Jameson Taillon

P Toronto Blue Jays

Age 35 RHP 6'5" / 230 lbs MLB

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	32	MIX3 levels	30	30	172	3.30	3.75	18.8%	5.0%	3.4	K 18.5% · BB 4.9% · FIP 3.93
2025	33	MIX2 levels	27	27	146	3.94	4.63	19.4%	5.1%	1.3	K 19.0% · BB 5.0% · FIP 4.80
2026	34	MIX3 levels	21	21	97	5.46	6.05	20.0%	8.2%	-0.7	K 20.5% · BB 8.4% · FIP 6.43
2027PROJ	35	MLBTOR	12	12	70	4.94	5.56	19.0%	7.0%	-0.1
2028PROJ	36	MLBTOR	9	9	55	5.53	5.93	18.0%	7.6%	-0.3
2029PROJ	37	MLBTOR	6	6	34	6.01	6.33	16.9%	8.2%	-0.3

Last 3 seasons WAR 4.0 · Next 3 projected WAR -0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%38

FB Velo12

xwOBA vs10

CompsMasato Yoshii (age 35) · Jose Oyervides (age 35) · Jarrett Grube (age 35)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 140132vR 124

ERA4.94

FIP5.56

K%19.0%

BB%7.0%

K-BB%12.0%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1291.8

Whiff%

p5826.5%

p3820.5%

xwOBA vs

p100.367

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)
2016	24	MIX MLE	2 levels	28	28	166	654	146	22	15	100%	5.9	21.2%	3.4%	17.8%	2.5%	2.88	3.12	+4.7
2016	24	MIX RAW	2 levels	28	28	166	654	146	22	15	100%	5.9	22.3%	3.4%	19.0%	2.3%	2.88	2.91	+5.2
2017	25	MIX MLE	3 levels	28	28	148	646	146	46	11	100%	5.3	21.3%	7.3%	14.0%	2.0%	4.33	3.34	+3.7
2017	25	MIX RAW	3 levels	28	28	148	646	146	46	11	100%	5.3	22.6%	7.1%	15.5%	1.7%	4.33	3.03	+4.4
2018	26	MLB MLE	Pittsburgh Pirates	32	32	191	785	179	42	20	100%	6.0	22.8%	5.4%	17.5%	2.8%	3.20	3.36	+4.8
2018	26	MLB RAW	Pittsburgh Pirates	32	32	191	785	179	42	20	100%	6.0	22.8%	5.4%	17.5%	2.5%	3.20	3.25	+5.1
2019	27	MLB MLE	Pittsburgh Pirates	7	7	37	158	30	7	4	100%	5.3	19.0%	4.4%	14.6%	2.7%	4.10	3.56	+0.8
2019	27	MLB RAW	Pittsburgh Pirates	7	7	37	158	30	7	4	100%	5.3	19.0%	4.4%	14.6%	2.5%	4.10	3.45	+0.9
2021	29	MIX MLE	2 levels	30	30	147	616	142	43	24	100%	4.9	23.2%	7.1%	16.1%	3.7%	4.34	4.09	+2.3
2021	29	MIX RAW	2 levels	30	30	147	616	142	43	24	100%	4.9	23.1%	7.0%	16.1%	3.9%	4.34	4.17	+2.1
2022	30	MLB MLE	New York Yankees	32	32	177	728	151	32	26	100%	5.5	20.7%	4.4%	16.3%	3.3%	3.91	3.74	+3.5
2022	30	MLB RAW	New York Yankees	32	32	177	728	151	32	26	100%	5.5	20.7%	4.4%	16.3%	3.6%	3.91	3.84	+3.3
2023	31	MLB MLE	Chicago Cubs	30	29	154	655	140	41	27	97%	5.1	21.4%	6.3%	15.1%	4.3%	4.84	4.44	+1.7
2023	31	MLB RAW	Chicago Cubs	30	29	154	655	140	41	27	97%	5.1	21.4%	6.3%	15.1%	4.1%	4.84	4.36	+1.9
2024	32	MIX MLE	3 levels	30	30	172	706	133	35	21	100%	5.7	18.5%	4.9%	13.6%	3.2%	3.30	3.93	+3.0
2024	32	MIX MLE	3 levels	30	30	172	706	133	35	21	100%	5.7	18.5%	4.9%	13.6%	3.2%	3.30	3.93	+3.0
2024	32	MIX RAW	3 levels	30	30	172	706	133	35	21	100%	5.7	18.8%	5.0%	13.9%	3.0%	3.30	3.75	+3.4
2025	33	MIX MLE	2 levels	27	27	146	593	115	30	28	100%	5.4	19.0%	5.0%	14.0%	4.9%	3.94	4.80	+1.0
2025	33	MIX MLE	2 levels	27	27	146	593	115	30	28	100%	5.4	19.0%	5.0%	14.0%	4.9%	3.94	4.80	+1.0
2025	33	MIX RAW	2 levels	27	27	146	593	115	30	28	100%	5.4	19.4%	5.1%	14.3%	4.7%	3.94	4.63	+1.3
2026	34	MIX MLE	3 levels	21	21	97	414	83	34	27	100%	4.6	20.5%	8.4%	12.2%	7.3%	5.46	6.43	-1.1
2026	34	MIX MLE	3 levels	21	21	97	414	83	34	27	100%	4.6	20.5%	8.4%	12.2%	7.3%	5.46	6.43	-1.1
2026	34	MIX RAW	3 levels	21	21	97	414	83	34	27	100%	4.6	20.0%	8.2%	11.8%	6.5%	5.46	6.05	-0.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			242	241	1323	5498	1149	315	197	100%	5.5	20.9%	5.7%	15.2%	3.6%	3.99	4.01	+21.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	35	MLB	TOR	12	12	70	296	56	21	15	100%	5.8	19.0%	7.0%	12.0%	5.1%	4.94	5.56	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	36	MLB MLE	TOR	9	9	55	232	42	18	13	100%	6.1	18.0%	7.6%	10.4%	5.5%	5.53	5.93	-0.3
2029	37	MLB MLE	TOR	6	6	34	141	24	12	8	100%	5.6	16.9%	8.2%	8.7%	5.9%	6.01	6.33	-0.3
2028	36	MLB CTX	TOR	9	9	55	232	42	18	13	100%	6.1	18.0%	7.6%	10.4%	5.5%	5.53	5.93	-0.3
2029	37	MLB CTX	TOR	6	6	34	144	24	12	8	100%	5.7	16.9%	8.2%	8.7%	5.9%	6.01	6.33	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		257	256	1411	5871	1215	344	218	100%	5.5	20.7%	5.9%	14.8%	3.7%	4.09	4.13	+21.1
/ 200 IP	—	RAW		36	36	200	832	172	49	31	100%	5.5	20.7%	5.9%	14.8%	3.7%	4.09	4.13	+3.0
Career	—	MLE		265	264	1436	5955	1248	334	213	100%	5.4	21.0%	5.6%	15.3%	3.6%	3.92	4.00	+21.0
/ 200 IP	—	MLE		37	37	200	829	174	47	30	100%	5.4	21.0%	5.6%	15.3%	3.6%	3.92	4.00	+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.

2026 AAABuffalo Bisons · 8 IPFIP 2.96 → 3.03 (+0.07)K% 16.7% → 14.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.67%	—	×0.860	14.33%
BB% (unintentional) /BF	10.00%	—	×0.900	9.00%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 2.96 → 3.03, 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).

2025 AAAIowa Cubs · 17 IPFIP 4.64 → 4.79 (+0.15)K% 23.0% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.97%	—	×0.860	19.76%
BB% (unintentional) /BF	4.05%	—	×0.900	3.65%
HR / BF /BF	5.41%	÷1.125	×1.100	5.28%

Result: FIP 4.64 → 4.79, 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 AAAIndianapolis Indians · 11 IPFIP 0.99 → 1.33 (+0.34)K% 31.2% → 27.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.25%	—	×0.880	27.50%
BB% (unintentional) /BF	4.17%	—	×1.050	4.38%
HR / BF /BF	0.00%	÷0.850	×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 70).

Result: FIP 0.99 → 1.33, 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).

2016 AAAIndianapolis Indians · 62 IPFIP 1.70 → 2.07 (+0.36)K% 25.8% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.85%	—	×0.880	22.75%
BB% (unintentional) /BF	2.54%	—	×1.050	2.67%
HR / BF /BF	0.85%	÷0.933	×1.100	1.00%

Result: FIP 1.70 → 2.07, 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).

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
Jameson Taillon (OGILVIE)	—	—	—	—	—	5.1%	—	6.08	17.6%	9.8%	88	+0.52	—	—	—
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	61
Jose Oyervides R 2017 · 5.38 FIP	35	SP	5.38	18.0%	6.3%	5.5%	.254	5.66	16.3%	5.1%	115	+0.28	3.01	407	54
Jarrett Grube R 2017 · 4.41 FIP	35	SP	4.41	15.8%	8.1%	3.0%	.296	—	—	—	—	—	3.75	393	49
Frankie De La Cruz R 2019 · 4.38 FIP	35	SP-	4.38	16.2%	8.0%	3.0%	.322	—	—	—	—	—	2.87	262	44
Leo Medrano R 2016 · 4.34 FIP	33	SP	4.34	11.0%	7.3%	2.3%	.312	—	—	—	—	—	3.76	222	44
Dennis Springer R 2000 · 5.32 FIP	35	SP	5.32	8.5%	8.5%	3.4%	.383	4.85	9.3%	6.6%	19	-0.47	4.58	654	43
Jesse Estrada R 2019 · 4.34 FIP	35	SP-	4.34	14.4%	6.6%	2.9%	.312	—	—	—	—	—	3.80	257	43
Mitch Talbot R 2019 · 5.01 FIP	35	SP	5.01	13.2%	4.3%	4.5%	.289	—	—	—	—	—	3.82	395	42
Hector Ambriz R 2019 · 6.40 FIP	35	SP	6.40	10.4%	7.5%	5.9%	.347	—	—	—	—	—	2.24	259	41
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	41
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	41
Michael Nix R 2016 · 4.60 FIP	33	SP	4.60	11.9%	11.6%	1.9%	.322	—	—	—	—	—	3.82	234	39
Juan Delgadillo R 2017 · 4.47 FIP	34	SP	4.47	10.9%	6.2%	2.7%	.311	—	—	—	—	—	4.47	143	39
Walter Silva R 2009 · 5.72 FIP	32	SP	5.72	9.1%	12.4%	3.3%	.330	—	—	—	—	—	3.67	453	34
Yohan Pino R 2017 · 5.33 FIP	33	SP-	5.33	15.2%	3.6%	5.6%	.296	—	—	—	—	—	3.84	193	33
Cesar Carrillo R 2019 · 6.22 FIP	35	SP-	6.22	11.0%	9.2%	5.3%	.392	—	—	—	—	—	4.14	336	31
Luis Mendoza R 2019 · 5.10 FIP	35	SP	5.10	9.7%	4.2%	4.2%	.378	—	—	—	—	—	3.17	374	31
J.D. Martin R 2018 · 4.94 FIP	35	SP	4.94	10.4%	11.9%	2.2%	.284	5.89	13.9%	1.1%	125	+0.95	4.79	414	31
Daniel Rodriguez L 2019 · 4.77 FIP	34	SP	4.77	20.8%	7.8%	4.5%	.329	—	—	—	—	—	2.89	391	28
Marlon Arias L 2019 · 4.83 FIP	34	SP	4.83	19.8%	11.2%	3.6%	.273	—	—	—	—	—	3.73	154	23

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	7.4	114	20.6%	6.1%	1.46	4.13
Doug Bird ('73-'83, 10 WAR*)	6.1	110	20.3%*	5.8%*	1.41*	4.43*
Phil Hughes ('18)	6.5	108	18.9%	5.7%	1.33	4.52
Lee Stange ('61-'70, 9 WAR*)	6.1	135	17.8%*	6.6%*	1.36*	4.14*
Ross Stripling ('24)	4.2	94	20.9%	5.6%	1.32	4.17
Mike Minor ('22)	7.0	128	21.6%	7.0%	1.30	4.25
Scott Bankhead ('86-'95, 10 WAR*)	4.5	100	21.2%*	7.3%*	1.36*	4.16*