Erik Swanson

P Toronto Blue Jays

Age 33 RHP 6'3" / 225 lbs MLB

Overview

MLBRP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	29	MIX2 levels	70	0	68	2.93	3.32	28.7%	7.9%	1.0	K 28.6% · BB 8.0% · FIP 3.37
2024	30	MIX3 levels	64	0	57	6.79	6.66	21.5%	10.3%	-1.4	K 20.0% · BB 10.0% · FIP 6.67
2025	31	MIX4 levels	13	0	11	12.66	6.94	14.0%	10.5%	-0.3	K 14.0% · BB 10.5% · FIP 6.14
2026	32	No MLB games played
2027PROJ	33	MLBTOR	54	0	57	4.53	4.63	22.7%	9.3%	-0.1
2028PROJ95% MLB	34	MLBTOR	39	0	41	4.77	4.94	21.8%	9.8%	-0.2
2029PROJ91% MLB	35	MLBTOR	29	0	30	5.07	5.27	20.8%	10.3%	-0.2

Last 3 seasons WAR -0.7 · Next 3 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff45Control50Command50FB velo50

CompsTony Barnette (age 33) · Mark Serrano (age 33) · Jim Henderson (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 121113vR 105

ERA4.53

FIP4.63

K%22.7%

BB%9.3%

K-BB%13.4%

Proj IP57

Value2027 · WAR

Runs saved vs league avg · 57 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL5050

CMD5050

K†5555

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	21	MIX MLE	4 levels	10	0	15	62	14	7	1	0%	1.5	22.6%	11.3%	11.3%	1.6%	2.35	3.51	—
2015	21	MIX RAW	4 levels	10	0	15	62	14	7	1	0%	1.5	22.6%	11.3%	11.3%	1.6%	2.35	3.49	—
2016	22	A MLE	Charleston RiverDogs	24	17	96	402	93	30	4	71%	4.0	17.1%	8.8%	8.3%	1.4%	3.46	3.56	—
2016	22	A RAW	Charleston RiverDogs	24	17	96	402	93	30	4	71%	4.0	23.1%	7.5%	15.7%	1.0%	3.46	2.64	—
2017	23	A+ MLE	Tampa Yankees	20	20	100	416	84	13	10	100%	5.0	15.5%	3.6%	12.0%	3.2%	3.95	3.98	—
2017	23	A+ RAW	Tampa Yankees	20	20	100	416	84	13	10	100%	5.0	20.2%	3.1%	17.1%	2.4%	3.95	3.11	—
2018	24	MIX MLE	2 levels	22	20	115	449	133	29	10	91%	5.2	25.2%	6.9%	18.3%	2.3%	2.58	3.14	—
2018	24	MIX RAW	2 levels	22	20	115	449	133	29	10	91%	5.2	29.6%	6.5%	23.2%	2.2%	2.58	2.67	—
2019	25	MIX MLE	2 levels	37	14	82	356	80	23	22	38%	2.2	21.5%	6.6%	14.9%	6.4%	5.68	5.62	-1.0
2019	25	MIX RAW	2 levels	37	14	82	356	80	23	22	38%	2.2	22.5%	6.5%	16.0%	6.2%	5.68	5.47	-0.9
2020	26	MLB MLE	Seattle Mariners	9	0	8	37	9	2	3	0%	0.9	24.3%	5.4%	18.9%	8.1%	12.91	6.18	-0.1
2020	26	MLB RAW	Seattle Mariners	9	0	8	37	9	2	3	0%	0.9	24.3%	5.4%	18.9%	8.1%	12.91	6.62	-0.2
2021	27	MIX MLE	2 levels	35	2	37	152	36	9	6	6%	1.1	24.3%	6.2%	18.1%	3.6%	3.38	3.79	+0.3
2021	27	MIX RAW	2 levels	35	2	37	152	36	9	6	6%	1.1	23.7%	5.9%	17.8%	3.9%	3.38	3.98	+0.3
2022	28	MIX MLE	3 levels	59	1	56	214	73	9	3	2%	0.9	34.0%	4.4%	29.6%	1.5%	1.62	1.60	+2.0
2022	28	MIX RAW	3 levels	59	1	56	214	73	9	3	2%	0.9	34.1%	4.2%	29.9%	1.4%	1.62	1.66	+1.9
2023	29	MIX MLE	2 levels	70	0	68	265	76	21	8	0%	1.0	28.6%	8.0%	20.6%	3.1%	2.93	3.37	+0.9
2023	29	MIX RAW	2 levels	70	0	68	265	76	21	8	0%	1.0	28.7%	7.9%	20.8%	3.0%	2.93	3.32	+1.0
2024	30	MIX MLE	3 levels	64	0	57	261	56	27	18	0%	0.9	20.0%	10.0%	10.0%	7.3%	6.79	6.67	-1.4
2024	30	MIX MLE	3 levels	64	0	57	261	56	27	18	0%	0.9	20.0%	10.0%	10.0%	7.3%	6.79	6.67	-1.4
2024	30	MIX RAW	3 levels	64	0	57	261	56	27	18	0%	0.9	21.5%	10.3%	11.1%	6.9%	6.79	6.66	-1.4
2025	31	MIX MLE	4 levels	13	0	11	57	8	6	3	0%	0.8	14.0%	10.5%	3.5%	5.3%	12.66	6.14	-0.2
2025	31	MIX MLE	4 levels	13	0	11	57	8	6	3	0%	0.8	14.0%	10.5%	3.5%	5.3%	12.66	6.14	-0.2
2025	31	MIX RAW	4 levels	13	0	11	57	8	6	3	0%	0.8	14.0%	10.5%	3.5%	5.3%	12.66	6.94	-0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			246	11	266	1092	281	71	49	4%	1.1	25.7%	6.5%	19.2%	4.5%	4.20	4.18	+1.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	TOR	54	0	57	241	55	22	8	0%	1.1	22.7%	9.3%	13.4%	3.4%	4.53	4.63	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	TOR	41	0	43	181	39	18	7	0%	1.0	21.8%	9.8%	12.0%	3.7%	4.77	4.94	-0.2
2029	35	MLB MLE	TOR	31	0	33	139	29	14	6	0%	1.1	20.8%	10.3%	10.5%	4.1%	5.07	5.27	-0.3
2030	36	MLB MLE	TOR	24	0	26	109	21	12	5	0%	1.1	19.8%	10.9%	8.8%	4.5%	5.41	5.64	-0.3
2028	34	MLB CTX	TOR	39	0	41	173	38	17	6	0%	1.1	21.8%	9.8%	12.0%	3.7%	4.77	4.94	-0.2
2029	35	MLB CTX	TOR	29	0	30	127	26	13	5	0%	1.0	20.8%	10.3%	10.5%	4.1%	5.07	5.27	-0.2
2030	36	MLB CTX	TOR	20	0	21	89	18	10	4	0%	1.1	19.8%	10.9%	8.8%	4.5%	5.41	5.64	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		333	11	358	1479	362	111	65	3%	1.1	24.5%	7.5%	17.0%	4.4%	4.41	4.37	+0.7
/ 200 IP	—	RAW		186	6	200	827	202	62	36	3%	1.1	24.5%	7.5%	17.0%	4.4%	4.41	4.37	+0.4
Career	—	MLE		363	74	645	2671	592	186	95	20%	1.8	22.2%	7.0%	15.2%	3.6%	3.97	4.06	+0.3
/ 200 IP	—	MLE		113	23	200	828	183	58	29	20%	1.8	22.2%	7.0%	15.2%	3.6%	3.97	4.06	+0.2

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 AAABuffalo Bisons · 17 IPFIP 7.60 → 8.12 (+0.51)K% 18.9% → 16.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.89%	—	×0.860	16.24%
BB% (unintentional) /BF	14.44%	—	×0.900	13.00%
HR / BF /BF	7.78%	÷0.990	×1.100	8.64%

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 98).

Result: FIP 7.60 → 8.12, 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 AAATacoma Rainiers · 24 IPFIP 4.81 → 5.26 (+0.44)K% 25.2% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.23%	—	×0.880	22.20%
BB% (unintentional) /BF	10.81%	—	×1.050	11.35%
HR / BF /BF	4.50%	÷1.049	×1.100	4.72%

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 110).

Result: FIP 4.81 → 5.26, 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 AAAScranton/Wilkes-Barre RailRiders · 72 IPFIP 3.33 → 3.73 (+0.40)K% 26.8% → 23.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.80%	—	×0.880	23.59%
BB% (unintentional) /BF	4.81%	—	×1.050	5.05%
HR / BF /BF	3.44%	÷1.046	×1.100	3.61%

Result: FIP 3.33 → 3.73, 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 AATrenton Thunder · 43 IPFIP 1.36 → 2.04 (+0.68)K% 34.8% → 28.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.81%	—	×0.810	28.20%
BB% (unintentional) /BF	9.49%	—	×1.100	10.44%
HR / BF /BF	0.00%	÷1.034	×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 107).

Result: FIP 1.36 → 2.04, 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+Tampa Yankees · 100 IPFIP 3.11 → 3.98 (+0.87)K% 20.2% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.19%	—	×0.770	15.55%
BB% (unintentional) /BF	3.12%	—	×1.150	3.59%
HR / BF /BF	2.40%	÷0.949	×1.250	3.17%

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 90).

Result: FIP 3.11 → 3.98, 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 ACharleston RiverDogs · 96 IPFIP 2.64 → 3.56 (+0.93)K% 23.1% → 17.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.13%	—	×0.740	17.12%
BB% (unintentional) /BF	7.46%	—	×1.180	8.81%
HR / BF /BF	1.00%	÷0.895	×1.300	1.45%

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 79).

Result: FIP 2.64 → 3.56, 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).

2015 AHickory Crawdads · 12 IPFIP 3.54 → 4.25 (+0.71)K% 20.8% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.83%	—	×0.740	15.42%
BB% (unintentional) /BF	8.33%	—	×1.180	9.83%
HR / BF /BF	2.08%	÷1.229	×1.300	2.20%

Result: FIP 3.54 → 4.25, 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
Erik Swanson (OGILVIE)	—	—	4.63	22.7%	9.3%	3.4%	—	5.22	21.0%	10.7%	101	+0.59	—	—	—
Tony Barnette R 2017 · 3.56 FIP	33	SU	3.56	22.6%	7.1%	2.7%	.335	2.61	25.0%	20.2%	26	-0.95	2.61	144	79
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	76
Jim Henderson R 2016 · 4.55 FIP	33	SU	4.55	25.8%	9.0%	4.5%	.287	—	—	—	—	—	1.86	167	75
Jose Manuel Lopez R 2017 · 3.61 FIP	32	SU	3.61	20.4%	10.0%	1.8%	.331	6.14	17.9%	3.7%	41	+2.53	3.50	170	75
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	75
Arcenio Leon R 2019 · 3.61 FIP	32	SU	3.61	21.4%	8.1%	2.4%	.314	—	—	—	—	—	3.00	115	75
Felipe Arredondo R 2019 · 4.65 FIP	32	SU	4.65	16.2%	7.1%	3.7%	.272	—	—	—	—	—	3.92	337	74
Jon Edwards R 2019 · 4.43 FIP	31	SU	4.43	25.1%	11.6%	3.6%	.290	—	—	—	—	—	2.40	132	73
Hirokazu Sawamura R 2021 · 4.48 FIP	33	SU	4.48	26.2%	11.2%	4.0%	.263	4.02	18.1%	6.8%	51	-0.46	4.02	104	72
Austin Adams R 2019 · 5.80 FIP	32	SU	5.80	20.8%	10.6%	5.7%	.280	—	—	—	—	—	3.40	162	72
Jean Machi R 2015 · 4.56 FIP	33	SU	4.56	16.3%	8.6%	3.2%	.276	4.24	18.5%	11.9%	128	-0.32	2.16	306	72
Chris Jakubauskas R 2011 · 4.42 FIP	32	SW	4.42	15.7%	7.9%	3.0%	.339	—	—	—	—	—	4.42	165	72
Adrian Ramirez R 2019 · 4.29 FIP	31	SU	4.29	21.7%	6.3%	4.0%	.327	—	—	—	—	—	3.04	137	71
Juan Sandoval R 2015 · 3.82 FIP	34	SU	3.82	15.4%	6.0%	2.3%	.294	3.33	17.4%	8.8%	116	-0.49	3.24	225	70
Mike Buddie R 2002 · 4.26 FIP	31	SU	4.26	15.1%	7.6%	2.7%	.297	—	—	—	—	—	3.76	123	70
Rafael Betancourt R 2008 · 4.12 FIP	33	SU	4.12	20.7%	6.5%	3.6%	.304	2.37	31.4%	27.3%	181	-1.75	1.79	686	69
Huascar Brazobán R 2023 · 3.52 FIP	33	SU	3.52	25.3%	11.3%	2.1%	.304	3.54	21.9%	11.8%	195	+0.02	3.08	370	69
Angel Sánchez R 2023 · 4.90 FIP	33	SW	4.90	19.0%	10.5%	3.8%	.333	3.77	11.8%	6.8%	27	-1.13	3.77	284	69
Jake Sanchez R 2023 · 4.70 FIP	33	SU	4.70	20.3%	10.6%	3.6%	.317	—	—	—	—	—	1.86	361	69
Ryan Brasier R 2021 · 4.85 FIP	33	SU	4.85	18.0%	8.0%	4.1%	.286	3.16	23.7%	17.9%	150	-1.69	2.31	426	69

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 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	2.1	47	24.1%	8.0%	1.64	4.44
Heath Hembree ('23)	1.8	51	25.4%	9.4%	1.67	4.37
Noé Ramirez ('22)	1.5	59	24.8%	9.4%	1.42	4.21
Joel Peralta ('16)	3.2	54	23.0%	7.0%	1.32	4.03
Bob Patterson ('85-'98, 4 WAR*)	3.1	51	23.0%*	6.7%*	1.32*	4.33*
Pete Ladd ('79-'86, 0 WAR*)	1.4	72	24.6%*	7.8%*	1.53*	4.42*
Julio Navarro ('62-'70, 1 WAR*)	1.1	53	21.7%*	7.8%*	1.55*	4.13*