Kyle Freeland

P Colorado Rockies

Age 34 LHP 6'4" / 202 lbs MLB peak 0.8 · 2027

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	31	MIX3 levels	24	24	123	5.04	4.75	17.8%	5.9%	0.9	K 17.3% · BB 5.3% · FIP 4.49
2025	32	MLBCOL	31	31	163	4.98	4.00	17.5%	5.1%	2.7
2026	33	MIX2 levels	27	26	138	6.51	4.84	18.2%	4.8%	0.9	K 17.6% · BB 4.7% · FIP 4.51
2027PROJ	34	MLBCOL	16	16	97	4.87	4.71	16.7%	5.3%	0.8
2028PROJ	35	MLBCOL	11	11	66	5.30	5.37	15.8%	5.9%	0.3
2029PROJ	36	MLBCOL	7	7	40	5.59	5.77	14.7%	6.5%	-0.0

Last 3 seasons WAR 4.5 · Next 3 projected WAR 1.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%18

xwOBA vs13

FB Velo10

Form4.75 ERA (proj 4.87) · K 14.3% (proj 16.7%) · BB 5.0% (proj 5.3%) · last 90d · 36 IP through Oct 27

CompsTsuyoshi Wada (age 34) · Daniel Rodriguez (age 34) · Orlando Lara (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 111119vR 127

ERA4.87

FIP4.71

K%16.7%

BB%5.3%

K-BB%11.4%

Proj IP97

Value2027 · WAR

Runs saved vs league avg · 97 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1091.3

Whiff%

p2822.2%

p1817.6%

xwOBA vs

p130.356

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)
2015	22	MIX MLE	2 levels	9	9	47	196	28	10	5	100%	5.2	8.7%	5.4%	3.2%	4.5%	4.05	5.51	—
2015	22	MIX RAW	2 levels	9	9	47	196	28	10	5	100%	5.2	14.3%	5.1%	9.2%	2.6%	4.05	3.94	—
2016	23	MIX MLE	2 levels	26	26	162	675	108	44	16	100%	6.2	13.6%	7.0%	6.5%	2.4%	3.89	4.17	—
2016	23	MIX RAW	2 levels	26	26	162	675	108	44	16	100%	6.2	16.0%	6.5%	9.5%	2.4%	3.89	3.87	—
2017	24	MLB MLE	Colorado Rockies	33	28	156	688	107	59	17	85%	4.7	15.6%	8.6%	7.0%	2.2%	4.10	4.08	+2.5
2017	24	MLB RAW	Colorado Rockies	33	28	156	688	107	59	17	85%	4.7	15.6%	8.6%	7.0%	2.5%	4.10	4.28	+2.1
2018	25	MLB MLE	Colorado Rockies	33	33	202	844	173	68	17	100%	6.1	20.5%	8.1%	12.4%	1.8%	2.85	3.37	+5.1
2018	25	MLB RAW	Colorado Rockies	33	33	202	844	173	68	17	100%	6.1	20.5%	8.1%	12.4%	2.0%	2.85	3.49	+4.7
2019	26	MIX MLE	2 levels	28	28	134	616	107	52	29	100%	4.8	16.8%	8.6%	8.3%	4.2%	7.19	5.09	+0.5
2019	26	MIX RAW	2 levels	28	28	134	616	107	52	29	100%	4.8	17.4%	8.4%	8.9%	4.7%	7.19	5.48	-0.1
2020	27	MLB MLE	Colorado Rockies	13	13	71	304	46	23	9	100%	5.4	15.1%	7.6%	7.6%	2.6%	4.33	4.22	+1.0
2020	27	MLB RAW	Colorado Rockies	13	13	71	304	46	23	9	100%	5.4	15.1%	7.6%	7.6%	3.0%	4.33	4.43	+0.8
2021	28	MIX MLE	2 levels	25	25	131	552	109	39	20	100%	5.2	20.4%	7.2%	13.2%	3.4%	4.13	4.18	+1.9
2021	28	MIX RAW	2 levels	25	25	131	552	109	39	20	100%	5.2	19.7%	7.1%	12.7%	3.6%	4.13	4.32	+1.7
2022	29	MLB MLE	Colorado Rockies	31	31	175	766	131	53	19	100%	5.6	17.1%	6.9%	10.2%	2.2%	4.53	3.74	+3.5
2022	29	MLB RAW	Colorado Rockies	31	31	175	766	131	53	19	100%	5.6	17.1%	6.9%	10.2%	2.5%	4.53	3.92	+3.1
2023	30	MLB MLE	Colorado Rockies	29	29	156	677	94	42	29	100%	5.4	13.9%	6.2%	7.7%	3.8%	5.03	4.80	+1.1
2023	30	MLB RAW	Colorado Rockies	29	29	156	677	94	42	29	100%	5.4	13.9%	6.2%	7.7%	4.3%	5.03	5.12	+0.5
2024	31	MIX MLE	3 levels	24	24	123	529	94	31	23	100%	5.1	17.3%	5.3%	12.0%	4.0%	5.04	4.49	+1.3
2024	31	MIX MLE	3 levels	24	24	123	529	94	31	23	100%	5.1	17.3%	5.3%	12.0%	4.0%	5.04	4.49	+1.3
2024	31	MIX RAW	3 levels	24	24	123	529	94	31	23	100%	5.1	17.8%	5.9%	11.9%	4.3%	5.04	4.75	+0.9
2025	32	MLB MLE	Colorado Rockies	31	31	163	709	124	36	22	100%	5.2	17.5%	5.1%	12.4%	2.8%	4.98	3.78	+3.2
2025	32	MLB MLE	Colorado Rockies	31	31	163	709	124	36	22	100%	5.2	17.5%	5.1%	12.4%	2.8%	4.98	3.78	+3.2
2025	32	MLB RAW	Colorado Rockies	31	31	163	709	124	36	22	100%	5.2	17.5%	5.1%	12.4%	3.1%	4.98	4.00	+2.7
2026	33	MIX MLE	2 levels	27	26	138	622	113	30	29	96%	5.1	17.6%	4.7%	12.9%	4.2%	6.51	4.51	+1.4
2026	33	MIX MLE	2 levels	27	26	138	622	113	30	29	96%	5.1	17.6%	4.7%	12.9%	4.2%	6.51	4.51	+1.4
2026	33	MIX RAW	2 levels	27	26	138	622	113	30	29	96%	5.1	18.2%	4.8%	13.3%	4.7%	6.51	4.84	+0.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			262	257	1396	6079	1052	409	209	98%	5.3	17.3%	6.7%	10.6%	3.4%	4.75	4.42	+16.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	COL	16	16	97	410	69	22	15	100%	6.1	16.7%	5.3%	11.4%	3.6%	4.87	4.71	+0.8
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	COL	11	11	66	280	44	16	11	100%	6.0	15.8%	5.9%	9.9%	3.9%	4.97	5.04	+0.3
2029	36	MLB MLE	COL	7	7	40	170	25	11	7	100%	5.7	14.7%	6.5%	8.3%	4.3%	5.23	5.41	-0.0
2028	35	MLB CTX	COL	11	11	66	279	44	16	13	100%	6.0	15.8%	5.9%	9.9%	4.5%	5.30	5.37	+0.3
2029	36	MLB CTX	COL	7	7	40	169	25	11	8	100%	5.7	14.7%	6.5%	8.3%	4.9%	5.59	5.77	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		280	275	1502	6529	1121	436	230	98%	5.4	17.2%	6.7%	10.5%	3.5%	4.79	4.43	+17.0
/ 200 IP	—	RAW		37	37	200	869	149	58	31	98%	5.4	17.2%	6.7%	10.5%	3.5%	4.79	4.43	+2.3
Career	—	MLE		309	303	1657	7178	1201	489	217	98%	5.4	16.7%	6.8%	9.9%	3.0%	4.68	4.21	+16.2
/ 200 IP	—	MLE		37	37	200	866	145	59	26	98%	5.4	16.7%	6.8%	9.9%	3.0%	4.68	4.21	+2.2

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 AAAAlbuquerque Isotopes · 8 IPFIP 4.73 → 4.84 (+0.11)K% 25.8% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.81%	—	×0.860	22.19%
BB% (unintentional) /BF	16.13%	—	×0.900	14.52%
HR / BF /BF	3.23%	÷1.096	×1.100	3.24%

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 119).

Result: FIP 4.73 → 4.84, 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 AAAAlbuquerque Isotopes · 10 IPFIP 2.87 → 3.02 (+0.14)K% 10.8% → 9.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	10.81%	—	×0.880	9.51%
BB% (unintentional) /BF	5.41%	—	×1.050	5.68%
HR / BF /BF	0.00%	÷1.172	×1.100	0.00%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, 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 134).

Result: FIP 2.87 → 3.02, 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).

2019 AAAAlbuquerque Isotopes · 30 IPFIP 4.40 → 4.62 (+0.22)K% 19.6% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.58%	—	×0.880	17.23%
BB% (unintentional) /BF	11.19%	—	×1.050	11.75%
HR / BF /BF	2.80%	÷1.136	×1.100	2.71%

Result: FIP 4.40 → 4.62, 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).

2016 AAHartford Yard Goats · 88 IPFIP 4.14 → 4.57 (+0.44)K% 13.9% → 11.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.90%	—	×0.810	11.26%
BB% (unintentional) /BF	6.81%	—	×1.100	7.49%
HR / BF /BF	2.45%	÷1.094	×1.200	2.69%

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 119).

Result: FIP 4.14 → 4.57, 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).

2016 AAAAlbuquerque Isotopes · 74 IPFIP 3.57 → 3.69 (+0.12)K% 18.5% → 16.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.51%	—	×0.880	16.29%
BB% (unintentional) /BF	6.17%	—	×1.050	6.48%
HR / BF /BF	2.27%	÷1.202	×1.100	2.08%

Result: FIP 3.57 → 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).

2015 A+Modesto Nuts · 40 IPFIP 4.37 → 5.51 (+1.14)K% 11.2% → 8.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	11.24%	—	×0.770	8.66%
BB% (unintentional) /BF	4.73%	—	×1.150	5.44%
HR / BF /BF	2.96%	÷0.827	×1.250	4.47%

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 65).

Result: FIP 4.37 → 5.51, 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).

2015 ROKGrand Junction Rockies · 7 IPFIP 1.22 → 2.36 (+1.14)K% 33.3% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.680	22.67%
BB% (unintentional) /BF	7.41%	—	×1.250	9.26%
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 1.22 → 2.36, 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
Kyle Freeland (OGILVIE)	—	—	—	—	—	3.6%	—	5.18	15.4%	9.3%	106	+0.47	—	—	—
Tsuyoshi Wada L 2015 · 3.66 FIP	34	SP	3.66	16.8%	7.1%	2.0%	.307	—	—	—	—	—	3.60	188	53
Daniel Rodriguez L 2019 · 4.77 FIP	34	SP	4.77	20.8%	7.8%	4.5%	.329	—	—	—	—	—	2.89	391	52
Orlando Lara L 2019 · 4.09 FIP	34	SP	4.09	22.0%	7.8%	3.4%	.329	—	—	—	—	—	3.85	426	50
Oscar Rivera L 2015 · 3.68 FIP	34	SP	3.68	14.2%	6.9%	1.7%	.298	4.66	10.4%	3.0%	129	+0.98	3.68	237	50
Mauricio Lara L 2015 · 3.62 FIP	36	SP	3.62	13.9%	6.9%	1.5%	.310	3.69	12.1%	5.1%	220	+0.07	3.62	444	49
Jorge Castillo L 2016 · 4.94 FIP	34	SP	4.94	13.0%	4.6%	4.3%	.246	4.93	16.8%	9.2%	179	-0.01	4.50	408	49
Arturo Lopez L 2017 · 4.34 FIP	34	SP	4.34	10.3%	5.4%	2.6%	.342	5.46	12.2%	5.4%	117	+1.12	4.34	445	48
Kwang Hyun Kim L 2021 · 4.21 FIP	33	SP-	4.21	17.7%	8.2%	2.9%	.266	—	—	—	—	—	3.76	146	44
Chris Narveson L 2016 · 4.59 FIP	34	SP-	4.59	16.2%	8.5%	3.2%	.253	4.59	12.2%	1.8%	103	+0.00	4.00	625	42
Francisley Bueno L 2015 · 3.77 FIP	34	SP	3.77	14.8%	7.1%	1.9%	.315	3.99	13.3%	6.6%	110	+0.22	2.43	188	42
Marlon Arias L 2019 · 4.83 FIP	34	SP	4.83	19.8%	11.2%	3.6%	.273	—	—	—	—	—	3.73	154	41
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	41
Masato Yoshii R 2000 · 5.32 FIP	35	SP	5.32	12.1%	6.5%	4.4%	.302	4.38	13.1%	8.0%	244	-0.94	4.15	757	37
Jose Contreras R 2006 · 3.83 FIP	34	SP	3.83	16.1%	6.1%	2.4%	.277	4.08	14.7%	7.3%	442	+0.25	2.43	1,279	35
Tomas Solis L 2017 · 5.48 FIP	34	SP	5.48	11.3%	7.9%	4.2%	.322	6.44	8.9%	1.4%	57	+0.96	4.20	327	35
Hiroki Kuroda R 2009 · 3.54 FIP	34	SP	3.54	17.9%	4.7%	2.5%	.270	3.43	19.1%	14.2%	618	-0.11	2.96	1,319	33
Hisashi Iwakuma R 2015 · 3.74 FIP	34	SP	3.74	21.5%	3.9%	3.6%	.270	4.44	16.9%	11.2%	230	+0.70	3.19	884	32
Merrill Kelly R 2023 · 3.73 FIP	34	SP	3.73	25.9%	9.6%	2.9%	.276	4.36	19.7%	12.0%	420	+0.63	3.60	1,170	31
Chris Michalak L 2006 · 5.71 FIP	35	SP-	5.71	6.2%	8.6%	3.7%	.273	—	—	—	—	—	4.71	186	29
Orlando Hernandez R 2004 · 3.77 FIP	34	SP	3.77	23.4%	10.0%	2.5%	.278	4.34	20.5%	11.7%	438	+0.57	3.35	1,315	28

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	8.0	123	17.1%	6.8%	1.35	4.78
Curt Young ('83-'93, 2 WAR*)	5.5	123	15.2%*	7.5%*	1.43*	4.74*
Brett Tomko ('11)	9.1	140	15.5%	7.4%	1.26	4.65
Jordan Lyles ('24)	7.5	116	17.4%	7.5%	1.41	5.22
Phil Hughes ('18)	6.5	108	18.9%	5.7%	1.33	4.52
Larry McWilliams ('78-'90, 10 WAR*)	7.8	130	19.0%*	8.1%*	1.24*	4.56*
Neal Heaton ('82-'93, 6 WAR*)	7.5	126	14.6%*	8.0%*	1.23*	4.66*