Jeff Hoffman

P Minnesota Twins

Age 34 RHP 6'5" / 235 lbs MLB peak 0.9 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR
2024	31	MLBPHI	68	66	2.17	2.27	33.6%	5.7%	1.8
2025	32	MLBTOR	71	68	4.37	4.64	29.3%	9.1%	-0.1
2026	33	MLBMIN	71	66	3.55	1.93	34.9%	8.6%	2.1
2027PROJ	34	MLBMIN	56	59	3.38	3.27	33.5%	8.6%	1.0
2028PROJ	35	MLBMIN	50	52	3.53	3.62	32.5%	9.1%	0.6
2029PROJ	36	MLBMIN	40	42	3.80	3.98	31.5%	9.7%	0.3

Last 3 seasons WAR 3.8 · Next 3 projected WAR 1.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%90

xwOBA vs80

FB Velo77

Form2.25 ERA (proj 3.38) · K 35.3% (proj 33.5%) · BB 15.3% (proj 8.6%) ▼ last 90d · 20 IP through Oct 27

CompsKazuhiro Sasaki (age 34) · Fernando Cruz (age 34) · Fernando Rodriguez Jr. (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9284vR 76

ERA3.38

FIP3.27

K%33.5%

BB%8.6%

K-BB%24.9%

Proj IP59

Value2027 · WAR

Runs saved vs league avg · 59 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p7796.4

Whiff%

p9038.0%

p9034.9%

xwOBA vs

p800.283

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	22	MIX MLE	2 levels	20	20	104	415	75	26	7	100%	5.2	14.3%	7.1%	7.2%	1.9%	3.03	3.84	—
2015	22	MIX RAW	2 levels	20	20	104	415	75	26	7	100%	5.2	18.1%	6.3%	11.8%	1.7%	3.03	3.28	—
2016	23	MIX MLE	2 levels	30	28	150	659	146	60	18	93%	5.0	19.9%	9.4%	10.5%	2.5%	4.20	3.97	+2.6
2016	23	MIX RAW	2 levels	30	28	150	659	146	60	18	93%	5.0	22.2%	9.1%	13.1%	2.7%	4.20	3.91	+2.7
2017	24	MIX MLE	2 levels	33	26	149	659	129	58	18	79%	4.5	18.7%	8.9%	9.8%	2.4%	5.50	3.99	+2.5
2017	24	MIX RAW	2 levels	33	26	149	659	129	58	18	79%	4.5	19.6%	8.8%	10.8%	2.7%	5.50	4.11	+2.3
2018	25	MIX MLE	3 levels	28	23	117	509	109	53	9	82%	4.2	19.9%	10.9%	9.0%	1.9%	5.29	3.84	+2.2
2018	25	MIX RAW	3 levels	28	23	117	509	109	53	9	82%	4.2	21.4%	10.4%	11.0%	1.8%	5.29	3.59	+2.6
2019	26	MIX MLE	2 levels	32	31	155	709	166	61	40	97%	4.9	21.8%	8.8%	12.9%	5.2%	7.18	5.25	+0.3
2019	26	MIX RAW	2 levels	32	31	155	709	166	61	40	97%	4.9	23.4%	8.6%	14.8%	5.6%	7.18	5.49	-0.2
2020	27	MLB MLE	Colorado Rockies	16	0	21	104	20	8	3	0%	1.3	19.2%	7.7%	11.5%	2.6%	9.28	3.85	+0.2
2020	27	MLB RAW	Colorado Rockies	16	0	21	104	20	8	3	0%	1.3	19.2%	7.7%	11.5%	2.9%	9.28	4.18	+0.1
2021	28	MIX MLE	3 levels	36	16	91	411	104	48	17	44%	2.5	24.4%	11.9%	12.5%	3.3%	4.34	4.37	+0.2
2021	28	MIX RAW	3 levels	36	16	91	411	104	48	17	44%	2.5	25.3%	11.7%	13.6%	4.1%	4.34	4.82	-0.3
2022	29	MLB MLE	Cincinnati Reds	35	1	45	197	45	22	5	3%	1.3	22.8%	11.2%	11.7%	2.4%	3.83	3.88	+0.4
2022	29	MLB RAW	Cincinnati Reds	35	1	45	197	45	22	5	3%	1.3	22.8%	11.2%	11.7%	2.5%	3.83	4.02	+0.3
2023	30	MIX MLE	2 levels	63	0	61	247	85	25	4	0%	1.0	33.2%	8.7%	24.5%	1.3%	3.08	2.13	+1.8
2023	30	MIX RAW	2 levels	63	0	61	247	85	25	4	0%	1.0	34.4%	10.1%	24.3%	1.6%	3.08	2.40	+1.6
2024	31	MLB MLE	Philadelphia Phillies	68	0	66	265	89	15	6	0%	1.0	33.6%	5.7%	27.9%	2.1%	2.17	2.14	+1.9
2024	31	MLB MLE	Philadelphia Phillies	68	0	66	265	89	15	6	0%	1.0	33.6%	5.7%	27.9%	2.1%	2.17	2.14	+1.9
2024	31	MLB RAW	Philadelphia Phillies	68	0	66	265	89	15	6	0%	1.0	33.6%	5.7%	27.9%	2.3%	2.17	2.27	+1.8
2025	32	MLB MLE	Toronto Blue Jays	71	0	68	287	84	26	15	0%	1.0	29.3%	9.1%	20.2%	5.2%	4.37	4.64	-0.1
2025	32	MLB MLE	Toronto Blue Jays	71	0	68	287	84	26	15	0%	1.0	29.3%	9.1%	20.2%	5.2%	4.37	4.64	-0.1
2025	32	MLB RAW	Toronto Blue Jays	71	0	68	287	84	26	15	0%	1.0	29.3%	9.1%	20.2%	5.2%	4.37	4.64	-0.1
2026	33	MLB MLE	Minnesota Twins	71	0	66	292	102	25	4	0%	0.9	34.9%	8.6%	26.4%	1.4%	3.55	1.98	+2.0
2026	33	MLB MLE	Minnesota Twins	71	0	66	292	102	25	4	0%	0.9	34.9%	8.6%	26.4%	1.4%	3.55	1.98	+2.0
2026	33	MLB RAW	Minnesota Twins	71	0	66	292	102	25	4	0%	0.9	34.9%	8.6%	26.4%	1.4%	3.55	1.93	+2.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			398	50	601	2634	665	249	91	13%	1.5	25.2%	9.5%	15.8%	3.5%	4.63	4.10	+3.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	MIN	56	0	59	249	83	21	7	0%	1.1	33.5%	8.6%	24.9%	2.8%	3.38	3.27	+1.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	MIN	50	0	52	220	72	20	7	0%	1.0	32.5%	9.1%	23.4%	3.1%	3.52	3.61	+0.6
2029	36	MLB MLE	MIN	40	0	42	177	56	17	6	0%	1.0	31.5%	9.7%	21.8%	3.5%	3.79	3.97	+0.3
2030	37	MLB MLE	MIN	29	0	30	127	39	13	5	0%	1.0	30.4%	10.4%	20.0%	3.9%	4.14	4.37	+0.1
2028	35	MLB CTX	MIN	50	0	52	220	71	20	7	0%	1.0	32.5%	9.1%	23.4%	3.1%	3.53	3.62	+0.6
2029	36	MLB CTX	MIN	40	0	42	177	56	17	6	0%	1.1	31.5%	9.7%	21.8%	3.5%	3.80	3.98	+0.3
2030	37	MLB CTX	MIN	29	0	30	127	39	13	5	0%	1.0	30.4%	10.4%	20.0%	3.9%	4.15	4.38	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		516	50	725	3158	831	299	109	10%	1.4	26.3%	9.5%	16.8%	3.5%	4.48	3.98	+4.9
/ 200 IP	—	RAW		142	14	200	871	229	82	30	10%	1.4	26.3%	9.5%	16.8%	3.5%	4.48	3.98	+1.4
Career	—	MLE		503	145	1095	4754	1091	435	136	29%	2.2	23.0%	9.2%	13.8%	2.9%	4.69	3.89	+4.1
/ 200 IP	—	MLE		92	26	200	869	199	79	25	29%	2.2	23.0%	9.2%	13.8%	2.9%	4.69	3.89	+1.1

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.

2023 AAALehigh Valley IronPigs · 9 IPFIP 3.32 → 3.67 (+0.36)K% 41.0% → 35.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.03%	—	×0.860	35.28%
BB% (unintentional) /BF	17.95%	—	×0.900	16.15%
HR / BF /BF	2.56%	÷1.028	×1.100	2.74%

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 106).

Result: FIP 3.32 → 3.67, 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).

2021 AAALouisville Bats · 15 IPFIP 2.96 → 3.36 (+0.39)K% 32.8% → 28.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.79%	—	×0.880	28.85%
BB% (unintentional) /BF	6.56%	—	×1.050	6.89%
HR / BF /BF	3.28%	÷1.088	×1.100	3.32%

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 118).

Result: FIP 2.96 → 3.36, 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 AAAAlbuquerque Isotopes · 85 IPFIP 4.61 → 4.83 (+0.22)K% 24.9% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.87%	—	×0.880	21.89%
BB% (unintentional) /BF	7.61%	—	×1.050	7.99%
HR / BF /BF	4.82%	÷1.136	×1.100	4.67%

Result: FIP 4.61 → 4.83, 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).

2018 AAAAlbuquerque Isotopes · 106 IPFIP 3.61 → 3.84 (+0.24)K% 22.6% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.62%	—	×0.880	19.90%
BB% (unintentional) /BF	10.42%	—	×1.050	10.94%
HR / BF /BF	2.00%	÷1.162	×1.100	1.89%

Result: FIP 3.61 → 3.84, 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 AAAAlbuquerque Isotopes · 50 IPFIP 3.14 → 3.35 (+0.21)K% 21.5% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.46%	—	×0.880	18.89%
BB% (unintentional) /BF	8.68%	—	×1.050	9.11%
HR / BF /BF	1.37%	÷1.202	×1.100	1.25%

Result: FIP 3.14 → 3.35, 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 AAAAlbuquerque Isotopes · 119 IPFIP 3.32 → 3.52 (+0.20)K% 24.2% → 21.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.22%	—	×0.880	21.31%
BB% (unintentional) /BF	8.59%	—	×1.050	9.02%
HR / BF /BF	2.15%	÷1.202	×1.100	1.97%

Result: FIP 3.32 → 3.52, 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+Dunedin Blue Jays · 56 IPFIP 3.49 → 4.12 (+0.63)K% 16.7% → 12.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.74%	—	×0.770	12.89%
BB% (unintentional) /BF	6.61%	—	×1.150	7.60%
HR / BF /BF	1.76%	÷1.059	×1.250	2.08%

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 112).

Result: FIP 3.49 → 4.12, 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).

2015 AANew Britain Rock Cats · 48 IPFIP 3.06 → 3.50 (+0.44)K% 19.7% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.68%	—	×0.810	15.94%
BB% (unintentional) /BF	5.85%	—	×1.100	6.44%
HR / BF /BF	1.60%	÷1.133	×1.200	1.69%

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 127).

Result: FIP 3.06 → 3.50, 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).

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
Jeff Hoffman (OGILVIE)	—	—	—	—	—	2.8%	—	3.92	31.7%	22.0%	124	+0.65	—	—	—
Kazuhiro Sasaki R 2002 · 2.76 FIP	34	SU	2.76	29.3%	6.4%	2.4%	.247	3.30	19.3%	10.6%	33	+0.54	2.76	223	68
Fernando Cruz R 2024 · 2.94 FIP	34	SU	2.94	37.8%	11.5%	2.9%	.328	3.39	32.1%	19.6%	103	+0.45	2.50	371	61
Fernando Rodriguez Jr. R 2018 · 4.07 FIP	34	SW	4.07	23.7%	9.9%	3.1%	.253	5.11	25.0%	13.8%	32	+1.04	3.34	335	57
Kiko Calero R 2009 · 2.27 FIP	34	SU	2.27	28.9%	10.9%	0.4%	.245	—	—	—	—	—	2.27	298	56
Jay Jackson R 2022 · 2.98 FIP	34	SU	2.98	27.5%	5.3%	2.8%	.327	4.83	26.2%	20.2%	85	+1.85	2.36	261	55
Jumbo Diaz R 2018 · 2.80 FIP	34	SU	2.80	23.2%	10.4%	0.6%	.296	2.98	25.0%	17.3%	56	+0.18	2.80	319	53
Tony Barnette R 2018 · 2.61 FIP	34	SU	2.61	25.0%	4.8%	1.8%	.239	—	—	—	—	—	2.61	144	52
Ryan Brasier R 2022 · 3.55 FIP	34	SU	3.55	24.3%	4.6%	3.5%	.331	2.95	22.3%	16.1%	114	-0.60	2.31	426	52
Huascar Brazobán R 2024 · 3.08 FIP	34	SU	3.08	23.5%	11.5%	0.9%	.259	3.71	21.3%	11.7%	144	+0.63	3.08	370	51
Akinori Otsuka R 2006 · 2.70 FIP	34	SU	2.70	20.3%	4.7%	1.3%	.292	2.39	17.6%	11.5%	32	-0.31	2.39	232	49
Joel Peralta R 2010 · 2.70 FIP	34	SU	2.70	25.9%	2.6%	2.6%	.192	3.40	27.0%	19.3%	206	+0.70	2.70	648	48
Preston Guilmet R 2021 · 4.17 FIP	34	SU	4.17	28.6%	6.6%	4.8%	.246	—	—	—	—	—	2.31	288	48
Brendan Donnelly R 2005 · 4.02 FIP	34	SU	4.02	19.6%	5.9%	3.3%	.264	4.02	17.6%	8.5%	98	-0.00	2.23	385	46
Neil Wagner R 2017 · 3.11 FIP	33	SU	3.11	20.7%	8.6%	1.2%	.257	—	—	—	—	—	3.11	135	46
Greg Burke R 2015 · 3.61 FIP	32	SU	3.61	22.1%	7.3%	2.7%	.241	—	—	—	—	—	3.61	139	45
Zack Segovia R 2016 · 3.33 FIP	33	SU	3.33	20.2%	5.9%	2.2%	.312	4.55	17.6%	4.0%	57	+1.22	3.33	144	45
Fernando Nieve R 2016 · 2.69 FIP	34	SU	2.69	24.7%	4.8%	1.9%	.333	1.96	30.7%	27.4%	32	-0.73	1.96	287	45
Dustin Molleken R 2017 · 3.38 FIP	32	SU	3.38	24.3%	12.4%	1.4%	.311	—	—	—	—	—	3.38	129	45
Anthony Telford R 2000 · 3.87 FIP	34	SU	3.87	20.6%	6.7%	3.0%	.287	4.54	16.2%	5.1%	24	+0.67	3.16	441	44
Jean Machi R 2016 · 4.36 FIP	34	SU	4.36	18.3%	6.6%	3.6%	.282	4.12	18.6%	12.0%	67	-0.24	2.16	306	44

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	3.9	56	26.9%	9.9%	1.32	4.40
Ed Nunez ('82-'94, 2 WAR*)	3.3	54	24.5%*	9.5%*	1.24*	4.37*
Tim Stoddard ('75-'89, 4 WAR*)	3.6	66	26.2%*	11.2%*	1.14*	4.24*
Doug Bair ('76-'90, 7 WAR*)	4.5	76	25.2%*	10.4%*	1.22*	4.12*
Kyle Farnsworth ('14)	4.9	62	22.5%	9.6%	1.20	4.26
David Hernandez ('19)	3.2	65	23.9%	9.1%	1.22	4.12
Russ Springer ('10)	4.3	66	20.9%	9.4%	1.27	4.52