Lou Trivino

P Lehigh Valley IronPigs

Age 35 RHP 6'5" / 232 lbs AAA peak 0.3 · 2027

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	32	MIX2 levels	11	0	11	4.91	3.92	22.9%	12.5%	—	K 22.9% · BB 12.5% · FIP 3.89
2025	33	MIX2 levels	54	2	56	3.40	3.98	19.3%	8.8%	0.4	K 17.9% · BB 8.2% · FIP 4.11
2026	34	MIX2 levels	42	0	50	4.11	3.06	26.5%	9.7%	0.9	K 24.0% · BB 7.1% · FIP 2.93
2027PROJ	35	MLBPHI	52	0	55	4.16	4.12	22.0%	8.0%	0.3
2028PROJ91% MLB	36	MLBPHI	27	0	28	4.36	4.49	21.0%	8.6%	0.0
2029PROJ82% MLB	37	MLBPHI	11	0	12	4.68	4.89	19.9%	9.2%	-0.0

Last 3 seasons WAR 1.3 · Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo54

K%21

xwOBA vs21

CompsJumbo Diaz (age 35) · Toby Borland (age 35) · Neil Wagner (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 117109vR 101

ERA4.16

FIP4.12

K%22.0%

BB%8.0%

K-BB%14.1%

Proj IP55

Value2027 · WAR

Runs saved vs league avg · 55 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL5050

CMD4040

K†5555

Statcast Percentiles

FB Velo

p5494.8

Whiff%

p4925.1%

p2117.9%

xwOBA vs

p210.346

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	23	A+ MLE	Stockton Ports	32	9	90	377	78	43	5	28%	2.8	15.9%	13.1%	2.8%	1.0%	3.91	3.95	—
2015	23	A+ RAW	Stockton Ports	32	9	90	377	78	43	5	28%	2.8	20.7%	11.4%	9.3%	1.3%	3.91	3.52	—
2016	24	MIX MLE	2 levels	45	0	60	259	61	22	1	0%	1.3	18.3%	9.7%	8.6%	0.5%	2.85	3.03	—
2016	24	MIX RAW	2 levels	45	0	60	259	61	22	1	0%	1.3	23.6%	8.5%	15.1%	0.4%	2.85	2.38	—
2017	25	MIX MLE	2 levels	48	0	68	288	65	19	0	0%	1.4	19.0%	7.1%	11.9%	0.0%	3.03	2.39	—
2017	25	MIX RAW	2 levels	48	0	68	288	65	19	0	0%	1.4	22.6%	6.6%	16.0%	0.0%	3.03	2.03	—
2018	26	MIX MLE	2 levels	73	1	79	318	92	28	8	1%	1.1	27.4%	9.0%	18.4%	2.9%	2.84	3.54	+1.0
2018	26	MIX RAW	2 levels	73	1	79	318	92	28	8	1%	1.1	28.9%	8.8%	20.1%	2.5%	2.84	3.15	+1.3
2019	27	MLB MLE	Oakland Athletics	61	0	60	269	57	29	7	0%	1.0	21.2%	10.8%	10.4%	2.9%	5.25	4.25	+0.2
2019	27	MLB RAW	Oakland Athletics	61	0	60	269	57	29	7	0%	1.0	21.2%	10.8%	10.4%	2.6%	5.25	4.17	+0.3
2020	28	MLB MLE	Oakland Athletics	20	0	23	93	26	10	3	0%	1.2	28.0%	10.8%	17.2%	3.5%	3.86	4.05	+0.1
2020	28	MLB RAW	Oakland Athletics	20	0	23	93	26	10	3	0%	1.2	28.0%	10.8%	17.2%	3.2%	3.86	3.83	+0.2
2021	29	MLB MLE	Oakland Athletics	71	0	74	310	67	32	5	0%	1.0	21.6%	10.3%	11.3%	1.8%	3.18	3.56	+0.9
2021	29	MLB RAW	Oakland Athletics	71	0	74	310	67	32	5	0%	1.0	21.6%	10.3%	11.3%	1.6%	3.18	3.47	+0.9
2022	30	MIX MLE	2 levels	65	1	55	258	69	22	7	2%	0.8	26.8%	8.8%	18.0%	2.2%	5.27	3.19	+0.9
2022	30	MIX RAW	2 levels	65	1	55	258	69	22	7	2%	0.8	26.7%	8.5%	18.2%	2.7%	5.27	3.45	+0.7
2024	32	MIX MLE	2 levels	11	0	11	48	11	6	1	0%	1.0	22.9%	12.5%	10.4%	2.1%	4.91	3.89	—
2024	32	MIX MLE	2 levels	11	0	11	48	11	6	1	0%	1.0	22.9%	12.5%	10.4%	2.1%	4.91	3.89	—
2024	32	MIX RAW	2 levels	11	0	11	48	11	6	1	0%	1.0	22.9%	12.5%	10.4%	2.1%	4.91	3.92	—
2025	33	MIX MLE	2 levels	54	2	56	238	46	21	6	4%	1.0	17.9%	8.2%	9.7%	2.7%	3.40	4.11	+0.3
2025	33	MIX MLE	2 levels	54	2	56	238	46	21	6	4%	1.0	17.9%	8.2%	9.7%	2.7%	3.40	4.11	+0.3
2025	33	MIX RAW	2 levels	54	2	56	238	46	21	6	4%	1.0	19.3%	8.8%	10.5%	2.5%	3.40	3.98	+0.4
2026	34	MIX MLE	2 levels	42	0	50	226	60	22	4	0%	1.2	24.0%	7.1%	16.9%	1.7%	4.11	2.93	+1.0
2026	34	MIX MLE	2 levels	42	0	50	226	60	22	4	0%	1.2	24.0%	7.1%	16.9%	1.7%	4.11	2.93	+1.0
2026	34	MIX RAW	2 levels	42	0	50	226	60	22	4	0%	1.2	26.5%	9.7%	16.8%	1.8%	4.11	3.06	+0.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			337	3	338	1464	343	144	36	1%	1.0	23.4%	9.8%	13.6%	2.5%	4.07	3.73	+3.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	35	MLB	PHI	52	0	55	232	51	19	6	0%	1.1	22.0%	8.0%	14.1%	2.7%	4.16	4.12	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	36	MLB MLE	PHI	29	0	30	128	27	11	4	0%	1.0	21.0%	8.6%	12.4%	3.1%	4.36	4.49	+0.0
2029	37	MLB MLE	PHI	14	0	15	64	13	6	2	0%	1.1	19.9%	9.2%	10.7%	3.5%	4.68	4.89	-0.1
2028	36	MLB CTX	PHI	27	0	28	118	25	10	4	0%	1.0	21.0%	8.6%	12.4%	3.1%	4.36	4.49	+0.0
2029	37	MLB CTX	PHI	11	0	12	51	10	5	2	0%	1.1	19.9%	9.2%	10.7%	3.5%	4.68	4.89	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		375	3	378	1633	378	159	41	1%	1.0	23.1%	9.7%	13.4%	2.5%	4.11	3.77	+3.5
/ 200 IP	—	RAW		198	2	200	863	200	84	22	1%	1.0	23.1%	9.7%	13.4%	2.5%	4.11	3.77	+1.8
Career	—	MLE		522	13	626	2684	576	259	48	2%	1.2	21.5%	9.6%	11.8%	1.8%	3.72	3.49	+3.2
/ 200 IP	—	MLE		167	4	200	858	184	83	15	2%	1.2	21.5%	9.6%	11.8%	1.8%	3.72	3.49	+1.7

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 AAALehigh Valley IronPigs · 44 IPFIP 2.61 → 2.93 (+0.32)K% 27.9% → 24.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.89%	—	×0.860	23.99%
BB% (unintentional) /BF	7.89%	—	×0.900	7.11%
HR / BF /BF	1.58%	÷1.000	×1.100	1.74%

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 100).

Result: FIP 2.61 → 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).

2025 AAALehigh Valley IronPigs · 8 IPFIP 2.28 → 2.46 (+0.18)K% 29.0% → 25.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.03%	—	×0.860	24.97%
BB% (unintentional) /BF	12.90%	—	×0.900	11.61%
HR / BF /BF	0.00%	÷0.947	×1.100	0.00%

Result: FIP 2.28 → 2.46, 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).

2024 AAAScranton/Wilkes-Barre RailRiders · 6 IPFIP 4.99 → 5.16 (+0.17)K% 20.7% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.69%	—	×0.860	17.79%
BB% (unintentional) /BF	13.79%	—	×0.900	12.41%
HR / BF /BF	3.45%	÷1.045	×1.100	3.63%

Result: FIP 4.99 → 5.16, 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 AAANashville Sounds · 35 IPFIP 2.11 → 2.36 (+0.25)K% 20.7% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.67%	—	×0.880	18.19%
BB% (unintentional) /BF	6.00%	—	×1.050	6.30%
HR / BF /BF	0.00%	÷0.868	×1.100	0.00%

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 74).

Result: FIP 2.11 → 2.36, 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).

2017 AAMidland RockHounds · 33 IPFIP 1.94 → 2.42 (+0.49)K% 24.6% → 20.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.64%	—	×0.810	19.96%
BB% (unintentional) /BF	7.25%	—	×1.100	7.97%
HR / BF /BF	0.00%	÷0.862	×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 72).

Result: FIP 1.94 → 2.42, 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 A+Stockton Ports · 42 IPFIP 2.02 → 2.71 (+0.69)K% 26.6% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.63%	—	×0.770	20.51%
BB% (unintentional) /BF	9.24%	—	×1.150	10.62%
HR / BF /BF	0.00%	÷1.066	×1.250	0.00%

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 113).

Result: FIP 2.02 → 2.71, 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).

2016 AAMidland RockHounds · 18 IPFIP 3.33 → 3.81 (+0.49)K% 16.0% → 13.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.00%	—	×0.810	12.96%
BB% (unintentional) /BF	6.67%	—	×1.100	7.33%
HR / BF /BF	1.33%	÷0.999	×1.200	1.60%

Result: FIP 3.33 → 3.81, 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+Stockton Ports · 90 IPFIP 3.53 → 3.95 (+0.42)K% 20.7% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.69%	—	×0.770	15.93%
BB% (unintentional) /BF	11.41%	—	×1.150	13.12%
HR / BF /BF	1.33%	÷1.715	×1.250	0.97%

Result: FIP 3.53 → 3.95, 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
Lou Trivino (OGILVIE)	—	—	4.12	22.0%	8.0%	2.7%	—	4.62	20.6%	11.9%	46	+0.50	—	—	—
Jumbo Diaz R 2019 · 2.98 FIP	35	SU	2.98	25.0%	7.7%	1.8%	.290	—	—	—	—	—	2.80	319	76
Toby Borland R 2004 · 4.28 FIP	35	SU	4.28	20.9%	8.1%	3.5%	.259	—	—	—	—	—	2.92	248	76
Neil Wagner R 2017 · 3.11 FIP	33	SU	3.11	20.7%	8.6%	1.2%	.257	—	—	—	—	—	3.11	135	76
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	74
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	74
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	74
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	73
Jean Machi R 2017 · 4.12 FIP	35	SU	4.12	18.6%	6.6%	3.2%	.285	—	—	—	—	—	2.16	306	73
Brendan Donnelly R 2006 · 4.21 FIP	35	SU	4.21	19.1%	9.0%	2.9%	.260	3.19	18.6%	10.1%	60	-1.02	2.23	385	73
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	72
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	71
Juan Sandoval R 2016 · 3.24 FIP	35	SU	3.24	18.2%	10.2%	0.7%	.288	4.40	16.3%	9.1%	116	+1.16	3.24	225	70
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	69
Brian Schlitter R 2021 · 4.70 FIP	35	SU	4.70	14.9%	9.1%	3.1%	.318	—	—	—	—	—	3.27	300	69
Rodolfo Aguirre R 2019 · 4.50 FIP	34	SU	4.50	21.3%	5.1%	4.7%	.244	—	—	—	—	—	3.39	212	68
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	68
Chris Nichting R 2001 · 4.11 FIP	35	SU	4.11	21.2%	3.7%	4.2%	.351	4.67	16.6%	13.3%	36	+0.56	4.11	103	64
Yoshihisa Hirano R 2019 · 3.72 FIP	35	SU	3.72	26.2%	8.6%	3.2%	.303	5.02	17.5%	4.8%	12	+1.30	3.45	132	64
Erubiel Gonzalez R 2015 · 3.43 FIP	36	SU	3.43	12.4%	6.0%	1.1%	.328	3.26	14.8%	10.4%	69	-0.17	2.99	119	64
Spencer Patton R 2023 · 4.33 FIP	35	SU	4.33	18.9%	9.7%	2.9%	.295	—	—	—	—	—	2.79	239	63

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	2.2	49	23.0%	10.1%	0.99	4.12
Al Reyes ('08)	2.1	54	23.2%	10.7%	1.11	3.84
Will Ohman ('12)	1.8	50	21.8%	10.3%	1.07	4.28
Cam Bedrosian ('21)	1.5	50	24.0%	10.2%	0.92	3.81
Tony Fossas ('88-'99, 2 WAR*)	2.1	42	21.9%*	9.3%*	0.99*	3.88*
Ray Searage ('81-'90, 4 WAR*)	1.4	41	21.0%*	10.8%*	0.84*	3.70*
Ed Vosberg ('86-'02, 1 WAR*)	1.2	47	21.0%*	9.6%*	0.86*	4.06*