Shane Bieber

P Toronto Blue Jays

Age 32 RHP 6'3" / 200 lbs MLB peak 0.2 · 2027

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MLBCLE	2	2	12	0.00	0.02	44.4%	2.2%	0.9
2025	30	MIX5 levels	14	14	69	2.86	3.46	27.8%	3.8%	1.6	K 22.7% · BB 3.9% · FIP 4.28
2026	31	MIX4 levels	16	16	73	4.95	5.21	18.1%	9.1%	0.2	K 17.3% · BB 9.5% · FIP 5.29
2027PROJ	32	MLBTOR	8	8	45	4.78	5.05	18.7%	8.1%	0.2
2028PROJ	33	MLBTOR	7	7	42	5.11	5.33	17.8%	8.6%	0.0
2029PROJ	34	MLBTOR	5	5	30	5.43	5.64	16.9%	9.1%	-0.1

Last 3 seasons WAR 2.7 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%23

FB Velo19

xwOBA vs10

Form2.59 ERA (proj 4.78) · K 21.8% (proj 18.7%) · BB 5.9% (proj 8.1%) ▲ last 90d · 24 IP through Oct 27

CompsStan Spencer (age 30) · Juan Delgadillo (age 32) · Tyler Herron (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 134126vR 118

ERA4.78

FIP5.05

K%18.7%

BB%8.1%

K-BB%10.5%

Proj IP45

Value2027 · WAR

Runs saved vs league avg · 45 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1992.3

Whiff%

p3723.5%

p2318.2%

xwOBA vs

p100.368

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)
2017	22	MIX MLE	3 levels	28	28	173	698	162	8	8	100%	6.2	18.0%	1.3%	16.7%	1.5%	2.86	2.56	—
2017	22	MIX RAW	3 levels	28	28	173	698	162	8	8	100%	6.2	23.2%	1.1%	22.1%	1.1%	2.86	1.97	—
2018	23	MIX MLE	3 levels	33	32	194	783	195	30	17	97%	5.9	23.5%	3.9%	19.6%	2.2%	3.29	2.83	+6.3
2018	23	MIX RAW	3 levels	33	32	194	783	195	30	17	97%	5.9	24.9%	3.8%	21.1%	2.2%	3.29	2.69	+6.7
2019	24	MLB MLE	Cleveland Indians	34	33	214	859	259	39	31	97%	6.3	30.2%	4.5%	25.6%	3.6%	3.28	3.11	+6.1
2019	24	MLB RAW	Cleveland Indians	34	33	214	859	259	39	31	97%	6.3	30.2%	4.5%	25.6%	3.6%	3.28	3.11	+6.2
2020	25	MLB MLE	Cleveland Indians	12	12	77	297	122	21	7	100%	6.4	41.1%	7.1%	34.0%	2.4%	1.63	1.82	+3.8
2020	25	MLB RAW	Cleveland Indians	12	12	77	297	122	21	7	100%	6.4	41.1%	7.1%	34.0%	2.4%	1.63	1.94	+3.6
2021	26	MIX MLE	3 levels	18	18	103	431	141	35	13	100%	5.7	33.1%	8.1%	24.9%	2.7%	3.33	2.83	+3.3
2021	26	MIX RAW	3 levels	18	18	103	431	141	35	13	100%	5.7	32.7%	8.1%	24.6%	3.0%	3.33	3.02	+3.1
2022	27	MLB MLE	Cleveland Guardians	31	31	200	791	198	36	18	100%	6.5	25.0%	4.6%	20.5%	2.3%	2.88	2.81	+6.6
2022	27	MLB RAW	Cleveland Guardians	31	31	200	791	198	36	18	100%	6.5	25.0%	4.6%	20.5%	2.3%	2.88	2.83	+6.6
2023	28	MIX MLE	3 levels	23	23	135	562	118	38	14	100%	5.9	20.1%	6.4%	13.7%	2.6%	3.66	3.66	+2.9
2023	28	MIX RAW	3 levels	23	23	135	562	118	38	14	100%	5.9	21.0%	6.8%	14.2%	2.5%	3.66	3.54	+3.1
2024	29	MLB MLE	Cleveland Guardians	2	2	12	45	20	1	0	100%	6.0	44.4%	2.2%	42.2%	0.0%	0.00	-0.37	+0.9
2024	29	MLB MLE	Cleveland Guardians	2	2	12	45	20	1	0	100%	6.0	44.4%	2.2%	42.2%	0.0%	0.00	-0.37	+0.9
2024	29	MLB RAW	Cleveland Guardians	2	2	12	45	20	1	0	100%	6.0	44.4%	2.2%	42.2%	0.0%	0.00	0.02	+0.9
2025	30	MIX MLE	5 levels	14	14	69	266	74	10	11	100%	5.0	22.7%	3.9%	18.7%	4.7%	2.86	4.28	+0.9
2025	30	MIX MLE	5 levels	14	14	69	266	74	10	11	100%	5.0	22.7%	3.9%	18.7%	4.7%	2.86	4.28	+0.9
2025	30	MIX RAW	5 levels	14	14	69	266	74	10	11	100%	5.0	27.8%	3.8%	24.1%	4.1%	2.86	3.46	+1.6
2026	31	MIX MLE	4 levels	16	16	73	320	58	29	14	100%	4.5	17.3%	9.5%	7.8%	4.4%	4.95	5.29	+0.1
2026	31	MIX MLE	4 levels	16	16	73	320	58	29	14	100%	4.5	17.3%	9.5%	7.8%	4.4%	4.95	5.29	+0.1
2026	31	MIX RAW	4 levels	16	16	73	320	58	29	14	100%	4.5	18.1%	9.1%	9.1%	4.4%	4.95	5.21	+0.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			154	152	939	3816	1039	218	112	99%	6.1	27.2%	5.7%	21.5%	2.9%	3.31	3.13	+26.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	TOR	8	8	45	190	35	15	7	100%	5.6	18.7%	8.1%	10.5%	3.9%	4.78	5.05	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	TOR	7	7	42	179	32	15	7	100%	6.0	17.8%	8.6%	9.2%	4.1%	5.11	5.33	+0.0
2029	34	MLB MLE	TOR	5	5	30	128	22	12	6	100%	6.1	16.9%	9.1%	7.8%	4.4%	5.43	5.64	-0.1
2028	33	MLB CTX	TOR	7	7	42	177	32	15	7	100%	6.0	17.8%	8.6%	9.2%	4.1%	5.11	5.33	+0.0
2029	34	MLB CTX	TOR	5	5	30	127	21	12	6	100%	6.0	16.9%	9.1%	7.8%	4.4%	5.43	5.64	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		166	164	1012	4123	1093	245	125	99%	6.1	26.5%	5.9%	20.6%	3.0%	3.45	3.28	+26.6
/ 200 IP	—	RAW		33	32	200	815	216	48	25	99%	6.1	26.5%	5.9%	20.6%	3.0%	3.45	3.28	+5.3
Career	—	MLE		211	209	1251	5052	1280	248	137	99%	5.9	25.3%	4.9%	20.4%	2.7%	3.14	3.08	+26.3
/ 200 IP	—	MLE		34	33	200	807	205	40	22	99%	5.9	25.3%	4.9%	20.4%	2.7%	3.14	3.08	+5.2

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.

2026 AAABuffalo Bisons · 13 IPFIP 5.77 → 6.13 (+0.36)K% 15.8% → 13.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.79%	—	×0.860	13.58%
BB% (unintentional) /BF	8.77%	—	×0.900	7.89%
HR / BF /BF	5.26%	÷1.000	×1.100	5.79%

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 100).

Result: FIP 5.77 → 6.13, 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).

2025 AAABuffalo Bisons · 18 IPFIP 3.10 → 3.86 (+0.76)K% 24.6% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.62%	—	×0.860	21.17%
BB% (unintentional) /BF	3.08%	—	×0.900	2.77%
HR / BF /BF	3.08%	÷0.847	×1.100	4.00%

Result: FIP 3.10 → 3.86, 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).

2018 AAAColumbus Clippers · 49 IPFIP 2.21 → 2.48 (+0.26)K% 26.7% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.70%	—	×0.880	23.50%
BB% (unintentional) /BF	3.41%	—	×1.050	3.58%
HR / BF /BF	1.70%	÷1.135	×1.100	1.65%

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 127).

Result: FIP 2.21 → 2.48, 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).

2018 AAAkron RubberDucks · 31 IPFIP 1.58 → 2.18 (+0.60)K% 24.6% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.59%	—	×0.810	19.92%
BB% (unintentional) /BF	0.82%	—	×1.100	0.90%
HR / BF /BF	0.82%	÷0.840	×1.200	1.17%

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 68).

Result: FIP 1.58 → 2.18, 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 A+Lynchburg Hillcats · 90 IPFIP 2.00 → 2.75 (+0.75)K% 22.9% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.91%	—	×0.770	17.64%
BB% (unintentional) /BF	0.56%	—	×1.150	0.64%
HR / BF /BF	1.40%	÷0.902	×1.250	1.94%

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 80).

Result: FIP 2.00 → 2.75, 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 AAAkron RubberDucks · 54 IPFIP 2.00 → 2.48 (+0.48)K% 22.4% → 18.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.37%	—	×0.810	18.12%
BB% (unintentional) /BF	2.28%	—	×1.100	2.51%
HR / BF /BF	0.91%	÷1.008	×1.200	1.09%

Result: FIP 2.00 → 2.48, 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 ALake County Captains · 29 IPFIP 1.49 → 2.15 (+0.65)K% 25.6% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.62%	—	×0.740	18.96%
BB% (unintentional) /BF	0.83%	—	×1.180	0.98%
HR / BF /BF	0.83%	÷1.129	×1.300	0.95%

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 126).

Result: FIP 1.49 → 2.15, 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
Shane Bieber (OGILVIE)	—	—	—	—	—	3.9%	—	5.46	17.4%	8.6%	73	+0.41	—	—	—
Stan Spencer R 2000 · 4.42 FIP	30	SP	4.42	19.2%	8.7%	3.4%	.259	—	—	—	—	—	3.61	119	78
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	73
Tyler Herron R 2017 · 4.02 FIP	30	SP	4.02	16.4%	8.7%	2.2%	.377	—	—	—	—	—	4.02	117	71
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	70
Chuck Smith R 2001 · 3.99 FIP	31	SP	3.99	18.4%	8.1%	2.6%	.289	—	—	—	—	—	3.08	211	70
Tim Adleman R 2019 · 4.30 FIP	31	SP	4.30	22.8%	7.8%	3.9%	.266	4.71	18.5%	11.1%	90	+0.41	3.63	605	67
Scott Carroll R 2017 · 5.71 FIP	32	SP	5.71	14.4%	8.6%	5.0%	.300	—	—	—	—	—	3.92	377	67
Jason Simontacchi R 2007 · 4.96 FIP	33	SP	4.96	13.0%	5.9%	4.0%	.331	—	—	—	—	—	4.79	356	65
Jesus Adrian Castillo R 2016 · 3.88 FIP	32	SP	3.88	12.8%	6.0%	2.0%	.245	4.27	13.6%	7.2%	58	+0.39	2.23	173	65
Jeremy Hefner R 2016 · 4.64 FIP	30	SP	4.64	16.8%	9.1%	3.3%	.305	—	—	—	—	—	3.56	322	65
Diego Moreno R 2019 · 4.08 FIP	32	SP	4.08	12.4%	6.9%	2.1%	.376	4.75	18.6%	9.2%	30	+0.67	2.29	187	63
Mario Gonzalez R 2017 · 4.53 FIP	30	SP	4.53	14.1%	5.0%	3.6%	.345	—	—	—	—	—	3.94	368	63
Patrick Johnson R 2019 · 4.14 FIP	30	SP	4.14	15.7%	9.3%	2.2%	.344	—	—	—	—	—	3.82	248	62
Mitch Atkins R 2017 · 4.77 FIP	31	SP	4.77	14.3%	8.1%	3.4%	.303	—	—	—	—	—	3.65	215	61
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	61
Nestor Molina R 2019 · 4.27 FIP	30	SP	4.27	16.1%	7.4%	2.9%	.325	—	—	—	—	—	3.01	401	61
Paolo Espino R 2019 · 4.54 FIP	32	SP	4.54	20.7%	6.4%	4.3%	.311	4.58	19.5%	14.5%	223	+0.04	3.42	933	60
Cody Mincey R 2022 · 5.56 FIP	30	SP	5.56	13.9%	8.4%	4.7%	.297	—	—	—	—	—	2.49	147	60
Matt Buschmann R 2016 · 4.84 FIP	32	SP	4.84	12.8%	8.4%	3.2%	.325	—	—	—	—	—	4.03	277	60
Brandon Beachy R 2019 · 4.19 FIP	32	SP	4.19	17.4%	9.5%	2.5%	.315	—	—	—	—	—	1.97	364	59

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	5.3	96	26.1%	6.1%	1.19	3.50
Julio Urías ('23)	3.6	102	24.3%	6.6%	1.05	3.11
Kenta Maeda ('25)	4.9	123	25.8%	7.0%	1.30	4.20
Alex Wood ('24)	6.3	114	22.1%	7.1%	0.91	3.78
John Candelaria ('75-'93, 42 WAR*)	12.6	140	22.5%*	5.7%*	1.34*	3.73*
Dick Hughes ('66-'68, 5 WAR*)	1.5	102	24.1%*	7.1%*	1.51*	3.68*
Roger Nelson ('67-'76, 10 WAR*)	3.2	106	19.5%*	7.1%*	0.98*	3.88*