Carson Ragsdale

P Gwinnett Stripers

Age 29 RHP 6'8" / 235 lbs AAA peak 0.1 · 2027

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	25	A+SF	7	7	28	2.93	1.18	37.8%	5.4%	—	K 29.1% · BB 6.2% · FIP 2.00
2024	26	MIX2 levels	27	26	121	4.18	4.13	29.1%	11.3%	—	K 24.1% · BB 11.4% · FIP 4.79
2025	27	MIX2 levels	28	19	95	5.70	5.66	19.3%	11.5%	-0.3	K 16.8% · BB 10.7% · FIP 6.07
2026	28	No MLB games played
2027PROJ	29	MLBBAL	1	1	7	5.59	5.59	17.5%	12.1%	-0.0
2028PROJ37% MLB	30	MLBBAL	3	3	20	5.57	5.64	17.8%	12.1%	-0.1
2029PROJ55% MLB	31	MLBBAL	4	4	25	5.64	5.75	17.8%	12.2%	-0.1

Last 3 seasons WAR -0.3 · Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control40Command40

CompsZack Segovia (age 32) · Travis Smith (age 29) · Reinier Roibal (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 139131vR 123

ERA5.59

FIP5.59

K%17.5%

BB%12.1%

K-BB%5.5%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL4040

CMD4040

K†4040

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	23	A MLE	San Jose Giants	24	24	114	494	167	45	13	100%	4.7	25.0%	10.7%	14.3%	3.4%	4.43	4.21	—
2021	23	A RAW	San Jose Giants	24	24	114	494	167	45	13	100%	4.7	33.8%	9.1%	24.7%	2.6%	4.43	2.84	—
2022	24	ROK MLE	ACL Giants Black	5	4	6	25	9	3	0	80%	1.1	36.0%	12.0%	24.0%	0.0%	0.00	1.58	—
2022	24	ROK RAW	ACL Giants Black	5	4	6	25	9	3	0	80%	1.1	36.0%	12.0%	24.0%	0.0%	0.00	1.51	—
2023	25	A+ MLE	Eugene Emeralds	7	7	28	111	42	6	1	100%	4.0	29.1%	6.2%	22.9%	1.0%	2.93	2.00	—
2023	25	A+ RAW	Eugene Emeralds	7	7	28	111	42	6	1	100%	4.0	37.8%	5.4%	32.4%	0.9%	2.93	1.18	—
2024	26	MIX MLE	2 levels	27	26	121	506	147	57	19	96%	4.5	24.1%	11.4%	12.7%	4.2%	4.18	4.79	—
2024	26	MIX MLE	2 levels	27	26	121	506	147	57	19	96%	4.5	24.1%	11.4%	12.7%	4.2%	4.18	4.79	—
2024	26	MIX RAW	2 levels	27	26	121	506	147	57	19	96%	4.5	29.1%	11.3%	17.8%	3.8%	4.18	4.13	—
2025	27	MIX MLE	2 levels	28	19	95	419	81	48	20	68%	3.4	16.8%	10.7%	6.1%	5.5%	5.70	6.07	-0.7
2025	27	MIX MLE	2 levels	28	19	95	419	81	48	20	68%	3.4	16.8%	10.7%	6.1%	5.5%	5.70	6.07	-0.7
2025	27	MIX RAW	2 levels	28	19	95	419	81	48	20	68%	3.4	19.3%	11.5%	7.9%	4.8%	5.70	5.66	-0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			2	0	5	25	4	1	1	0%	2.5	16.0%	4.0%	12.0%	4.0%	14.40	4.70	-0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	BAL	1	1	7	30	5	4	1	100%	7.0	17.5%	12.1%	5.5%	3.8%	5.59	5.59	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	BAL	9	9	54	227	40	27	9	100%	6.0	17.8%	12.1%	5.7%	3.9%	5.57	5.64	-0.1
2029	31	MLB MLE	BAL	8	8	45	190	34	23	8	100%	5.6	17.8%	12.2%	5.6%	4.0%	5.64	5.75	-0.2
2028	30	MLB CTX	BAL	3	3	20	84	15	10	3	100%	6.7	17.8%	12.1%	5.7%	3.9%	5.57	5.64	-0.1
2029	31	MLB CTX	BAL	4	4	25	106	19	13	4	100%	6.2	17.8%	12.2%	5.6%	4.0%	5.64	5.75	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	7	50	213	37	24	8	78%	5.5	17.6%	11.2%	6.4%	4.0%	6.50	5.22	+0.1
/ 200 IP	—	RAW		38	30	200	860	149	97	32	79%	5.3	17.6%	11.2%	6.4%	4.0%	6.50	5.22	+0.4
Career	—	MLE		91	80	362	1555	357	165	62	88%	4.0	23.0%	10.6%	12.3%	4.0%	4.50	4.70	-0.3
/ 200 IP	—	MLE		50	44	200	858	197	91	34	88%	4.0	23.0%	10.6%	12.3%	4.0%	4.50	4.70	-0.5

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.

2025 AAAGwinnett Stripers · 90 IPFIP 5.61 → 6.07 (+0.46)K% 19.5% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.54%	—	×0.860	16.81%
BB% (unintentional) /BF	11.93%	—	×0.900	10.74%
HR / BF /BF	4.82%	÷0.961	×1.100	5.52%

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 92).

Result: FIP 5.61 → 6.07, 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).

2024 AARichmond Flying Squirrels · 67 IPFIP 3.57 → 4.49 (+0.92)K% 33.5% → 27.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.46%	—	×0.810	27.10%
BB% (unintentional) /BF	11.52%	—	×1.100	12.68%
HR / BF /BF	3.35%	÷1.062	×1.200	3.78%

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 112).

Result: FIP 3.57 → 4.49, 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 AAASacramento River Cats · 54 IPFIP 4.77 → 5.13 (+0.35)K% 24.1% → 20.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.05%	—	×0.860	20.68%
BB% (unintentional) /BF	10.97%	—	×0.900	9.87%
HR / BF /BF	4.22%	÷1.010	×1.100	4.59%

Result: FIP 4.77 → 5.13, 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+Eugene Emeralds · 28 IPFIP 1.08 → 2.00 (+0.92)K% 37.8% → 29.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.84%	—	×0.770	29.14%
BB% (unintentional) /BF	5.41%	—	×1.150	6.22%
HR / BF /BF	0.90%	÷1.076	×1.250	1.05%

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 115).

Result: FIP 1.08 → 2.00, 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 ROKACL Giants Black · 6 IPFIP 1.58 → 2.93 (+1.35)K% 36.0% → 24.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.00%	—	×0.680	24.48%
BB% (unintentional) /BF	12.00%	—	×1.250	15.00%
HR / BF /BF	0.00%	÷1.073	×1.400	0.00%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 115).

Result: FIP 1.58 → 2.93, 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).

2021 ASan Jose Giants · 114 IPFIP 2.84 → 4.21 (+1.37)K% 33.8% → 25.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.81%	—	×0.740	25.02%
BB% (unintentional) /BF	9.11%	—	×1.180	10.75%
HR / BF /BF	2.63%	÷1.008	×1.300	3.40%

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 102).

Result: FIP 2.84 → 4.21, 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
Carson Ragsdale (OGILVIE)	—	—	5.59	17.5%	12.1%	3.8%	—	5.69	17.8%	5.6%	99	+0.10	—	—	—
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	80
Travis Smith R 2002 · 5.28 FIP	29	SP	5.28	13.1%	8.2%	4.1%	.324	5.71	15.0%	9.0%	51	+0.43	3.67	105	79
Reinier Roibal R 2019 · 4.91 FIP	30	SP	4.91	17.5%	11.8%	3.3%	.426	—	—	—	—	—	3.11	133	77
Daniel Guerrero R 2016 · 4.81 FIP	31	SP	4.81	12.4%	11.6%	2.3%	.328	4.93	11.7%	2.0%	175	+0.12	4.61	269	75
David Griffin R 2023 · 5.83 FIP	27	SP-	5.83	14.2%	9.2%	5.0%	.306	—	—	—	—	—	4.43	239	72
David Fletcher R 2024 · 5.67 FIP	30	SP-	5.67	7.5%	10.3%	3.5%	.294	—	—	—	—	—	5.67	100	71
Miguel Ruiz R 2015 · 5.77 FIP	29	SP-	5.77	8.8%	8.0%	4.4%	.346	5.60	10.6%	-0.4%	53	-0.17	5.60	117	71
Robert Ellis R 2001 · 4.84 FIP	30	SP	4.84	9.9%	7.7%	2.9%	.287	8.08	9.0%	-2.2%	18	+3.24	4.84	110	69
Noah Song R 2023 · 6.06 FIP	26	SP	6.06	12.0%	13.2%	4.2%	.239	3.80	19.8%	8.3%	116	-2.26	3.68	138	69
Walter Silva R 2009 · 5.72 FIP	32	SP	5.72	9.1%	12.4%	3.3%	.330	—	—	—	—	—	3.67	453	69
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	68
Marco Quevedo R 2016 · 4.57 FIP	29	SP	4.57	13.6%	6.2%	3.3%	.258	5.02	11.5%	3.2%	107	+0.45	4.13	300	68
Erik Hiljus R 2002 · 6.07 FIP	29	SP	6.07	14.1%	9.7%	5.3%	.281	—	—	—	—	—	3.35	112	68
Blair Henley R 2024 · 5.41 FIP	27	SP	5.41	17.2%	12.4%	4.0%	.318	—	—	—	—	—	3.97	187	68
Kohei Arihara R 2022 · 4.58 FIP	29	SP-	4.58	16.4%	7.2%	3.5%	.333	—	—	—	—	—	4.58	135	67
Travis Driskill R 2002 · 4.95 FIP	30	SP-	4.95	13.2%	8.0%	3.6%	.291	4.26	15.3%	12.0%	48	-0.69	4.26	181	67
Andres Ivan Meza R 2015 · 4.45 FIP	28	SP	4.45	10.9%	5.6%	2.9%	.322	4.14	12.5%	4.0%	85	-0.31	4.14	275	67
Jordan Cooper R 2015 · 5.01 FIP	26	SP	5.01	9.2%	10.2%	2.5%	.305	—	—	—	—	—	5.01	106	66
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	66
Mark Appel R 2021 · 5.90 FIP	30	SP-	5.90	15.6%	15.6%	3.9%	.260	4.22	18.5%	8.1%	40	-1.68	4.22	363	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	0.9	57	17.6%	11.9%	1.50	5.85
Matt Perisho ('05)	1.4	69	15.2%	12.2%	1.37	6.39
Scott Proctor ('11)	1.7	57	19.0%	10.9%	1.52	4.78
Dave Stevens ('00)	1.3	50	14.6%	11.3%	1.76	6.02
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Darrel Akerfelds ('86-'91, -3 WAR*)	1.2	78	15.8%*	11.9%*	1.61*	5.40*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*