Spencer Arrighetti

P Toronto Blue Jays

Age 27 RHP 6'2" / 186 lbs MLB peak 0.3 · 2027

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	MIX2 levels	31	30	153	4.40	3.93	27.1%	10.8%	2.7	K 27.1% · BB 10.3% · FIP 3.99
2025	25	MIX3 levels	10	10	46	5.44	5.43	20.3%	12.1%	-0.0	K 19.9% · BB 12.8% · FIP 5.22
2026	26	MIX2 levels	29	24	131	4.47	4.67	22.8%	12.8%	1.1	K 22.2% · BB 12.6% · FIP 4.66
2027PROJ	27	MLBTOR	10	10	62	4.86	5.00	22.6%	12.4%	0.3
2028PROJ95% MLB	28	MLBTOR	8	8	51	5.00	5.09	22.4%	12.6%	0.2
2029PROJ95% MLB	29	MLBTOR	7	7	41	5.15	5.25	21.8%	12.8%	0.1

Last 3 seasons WAR 3.8 · Next 3 projected WAR 0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%45

FB Velo21

xwOBA vs19

Form5.87 ERA (proj 4.86) · K 15.5% (proj 22.6%) · BB 14.1% (proj 12.4%) ▼▼ last 60d · 15 IP through Oct 27

CompsTaylor Jungmann (age 27) · Jay Witasick (age 27) · Brandon Duckworth (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 129121vR 113

ERA4.86

FIP5.00

K%22.6%

BB%12.4%

K-BB%10.2%

Proj IP62

Value2027 · WAR

Runs saved vs league avg · 62 IP

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL4040

CMD5050

K†5555

Statcast Percentiles

FB Velo

p2192.4

Whiff%

p5125.5%

p4521.5%

xwOBA vs

p190.349

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)
2021	21	MIX MLE	2 levels	6	2	14	55	22	2	1	33%	2.3	40.0%	3.6%	36.4%	1.8%	2.63	1.18	—
2021	21	MIX RAW	2 levels	6	2	14	55	22	2	1	33%	2.3	40.0%	3.6%	36.4%	1.8%	2.63	1.27	—
2022	22	MIX MLE	2 levels	27	17	107	474	152	55	9	63%	4.0	24.9%	13.2%	11.7%	2.4%	4.72	3.97	—
2022	22	MIX RAW	2 levels	27	17	107	474	152	55	9	63%	4.0	32.1%	11.6%	20.5%	1.9%	4.72	2.89	—
2023	23	MIX MLE	2 levels	28	21	125	521	141	59	11	75%	4.5	22.5%	11.1%	11.4%	2.3%	4.40	3.89	—
2023	23	MIX RAW	2 levels	28	21	125	521	141	59	11	75%	4.5	27.1%	11.3%	15.7%	2.1%	4.40	3.40	—
2024	24	MIX MLE	2 levels	31	30	153	669	181	72	21	97%	4.9	27.1%	10.3%	16.8%	3.4%	4.40	3.99	+2.6
2024	24	MIX MLE	2 levels	31	30	153	669	181	72	21	97%	4.9	27.1%	10.3%	16.8%	3.4%	4.40	3.99	+2.6
2024	24	MIX RAW	2 levels	31	30	153	669	181	72	21	97%	4.9	27.1%	10.8%	16.3%	3.1%	4.40	3.93	+2.7
2025	25	MIX MLE	3 levels	10	10	46	207	42	25	9	100%	4.6	19.9%	12.8%	7.1%	4.0%	5.44	5.22	+0.1
2025	25	MIX MLE	3 levels	10	10	46	207	42	25	9	100%	4.6	19.9%	12.8%	7.1%	4.0%	5.44	5.22	+0.1
2025	25	MIX RAW	3 levels	10	10	46	207	42	25	9	100%	4.6	20.3%	12.1%	8.2%	4.3%	5.44	5.43	-0.0
2026	26	MIX MLE	2 levels	29	24	131	571	130	73	19	83%	4.5	22.2%	12.6%	9.6%	3.3%	4.47	4.66	+1.1
2026	26	MIX MLE	2 levels	29	24	131	571	130	73	19	83%	4.5	22.2%	12.6%	9.6%	3.3%	4.47	4.66	+1.1
2026	26	MIX RAW	2 levels	29	24	131	571	130	73	19	83%	4.5	22.8%	12.8%	10.0%	3.3%	4.47	4.67	+1.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			60	54	291	1280	308	149	45	90%	4.8	24.1%	11.6%	12.4%	3.5%	4.79	4.53	+2.9
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	TOR	10	10	62	262	59	32	9	100%	6.2	22.6%	12.4%	10.2%	3.4%	4.86	5.00	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	TOR	9	9	54	227	51	29	8	100%	6.0	22.4%	12.6%	9.9%	3.5%	5.00	5.09	+0.2
2029	29	MLB MLE	TOR	7	7	43	183	40	23	7	100%	6.2	21.8%	12.8%	9.1%	3.6%	5.15	5.25	+0.1
2030	30	MLB MLE	TOR	8	8	45	191	44	23	7	100%	5.7	23.1%	12.3%	10.9%	3.8%	5.17	5.19	+0.1
2028	28	MLB CTX	TOR	8	8	51	215	48	27	8	100%	6.4	22.4%	12.6%	9.9%	3.5%	5.00	5.09	+0.2
2029	29	MLB CTX	TOR	7	7	41	173	38	22	6	100%	5.9	21.8%	12.8%	9.1%	3.6%	5.15	5.25	+0.1
2030	30	MLB CTX	TOR	7	7	43	182	42	22	7	100%	6.1	23.1%	12.3%	10.9%	3.8%	5.17	5.19	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		83	77	426	1851	436	221	66	93%	5.1	23.6%	11.9%	11.7%	3.6%	4.89	4.57	+4.1
/ 200 IP	—	RAW		39	36	200	869	205	104	31	93%	5.2	23.6%	11.9%	11.7%	3.6%	4.89	4.57	+1.9
Career	—	MLE		131	104	576	2497	606	290	75	79%	4.4	24.3%	11.6%	12.7%	3.0%	4.52	4.16	+3.3
/ 200 IP	—	MLE		46	36	200	868	211	101	26	79%	4.4	24.3%	11.6%	12.7%	3.0%	4.52	4.16	+1.5

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.

2026 AAABuffalo Bisons · 20 IPFIP 2.67 → 2.96 (+0.28)K% 30.4% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.38%	—	×0.860	26.13%
BB% (unintentional) /BF	11.39%	—	×0.900	10.25%
HR / BF /BF	1.27%	÷1.000	×1.100	1.39%

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 2.67 → 2.96, 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 AACorpus Christi Hooks · 6 IPFIP 3.75 → 4.46 (+0.71)K% 23.1% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.810	18.69%
BB% (unintentional) /BF	3.85%	—	×1.100	4.23%
HR / BF /BF	3.85%	÷1.057	×1.200	4.37%

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 111).

Result: FIP 3.75 → 4.46, 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 AAASugar Land Space Cowboys · 5 IPFIP 7.83 → 8.50 (+0.67)K% 20.0% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.860	17.20%
BB% (unintentional) /BF	16.00%	—	×0.900	14.40%
HR / BF /BF	8.00%	÷0.961	×1.100	9.16%

Result: FIP 7.83 → 8.50, 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).

2024 AAASugar Land Space Cowboys · 8 IPFIP 3.21 → 3.29 (+0.08)K% 27.0% → 23.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.03%	—	×0.860	23.24%
BB% (unintentional) /BF	18.92%	—	×0.900	17.03%
HR / BF /BF	0.00%	÷0.903	×1.100	0.00%

Result: FIP 3.21 → 3.29, 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).

2023 AAASugar Land Space Cowboys · 64 IPFIP 4.28 → 4.71 (+0.43)K% 23.1% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.13%	—	×0.860	19.90%
BB% (unintentional) /BF	13.43%	—	×0.900	12.09%
HR / BF /BF	2.61%	÷0.896	×1.100	3.21%

Result: FIP 4.28 → 4.71, 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).

2023 AACorpus Christi Hooks · 61 IPFIP 2.48 → 3.02 (+0.54)K% 31.2% → 25.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.23%	—	×0.810	25.29%
BB% (unintentional) /BF	9.09%	—	×1.100	10.00%
HR / BF /BF	1.58%	÷1.322	×1.200	1.44%

Result: FIP 2.48 → 3.02, 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).

2022 A+Asheville Tourists · 86 IPFIP 2.76 → 3.83 (+1.08)K% 31.6% → 24.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.55%	—	×0.770	24.30%
BB% (unintentional) /BF	11.70%	—	×1.150	13.46%
HR / BF /BF	1.53%	÷0.972	×1.250	1.96%

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 94).

Result: FIP 2.76 → 3.83, 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).

2022 AACorpus Christi Hooks · 21 IPFIP 3.62 → 4.63 (+1.01)K% 34.6% → 28.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.57%	—	×0.810	28.00%
BB% (unintentional) /BF	11.11%	—	×1.100	12.22%
HR / BF /BF	3.70%	÷1.040	×1.200	4.27%

Result: FIP 3.62 → 4.63, 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
Spencer Arrighetti (OGILVIE)	—	—	5.00	22.6%	12.4%	3.4%	—	5.17	22.5%	9.9%	142	+0.17	—	—	—
Taylor Jungmann R 2017 · 3.88 FIP	27	SP-	3.88	18.8%	11.1%	1.8%	.279	—	—	—	—	—	3.59	435	72
Jay Witasick R 2000 · 4.76 FIP	27	SP-	4.76	17.4%	9.8%	3.4%	.318	3.20	24.2%	16.1%	193	-1.56	2.76	731	69
Brandon Duckworth R 2003 · 4.52 FIP	27	SP-	4.52	16.0%	9.7%	2.8%	.284	5.07	12.6%	5.0%	101	+0.55	3.36	511	66
Brad Peacock R 2014 · 4.73 FIP	26	SP	4.73	20.2%	11.2%	3.5%	.302	3.50	24.9%	15.4%	281	-1.23	2.97	748	66
Claudio Vargas R 2005 · 4.98 FIP	27	SP	4.98	16.2%	7.2%	4.3%	.285	4.61	16.6%	9.2%	339	-0.37	3.66	765	65
Tyler Chatwood R 2017 · 4.54 FIP	27	SP-	4.54	19.0%	11.9%	2.8%	.279	4.53	20.6%	5.2%	199	-0.01	3.30	879	65
Joaquín Benoit R 2004 · 4.49 FIP	27	SP-	4.49	20.8%	6.8%	4.2%	.302	3.31	23.7%	14.5%	249	-1.18	1.99	1,064	65
James McDonald R 2012 · 4.18 FIP	27	SP	4.18	21.2%	8.8%	3.2%	.264	3.74	18.1%	4.3%	30	-0.44	2.99	506	64
Matt Andriese R 2017 · 4.71 FIP	27	SP	4.71	20.3%	7.2%	4.4%	.290	3.99	24.5%	17.5%	181	-0.72	3.08	744	63
Daniel Ponce de Leon R 2019 · 4.09 FIP	27	SP	4.09	22.8%	12.0%	2.5%	.246	5.09	22.7%	10.1%	182	+1.00	3.35	768	63
Rorik Maltrud R 2024 · 3.91 FIP	24	SP-	3.91	20.4%	9.6%	2.4%	.300	4.40	18.6%	9.4%	193	+0.49	3.91	298	63
Ross Ohlendorf R 2010 · 4.31 FIP	27	SP	4.31	16.6%	8.8%	2.7%	.275	4.60	16.6%	9.3%	148	+0.29	3.30	617	63
Jimmy Nelson R 2016 · 4.57 FIP	27	SP	4.57	17.3%	10.4%	2.9%	.289	3.16	27.2%	18.6%	238	-1.41	1.32	720	62
John Maine R 2008 · 4.20 FIP	27	SP	4.20	20.1%	10.7%	2.6%	.262	4.64	17.3%	6.3%	121	+0.44	3.91	582	62
Austin Bergner R 2024 · 4.84 FIP	27	SP	4.84	22.2%	12.5%	3.7%	.325	4.42	18.7%	7.3%	107	-0.42	4.06	464	62
Armando Galarraga R 2009 · 5.20 FIP	27	SP	5.20	14.8%	10.3%	3.7%	.293	5.57	12.7%	3.5%	211	+0.37	3.92	584	62
Rafael Montero R 2017 · 3.88 FIP	26	SP-	3.88	22.0%	11.2%	2.2%	.339	3.41	28.7%	22.8%	47	-0.47	2.43	714	62
Riley Gowens R 2024 · 4.55 FIP	24	SP	4.55	22.6%	10.3%	3.7%	.279	4.37	21.3%	12.1%	173	-0.18	4.30	295	61
Heath Fillmyer R 2021 · 5.59 FIP	27	SP-	5.59	19.3%	10.8%	5.0%	.298	—	—	—	—	—	3.52	687	61
David Phelps R 2014 · 4.00 FIP	27	SP-	4.00	18.5%	8.9%	2.5%	.293	3.31	23.8%	15.6%	254	-0.69	2.50	672	61

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	2.5	71	23.4%	12.0%	1.37	4.89
Tim Birtsas ('85-'90, -0 WAR*)	1.6	82	21.4%*	11.7%*	1.31*	4.63*
David West ('88-'98, 1 WAR*)	2.8	71	22.1%*	12.1%*	1.28*	4.79*
Jeff Jones ('80-'84, -2 WAR*)	1.0	41	22.0%*	12.4%*	1.48*	4.53*
Britt Reames ('06)	1.1	73	20.7%	12.0%	1.32	5.28
Jay Witasick ('07)	3.7	73	19.6%	11.0%	1.19	4.64
Jake Faria ('23)	1.0	68	20.9%	10.3%	1.32	4.87