Porter Hodge

P Chicago Cubs

Age 26 RHP 6'4" / 230 lbs MLB peak 0.1 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	22	AATennessee Smo…	35	12	81	5.13	2.78	28.5%	13.0%	—	K 23.1% · BB 14.3% · FIP 3.47
2024	23	MIX3 levels	54	0	63	2.73	2.70	31.5%	12.6%	1.4	K 28.8% · BB 12.4% · FIP 2.95
2025	24	MIX2 levels	51	0	49	6.39	5.01	29.5%	14.3%	-0.3	K 27.8% · BB 13.6% · FIP 5.00
2026	25	No MLB games played
2027PROJ	26	MLBCHC	28	0	29	4.19	4.37	28.9%	12.5%	0.1
2028PROJ88% MLB	27	MLBCHC	36	0	38	4.32	4.40	28.4%	12.2%	0.1
2029PROJ91% MLB	28	MLBCHC	30	0	32	4.42	4.48	27.9%	12.2%	0.0

Last 3 seasons WAR 1.1 · Next 3 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

K%77

FB Velo71

xwOBA vs45

CompsPeyton Gray (age 26) · Kiko Calero (age 28) · Dylan King (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 116108vR 100

ERA4.19

FIP4.37

K%28.9%

BB%12.5%

K-BB%16.4%

Proj IP35

Value2027 · WAR

Runs saved vs league avg · 35 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL3535

CMD5555

K†6565

Statcast Percentiles

FB Velo

p7196.0

Whiff%

p5926.7%

p7727.2%

xwOBA vs

p450.317

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)
2019	18	ROK MLE	AZL Cubs 1	5	4	8	43	4	8	0	80%	1.6	9.3%	18.6%	-9.3%	0.0%	10.12	4.67	—
2019	18	ROK RAW	AZL Cubs 1	5	4	8	43	4	8	0	80%	1.6	9.3%	18.6%	-9.3%	0.0%	10.12	5.10	—
2021	20	MIX MLE	2 levels	14	10	51	235	64	17	5	71%	3.6	19.3%	8.8%	10.5%	2.9%	5.86	4.20	—
2021	20	MIX RAW	2 levels	14	10	51	235	64	17	5	71%	3.6	27.2%	7.2%	20.0%	2.1%	5.86	2.86	—
2022	21	MIX MLE	2 levels	25	24	109	466	141	55	4	96%	4.4	22.7%	13.8%	8.9%	1.2%	2.63	3.57	—
2022	21	MIX RAW	2 levels	25	24	109	466	141	55	4	96%	4.4	30.3%	11.8%	18.5%	0.9%	2.63	2.51	—
2023	22	AA MLE	Tennessee Smokies	35	12	81	361	103	47	3	34%	2.3	23.1%	14.3%	8.8%	0.9%	5.13	3.47	—
2023	22	AA RAW	Tennessee Smokies	35	12	81	361	103	47	3	34%	2.3	28.5%	13.0%	15.5%	0.8%	5.13	2.78	—
2024	23	MIX MLE	3 levels	54	0	63	254	80	32	3	0%	1.2	28.8%	12.4%	16.4%	1.3%	2.73	2.95	+1.2
2024	23	MIX MLE	3 levels	54	0	63	254	80	32	3	0%	1.2	28.8%	12.4%	16.4%	1.3%	2.73	2.95	+1.2
2024	23	MIX RAW	3 levels	54	0	63	254	80	32	3	0%	1.2	31.5%	12.6%	18.9%	1.2%	2.73	2.70	+1.4
2025	24	MIX MLE	2 levels	51	0	49	224	66	32	10	0%	1.0	27.8%	13.6%	14.2%	4.6%	6.39	5.00	-0.3
2025	24	MIX MLE	2 levels	51	0	49	224	66	32	10	0%	1.0	27.8%	13.6%	14.2%	4.6%	6.39	5.00	-0.3
2025	24	MIX RAW	2 levels	51	0	49	224	66	32	10	0%	1.0	29.5%	14.3%	15.2%	4.5%	6.39	5.01	-0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			75	0	76	311	92	36	11	0%	1.0	29.6%	11.6%	18.0%	3.5%	3.79	3.98	+0.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	CHC	28	0	29	122	35	15	4	0%	1.0	28.9%	12.5%	16.4%	3.2%	4.19	4.37	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	CHC	41	0	44	184	52	22	6	0%	1.1	28.4%	12.2%	16.1%	3.2%	4.32	4.40	+0.1
2029	28	MLB MLE	CHC	34	0	35	149	41	18	5	0%	1.0	27.9%	12.2%	15.7%	3.3%	4.42	4.48	+0.0
2028	27	MLB CTX	CHC	36	0	38	160	46	20	5	0%	1.1	28.4%	12.2%	16.1%	3.2%	4.32	4.40	+0.1
2029	28	MLB CTX	CHC	30	0	32	135	38	16	4	0%	1.1	27.9%	12.2%	15.7%	3.3%	4.42	4.48	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		142	0	146	607	175	72	21	0%	1.0	28.9%	11.9%	17.0%	3.4%	4.07	4.03	+0.9
/ 200 IP	—	RAW		194	0	200	831	240	99	29	0%	1.0	28.9%	11.9%	17.0%	3.4%	4.07	4.03	+1.2
Career	—	MLE		184	50	361	1583	374	207	29	27%	2.0	23.6%	13.1%	10.6%	1.8%	4.34	3.77	+0.6
/ 200 IP	—	MLE		102	28	200	878	207	115	16	27%	2.0	23.6%	13.1%	10.6%	1.8%	4.34	3.77	+0.8

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.

2025 AAAIowa Cubs · 16 IPFIP 3.43 → 3.57 (+0.14)K% 33.8% → 29.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.77%	—	×0.860	29.04%
BB% (unintentional) /BF	19.48%	—	×0.900	17.53%
HR / BF /BF	1.30%	÷1.125	×1.100	1.27%

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 125).

Result: FIP 3.43 → 3.57, 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 AAAIowa Cubs · 16 IPFIP 3.60 → 3.73 (+0.13)K% 26.3% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.32%	—	×0.860	22.63%
BB% (unintentional) /BF	15.79%	—	×0.900	14.21%
HR / BF /BF	1.32%	÷1.079	×1.100	1.34%

Result: FIP 3.60 → 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).

2023 AATennessee Smokies · 81 IPFIP 2.80 → 3.47 (+0.67)K% 28.5% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.53%	—	×0.810	23.11%
BB% (unintentional) /BF	13.02%	—	×1.100	14.32%
HR / BF /BF	0.83%	÷1.082	×1.200	0.92%

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 116).

Result: FIP 2.80 → 3.47, 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 AMyrtle Beach Pelicans · 69 IPFIP 2.41 → 3.41 (+1.00)K% 29.3% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.32%	—	×0.740	21.69%
BB% (unintentional) /BF	12.70%	—	×1.180	14.99%
HR / BF /BF	0.33%	÷0.942	×1.300	0.45%

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 88).

Result: FIP 2.41 → 3.41, 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+South Bend Cubs · 40 IPFIP 2.70 → 3.86 (+1.16)K% 32.1% → 24.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.08%	—	×0.770	24.70%
BB% (unintentional) /BF	10.06%	—	×1.150	11.57%
HR / BF /BF	1.89%	÷0.938	×1.250	2.52%

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 88).

Result: FIP 2.70 → 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).

2021 ROKACL Cubs · 29 IPFIP 3.76 → 5.37 (+1.61)K% 24.8% → 16.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.82%	—	×0.680	16.88%
BB% (unintentional) /BF	6.38%	—	×1.250	7.98%
HR / BF /BF	3.55%	÷1.014	×1.400	4.90%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 103).

Result: FIP 3.76 → 5.37, 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 AMyrtle Beach Pelicans · 22 IPFIP 1.57 → 2.44 (+0.87)K% 30.9% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.85%	—	×0.740	22.83%
BB% (unintentional) /BF	8.51%	—	×1.180	10.04%
HR / BF /BF	0.00%	÷0.977	×1.300	0.00%

Result: FIP 1.57 → 2.44, 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 ROKAZL Cubs 1 · 8 IPFIP 4.67 → 5.51 (+0.84)K% 9.3% → 6.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	9.30%	—	×0.680	6.33%
BB% (unintentional) /BF	18.60%	—	×1.250	23.26%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Result: FIP 4.67 → 5.51, 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
Porter Hodge (OGILVIE)	—	—	4.37	28.9%	12.5%	3.2%	—	4.44	28.1%	15.9%	79	+0.07	—	—	—
Peyton Gray R 2021 · 4.27 FIP	26	SU	4.27	29.2%	14.1%	3.4%	.307	—	—	—	—	—	3.62	160	75
Kiko Calero R 2003 · 3.54 FIP	28	SU	3.54	31.5%	11.1%	3.1%	.273	3.11	26.1%	18.9%	159	-0.43	2.27	298	74
Dylan King R 2022 · 3.78 FIP	25	SW	3.78	26.7%	9.8%	3.1%	.266	—	—	—	—	—	3.78	121	73
Michael Flynn R 2023 · 4.31 FIP	26	SU	4.31	26.5%	11.2%	3.7%	.299	4.36	21.4%	10.8%	92	+0.05	3.89	168	72
Zach Franklin R 2024 · 3.24 FIP	25	SU	3.24	26.4%	10.9%	1.8%	.301	4.15	27.5%	18.3%	117	+0.91	3.24	158	72
Michael Dimock R 2016 · 3.91 FIP	26	SU	3.91	26.8%	9.8%	3.3%	.289	3.79	20.9%	11.9%	66	-0.12	3.08	166	72
Jeff Ames R 2017 · 3.94 FIP	26	SU	3.94	25.1%	13.4%	2.3%	.310	4.65	25.4%	10.8%	79	+0.71	3.85	272	71
Lucas Wepf R 2024 · 3.80 FIP	24	SU	3.80	27.4%	10.9%	3.0%	.304	4.09	25.4%	11.8%	80	+0.29	2.90	195	71
Eric Orze R 2024 · 3.88 FIP	26	SU	3.88	28.1%	10.9%	3.2%	.261	3.43	22.3%	13.6%	135	-0.45	3.33	354	71
Trent Harris R 2024 · 3.45 FIP	25	SU	3.45	26.9%	9.5%	2.6%	.258	3.36	24.7%	16.7%	121	-0.09	3.06	198	70
Jesus Pirela R 2015 · 3.84 FIP	26	SU	3.84	23.7%	11.6%	2.3%	.305	3.92	17.1%	13.9%	45	+0.08	3.24	161	70
Fernando Rodriguez Jr. R 2011 · 3.85 FIP	27	SU	3.85	24.7%	10.8%	2.7%	.315	3.90	25.2%	16.5%	70	+0.05	3.34	335	70
Jon Edwards R 2015 · 3.40 FIP	27	SU	3.40	31.7%	13.1%	2.4%	.264	2.40	30.3%	22.6%	30	-1.00	2.40	132	70
Madison Younginer IV R 2017 · 4.22 FIP	26	SU	4.22	23.0%	9.8%	3.3%	.370	4.73	14.0%	-5.3%	27	+0.51	3.08	219	70
Ronald Peña R 2018 · 4.19 FIP	26	SU	4.19	23.4%	11.6%	2.9%	.273	4.52	18.7%	7.1%	88	+0.33	3.72	187	70
Tyler Kinley R 2017 · 3.74 FIP	26	SU	3.74	25.0%	10.3%	2.6%	.295	3.82	25.0%	11.7%	140	+0.08	1.58	602	70
Scott Dohmann R 2004 · 4.44 FIP	26	SU	4.44	24.7%	9.6%	4.0%	.270	4.80	20.6%	8.5%	112	+0.36	4.28	173	69
Joshua Loeschorn R 2023 · 3.86 FIP	23	SU	3.86	24.5%	7.7%	3.4%	.272	4.43	17.1%	8.4%	83	+0.57	3.08	151	69
Simon Castro R 2015 · 3.28 FIP	27	SU	3.28	26.4%	8.5%	2.4%	.320	3.58	26.0%	17.6%	128	+0.30	3.01	185	69
Jason Bulger R 2008 · 4.60 FIP	29	SU	4.60	27.4%	12.3%	4.1%	.293	3.94	25.1%	13.3%	90	-0.66	3.78	106	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	1.0	39	28.8%	12.1%	1.30	4.10
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*
Colin Poche ('25)	1.1	54	26.7%	10.2%	1.32	4.01
Antonio Bastardo ('17)	2.0	56	28.0%	11.4%	1.01	4.01
Chasen Shreve ('24)	1.8	45	25.2%	10.8%	1.54	3.96
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Rod Scurry ('80-'88, 5 WAR*)	2.3	58	29.6%*	13.6%*	0.91*	3.67*