Kevin Gausman

P Chicago Cubs

Age 36 RHP 6'2" / 205 lbs MLB Svc 12.0 · Ctrl thru 2027 peak 2.2 · 2027

Overview

MLBSP40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR
2024	33	MLBTOR	31	31	181	3.83	3.67	21.4%	7.4%	3.8
2025	34	MLBTOR	32	32	193	3.59	3.30	24.4%	6.2%	5.0
2026	35	MLBCHC	32	32	178	4.51	3.71	24.5%	6.1%	3.6
2027PROJ	36	MLBCHC	22	22	132	4.00	4.00	24.2%	6.3%	2.2
2028PROJ	37	MLBCHC	16	16	97	4.17	4.33	23.1%	7.0%	1.1
2029PROJ	38	MLBCHC	10	10	63	4.52	4.75	21.9%	7.7%	0.4

Last 3 seasons WAR 12.4 · Next 3 projected WAR 3.7Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service12.878First FA2028

2027Ext / FA-deal$14M

Skills · percentileStatcast 2026

K%62

xwOBA vs53

FB Velo40

Form5.27 ERA (proj 4.00) · K 29.9% (proj 24.2%) · BB 5.1% (proj 6.3%) ▲▲ last 60d · 27 IP through Oct 27

CompsHiroki Kuroda (age 36) · Jose Contreras (age 36) · Steve Sparks (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10799vR 91

ERA4.00

FIP4.00

K%24.2%

BB%6.3%

K-BB%17.8%

Proj IP132

Value2027 · WAR

Runs saved vs league avg · 132 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p4093.8

Whiff%

p6527.7%

p6224.5%

xwOBA vs

p530.309

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status FA

MLB Debut 2013

Service 12.878 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$14M	+2.2	$18M	+$3M
Totals		$14M		$18M	+$3M

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	22	MLB MLE	Baltimore Orioles	20	5	48	201	49	11	8	25%	2.4	24.4%	5.5%	18.9%	3.6%	5.66	3.71	+0.5
2013	22	MLB RAW	Baltimore Orioles	20	5	48	201	49	11	8	25%	2.4	24.4%	5.5%	18.9%	4.0%	5.66	3.92	+0.4
2014	23	MLB MLE	Baltimore Orioles	20	20	113	476	88	38	7	100%	5.7	18.5%	8.0%	10.5%	1.3%	3.57	3.28	+3.0
2014	23	MLB RAW	Baltimore Orioles	20	20	113	476	88	38	7	100%	5.7	18.5%	8.0%	10.5%	1.5%	3.57	3.36	+2.9
2015	24	MIX MLE	4 levels	31	23	135	559	127	34	22	74%	4.3	22.0%	6.5%	15.4%	3.3%	4.01	3.89	+2.4
2015	24	MIX RAW	4 levels	31	23	135	559	127	34	22	74%	4.3	22.7%	6.1%	16.6%	3.9%	4.01	4.10	+2.1
2016	25	MIX MLE	4 levels	33	33	191	808	193	51	28	100%	5.8	23.0%	6.1%	16.9%	3.3%	3.59	3.76	+3.8
2016	25	MIX RAW	4 levels	33	33	191	808	193	51	28	100%	5.8	23.9%	6.3%	17.6%	3.5%	3.59	3.79	+3.7
2017	26	MLB MLE	Baltimore Orioles	34	34	187	816	179	71	29	100%	5.5	21.9%	8.7%	13.2%	3.2%	4.68	4.11	+2.9
2017	26	MLB RAW	Baltimore Orioles	34	34	187	816	179	71	29	100%	5.5	21.9%	8.7%	13.2%	3.6%	4.68	4.34	+2.3
2018	27	MLB MLE	Atlanta Braves	31	31	184	776	148	49	26	100%	5.9	19.1%	6.3%	12.8%	3.4%	3.92	4.13	+2.8
2018	27	MLB RAW	Atlanta Braves	31	31	184	776	148	49	26	100%	5.9	19.1%	6.3%	12.8%	3.4%	3.92	4.13	+2.8
2019	28	MIX MLE	4 levels	34	20	120	521	133	31	17	59%	3.5	25.3%	6.4%	18.8%	3.1%	5.24	3.47	+2.8
2019	28	MIX RAW	4 levels	34	20	120	521	133	31	17	59%	3.5	25.5%	6.0%	19.6%	3.3%	5.24	3.50	+2.8
2020	29	MLB MLE	San Francisco Giants	12	10	60	245	79	16	8	83%	5.0	32.2%	6.5%	25.7%	3.5%	3.62	3.14	+1.7
2020	29	MLB RAW	San Francisco Giants	12	10	60	245	79	16	8	83%	5.0	32.2%	6.5%	25.7%	3.3%	3.62	3.00	+1.8
2021	30	MLB MLE	San Francisco Giants	33	33	192	775	227	49	20	100%	5.8	29.3%	6.3%	23.0%	2.8%	2.81	2.96	+5.9
2021	30	MLB RAW	San Francisco Giants	33	33	192	775	227	49	20	100%	5.8	29.3%	6.3%	23.0%	2.6%	2.81	2.86	+6.2
2022	31	MLB MLE	Toronto Blue Jays	31	31	175	725	205	28	15	100%	5.6	28.3%	3.9%	24.4%	2.1%	3.35	2.34	+7.0
2022	31	MLB RAW	Toronto Blue Jays	31	31	175	725	205	28	15	100%	5.6	28.3%	3.9%	24.4%	2.1%	3.35	2.35	+6.9
2023	32	MLB MLE	Toronto Blue Jays	31	31	185	763	237	55	19	100%	6.0	31.1%	7.2%	23.9%	2.5%	3.16	2.76	+6.2
2023	32	MLB RAW	Toronto Blue Jays	31	31	185	763	237	55	19	100%	6.0	31.1%	7.2%	23.9%	2.5%	3.16	2.76	+6.2
2024	33	MLB MLE	Toronto Blue Jays	31	31	181	756	162	56	20	100%	5.8	21.4%	7.4%	14.0%	2.6%	3.83	3.68	+3.8
2024	33	MLB MLE	Toronto Blue Jays	31	31	181	756	162	56	20	100%	5.8	21.4%	7.4%	14.0%	2.6%	3.83	3.68	+3.8
2024	33	MLB RAW	Toronto Blue Jays	31	31	181	756	162	56	20	100%	5.8	21.4%	7.4%	14.0%	2.6%	3.83	3.67	+3.8
2025	34	MLB MLE	Toronto Blue Jays	32	32	193	775	189	48	21	100%	6.0	24.4%	6.2%	18.2%	2.7%	3.59	3.31	+5.0
2025	34	MLB MLE	Toronto Blue Jays	32	32	193	775	189	48	21	100%	6.0	24.4%	6.2%	18.2%	2.7%	3.59	3.31	+5.0
2025	34	MLB RAW	Toronto Blue Jays	32	32	193	775	189	48	21	100%	6.0	24.4%	6.2%	18.2%	2.7%	3.59	3.30	+5.0
2026	35	MLB MLE	Chicago Cubs	32	32	178	750	184	46	26	100%	5.6	24.5%	6.1%	18.4%	3.6%	4.51	3.78	+3.5
2026	35	MLB MLE	Chicago Cubs	32	32	178	750	184	46	26	100%	5.6	24.5%	6.1%	18.4%	3.6%	4.51	3.78	+3.5
2026	35	MLB RAW	Chicago Cubs	32	32	178	750	184	46	26	100%	5.6	24.5%	6.1%	18.4%	3.5%	4.51	3.71	+3.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			393	354	2089	8736	2138	570	259	90%	5.3	24.5%	6.5%	17.9%	3.0%	3.87	3.48	+48.9
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	CHC	22	22	132	557	135	35	18	100%	6.0	24.2%	6.3%	17.8%	3.2%	4.00	4.00	+2.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	CHC	16	16	97	409	94	29	15	100%	6.0	23.1%	7.0%	16.1%	3.6%	4.24	4.40	+1.1
2029	38	MLB MLE	CHC	10	10	63	266	58	20	11	100%	6.3	21.9%	7.7%	14.2%	4.1%	4.60	4.83	+0.4
2028	37	MLB CTX	CHC	16	16	97	410	95	29	14	100%	6.1	23.1%	7.0%	16.1%	3.5%	4.17	4.33	+1.1
2029	38	MLB CTX	CHC	10	10	63	266	58	20	10	100%	6.3	21.9%	7.7%	14.2%	3.9%	4.52	4.75	+0.4
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		420	381	2248	9411	2291	619	284	91%	5.4	24.3%	6.6%	17.8%	3.0%	3.90	3.53	+51.2
/ 200 IP	—	RAW		37	34	200	837	204	55	25	91%	5.4	24.3%	6.6%	17.8%	3.0%	3.90	3.53	+4.6
Career	—	MLE		405	366	2140	8946	2187	586	260	90%	5.3	24.4%	6.6%	17.9%	2.9%	3.85	3.46	+50.3
/ 200 IP	—	MLE		38	34	200	836	204	55	24	90%	5.3	24.4%	6.6%	17.9%	2.9%	3.85	3.46	+4.5

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.

2019 AAAGwinnett Stripers · 7 IPFIP 2.47 → 3.33 (+0.85)K% 37.0% → 32.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.04%	—	×0.880	32.59%
BB% (unintentional) /BF	3.70%	—	×1.050	3.89%
HR / BF /BF	3.70%	÷0.899	×1.100	4.53%

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 80).

Result: FIP 2.47 → 3.33, 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 AAMississippi Braves · 6 IPFIP 1.95 → 2.17 (+0.22)K% 13.6% → 11.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.64%	—	×0.810	11.05%
BB% (unintentional) /BF	0.00%	—	×1.100	0.00%
HR / BF /BF	0.00%	÷0.900	×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 80).

Result: FIP 1.95 → 2.17, 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 A+Florida Fire Frogs · 5 IPFIP 3.90 → 5.49 (+1.58)K% 28.6% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.57%	—	×0.770	22.00%
BB% (unintentional) /BF	4.76%	—	×1.150	5.48%
HR / BF /BF	4.76%	÷0.920	×1.250	6.47%

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 84).

Result: FIP 3.90 → 5.49, 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 AAANorfolk Tides · 6 IPFIP 0.80 → 1.27 (+0.47)K% 40.9% → 36.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.91%	—	×0.880	36.00%
BB% (unintentional) /BF	9.09%	—	×1.050	9.55%
HR / BF /BF	0.00%	÷0.776	×1.100	0.00%

Result: FIP 0.80 → 1.27, 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).

2015 AAANorfolk Tides · 14 IPFIP 4.33 → 4.66 (+0.33)K% 25.5% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.45%	—	×0.880	22.40%
BB% (unintentional) /BF	10.91%	—	×1.050	11.45%
HR / BF /BF	3.64%	÷1.097	×1.100	3.65%

Result: FIP 4.33 → 4.66, 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+Frederick Keys · 5 IPFIP 3.31 → 4.05 (+0.74)K% 30.0% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.00%	—	×0.770	23.10%
BB% (unintentional) /BF	0.00%	—	×1.150	0.00%
HR / BF /BF	5.00%	÷1.184	×1.250	5.28%

Result: FIP 3.31 → 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).

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
Kevin Gausman (OGILVIE)	—	—	—	—	—	3.2%	—	4.57	22.6%	15.4%	160	+0.57	—	—	—
Hiroki Kuroda R 2011 · 3.64 FIP	36	SP	3.64	19.2%	5.1%	2.8%	.282	3.50	18.2%	13.3%	620	-0.14	2.96	1,319	71
Jose Contreras R 2008 · 4.08 FIP	36	SP	4.08	13.4%	6.7%	2.3%	.291	3.52	20.1%	12.1%	202	-0.56	2.43	1,279	48
Steve Sparks R 2001 · 4.14 FIP	36	SP	4.14	11.8%	6.4%	2.2%	.284	4.69	11.2%	3.7%	417	+0.55	3.78	1,320	41
Yasutomo Kubo R 2019 · 3.98 FIP	38	SP	3.98	20.4%	4.7%	3.6%	.327	—	—	—	—	—	3.98	152	37
Kenshin Kawakami R 2010 · 4.06 FIP	35	SP	4.06	15.1%	5.6%	2.8%	.293	—	—	—	—	—	3.97	244	34
Yoanner Negrin R 2019 · 3.87 FIP	35	SP	3.87	17.5%	8.1%	2.2%	.280	—	—	—	—	—	3.15	485	30
Jarrett Grube R 2017 · 4.41 FIP	35	SP	4.41	15.8%	8.1%	3.0%	.296	—	—	—	—	—	3.75	393	30
Jorge Martinez R 2019 · 3.71 FIP	34	SP	3.71	16.3%	5.7%	2.3%	.348	—	—	—	—	—	3.53	214	27
Austin Bibens-Dirkx R 2021 · 4.20 FIP	36	SP-	4.20	15.8%	5.6%	3.1%	.333	—	—	—	—	—	3.97	567	26
Frankie De La Cruz R 2019 · 4.38 FIP	35	SP-	4.38	16.2%	8.0%	3.0%	.322	—	—	—	—	—	2.87	262	25
Angel Castro R 2017 · 3.51 FIP	34	SP	3.51	14.5%	7.4%	1.3%	.332	—	—	—	—	—	3.51	292	23
Walter Silva R 2015 · 4.15 FIP	38	SP	4.15	14.8%	7.4%	2.5%	.311	3.91	10.4%	3.7%	209	-0.24	3.67	453	23
Chris Smith R 2017 · 5.08 FIP	36	SP-	5.08	15.6%	7.5%	4.3%	.286	—	—	—	—	—	3.79	477	20
Jesse Estrada R 2019 · 4.34 FIP	35	SP-	4.34	14.4%	6.6%	2.9%	.312	—	—	—	—	—	3.80	257	19
David Buchanan R 2024 · 4.26 FIP	35	SP-	4.26	14.7%	6.5%	2.9%	.337	5.56	12.2%	4.1%	29	+1.30	3.88	560	19
Pablo Ortega R 2015 · 4.52 FIP	38	SP	4.52	8.6%	7.3%	2.2%	.291	4.24	11.5%	6.0%	236	-0.28	4.01	375	18
Lorenzo Barcelo R 2015 · 3.28 FIP	37	SP	3.28	13.2%	3.6%	1.5%	.345	3.48	12.8%	11.7%	45	+0.20	3.14	259	16
Jonathan Castellanos R 2017 · 4.91 FIP	35	SP	4.91	8.4%	9.2%	2.5%	.314	5.24	11.0%	2.0%	67	+0.33	3.40	394	15
Francisco Rodriguez R 2019 · 5.18 FIP	36	SP	5.18	10.7%	9.3%	3.3%	.339	—	—	—	—	—	3.16	334	13
Tsuyoshi Wada L 2015 · 3.66 FIP	34	SP	3.66	16.8%	7.1%	2.0%	.307	—	—	—	—	—	3.60	188	10

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	11.9	140	24.3%	6.7%	1.17	3.91
John Candelaria ('75-'93, 42 WAR*)	12.6	140	22.5%*	5.7%*	1.34*	3.73*
Danny Darwin ('78-'98, 36 WAR*)	15.1	151	20.5%*	6.7%*	1.21*	4.02*
Sonny Siebert ('64-'75, 28 WAR*)	10.8	179	22.1%*	7.5%*	1.17*	3.86*
Lance Lynn ('24)	10.0	154	23.7%	8.3%	1.04	3.74
Jeff Samardzija ('20)	8.2	150	21.0%	7.1%	1.12	4.15
Mike Minor ('22)	7.0	128	21.6%	7.0%	1.30	4.25