Andry Lara

P Rochester Red Wings

Age 24 RHP 6'4" / 180 lbs AAA

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	21	MIX2 levels	25	25	135	3.34	3.66	24.3%	8.1%	—	K 19.4% · BB 9.0% · FIP 4.57
2025	22	MIX4 levels	31	10	70	7.81	4.61	14.7%	11.2%	-0.0	K 12.5% · BB 10.7% · FIP 4.80
2026	23	AAAWSH	34	20	110	5.32	4.36	18.8%	8.7%	—	K 16.1% · BB 7.8% · FIP 4.59
2027PROJ	24	MLBWSH	3	3	16	4.92	5.12	14.5%	9.0%	0.1
2028PROJ48% MLB	25	MLBWSH	13	13	75	4.86	4.89	16.7%	8.7%	0.4
2029PROJ69% MLB	26	MLBWSH	18	18	107	4.78	4.76	18.0%	8.6%	0.8

Last 3 seasons WAR -0.0 · Next 3 projected WAR 1.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo45

K%10

xwOBA vs10

Career WAR0.0 WAR median (P10 -0.6 / P90 5.3, comp-based) · star 0% · didn't stick 85%

CompsBuck Farmer (age 24) · D.J. Houlton (age 25) · Preston Morrison (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 130122vR 114

ERA4.92

FIP5.12

K%14.5%

BB%9.0%

K-BB%5.5%

Proj IP155

Value2027 · WAR

Runs saved vs league avg · 155 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p4594.2

Whiff%

p1013.3%

p1012.8%

xwOBA vs

p100.394

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	18	MIX MLE	2 levels	11	9	48	205	52	21	7	82%	4.4	19.1%	9.7%	9.4%	4.1%	4.66	4.98	—
2021	18	MIX RAW	2 levels	11	9	48	205	52	21	7	82%	4.4	25.4%	10.2%	15.1%	3.4%	4.66	4.13	—
2022	19	A MLE	Fredericksburg Nationals	23	23	101	451	105	44	10	100%	4.4	17.2%	11.5%	5.7%	2.7%	5.51	4.58	—
2022	19	A RAW	Fredericksburg Nationals	23	23	101	451	105	44	10	100%	4.4	23.3%	9.8%	13.5%	2.2%	5.51	3.61	—
2023	20	A+ MLE	Wilmington Blue Rocks	23	23	98	416	66	34	11	100%	4.3	12.2%	9.4%	2.8%	3.6%	4.58	5.25	—
2023	20	A+ RAW	Wilmington Blue Rocks	23	23	98	416	66	34	11	100%	4.3	15.9%	8.2%	7.7%	2.6%	4.58	4.25	—
2024	21	MIX MLE	2 levels	25	25	135	543	132	44	16	100%	5.4	19.4%	9.0%	10.4%	3.6%	3.34	4.57	—
2024	21	MIX MLE	2 levels	25	25	135	543	132	44	16	100%	5.4	19.4%	9.0%	10.4%	3.6%	3.34	4.57	—
2024	21	MIX RAW	2 levels	25	25	135	543	132	44	16	100%	5.4	24.3%	8.1%	16.2%	2.9%	3.34	3.66	—
2025	22	MIX MLE	4 levels	31	10	70	348	51	39	7	32%	2.3	12.5%	10.7%	1.8%	2.5%	7.81	4.80	-0.2
2025	22	MIX MLE	4 levels	31	10	70	348	51	39	7	32%	2.3	12.5%	10.7%	1.8%	2.5%	7.81	4.80	-0.2
2025	22	MIX RAW	4 levels	31	10	70	348	51	39	7	32%	2.3	14.7%	11.2%	3.4%	2.0%	7.81	4.61	-0.0
2026	23	AAA MLE	Rochester Red Wings	34	20	110	485	91	42	15	59%	3.2	16.1%	7.8%	8.3%	3.4%	5.32	4.59	—
2026	23	AAA MLE	Rochester Red Wings	34	20	110	485	91	42	15	59%	3.2	16.1%	7.8%	8.3%	3.4%	5.32	4.59	—
2026	23	AAA RAW	Rochester Red Wings	34	20	110	485	91	42	15	59%	3.2	18.8%	8.7%	10.1%	3.1%	5.32	4.36	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			9	0	14	78	10	8	2	0%	1.6	12.8%	10.3%	2.6%	2.6%	8.79	5.19	-0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	24	MLB	WSH	3	3	16	68	10	6	2	100%	5.3	14.5%	9.0%	5.5%	3.1%	4.92	5.12	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	25	MLB MLE	WSH	26	26	155	653	109	57	20	100%	5.9	16.7%	8.7%	7.9%	3.1%	4.86	4.89	+0.9
2029	26	MLB MLE	WSH	26	26	155	653	117	56	20	100%	5.9	18.0%	8.6%	9.4%	3.1%	4.78	4.76	+1.1
2030	27	MLB MLE	WSH	19	19	112	471	85	41	15	100%	5.9	18.1%	8.6%	9.5%	3.1%	4.76	4.77	+0.8
2031	28	MLB MLE	WSH	18	18	108	458	83	40	15	100%	6.0	18.1%	8.8%	9.4%	3.2%	4.80	4.84	+0.7
2032	29	MLB MLE	WSH	17	17	100	421	74	38	14	100%	5.9	17.5%	9.0%	8.6%	3.4%	4.92	5.00	+0.5
2033	30	MLB MLE	WSH	15	15	90	381	64	35	14	100%	6.0	16.8%	9.3%	7.6%	3.6%	5.09	5.21	+0.2
2028	25	MLB CTX	WSH	13	13	75	317	53	28	10	100%	5.8	16.7%	8.7%	7.9%	3.1%	4.86	4.89	+0.4
2029	26	MLB CTX	WSH	18	18	107	452	81	39	14	100%	5.9	18.0%	8.6%	9.4%	3.1%	4.78	4.76	+0.8
2030	27	MLB CTX	WSH	15	15	88	372	67	32	12	100%	5.9	18.1%	8.6%	9.5%	3.1%	4.76	4.77	+0.6
2031	28	MLB CTX	WSH	15	15	92	388	70	34	13	100%	6.1	18.1%	8.8%	9.4%	3.2%	4.80	4.84	+0.6
2032	29	MLB CTX	WSH	15	15	88	372	65	33	13	100%	5.9	17.5%	9.0%	8.6%	3.4%	4.92	5.00	+0.4
2033	30	MLB CTX	WSH	14	14	82	346	58	32	12	100%	5.9	16.8%	9.3%	7.6%	3.6%	5.09	5.21	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		98	89	546	2324	405	206	75	91%	5.6	17.4%	8.9%	8.6%	3.2%	4.97	4.53	+5.5
/ 200 IP	—	RAW		36	33	200	851	148	75	27	91%	5.6	17.4%	8.9%	8.6%	3.2%	4.97	4.53	+2.0
Career	—	MLE		147	110	563	2448	395	235	80	75%	3.8	16.1%	9.6%	6.5%	3.3%	5.00	4.76	+4.3
/ 200 IP	—	MLE		52	39	200	870	140	83	29	75%	3.8	16.1%	9.6%	6.5%	3.3%	5.00	4.76	+1.2

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 AAARochester Red Wings · 110 IPFIP 4.31 → 4.59 (+0.28)K% 18.8% → 16.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.76%	—	×0.860	16.14%
BB% (unintentional) /BF	8.66%	—	×0.900	7.79%
HR / BF /BF	3.09%	÷1.000	×1.100	3.40%

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 4.31 → 4.59, 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 AAARochester Red Wings · 36 IPFIP 4.64 → 4.83 (+0.19)K% 14.4% → 12.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.36%	—	×0.860	12.35%
BB% (unintentional) /BF	12.15%	—	×0.900	10.94%
HR / BF /BF	2.21%	÷0.960	×1.100	2.53%

Result: FIP 4.64 → 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).

2025 A+Wilmington Blue Rocks · 11 IPFIP 2.38 → 2.96 (+0.57)K% 21.3% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.28%	—	×0.770	16.38%
BB% (unintentional) /BF	8.51%	—	×1.150	9.79%
HR / BF /BF	0.00%	÷0.967	×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 93).

Result: FIP 2.38 → 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 AAHarrisburg Senators · 8 IPFIP 4.91 → 5.57 (+0.66)K% 11.9% → 9.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	11.90%	—	×0.810	9.64%
BB% (unintentional) /BF	11.90%	—	×1.100	13.10%
HR / BF /BF	2.38%	÷0.963	×1.200	2.97%

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 93).

Result: FIP 4.91 → 5.57, 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 AAHarrisburg Senators · 104 IPFIP 4.11 → 4.96 (+0.85)K% 22.0% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.04%	—	×0.810	17.85%
BB% (unintentional) /BF	8.29%	—	×1.100	9.12%
HR / BF /BF	3.32%	÷0.990	×1.200	4.02%

Result: FIP 4.11 → 4.96, 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).

2024 A+Wilmington Blue Rocks · 31 IPFIP 2.23 → 3.20 (+0.98)K% 32.2% → 24.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.23%	—	×0.770	24.82%
BB% (unintentional) /BF	7.44%	—	×1.150	8.55%
HR / BF /BF	1.65%	÷1.016	×1.250	2.03%

Result: FIP 2.23 → 3.20, 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 A+Wilmington Blue Rocks · 98 IPFIP 4.25 → 5.25 (+1.00)K% 15.9% → 12.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.87%	—	×0.770	12.22%
BB% (unintentional) /BF	8.17%	—	×1.150	9.40%
HR / BF /BF	2.64%	÷0.913	×1.250	3.62%

Result: FIP 4.25 → 5.25, 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).

2022 AFredericksburg Nationals · 101 IPFIP 3.59 → 4.58 (+0.99)K% 23.3% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.28%	—	×0.740	17.23%
BB% (unintentional) /BF	9.76%	—	×1.180	11.51%
HR / BF /BF	2.22%	÷1.074	×1.300	2.68%

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 115).

Result: FIP 3.59 → 4.58, 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
Andry Lara (OGILVIE)	—	—	—	—	—	3.1%	—	4.81	17.5%	8.9%	421	-0.31	—	—	—
Buck Farmer R 2015 · 4.41 FIP	24	SP-	4.41	16.4%	7.4%	3.2%	.307	4.01	19.6%	10.9%	370	-0.40	3.16	907	84
D.J. Houlton R 2005 · 4.85 FIP	25	SP-	4.85	15.6%	8.5%	3.6%	.297	4.74	18.6%	12.4%	28	-0.11	4.74	157	83
Preston Morrison R 2017 · 4.97 FIP	24	SP-	4.97	13.4%	7.8%	3.7%	.300	4.94	17.1%	9.4%	58	-0.03	2.93	305	83
Shaun Anderson R 2019 · 4.24 FIP	24	SP-	4.24	18.0%	8.3%	2.9%	.317	4.59	19.5%	9.2%	150	+0.35	3.58	880	81
Kyle Lloyd R 2015 · 4.03 FIP	24	SP-	4.03	18.3%	8.1%	2.7%	.327	3.80	17.3%	8.9%	324	-0.23	3.50	572	81
Forrest Snow R 2015 · 5.03 FIP	26	SP-	5.03	16.1%	8.2%	4.1%	.263	4.14	21.8%	14.2%	256	-0.89	3.02	406	81
Grahamm Wiest R 2015 · 5.13 FIP	23	SP-	5.13	11.1%	7.8%	3.6%	.296	—	—	—	—	—	5.13	120	81
José Ureña R 2016 · 4.27 FIP	24	SP-	4.27	16.3%	7.8%	2.8%	.279	4.40	16.9%	10.0%	428	+0.13	3.86	1,251	80
Randy Bell R 2018 · 4.36 FIP	23	SP-	4.36	14.4%	6.6%	3.0%	.349	—	—	—	—	—	4.36	120	80
Sal Romano R 2018 · 4.46 FIP	24	SP-	4.46	16.3%	7.3%	3.3%	.281	3.82	19.5%	12.1%	141	-0.64	3.39	731	80
Frank Batista R 2015 · 4.29 FIP	26	SP-	4.29	12.1%	8.2%	2.1%	.280	—	—	—	—	—	4.29	118	80
Brooks Hall R 2015 · 4.12 FIP	25	SP-	4.12	14.3%	6.9%	2.5%	.291	4.00	14.0%	7.0%	153	-0.12	3.45	274	79
Brett Ash R 2015 · 4.16 FIP	24	SP-	4.16	10.5%	6.7%	2.0%	.329	4.64	8.5%	1.9%	212	+0.48	4.16	349	79
Mike Wright Jr. R 2015 · 4.07 FIP	25	SP	4.07	15.7%	7.9%	2.3%	.260	4.25	17.2%	9.8%	343	+0.18	3.76	725	79
Trenton Toplikar R 2019 · 4.32 FIP	23	SP-	4.32	14.8%	10.1%	2.2%	.248	5.39	16.5%	6.4%	123	+1.07	4.32	232	79
Zach Lewis R 2019 · 4.14 FIP	24	SP-	4.14	14.9%	9.4%	2.0%	.331	—	—	—	—	—	3.57	266	79
Tyler Cravy R 2015 · 3.94 FIP	26	SP-	3.94	17.0%	9.0%	2.1%	.305	4.61	18.6%	7.8%	138	+0.67	3.94	276	78
Logan Martin R 2024 · 3.95 FIP	23	SP-	3.95	16.9%	8.9%	2.1%	.278	4.58	17.6%	5.0%	140	+0.63	3.95	242	78
Mike Augliera R 2015 · 4.27 FIP	25	SP-	4.27	12.0%	7.2%	2.3%	.350	—	—	—	—	—	4.27	114	78
Tyrell Jenkins R 2016 · 4.88 FIP	24	SP-	4.88	12.5%	11.6%	2.5%	.294	6.04	12.6%	-1.1%	82	+1.16	4.30	356	78

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	4.4	127	16.9%	8.8%	1.24	4.93
Nate Robertson ('10)	5.8	144	15.3%	8.3%	1.25	5.01
Dave Lemanczyk ('73-'80, 2 WAR*)	4.6	130	16.9%*	9.0%*	1.15*	4.83*
Bob Milacki ('88-'96, 5 WAR*)	4.0	114	15.2%*	8.4%*	1.26*	4.64*
Al Nipper ('83-'90, 4 WAR*)	4.0	133	14.8%*	8.5%*	1.23*	4.56*
Paul Wilson ('05)	4.7	135	14.9%	8.1%	1.20	4.86
Garrett Stephenson ('03)	3.3	109	14.5%	8.4%	1.26	4.55