Ben Casparius

P Oklahoma City Comets

Age 28 RHP 6'2" / 215 lbs AAA peak 0.1 · 2027 ILInjured 60-Day (D60)

Overview

AAARPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX3 levels	24	19	97	3.25	3.02	28.4%	12.0%	2.8	K 23.7% · BB 11.5% · FIP 3.60
2025	26	MIX2 levels	51	3	83	4.55	3.39	22.1%	5.9%	1.2	K 21.3% · BB 6.3% · FIP 3.36
2026	27	MIX2 levels	17	0	15	8.40	6.77	17.5%	23.8%	-0.4	K 15.1% · BB 23.7% · FIP 5.89
2027PROJ	28	MLBLAD	29	0	30	4.29	4.33	22.8%	10.1%	0.1
2028PROJ89% MLB	29	MLBLAD	31	0	33	4.41	4.49	22.3%	10.2%	0.0
2029PROJ91% MLB	30	MLBLAD	22	0	23	4.57	4.68	21.7%	10.5%	-0.0

Last 3 seasons WAR 3.6 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsSam Lewis (age 27) · Edwin Quirarte (age 28) · Nelson Gonzalez (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 115107vR 99

ERA4.29

FIP4.33

K%22.8%

BB%10.1%

K-BB%12.7%

Proj IP35

Value2027 · WAR

Runs saved vs league avg · 35 IP

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)
2021	22	MIX MLE	2 levels	5	1	6	29	10	3	0	20%	1.2	34.5%	10.3%	24.1%	0.0%	3.00	1.50	—
2021	22	MIX RAW	2 levels	5	1	6	29	10	3	0	20%	1.2	34.5%	10.3%	24.1%	0.0%	3.00	1.27	—
2022	23	MIX MLE	2 levels	27	16	90	405	110	46	14	59%	3.3	20.6%	13.2%	7.4%	4.1%	5.22	5.29	—
2022	23	MIX RAW	2 levels	27	16	90	405	110	46	14	59%	3.3	27.2%	11.4%	15.8%	3.5%	5.22	4.22	—
2023	24	MIX MLE	2 levels	26	21	108	474	120	55	20	81%	4.1	20.1%	13.0%	7.2%	4.9%	5.27	5.73	—
2023	24	MIX RAW	2 levels	26	21	108	474	120	55	20	81%	4.1	25.3%	11.6%	13.7%	4.2%	5.27	4.82	—
2024	25	MIX MLE	3 levels	24	19	97	415	118	50	6	79%	4.0	23.7%	11.5%	12.1%	1.9%	3.25	3.60	+2.1
2024	25	MIX MLE	3 levels	24	19	97	415	118	50	6	79%	4.0	23.7%	11.5%	12.1%	1.9%	3.25	3.60	+2.1
2024	25	MIX RAW	3 levels	24	19	97	415	118	50	6	79%	4.0	28.4%	12.0%	16.4%	1.4%	3.25	3.02	+2.8
2025	26	MIX MLE	2 levels	51	3	83	353	78	21	9	6%	1.6	21.3%	6.3%	15.0%	2.3%	4.55	3.36	+1.2
2025	26	MIX MLE	2 levels	51	3	83	353	78	21	9	6%	1.6	21.3%	6.3%	15.0%	2.3%	4.55	3.36	+1.2
2025	26	MIX RAW	2 levels	51	3	83	353	78	21	9	6%	1.6	22.1%	5.9%	16.1%	2.5%	4.55	3.39	+1.2
2026	27	MIX MLE	2 levels	17	0	15	80	14	19	2	0%	0.9	15.1%	23.7%	-8.6%	1.9%	8.40	5.89	-0.2
2026	27	MIX MLE	2 levels	17	0	15	80	14	19	2	0%	0.9	15.1%	23.7%	-8.6%	1.9%	8.40	5.89	-0.2
2026	27	MIX RAW	2 levels	17	0	15	80	14	19	2	0%	0.9	17.5%	23.8%	-6.2%	2.5%	8.40	6.77	-0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			54	3	91	393	87	29	9	6%	1.7	22.1%	7.4%	14.8%	2.3%	4.67	3.43	+1.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	LAD	29	0	30	127	29	13	3	0%	1.0	22.8%	10.1%	12.7%	2.7%	4.29	4.33	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	LAD	35	0	37	156	35	16	5	0%	1.1	22.3%	10.2%	12.1%	2.9%	4.41	4.49	+0.0
2029	30	MLB MLE	LAD	24	0	26	108	23	11	3	0%	1.1	21.7%	10.5%	11.2%	3.1%	4.57	4.68	-0.0
2028	29	MLB CTX	LAD	31	0	33	139	31	14	4	0%	1.1	22.3%	10.2%	12.1%	2.9%	4.41	4.49	+0.0
2029	30	MLB CTX	LAD	22	0	23	97	21	10	3	0%	1.0	21.7%	10.5%	11.2%	3.1%	4.57	4.68	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		107	3	147	630	139	53	16	3%	1.4	22.1%	8.5%	13.6%	2.6%	4.59	3.71	+1.5
/ 200 IP	—	RAW		146	4	200	858	189	72	22	3%	1.4	22.1%	8.5%	13.6%	2.6%	4.59	3.71	+2.0
Career	—	MLE		150	60	398	1756	374	207	57	40%	2.7	21.3%	11.8%	9.5%	3.3%	4.70	4.59	+1.2
/ 200 IP	—	MLE		75	30	200	882	188	104	29	40%	2.7	21.3%	11.8%	9.5%	3.3%	4.70	4.59	+1.6

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 AAAOklahoma City Comets · 10 IPFIP 5.91 → 5.89 (−0.03)K% 17.5% → 15.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.54%	—	×0.860	15.09%
BB% (unintentional) /BF	26.32%	—	×0.900	23.68%
HR / BF /BF	1.75%	÷1.000	×1.100	1.93%

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 5.91 → 5.89, 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).

2025 AAAOklahoma City Comets · 5 IPFIP 2.89 → 3.72 (+0.83)K% 35.0% → 30.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.00%	—	×0.860	30.10%
BB% (unintentional) /BF	0.00%	—	×0.900	0.00%
HR / BF /BF	5.00%	÷0.956	×1.100	5.75%

Result: FIP 2.89 → 3.72, 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 AAAOklahoma City Baseball Club · 67 IPFIP 3.29 → 3.61 (+0.32)K% 25.4% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.44%	—	×0.860	21.88%
BB% (unintentional) /BF	12.37%	—	×0.900	11.13%
HR / BF /BF	1.41%	÷0.896	×1.100	1.73%

Result: FIP 3.29 → 3.61, 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 AATulsa Drillers · 22 IPFIP 2.70 → 3.57 (+0.87)K% 35.8% → 29.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.79%	—	×0.810	28.99%
BB% (unintentional) /BF	11.58%	—	×1.100	12.74%
HR / BF /BF	2.11%	÷1.063	×1.200	2.38%

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 113).

Result: FIP 2.70 → 3.57, 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 AATulsa Drillers · 71 IPFIP 5.11 → 5.91 (+0.80)K% 23.5% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.53%	—	×0.810	19.06%
BB% (unintentional) /BF	11.46%	—	×1.100	12.60%
HR / BF /BF	4.64%	÷1.083	×1.200	5.15%

Result: FIP 5.11 → 5.91, 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).

2023 A+Great Lakes Loons · 37 IPFIP 3.97 → 5.33 (+1.36)K% 29.1% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.14%	—	×0.770	22.44%
BB% (unintentional) /BF	11.92%	—	×1.150	13.71%
HR / BF /BF	3.31%	÷0.951	×1.250	4.35%

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 90).

Result: FIP 3.97 → 5.33, 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).

2022 A+Great Lakes Loons · 60 IPFIP 4.66 → 5.83 (+1.17)K% 23.6% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.59%	—	×0.770	18.17%
BB% (unintentional) /BF	11.27%	—	×1.150	12.96%
HR / BF /BF	3.87%	÷1.013	×1.250	4.78%

Result: FIP 4.66 → 5.83, 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 ARancho Cucamonga Quakes · 30 IPFIP 2.93 → 4.03 (+1.10)K% 35.5% → 26.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.54%	—	×0.740	26.30%
BB% (unintentional) /BF	11.57%	—	×1.180	13.65%
HR / BF /BF	2.48%	÷1.247	×1.300	2.59%

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 149).

Result: FIP 2.93 → 4.03, 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 Casparius (OGILVIE)	—	—	—	—	—	2.7%	—	4.57	22.1%	11.7%	62	+0.24	—	—	—
Sam Lewis R 2019 · 3.41 FIP	27	SP-	3.41	21.0%	10.8%	1.3%	.246	—	—	—	—	—	2.21	224	68
Edwin Quirarte R 2015 · 3.41 FIP	28	SW	3.41	16.7%	6.2%	1.7%	.311	3.48	12.7%	4.9%	83	+0.06	3.16	157	68
Nelson Gonzalez R 2018 · 5.03 FIP	28	SW	5.03	19.2%	8.2%	4.6%	.311	6.22	16.9%	4.6%	74	+1.19	3.42	258	67
Daniel Robert R 2023 · 3.45 FIP	28	SU	3.45	22.7%	10.7%	1.7%	.310	3.02	25.4%	17.1%	87	-0.43	2.32	186	67
Coleman Huntley III R 2021 · 3.85 FIP	28	SW	3.85	20.2%	7.4%	2.8%	.348	3.56	23.4%	13.2%	86	-0.29	2.38	160	67
Carlos Torres R 2010 · 4.50 FIP	27	SW	4.50	18.3%	11.3%	2.8%	.438	3.89	20.1%	13.2%	139	-0.61	2.89	604	67
Trevor May R 2018 · 3.74 FIP	28	SU	3.74	26.1%	9.8%	2.9%	.291	3.47	31.9%	23.6%	150	-0.27	3.05	477	65
Mayckol Guaipe R 2019 · 4.18 FIP	28	SW	4.18	26.0%	7.6%	4.2%	.432	—	—	—	—	—	1.88	136	64
Reinier Roibal R 2016 · 4.37 FIP	27	SW	4.37	16.9%	7.1%	3.3%	.371	4.91	17.5%	5.7%	37	+0.54	3.11	133	64
Calvin Drummond R 2016 · 3.55 FIP	26	SW	3.55	16.9%	11.1%	0.9%	.316	—	—	—	—	—	3.48	112	64
Luis Santos R 2019 · 4.31 FIP	28	SU	4.31	22.9%	10.0%	3.4%	.312	—	—	—	—	—	3.53	472	63
Dustin Nippert R 2009 · 4.09 FIP	28	SP-	4.09	18.0%	9.7%	2.3%	.271	4.49	17.9%	6.1%	57	+0.40	3.83	268	63
Connor Schultz R 2024 · 3.88 FIP	25	SU	3.88	19.7%	5.3%	3.2%	.283	4.02	18.8%	10.4%	156	+0.14	3.53	203	63
Emmanuel Chapman R 2024 · 4.08 FIP	25	SW	4.08	19.7%	10.6%	2.4%	.256	4.52	17.8%	1.3%	117	+0.44	3.81	198	63
Yoanner Negrin R 2015 · 3.79 FIP	31	SW	3.79	15.1%	7.5%	1.9%	.256	3.29	15.0%	8.5%	270	-0.50	3.15	485	63
Todd Wellemeyer R 2007 · 4.74 FIP	28	SW	4.74	17.0%	10.8%	3.1%	.270	4.86	15.5%	6.4%	373	+0.12	3.35	615	63
Cody Poteet R 2022 · 4.79 FIP	28	SW	4.79	18.4%	9.6%	3.7%	.244	3.73	21.1%	13.3%	68	-1.06	3.52	619	63
Alfonso Sanchez R 2016 · 5.26 FIP	28	SW	5.26	15.9%	7.4%	4.7%	.244	5.55	11.2%	2.3%	115	+0.29	4.51	224	62
Luis Mateo R 2017 · 4.60 FIP	27	SU	4.60	17.6%	11.2%	2.9%	.309	5.55	8.6%	-4.8%	43	+0.95	3.48	160	62
Ramon Delgado R 2016 · 4.60 FIP	29	SW	4.60	13.8%	5.9%	3.5%	.332	4.31	11.2%	7.2%	74	-0.29	4.31	135	62

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	1.0	48	22.3%	8.9%	1.01	4.53
Kevin Quackenbush ('21)	1.0	52	21.0%	9.2%	1.04	4.41
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Juan Gutierrez ('14)	1.4	57	19.4%	8.4%	1.04	4.49
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Jay Ritchie ('64-'68, 2 WAR*)	1.5	58	21.1%*	8.0%*	1.01*	4.21*
Gary Wayne ('89-'94, 2 WAR*)	1.2	62	19.9%*	9.4%*	1.05*	3.88*