	12.7%	2.2%	3.88	3.61	+2.0

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.

2025 AAALouisville Bats · 27 IPFIP 3.17 → 3.56 (+0.38)K% 23.9% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.89%	—	×0.860	20.55%
BB% (unintentional) /BF	8.85%	—	×0.900	7.96%
HR / BF /BF	1.77%	÷0.901	×1.100	2.16%

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 80).

Result: FIP 3.17 → 3.56, 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 AAALouisville Bats · 8 IPFIP 3.52 → 3.68 (+0.16)K% 22.5% → 19.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.50%	—	×0.860	19.35%
BB% (unintentional) /BF	7.50%	—	×0.900	6.75%
HR / BF /BF	2.50%	÷1.111	×1.100	2.48%

Result: FIP 3.52 → 3.68, 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).

2021 AAALas Vegas Aviators · 35 IPFIP 3.94 → 4.62 (+0.68)K% 30.1% → 26.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.13%	—	×0.880	26.51%
BB% (unintentional) /BF	12.82%	—	×1.050	13.46%
HR / BF /BF	3.21%	÷0.941	×1.100	3.75%

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 88).

Result: FIP 3.94 → 4.62, 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 AARichmond Flying Squirrels · 38 IPFIP 2.27 → 2.80 (+0.53)K% 25.0% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.810	20.25%
BB% (unintentional) /BF	10.12%	—	×1.100	11.13%
HR / BF /BF	0.00%	÷0.890	×1.200	0.00%

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 78).

Result: FIP 2.27 → 2.80, 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 AAASacramento River Cats · 11 IPFIP 2.91 → 3.31 (+0.40)K% 26.7% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.67%	—	×0.880	23.47%
BB% (unintentional) /BF	6.67%	—	×1.050	7.00%
HR / BF /BF	2.22%	÷1.027	×1.100	2.38%

Result: FIP 2.91 → 3.31, 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).

2018 AAABuffalo Bisons · 19 IPFIP 2.62 → 2.89 (+0.27)K% 21.6% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.59%	—	×0.880	19.00%
BB% (unintentional) /BF	5.68%	—	×1.050	5.97%
HR / BF /BF	1.14%	÷1.080	×1.100	1.16%

Result: FIP 2.62 → 2.89, 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).

2017 AAANashville Sounds · 54 IPFIP 3.36 → 3.85 (+0.49)K% 19.3% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.34%	—	×0.880	17.02%
BB% (unintentional) /BF	7.82%	—	×1.050	8.21%
HR / BF /BF	1.65%	÷0.868	×1.100	2.09%

Result: FIP 3.36 → 3.85, 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).

2016 AAAAlbuquerque Isotopes · 47 IPFIP 3.93 → 4.06 (+0.13)K% 18.7% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.66%	—	×0.880	16.42%
BB% (unintentional) /BF	8.61%	—	×1.050	9.04%
HR / BF /BF	2.39%	÷1.202	×1.100	2.19%

Result: FIP 3.93 → 4.06, 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
Sam Moll (OGILVIE)	—	—	4.37	22.2%	10.6%	2.6%	—	4.87	20.8%	9.3%	38	+0.50	—	—	—
Brian Shouse L 2004 · 3.47 FIP	35	SU	3.47	18.5%	8.2%	1.6%	.250	3.57	14.8%	8.9%	139	+0.10	2.32	339	79
John Bale L 2009 · 4.31 FIP	35	SU	4.31	17.6%	11.8%	2.2%	.333	—	—	—	—	—	2.49	168	76
Heriberto Ruelas L 2017 · 3.42 FIP	35	SU	3.42	17.2%	6.7%	1.7%	.294	—	—	—	—	—	2.95	117	76
Juan Pablo Perez L 2013 · 3.68 FIP	34	SU	3.68	25.2%	11.5%	2.3%	.250	3.68	26.5%	11.2%	51	-0.00	1.75	104	74
Hideki Okajima L 2010 · 4.27 FIP	34	SU	4.27	15.5%	7.0%	2.9%	.333	—	—	—	—	—	3.05	238	73
Clay Rapada L 2015 · 3.84 FIP	34	SU	3.84	14.3%	8.0%	1.7%	.299	—	—	—	—	—	3.00	120	70
Tim Byrdak L 2009 · 5.07 FIP	35	SU	5.07	22.2%	13.8%	3.8%	.185	3.48	23.8%	13.5%	107	-1.59	2.85	320	70
Brandon Mann L 2018 · 3.59 FIP	34	SU	3.59	17.8%	11.4%	1.0%	.232	—	—	—	—	—	3.59	190	70
Scott Rice L 2015 · 3.67 FIP	33	SU	3.67	22.9%	17.2%	0.6%	.266	—	—	—	—	—	3.10	104	64
Raul Valdes L 2013 · 4.07 FIP	35	SU	4.07	24.3%	5.3%	4.3%	.350	—	—	—	—	—	2.29	160	63
Hisanori Takahashi L 2010 · 3.50 FIP	35	SW	3.50	22.1%	7.0%	2.5%	.292	3.81	21.1%	15.0%	118	+0.31	3.50	240	62
Luke Westphal L 2024 · 5.19 FIP	35	SW	5.19	15.7%	16.4%	2.4%	.299	—	—	—	—	—	2.97	294	49
Brendan Donnelly R 2006 · 4.21 FIP	35	SU	4.21	19.1%	9.0%	2.9%	.260	3.19	18.6%	10.1%	60	-1.02	2.23	385	42
Jean Machi R 2017 · 4.12 FIP	35	SU	4.12	18.6%	6.6%	3.2%	.285	—	—	—	—	—	2.16	306	40
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	39
Juan Sandoval R 2016 · 3.24 FIP	35	SU	3.24	18.2%	10.2%	0.7%	.288	4.40	16.3%	9.1%	116	+1.16	3.24	225	39
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	38
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	38
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	38
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	37

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	1.6	41	23.2%	11.1%	0.91	4.13
José Cisnero ('24)	1.4	46	24.0%	11.3%	1.01	4.16
Yorkis Perez ('02)	1.4	40	20.8%	11.8%	0.93	4.44
Ray Searage ('81-'90, 4 WAR*)	1.4	41	21.0%*	10.8%*	0.84*	3.70*
Cam Bedrosian ('21)	1.5	50	24.0%	10.2%	0.92	3.81
Ed Vosberg ('86-'02, 1 WAR*)	1.2	47	21.0%*	9.6%*	0.86*	4.06*
Tony Fossas ('88-'99, 2 WAR*)	2.1	42	21.9%*	9.3%*	0.99*	3.88*