Sam Carlson

P Sugar Land Space Cowboys

Age 28 RHP 6'4" / 195 lbs AAA peak 0.1 · 2027

Overview

AAAPROSPECT

ETA2029MLB%10%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	AAMIL	44	49	4.25	2.71	23.5%	8.8%	—	K 19.0% · BB 9.6% · FIP 3.22
2025	26	AAALAD	45	60	4.22	3.17	28.6%	13.2%	—	K 24.6% · BB 11.9% · FIP 3.45
2026	27	MIX2 levels	36	42	4.10	3.32	29.1%	8.9%	—	K 24.7% · BB 8.4% · FIP 3.69
2027PROJ	28	MLBHOU	11	12	4.19	4.19	24.8%	10.4%	0.1
2028PROJ37% MLB	29	MLBHOU	34	36	4.28	4.33	24.3%	10.4%	0.1
2029PROJ55% MLB	30	MLBHOU	44	46	4.41	4.50	23.8%	10.5%	0.0

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

Stuff55Control40Command50

Career WAR0.0 WAR median (P10 -0.1 / P90 0.4, comp-based) · star 0% · didn't stick 95%

CompsTaylor Cole (age 28) · Dalier Hinojosa (age 29) · Trent Harris (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 113105vR 97

ERA4.19

FIP4.19

K%24.8%

BB%10.4%

K-BB%14.4%

Proj IP120

Value2027 · WAR

Runs saved vs league avg · 120 IP

Grades · Contract

Scouting Grades

STUF5555

CTRL4040

CMD5050

K†6060

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	18	ROK MLE	AZL Mariners	2	2	3	13	3	0	0	100%	1.5	23.1%	0.0%	23.1%	0.0%	3.00	1.15	—
2017	18	ROK RAW	AZL Mariners	2	2	3	13	3	0	0	100%	1.5	23.1%	0.0%	23.1%	0.0%	3.00	1.10	—
2021	22	A MLE	Modesto Nuts	19	19	100	462	112	44	7	100%	5.3	17.9%	11.2%	6.7%	2.3%	4.77	4.26	—
2021	22	A RAW	Modesto Nuts	19	19	100	462	112	44	7	100%	5.3	24.2%	9.5%	14.7%	1.5%	4.77	3.09	—
2022	23	A MLE	Modesto Nuts	16	11	57	251	60	24	4	69%	3.5	17.7%	11.3%	6.4%	2.4%	4.61	4.37	—
2022	23	A RAW	Modesto Nuts	16	11	57	251	60	24	4	69%	3.5	23.9%	9.6%	14.3%	1.6%	4.61	3.17	—
2023	24	A+ MLE	Everett AquaSox	39	1	48	200	61	20	3	3%	1.2	23.5%	11.5%	12.0%	1.9%	5.25	3.59	—
2023	24	A+ RAW	Everett AquaSox	39	1	48	200	61	20	3	3%	1.2	30.5%	10.0%	20.5%	1.5%	5.25	2.62	—
2024	25	AA MLE	Biloxi Shuckers	44	0	49	217	51	19	2	0%	1.1	19.0%	9.6%	9.4%	0.9%	4.25	3.22	—
2024	25	AA MLE	Biloxi Shuckers	44	0	49	217	51	19	2	0%	1.1	19.0%	9.6%	9.4%	0.9%	4.25	3.22	—
2024	25	AA RAW	Biloxi Shuckers	44	0	49	217	51	19	2	0%	1.1	23.5%	8.8%	14.7%	0.9%	4.25	2.71	—
2025	26	AAA MLE	Oklahoma City Comets	45	0	60	273	78	36	4	0%	1.3	24.6%	11.9%	12.7%	1.7%	4.22	3.45	—
2025	26	AAA MLE	Oklahoma City Comets	45	0	60	273	78	36	4	0%	1.3	24.6%	11.9%	12.7%	1.7%	4.22	3.45	—
2025	26	AAA RAW	Oklahoma City Comets	45	0	60	273	78	36	4	0%	1.3	28.6%	13.2%	15.4%	1.5%	4.22	3.17	—
2026	27	MIX MLE	2 levels	36	0	42	179	52	16	5	0%	1.2	24.7%	8.4%	16.3%	2.9%	4.10	3.69	—
2026	27	MIX MLE	2 levels	36	0	42	179	52	16	5	0%	1.2	24.7%	8.4%	16.3%	2.9%	4.10	3.69	—
2026	27	MIX RAW	2 levels	36	0	42	179	52	16	5	0%	1.2	29.1%	8.9%	20.1%	2.8%	4.10	3.32	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	HOU	11	0	12	51	13	5	1	0%	1.1	24.8%	10.4%	14.4%	2.7%	4.19	4.19	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	HOU	92	0	97	410	99	42	12	0%	1.1	24.3%	10.4%	13.9%	2.9%	4.28	4.33	+0.3
2029	30	MLB MLE	HOU	79	0	83	350	83	37	11	0%	1.0	23.8%	10.5%	13.3%	3.1%	4.41	4.50	+0.0
2028	29	MLB CTX	HOU	34	0	36	152	37	16	4	0%	1.1	24.3%	10.4%	13.9%	2.9%	4.28	4.33	+0.1
2029	30	MLB CTX	HOU	44	0	46	194	46	20	6	0%	1.0	23.8%	10.5%	13.3%	3.1%	4.41	4.50	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		77	0	81	344	82	36	10	0%	1.1	24.0%	10.4%	13.6%	3.0%	4.35	4.04	+0.5
/ 200 IP	—	RAW		190	0	200	844	202	88	25	0%	1.1	24.0%	10.4%	13.6%	3.0%	4.35	4.04	+1.2
Career	—	MLE		201	33	358	1595	330	172	32	16%	1.8	20.7%	10.8%	9.9%	2.0%	4.55	3.83	+0.3
/ 200 IP	—	MLE		112	18	200	892	184	96	18	16%	1.8	20.7%	10.8%	9.9%	2.0%	4.55	3.83	+0.3

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 AAASugar Land Space Cowboys · 36 IPFIP 3.33 → 3.69 (+0.37)K% 28.7% → 24.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.67%	—	×0.860	24.65%
BB% (unintentional) /BF	9.33%	—	×0.900	8.40%
HR / BF /BF	2.67%	÷1.000	×1.100	2.93%

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 3.33 → 3.69, 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).

2026 AAReading Fightin Phils · 5 IPFIP 3.25 → 4.21 (+0.96)K% 31.0% → 25.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.03%	—	×0.810	25.14%
BB% (unintentional) /BF	6.90%	—	×1.100	7.59%
HR / BF /BF	3.45%	÷1.000	×1.200	4.14%

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 100).

Result: FIP 3.25 → 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).

2025 AAAOklahoma City Comets · 60 IPFIP 3.16 → 3.45 (+0.29)K% 28.6% → 24.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.57%	—	×0.860	24.57%
BB% (unintentional) /BF	13.19%	—	×0.900	11.87%
HR / BF /BF	1.47%	÷0.956	×1.100	1.69%

Result: FIP 3.16 → 3.45, 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 AABiloxi Shuckers · 49 IPFIP 2.73 → 3.22 (+0.49)K% 23.5% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.50%	—	×0.810	19.04%
BB% (unintentional) /BF	8.76%	—	×1.100	9.63%
HR / BF /BF	0.92%	÷1.198	×1.200	0.92%

Result: FIP 2.73 → 3.22, 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+Everett AquaSox · 48 IPFIP 2.61 → 3.59 (+0.98)K% 30.5% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.50%	—	×0.770	23.48%
BB% (unintentional) /BF	10.00%	—	×1.150	11.50%
HR / BF /BF	1.50%	÷1.012	×1.250	1.85%

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 102).

Result: FIP 2.61 → 3.59, 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 AModesto Nuts · 57 IPFIP 3.17 → 4.37 (+1.20)K% 23.9% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.90%	—	×0.740	17.69%
BB% (unintentional) /BF	9.56%	—	×1.180	11.28%
HR / BF /BF	1.59%	÷0.855	×1.300	2.42%

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 71).

Result: FIP 3.17 → 4.37, 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 AModesto Nuts · 100 IPFIP 3.09 → 4.26 (+1.17)K% 24.2% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.24%	—	×0.740	17.94%
BB% (unintentional) /BF	9.52%	—	×1.180	11.24%
HR / BF /BF	1.52%	÷0.861	×1.300	2.29%

Result: FIP 3.09 → 4.26, 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 Carlson (OGILVIE)	—	—	4.19	24.8%	10.4%	2.7%	—	4.41	24.0%	13.6%	180	+0.22	—	—	—
Taylor Cole R 2018 · 3.70 FIP	28	SU	3.70	25.4%	10.4%	2.6%	.291	3.49	22.0%	13.9%	72	-0.21	3.49	433	80
Dalier Hinojosa R 2015 · 3.41 FIP	29	SU	3.41	20.4%	9.8%	1.4%	.283	4.30	18.7%	6.1%	24	+0.89	3.41	104	77
Trent Harris R 2024 · 3.45 FIP	25	SU	3.45	26.9%	9.5%	2.6%	.258	3.36	24.7%	16.7%	121	-0.09	3.06	198	76
Cody Satterwhite R 2015 · 3.71 FIP	28	SU	3.71	20.2%	9.8%	1.9%	.333	4.04	17.7%	10.2%	75	+0.33	3.69	147	75
Blake Smith R 2016 · 3.59 FIP	28	SU	3.59	22.4%	8.6%	2.4%	.307	—	—	—	—	—	3.17	124	75
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	75
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	74
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	74
Nick Merkel R 2024 · 3.15 FIP	26	SU	3.15	21.3%	10.6%	0.9%	.268	3.89	19.8%	9.7%	50	+0.74	3.15	205	74
Dayan Díaz R 2017 · 3.45 FIP	28	SU	3.45	25.1%	8.7%	2.5%	.358	3.96	29.4%	19.3%	16	+0.51	3.08	205	74
Andrew Robinson R 2016 · 3.19 FIP	28	SU	3.19	22.2%	7.9%	1.8%	.247	4.32	23.4%	14.6%	39	+1.13	3.19	160	74
Aquilino López R 2003 · 3.42 FIP	28	SU	3.42	20.3%	9.2%	1.6%	.243	4.81	21.2%	11.7%	38	+1.39	3.10	207	74
Luis Santos R 2019 · 4.31 FIP	28	SU	4.31	22.9%	10.0%	3.4%	.312	—	—	—	—	—	3.53	472	73
Ryan Tepera R 2016 · 3.11 FIP	28	SU	3.11	22.6%	8.9%	1.4%	.266	3.81	24.3%	15.9%	164	+0.70	2.35	445	73
Fernando Rodriguez Jr. R 2012 · 3.90 FIP	28	SU	3.90	25.2%	8.7%	3.3%	.299	3.34	26.5%	16.9%	75	-0.56	3.34	335	73
Murphy Smith R 2016 · 3.54 FIP	28	SU	3.54	19.3%	9.3%	1.6%	.245	4.43	13.6%	6.8%	145	+0.89	3.16	300	72
Matt Ramsey R 2018 · 3.78 FIP	28	SU	3.78	24.9%	8.8%	3.0%	.276	2.42	21.7%	12.6%	34	-1.36	2.42	125	72
Taylor Williams R 2019 · 4.15 FIP	28	SU	4.15	21.9%	8.4%	3.3%	.275	3.85	22.1%	12.1%	103	-0.30	2.51	309	72
Grant Sides R 2016 · 3.83 FIP	27	SU	3.83	22.4%	11.9%	2.0%	.247	3.31	21.7%	11.9%	47	-0.52	3.31	159	72
A.J. Schugel R 2017 · 4.01 FIP	28	SU	4.01	20.1%	8.1%	2.9%	.307	6.37	17.6%	10.6%	13	+2.36	2.80	299	72

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	1.5	100	24.3%	10.4%	1.11	4.28
Scipio Spinks ('69-'73, 2 WAR*)	1.0	67	23.7%*	12.2%*	1.04*	4.52*
Ian Anderson ('25)	1.4	94	22.2%	10.5%	0.99	4.22
Floyd Youmans ('85-'89, 6 WAR*)	2.7	108	23.5%*	11.9%*	1.06*	4.23*
John Patterson ('07)	2.3	76	21.2%	9.1%	1.19	4.32
Nate Karns ('19)	1.6	105	24.0%	9.3%	1.34	4.30
Ken Kravec ('75-'82, 5 WAR*)	4.3	123	23.6%*	10.7%*	1.11*	4.73*