Kyle Gibson

P Durham Bulls

Age 39 RHP 6'6" / 200 lbs AAA peak 0.2 · 2027

Overview

AAASP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	35	MLBBAL	33	33	192	4.73	3.88	19.5%	6.8%	3.5
2024	36	MLBSTL	30	30	170	4.24	4.27	20.9%	9.3%	2.3
2025	37	MIX3 levels	11	11	42	6.26	4.52	23.8%	7.9%	0.4	K 21.1% · BB 7.3% · FIP 4.41
2026	38	No MLB games played
2027PROJ	39	MLBBAL	2	2	9	4.79	4.76	20.0%	8.7%	0.1
2028PROJ	40	MLBBAL	5	5	30	5.03	5.19	18.8%	9.4%	0.1

Last 3 seasons WAR 6.2 · Next 2 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo10

K%10

xwOBA vs10

CompsFrancisco Campos (age 42) · Walter Silva (age 39) · Pablo Ortega (age 39)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 124115vR 107

ERA4.79

FIP4.76

K%20.0%

BB%8.7%

K-BB%11.3%

Proj IP44

Value2027 · WAR

Runs saved vs league avg · 44 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1091.5

Whiff%

p1720.6%

p1013.7%

xwOBA vs

p100.441

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)
2013	25	MLB MLE	Minnesota Twins	10	10	51	238	29	20	7	100%	5.1	12.2%	8.4%	3.8%	2.9%	6.53	4.74	+0.4
2013	25	MLB RAW	Minnesota Twins	10	10	51	238	29	20	7	100%	5.1	12.2%	8.4%	3.8%	2.9%	6.53	4.92	+0.3
2014	26	MLB MLE	Minnesota Twins	31	31	179	757	107	57	12	100%	5.8	14.1%	7.5%	6.6%	1.6%	4.47	3.73	+3.6
2014	26	MLB RAW	Minnesota Twins	31	31	179	757	107	57	12	100%	5.8	14.1%	7.5%	6.6%	1.6%	4.47	3.73	+3.6
2015	27	MLB MLE	Minnesota Twins	32	32	195	821	145	59	18	100%	6.1	17.7%	7.2%	10.5%	2.2%	3.84	3.72	+4.0
2015	27	MLB RAW	Minnesota Twins	32	32	195	821	145	59	18	100%	6.1	17.7%	7.2%	10.5%	2.2%	3.84	3.72	+4.0
2016	28	MIX MLE	3 levels	28	28	163	714	114	56	20	100%	5.8	15.9%	8.0%	8.0%	3.0%	4.70	4.44	+1.8
2016	28	MIX RAW	3 levels	28	28	163	714	114	56	20	100%	5.8	16.0%	7.8%	8.1%	2.8%	4.70	4.33	+2.0
2017	29	MIX MLE	2 levels	32	32	175	761	144	65	25	100%	5.5	18.6%	8.6%	10.0%	3.3%	4.77	4.42	+2.0
2017	29	MIX RAW	2 levels	32	32	175	761	144	65	25	100%	5.5	18.9%	8.5%	10.4%	3.3%	4.77	4.42	+2.0
2018	30	MLB MLE	Minnesota Twins	32	32	197	826	179	77	23	100%	6.1	21.7%	9.3%	12.3%	2.8%	3.62	3.97	+3.4
2018	30	MLB RAW	Minnesota Twins	32	32	197	826	179	77	23	100%	6.1	21.7%	9.3%	12.3%	2.8%	3.62	3.97	+3.3
2019	31	MLB MLE	Minnesota Twins	34	29	160	706	160	56	23	85%	4.7	22.7%	7.9%	14.7%	3.2%	4.84	3.97	+2.7
2019	31	MLB RAW	Minnesota Twins	34	29	160	706	160	56	23	85%	4.7	22.7%	7.9%	14.7%	3.3%	4.84	4.02	+2.6
2020	32	MLB MLE	Texas Rangers	12	12	67	301	58	29	12	100%	5.6	19.3%	9.6%	9.6%	3.7%	5.35	4.73	+0.5
2020	32	MLB RAW	Texas Rangers	12	12	67	301	58	29	12	100%	5.6	19.3%	9.6%	9.6%	4.0%	5.35	4.99	+0.3
2021	33	MLB MLE	Philadelphia Phillies	31	30	182	754	155	62	17	97%	5.9	20.6%	8.2%	12.3%	2.1%	3.71	3.56	+4.1
2021	33	MLB RAW	Philadelphia Phillies	31	30	182	754	155	62	17	97%	5.9	20.6%	8.2%	12.3%	2.3%	3.71	3.63	+3.9
2022	34	MLB MLE	Philadelphia Phillies	31	31	168	718	144	48	24	100%	5.4	20.1%	6.7%	13.4%	3.1%	5.05	3.96	+2.9
2022	34	MLB RAW	Philadelphia Phillies	31	31	168	718	144	48	24	100%	5.4	20.1%	6.7%	13.4%	3.3%	5.05	4.10	+2.6
2023	35	MLB MLE	Baltimore Orioles	33	33	192	807	157	55	23	100%	5.8	19.5%	6.8%	12.6%	2.9%	4.73	3.90	+3.5
2023	35	MLB RAW	Baltimore Orioles	33	33	192	807	157	55	23	100%	5.8	19.5%	6.8%	12.6%	2.9%	4.73	3.88	+3.5
2024	36	MLB MLE	St. Louis Cardinals	30	30	170	722	151	67	23	100%	5.7	20.9%	9.3%	11.6%	3.4%	4.24	4.39	+2.0
2024	36	MLB MLE	St. Louis Cardinals	30	30	170	722	151	67	23	100%	5.7	20.9%	9.3%	11.6%	3.4%	4.24	4.39	+2.0
2024	36	MLB RAW	St. Louis Cardinals	30	30	170	722	151	67	23	100%	5.7	20.9%	9.3%	11.6%	3.2%	4.24	4.27	+2.3
2025	37	MIX MLE	3 levels	11	11	42	189	45	15	8	100%	3.8	21.1%	7.3%	13.8%	3.9%	6.26	4.41	+0.5
2025	37	MIX MLE	3 levels	11	11	42	189	45	15	8	100%	3.8	21.1%	7.3%	13.8%	3.9%	6.26	4.41	+0.5
2025	37	MIX RAW	3 levels	11	11	42	189	45	15	8	100%	3.8	23.8%	7.9%	15.9%	4.2%	6.26	4.52	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			334	328	1878	8069	1520	649	233	98%	5.6	18.8%	8.0%	10.8%	2.9%	4.60	4.13	+28.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	39	MLB	BAL	2	2	9	38	8	3	1	100%	4.5	20.0%	8.7%	11.3%	3.4%	4.79	4.76	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	40	MLB MLE	BAL	5	5	30	126	24	12	5	100%	6.0	18.8%	9.4%	9.5%	3.9%	5.03	5.19	+0.1
2028	40	MLB CTX	BAL	5	5	30	127	24	12	5	100%	6.0	18.8%	9.4%	9.5%	3.9%	5.03	5.19	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		339	333	1908	8195	1544	661	238	98%	5.6	18.8%	8.1%	10.8%	2.9%	4.60	4.12	+28.8
/ 200 IP	—	RAW		36	35	200	859	162	69	25	98%	5.6	18.8%	8.1%	10.8%	2.9%	4.60	4.12	+3.0
Career	—	MLE		347	341	1940	8314	1580	666	234	98%	5.6	19.0%	8.0%	11.0%	2.8%	4.50	4.06	+28.3
/ 200 IP	—	MLE		36	35	200	857	163	69	24	98%	5.6	19.0%	8.0%	11.0%	2.8%	4.50	4.06	+3.0

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 AAADurham Bulls · 24 IPFIP 1.27 → 1.56 (+0.29)K% 30.9% → 26.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.93%	—	×0.860	26.60%
BB% (unintentional) /BF	6.19%	—	×0.900	5.57%
HR / BF /BF	0.00%	÷1.380	×1.100	0.00%

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 176).

Result: FIP 1.27 → 1.56, 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).

2017 AAARochester Red Wings · 17 IPFIP 1.98 → 2.49 (+0.51)K% 33.8% → 29.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.82%	—	×0.880	29.76%
BB% (unintentional) /BF	7.35%	—	×1.050	7.72%
HR / BF /BF	1.47%	÷0.956	×1.100	1.69%

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 91).

Result: FIP 1.98 → 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).

2016 A+Fort Myers Miracle · 9 IPFIP 1.49 → 2.00 (+0.51)K% 23.5% → 18.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.53%	—	×0.770	18.12%
BB% (unintentional) /BF	2.94%	—	×1.150	3.38%
HR / BF /BF	0.00%	÷0.881	×1.250	0.00%

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 76).

Result: FIP 1.49 → 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).

2016 AAARochester Red Wings · 6 IPFIP 3.88 → 4.03 (+0.15)K% 7.4% → 6.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	7.41%	—	×0.880	6.52%
BB% (unintentional) /BF	11.11%	—	×1.050	11.67%
HR / BF /BF	0.00%	÷0.951	×1.100	0.00%

Result: FIP 3.88 → 4.03, 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).

	Profile at Match Age	Next 3 Yrs	Career
Kyle Gibson (OGILVIE)	—	—	—	—	—	3.4%	—	5.19	18.8%	9.5%	30	+0.43	—	—	—
Francisco Campos R 2015 · 4.77 FIP	42	SP	4.77	11.5%	7.9%	3.0%	.303	4.08	12.2%	7.0%	197	-0.69	4.06	332	60
Walter Silva R 2016 · 4.22 FIP	39	SP	4.22	10.3%	5.5%	2.4%	.294	4.35	10.0%	1.8%	235	+0.13	3.67	453	58
Pablo Ortega R 2016 · 4.01 FIP	39	SP	4.01	8.9%	4.8%	1.9%	.262	4.49	13.3%	7.1%	148	+0.48	4.01	375	52
Yasutomo Kubo R 2019 · 3.98 FIP	38	SP	3.98	20.4%	4.7%	3.6%	.327	—	—	—	—	—	3.98	152	51
Logan Duran R 2019 · 3.66 FIP	37	SP-	3.66	15.5%	8.9%	1.4%	.427	—	—	—	—	—	3.42	187	36
Mauricio Lara L 2017 · 3.70 FIP	38	SP	3.70	12.0%	6.3%	1.5%	.301	4.96	12.3%	5.5%	111	+1.26	3.62	444	29
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	26
Jason Lane L 2015 · 5.56 FIP	38	SP	5.56	8.4%	6.2%	4.3%	.307	—	—	—	—	—	5.56	164	18

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	9.8	139	18.9%	8.3%	1.13	4.61
Jason Hammel ('18)	9.1	139	18.2%	7.2%	1.15	4.62
Tim Leary ('81-'94, 9 WAR*)	7.5	136	18.1%*	8.1%*	1.18*	4.72*
Milt Wilcox ('70-'86, 16 WAR*)	10.1	126	20.1%*	8.9%*	1.23*	4.40*
Steve Hargan ('65-'77, 8 WAR*)	8.2	136	17.2%*	8.6%*	0.98*	4.65*
Edwin Jackson ('19)	9.8	115	17.6%	9.1%	1.14	4.78
Chris Capuano ('16)	7.1	119	19.5%	7.5%	1.23	4.38

			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 Gibson (OGILVIE)	—	—	—	—	—	3.4%	—	5.19	18.8%	9.5%	30	+0.43	—	—	—
Francisco Campos R 2015 · 4.77 FIP	42	SP	4.77	11.5%	7.9%	3.0%	.303	4.08	12.2%	7.0%	197	-0.69	4.06	332	60
Walter Silva R 2016 · 4.22 FIP	39	SP	4.22	10.3%	5.5%	2.4%	.294	4.35	10.0%	1.8%	235	+0.13	3.67	453	58
Pablo Ortega R 2016 · 4.01 FIP	39	SP	4.01	8.9%	4.8%	1.9%	.262	4.49	13.3%	7.1%	148	+0.48	4.01	375	52
Yasutomo Kubo R 2019 · 3.98 FIP	38	SP	3.98	20.4%	4.7%	3.6%	.327	—	—	—	—	—	3.98	152	51
Logan Duran R 2019 · 3.66 FIP	37	SP-	3.66	15.5%	8.9%	1.4%	.427	—	—	—	—	—	3.42	187	36
Mauricio Lara L 2017 · 3.70 FIP	38	SP	3.70	12.0%	6.3%	1.5%	.301	4.96	12.3%	5.5%	111	+1.26	3.62	444	29
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	26
Jason Lane L 2015 · 5.56 FIP	38	SP	5.56	8.4%	6.2%	4.3%	.307	—	—	—	—	—	5.56	164	18

Kyle Gibson

Contract

Career Stats + Projections

How the minor-league lines were translated

Career Path Comps

Career Comps