Dylan Cumming

P Birmingham Barons

Age 28 RHP 6'4" / 175 lbs AA peak 0.4 · 2027

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	27	20	116	4.11	3.01	27.2%	8.9%	—	K 21.6% · BB 9.8% · FIP 3.75
2025	26	MIX2 levels	29	14	76	5.00	3.14	22.3%	7.4%	—	K 17.5% · BB 8.4% · FIP 3.96
2026	27	MIX2 levels	26	25	123	5.65	4.28	20.0%	7.9%	—	K 16.0% · BB 8.7% · FIP 5.05
2027PROJ	28	MLBCWS	1	1	2	5.12	5.12	14.9%	8.9%	0.0
2028PROJ31% MLB	29	MLBCWS	3	3	19	5.12	5.17	15.6%	9.2%	0.0
2029PROJ51% MLB	30	MLBCWS	4	4	26	5.19	5.28	15.8%	9.5%	0.0

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

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control55Command45

Career WAR0.0 WAR median (P10 -0.2 / P90 0.3, comp-based) · star 0% · didn't stick 98%

CompsScott McGregor (age 28) · Clay Condrey (age 27) · David Griffin (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 130122vR 114

ERA5.12

FIP5.12

K%14.9%

BB%8.9%

K-BB%6.0%

Proj IP75

Value2027 · WAR

Runs saved vs league avg · 75 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL5555

CMD4545

K†3030

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)
2023	24	A MLE	San Jose Giants	34	7	92	397	86	36	5	21%	2.7	16.0%	10.7%	5.3%	1.8%	2.93	4.11	—
2023	24	A RAW	San Jose Giants	34	7	92	397	86	36	5	21%	2.7	21.7%	9.1%	12.6%	1.3%	2.93	3.11	—
2024	25	MIX MLE	2 levels	27	20	116	508	138	45	10	74%	4.3	21.6%	9.8%	11.8%	2.2%	4.11	3.75	—
2024	25	MIX MLE	2 levels	27	20	116	508	138	45	10	74%	4.3	21.6%	9.8%	11.8%	2.2%	4.11	3.75	—
2024	25	MIX RAW	2 levels	27	20	116	508	138	45	10	74%	4.3	27.2%	8.9%	18.3%	2.0%	4.11	3.01	—
2025	26	MIX MLE	2 levels	29	14	76	336	75	25	6	48%	2.6	17.5%	8.4%	9.1%	2.3%	5.00	3.96	—
2025	26	MIX MLE	2 levels	29	14	76	336	75	25	6	48%	2.6	17.5%	8.4%	9.1%	2.3%	5.00	3.96	—
2025	26	MIX RAW	2 levels	29	14	76	336	75	25	6	48%	2.6	22.3%	7.4%	14.9%	1.8%	5.00	3.14	—
2026	27	MIX MLE	2 levels	26	25	123	546	109	43	18	96%	4.7	16.0%	8.7%	7.3%	4.0%	5.65	5.05	—
2026	27	MIX MLE	2 levels	26	25	123	546	109	43	18	96%	4.7	16.0%	8.7%	7.3%	4.0%	5.65	5.05	—
2026	27	MIX RAW	2 levels	26	25	123	546	109	43	18	96%	4.7	20.0%	7.9%	12.1%	3.3%	5.65	4.28	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	CWS	1	1	2	8	1	1	0	100%	2.0	14.9%	8.9%	6.0%	3.2%	5.12	5.12	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	CWS	10	10	59	251	39	23	8	100%	5.9	15.6%	9.2%	6.3%	3.3%	5.12	5.17	+0.2
2029	30	MLB MLE	CWS	8	8	50	212	34	20	7	100%	6.3	15.8%	9.5%	6.3%	3.5%	5.19	5.28	+0.1
2028	29	MLB CTX	CWS	3	3	19	80	12	7	3	100%	6.3	15.6%	9.2%	6.3%	3.3%	5.12	5.17	+0.0
2029	30	MLB CTX	CWS	4	4	26	110	17	10	4	100%	6.5	15.8%	9.5%	6.3%	3.5%	5.19	5.28	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		7	7	44	188	29	18	6	100%	6.3	15.7%	9.4%	6.3%	3.4%	5.16	4.85	+0.3
/ 200 IP	—	RAW		33	33	200	844	131	81	27	100%	6.0	15.7%	9.4%	6.3%	3.4%	5.16	4.85	+1.2
Career	—	MLE		116	66	406	1787	319	168	48	57%	3.5	17.9%	9.4%	8.5%	2.7%	4.47	4.27	+0.2
/ 200 IP	—	MLE		57	32	200	880	157	83	24	57%	3.5	17.9%	9.4%	8.5%	2.7%	4.47	4.27	+0.4

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 AABirmingham Barons · 101 IPFIP 4.39 → 5.13 (+0.74)K% 18.0% → 14.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.04%	—	×0.810	14.61%
BB% (unintentional) /BF	8.69%	—	×1.100	9.55%
HR / BF /BF	3.12%	÷1.000	×1.200	3.74%

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 4.39 → 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).

2026 A+Winston-Salem Dash · 22 IPFIP 3.45 → 4.65 (+1.20)K% 28.9% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.87%	—	×0.770	22.23%
BB% (unintentional) /BF	4.12%	—	×1.150	4.74%
HR / BF /BF	4.12%	÷1.000	×1.250	5.15%

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 100).

Result: FIP 3.45 → 4.65, 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 A+Winston-Salem Dash · 56 IPFIP 3.15 → 4.05 (+0.90)K% 20.7% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.72%	—	×0.770	15.95%
BB% (unintentional) /BF	5.58%	—	×1.150	6.41%
HR / BF /BF	1.99%	÷0.923	×1.250	2.70%

Result: FIP 3.15 → 4.05, 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 AARichmond Flying Squirrels · 20 IPFIP 3.10 → 3.71 (+0.61)K% 27.1% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.06%	—	×0.810	21.92%
BB% (unintentional) /BF	12.94%	—	×1.100	14.24%
HR / BF /BF	1.18%	÷1.183	×1.200	1.19%

Result: FIP 3.10 → 3.71, 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 · 82 IPFIP 3.61 → 4.27 (+0.66)K% 23.3% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.28%	—	×0.810	18.86%
BB% (unintentional) /BF	9.26%	—	×1.100	10.19%
HR / BF /BF	2.38%	÷1.062	×1.200	2.69%

Result: FIP 3.61 → 4.27, 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 A+Eugene Emeralds · 34 IPFIP 1.25 → 2.24 (+0.99)K% 38.5% → 29.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.46%	—	×0.770	29.62%
BB% (unintentional) /BF	7.69%	—	×1.150	8.85%
HR / BF /BF	0.77%	÷1.010	×1.250	0.95%

Result: FIP 1.25 → 2.24, 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 ASan Jose Giants · 92 IPFIP 3.11 → 4.11 (+1.00)K% 21.7% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.66%	—	×0.740	16.03%
BB% (unintentional) /BF	9.07%	—	×1.180	10.70%
HR / BF /BF	1.26%	÷0.890	×1.300	1.84%

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 78).

Result: FIP 3.11 → 4.11, 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
Dylan Cumming (OGILVIE)	—	—	5.12	14.9%	8.9%	3.2%	—	5.22	15.7%	6.3%	110	+0.10	—	—	—
Scott McGregor R 2015 · 4.37 FIP	28	SP-	4.37	11.8%	7.6%	2.4%	.293	—	—	—	—	—	4.37	107	84
Clay Condrey R 2003 · 5.41 FIP	27	SP-	5.41	14.9%	10.1%	4.2%	.303	4.07	13.1%	7.4%	29	-1.34	3.18	250	81
David Griffin R 2023 · 5.83 FIP	27	SP-	5.83	14.2%	9.2%	5.0%	.306	—	—	—	—	—	4.43	239	80
Colin Bates R 2015 · 4.57 FIP	27	SP-	4.57	10.5%	6.5%	2.8%	.301	—	—	—	—	—	4.57	111	80
Juan Omar Espinoza R 2015 · 4.81 FIP	31	SP-	4.81	8.9%	6.6%	3.0%	.346	4.84	8.4%	-0.8%	52	+0.03	4.81	104	79
Ivan Zavala R 2015 · 4.51 FIP	28	SP-	4.51	7.0%	4.7%	2.6%	.312	4.73	12.2%	4.3%	50	+0.22	4.27	209	79
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	78
Aldo Montes R 2017 · 4.96 FIP	27	SP-	4.96	12.4%	8.5%	3.3%	.322	4.69	18.2%	7.6%	75	-0.27	4.69	210	78
Mike Connolly R 2018 · 5.13 FIP	26	SW	5.13	13.2%	9.4%	3.5%	.321	—	—	—	—	—	3.94	328	78
Frank Batista R 2015 · 4.29 FIP	26	SP-	4.29	12.1%	8.2%	2.1%	.280	—	—	—	—	—	4.29	118	78
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	78
Nolan Sanburn R 2017 · 4.55 FIP	26	SW	4.55	15.0%	10.4%	2.5%	.310	—	—	—	—	—	3.82	169	78
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	77
Luke Irvine R 2016 · 4.31 FIP	27	SP-	4.31	13.4%	9.8%	2.0%	.302	—	—	—	—	—	4.31	104	77
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	76
Matthew Shepherd R 2015 · 4.98 FIP	25	SP-	4.98	13.7%	9.5%	3.3%	.390	—	—	—	—	—	4.98	116	76
Mike Augliera R 2015 · 4.27 FIP	25	SP-	4.27	12.0%	7.2%	2.3%	.350	—	—	—	—	—	4.27	114	76
Shawn Haviland R 2015 · 3.95 FIP	29	SP-	3.95	14.6%	6.0%	2.4%	.303	4.67	16.1%	8.8%	169	+0.72	3.69	283	76
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	74
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	74

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	62	15.4%	9.2%	1.29	5.14
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Jose Cabrera ('02)	1.4	68	16.2%	7.9%	1.39	4.95
Carlos Almánzar ('05)	1.2	60	16.3%	7.9%	1.32	4.82
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*