Trent Harris

P Sacramento River Cats

Age 28 RHP 6'1" / 206 lbs AAA peak 0.5 · 2027

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX3 levels	36	0	80	1.81	2.38	34.5%	8.2%	—	K 26.9% · BB 9.5% · FIP 3.45
2025	26	MIX2 levels	43	0	57	4.40	3.19	27.1%	7.9%	—	K 22.8% · BB 7.5% · FIP 3.70
2026	27	MIX2 levels	51	3	64	2.83	2.82	29.2%	9.2%	1.3	K 26.5% · BB 8.6% · FIP 3.06
2027PROJ	28	MLBSF	44	0	46	3.80	3.77	26.2%	8.3%	0.4
2028PROJ77% MLB	29	MLBSF	41	0	43	3.93	3.98	25.3%	8.6%	0.3
2029PROJ81% MLB	30	MLBSF	37	0	39	4.11	4.21	24.5%	9.0%	0.2

Last 3 seasons WAR 1.3 · Next 3 projected WAR 0.9Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs90

K%85

FB Velo41

Form2.31 ERA (proj 3.80) · K 28.7% (proj 26.2%) · BB 7.4% (proj 8.3%) ▲ last 90d · 23 IP through Oct 27

Career WAR0.0 WAR median (P10 -0.3 / P90 1.3, comp-based) · star 0% · didn't stick 90%

CompsMatt Ramsey (age 28) · Ryan Brasier (age 28) · Scott Atchison (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10597vR 89

ERA3.80

FIP3.77

K%26.2%

BB%8.3%

K-BB%17.9%

Proj IP65

Value2027 · WAR

Runs saved vs league avg · 65 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p4193.9

Whiff%

p3723.4%

p8528.7%

xwOBA vs

p900.241

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)
2023	24	MIX MLE	2 levels	15	0	21	81	33	3	0	0%	1.4	40.7%	3.7%	37.0%	0.0%	0.43	0.13	—
2023	24	MIX RAW	2 levels	15	0	21	81	33	3	0	0%	1.4	40.7%	3.7%	37.0%	0.0%	0.43	0.39	—
2024	25	MIX MLE	3 levels	36	0	80	304	105	25	6	0%	2.2	26.9%	9.5%	17.3%	2.6%	1.81	3.45	—
2024	25	MIX MLE	3 levels	36	0	80	304	105	25	6	0%	2.2	26.9%	9.5%	17.3%	2.6%	1.81	3.45	—
2024	25	MIX RAW	3 levels	36	0	80	304	105	25	6	0%	2.2	34.5%	8.2%	26.3%	2.0%	1.81	2.38	—
2025	26	MIX MLE	2 levels	43	0	57	240	65	19	6	0%	1.3	22.8%	7.5%	15.3%	2.9%	4.40	3.70	—
2025	26	MIX MLE	2 levels	43	0	57	240	65	19	6	0%	1.3	22.8%	7.5%	15.3%	2.9%	4.40	3.70	—
2025	26	MIX RAW	2 levels	43	0	57	240	65	19	6	0%	1.3	27.1%	7.9%	19.2%	2.5%	4.40	3.19	—
2026	27	MIX MLE	2 levels	51	3	64	271	79	25	5	6%	1.2	26.5%	8.6%	17.9%	2.0%	2.83	3.06	+1.1
2026	27	MIX MLE	2 levels	51	3	64	271	79	25	5	6%	1.2	26.5%	8.6%	17.9%	2.0%	2.83	3.06	+1.1
2026	27	MIX RAW	2 levels	51	3	64	271	79	25	5	6%	1.2	29.2%	9.2%	19.9%	1.8%	2.83	2.82	+1.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			22	0	23	94	27	7	1	0%	1.1	28.7%	7.4%	21.3%	1.1%	2.31	2.24	+0.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	SF	44	0	46	194	51	16	5	0%	1.0	26.2%	8.3%	17.9%	2.6%	3.80	3.77	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	SF	53	0	56	236	60	20	7	0%	1.1	25.3%	8.6%	16.7%	2.8%	3.93	3.98	+0.4
2029	30	MLB MLE	SF	46	0	48	205	50	18	6	0%	1.1	24.5%	9.0%	15.5%	3.0%	4.11	4.21	+0.2
2028	29	MLB CTX	SF	41	0	43	182	46	16	5	0%	1.0	25.3%	8.6%	16.7%	2.8%	3.93	3.98	+0.3
2029	30	MLB CTX	SF	37	0	39	165	40	15	5	0%	1.1	24.5%	9.0%	15.5%	3.0%	4.11	4.21	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		100	0	105	440	113	37	11	0%	1.1	25.7%	8.5%	17.2%	2.5%	3.64	3.39	+1.5
/ 200 IP	—	RAW		190	0	200	836	215	70	21	0%	1.1	25.7%	8.5%	17.2%	2.5%	3.64	3.39	+2.8
Career	—	MLE		145	3	222	896	241	73	20	2%	1.5	26.9%	8.2%	18.7%	2.3%	2.64	3.10	+1.2
/ 200 IP	—	MLE		131	3	200	808	218	66	18	2%	1.5	26.9%	8.2%	18.7%	2.3%	2.64	3.10	+1.9

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 AAASacramento River Cats · 40 IPFIP 3.15 → 3.49 (+0.34)K% 29.4% → 25.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.38%	—	×0.860	25.27%
BB% (unintentional) /BF	10.17%	—	×0.900	9.15%
HR / BF /BF	2.26%	÷1.000	×1.100	2.49%

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 3.15 → 3.49, 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 AAASacramento River Cats · 41 IPFIP 3.82 → 4.25 (+0.43)K% 22.7% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.73%	—	×0.860	19.55%
BB% (unintentional) /BF	8.52%	—	×0.900	7.67%
HR / BF /BF	2.84%	÷0.938	×1.100	3.33%

Result: FIP 3.82 → 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).

2025 AARichmond Flying Squirrels · 16 IPFIP 1.45 → 2.17 (+0.72)K% 39.1% → 31.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.06%	—	×0.810	31.64%
BB% (unintentional) /BF	6.25%	—	×1.100	6.88%
HR / BF /BF	1.56%	÷1.183	×1.200	1.59%

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 137).

Result: FIP 1.45 → 2.17, 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 A+Eugene Emeralds · 45 IPFIP 2.63 → 3.82 (+1.19)K% 34.9% → 26.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.88%	—	×0.770	26.86%
BB% (unintentional) /BF	6.98%	—	×1.150	8.02%
HR / BF /BF	2.91%	÷1.010	×1.250	3.60%

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 102).

Result: FIP 2.63 → 3.82, 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 ASan Jose Giants · 32 IPFIP 1.74 → 2.93 (+1.19)K% 36.4% → 26.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.36%	—	×0.740	26.91%
BB% (unintentional) /BF	9.92%	—	×1.180	11.70%
HR / BF /BF	0.83%	÷0.959	×1.300	1.12%

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 92).

Result: FIP 1.74 → 2.93, 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 ROKACL Giants Black · 12 IPFIP -0.40 → 0.87 (+1.27)K% 44.7% → 30.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	44.68%	—	×0.680	30.38%
BB% (unintentional) /BF	2.13%	—	×1.250	2.66%
HR / BF /BF	0.00%	÷1.031	×1.400	0.00%

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 106).

Result: FIP -0.40 → 0.87, 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 ASan Jose Giants · 9 IPFIP 0.86 → 1.77 (+0.91)K% 35.3% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.29%	—	×0.740	26.12%
BB% (unintentional) /BF	5.88%	—	×1.180	6.94%
HR / BF /BF	0.00%	÷0.890	×1.300	0.00%

Result: FIP 0.86 → 1.77, 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
Trent Harris (OGILVIE)	—	—	—	—	—	2.6%	—	4.09	24.9%	16.1%	104	+0.32	—	—	—
Matt Ramsey R 2018 · 3.78 FIP	28	SU	3.78	24.9%	8.8%	3.0%	.276	2.42	21.7%	12.6%	34	-1.36	2.42	125	89
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	86
Scott Atchison R 2004 · 3.61 FIP	28	SU	3.61	27.1%	9.0%	3.0%	.309	4.55	19.1%	11.5%	31	+0.94	2.52	340	85
Jason Motte R 2010 · 3.24 FIP	28	SU	3.24	26.0%	7.2%	2.6%	.269	2.69	27.3%	21.8%	140	-0.55	2.22	387	85
Marcos Mateo R 2011 · 3.40 FIP	27	SU	3.40	25.5%	10.2%	2.1%	.361	—	—	—	—	—	3.12	104	83
Michael Flynn R 2024 · 3.99 FIP	27	SU	3.99	27.6%	8.3%	3.9%	.277	4.68	16.2%	3.7%	50	+0.69	3.89	168	82
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	82
Dayan Díaz R 2017 · 3.45 FIP	28	SU	3.45	25.1%	8.7%	2.5%	.358	3.96	29.4%	19.3%	16	+0.51	3.08	205	82
Josh Lueke R 2013 · 4.09 FIP	28	SU	4.09	25.3%	11.1%	3.1%	.333	3.28	24.6%	20.9%	90	-0.81	2.29	191	81
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	81
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	81
Rafael Betancourt R 2003 · 3.81 FIP	28	SU	3.81	23.4%	7.1%	3.2%	.216	2.84	25.0%	20.8%	191	-0.97	1.79	686	81
Andrew Robinson R 2016 · 3.19 FIP	28	SU	3.19	22.2%	7.9%	1.8%	.247	4.32	23.4%	14.6%	39	+1.13	3.19	160	81
Simon Castro R 2016 · 3.01 FIP	28	SU	3.01	22.7%	5.6%	2.0%	.313	3.99	28.3%	18.0%	75	+0.98	3.01	185	81
Jason Stoffel R 2016 · 3.49 FIP	27	SU	3.49	27.2%	8.0%	3.0%	.293	—	—	—	—	—	3.49	103	81
Gerardo Sanchez R 2017 · 3.47 FIP	28	SU	3.47	21.6%	8.4%	2.1%	.355	3.58	20.5%	15.1%	56	+0.11	2.65	137	80
Sam Wolff R 2019 · 2.66 FIP	28	SU	2.66	24.8%	8.8%	1.0%	.289	3.23	26.0%	17.4%	22	+0.57	2.66	178	80
Matt Pushard R 2024 · 3.87 FIP	26	SU	3.87	24.1%	8.9%	3.0%	.242	3.29	22.2%	14.0%	115	-0.58	2.84	220	80
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	80
Leonel Campos R 2015 · 2.62 FIP	28	SU	2.62	30.1%	11.1%	1.2%	.259	3.63	25.2%	12.2%	118	+1.01	2.62	168	80

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	48	25.8%	8.5%	1.01	3.74
Josh Fields ('18)	1.4	46	27.5%	8.0%	0.98	3.71
Danny Farquhar ('18)	1.4	54	26.9%	9.2%	0.99	3.93
David Carpenter ('19)	1.1	43	23.5%	8.4%	0.92	3.69
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*