Cole McDonald

P Sugar Land Space Cowboys

Age 30 RHP 6'1" / 218 lbs AAA

Overview

AAAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	25	A+HOU	28	5	60	6.86	3.78	34.4%	17.2%	—	K 26.5% · BB 19.8% · FIP 5.07
2023	26	MIX2 levels	39	0	53	3.59	2.04	33.0%	9.8%	—	K 26.1% · BB 11.3% · FIP 2.81
2024	27	MIX2 levels	40	0	45	5.44	4.33	25.3%	12.9%	—	K 20.9% · BB 12.7% · FIP 5.01
2025	28	No MLB games played
2026	29	No MLB games played
2027PROJ	30	MLBHOU	1	0	1	4.67	4.67	21.9%	10.6%	-0.0
2028PROJ31% MLB	31	MLBHOU	6	0	6	4.76	4.84	21.6%	10.8%	-0.0

Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsJoe Nelson (age 31) · Jim Miller (age 30) · Wirfin Obispo (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 122114vR 106

ERA4.67

FIP4.67

K%21.9%

BB%10.6%

K-BB%11.2%

Proj IP26

Value2027 · WAR

Runs saved vs league avg · 26 IP

Grades · Contract

Scouting Grades

K†5050

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)
2019	22	ROK MLE	GCL Astros	1	1	2	6	2	0	0	100%	2.0	33.3%	0.0%	33.3%	0.0%	0.00	0.29	—
2019	22	ROK RAW	GCL Astros	1	1	2	6	2	0	0	100%	2.0	33.3%	0.0%	33.3%	0.0%	0.00	1.10	—
2021	24	MIX MLE	2 levels	4	4	10	41	19	6	0	100%	2.4	46.3%	14.6%	31.7%	0.0%	1.86	1.04	—
2021	24	MIX RAW	2 levels	4	4	10	41	19	6	0	100%	2.4	46.3%	14.6%	31.7%	0.0%	1.86	1.03	—
2022	25	A+ MLE	Asheville Tourists	28	5	60	291	100	50	7	18%	2.2	26.5%	19.8%	6.7%	3.1%	6.86	5.07	—
2022	25	A+ RAW	Asheville Tourists	28	5	60	291	100	50	7	18%	2.2	34.4%	17.2%	17.2%	2.4%	6.86	3.78	—
2023	26	MIX MLE	2 levels	39	0	53	224	74	22	2	0%	1.4	26.1%	11.3%	14.8%	0.9%	3.59	2.81	—
2023	26	MIX RAW	2 levels	39	0	53	224	74	22	2	0%	1.4	33.0%	9.8%	23.2%	0.9%	3.59	2.04	—
2024	27	MIX MLE	2 levels	40	0	45	194	49	25	6	0%	1.1	20.9%	12.7%	8.2%	3.8%	5.44	5.01	—
2024	27	MIX MLE	2 levels	40	0	45	194	49	25	6	0%	1.1	20.9%	12.7%	8.2%	3.8%	5.44	5.01	—
2024	27	MIX RAW	2 levels	40	0	45	194	49	25	6	0%	1.1	25.3%	12.9%	12.4%	3.1%	5.44	4.33	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	HOU	1	0	1	4	1	0	0	0%	1.0	21.9%	10.6%	11.2%	3.1%	4.67	4.67	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	HOU	20	0	21	87	19	9	3	0%	1.0	21.6%	10.8%	10.8%	3.3%	4.76	4.84	-0.1
2028	31	MLB CTX	HOU	6	0	6	25	5	3	1	0%	1.0	21.6%	10.8%	10.8%	3.3%	4.76	4.84	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		6	0	6	27	6	3	1	0%	1.1	21.6%	10.8%	10.8%	3.3%	4.76	4.46	+0.0
/ 200 IP	—	RAW		190	0	200	844	185	93	31	0%	1.1	21.6%	10.8%	10.8%	3.3%	4.76	4.46	+0.2
Career	—	MLE		112	10	169	756	197	113	18	9%	1.5	26.1%	15.0%	11.1%	2.4%	5.10	4.13	-0.1
/ 200 IP	—	MLE		132	12	200	893	233	134	22	9%	1.5	26.1%	15.0%	11.1%	2.4%	5.10	4.13	-0.7

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.

2024 AAASugar Land Space Cowboys · 21 IPFIP 6.72 → 7.49 (+0.77)K% 18.4% → 15.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.37%	—	×0.860	15.80%
BB% (unintentional) /BF	14.29%	—	×0.900	12.86%
HR / BF /BF	6.12%	÷0.903	×1.100	7.46%

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 81).

Result: FIP 6.72 → 7.49, 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 AACorpus Christi Hooks · 24 IPFIP 1.82 → 2.49 (+0.66)K% 32.3% → 26.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.29%	—	×0.810	26.16%
BB% (unintentional) /BF	11.46%	—	×1.100	12.60%
HR / BF /BF	0.00%	÷0.970	×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 94).

Result: FIP 1.82 → 2.49, 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).

2023 AACorpus Christi Hooks · 48 IPFIP 2.21 → 2.81 (+0.60)K% 32.2% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.20%	—	×0.810	26.08%
BB% (unintentional) /BF	10.24%	—	×1.100	11.27%
HR / BF /BF	0.98%	÷1.322	×1.200	0.89%

Result: FIP 2.21 → 2.81, 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+Asheville Tourists · 60 IPFIP 3.69 → 5.07 (+1.37)K% 34.4% → 26.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.36%	—	×0.770	26.46%
BB% (unintentional) /BF	17.18%	—	×1.150	19.76%
HR / BF /BF	2.41%	÷0.972	×1.250	3.09%

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 94).

Result: FIP 3.69 → 5.07, 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).

2021 ROKFCL Astros · 9 IPFIP 0.29 → 1.99 (+1.70)K% 50.0% → 34.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	50.00%	—	×0.680	34.00%
BB% (unintentional) /BF	11.11%	—	×1.250	13.89%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 0.29 → 1.99, 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
Cole McDonald (OGILVIE)	—	—	4.67	21.9%	10.6%	3.1%	—	4.84	21.6%	10.8%	21	+0.17	—	—	—
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	87
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	87
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	85
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	84
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	84
Erik Davis R 2017 · 4.25 FIP	30	SU	4.25	22.2%	11.1%	3.0%	.349	3.52	17.4%	8.5%	65	-0.73	3.05	227	80
Esteban Haro R 2016 · 4.55 FIP	30	SU	4.55	17.1%	10.2%	2.9%	.338	3.83	11.6%	6.3%	75	-0.72	3.76	164	79
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	78
Scott Atchison R 2007 · 4.55 FIP	31	SU	4.55	19.1%	7.6%	3.8%	.297	4.59	16.2%	9.5%	60	+0.04	2.52	340	78
Mike Broadway R 2017 · 4.73 FIP	30	SU	4.73	18.3%	10.2%	3.4%	.245	4.65	23.0%	12.4%	49	-0.08	1.74	195	76
Andrew Robinson R 2017 · 4.32 FIP	29	SU	4.32	23.4%	8.8%	3.8%	.245	—	—	—	—	—	3.19	160	75
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	75
Jose Manuel Lopez R 2015 · 5.21 FIP	30	SU	5.21	18.6%	7.6%	4.9%	.373	3.56	18.5%	9.3%	93	-1.65	3.50	170	75
Francisco Mendoza R 2016 · 3.81 FIP	28	SU	3.81	17.9%	7.7%	2.3%	.344	—	—	—	—	—	3.13	120	75
Hirokazu Sawamura R 2021 · 4.48 FIP	33	SU	4.48	26.2%	11.2%	4.0%	.263	4.02	18.1%	6.8%	51	-0.46	4.02	104	74
Blake Smith R 2016 · 3.59 FIP	28	SU	3.59	22.4%	8.6%	2.4%	.307	—	—	—	—	—	3.17	124	74
Kiko Calero R 2005 · 3.51 FIP	30	SU	3.51	22.7%	7.0%	2.6%	.252	3.23	23.3%	13.9%	99	-0.28	2.27	298	73
Jeremy Fikac R 2004 · 4.91 FIP	29	SU	4.91	19.6%	8.0%	4.5%	.276	—	—	—	—	—	3.10	136	73
Leonel Campos R 2017 · 3.70 FIP	30	SU	3.70	25.7%	11.8%	2.3%	.241	—	—	—	—	—	2.62	168	73
Jason Urquidez R 2015 · 3.59 FIP	32	SU	3.59	15.6%	9.3%	1.1%	.386	1.81	25.5%	20.7%	90	-1.78	1.25	123	73