Lazaro Estrada

P Buffalo Bisons

Age 28 RHP 5'10" / 180 lbs AAA

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX3 levels	22	22	98	3.29	2.87	28.0%	8.2%	—	K 22.3% · BB 9.1% · FIP 3.64
2025	26	MIX2 levels	28	20	105	5.93	4.32	23.5%	7.1%	1.3	K 19.8% · BB 6.7% · FIP 5.10
2026	27	MIX3 levels	27	5	51	4.24	4.47	21.4%	11.0%	0.0	K 19.1% · BB 10.3% · FIP 4.85
2027PROJ	28	MLBTOR	7	7	40	4.68	4.96	19.1%	8.7%	0.2
2028PROJ78% MLB	29	MLBTOR	6	6	34	4.88	5.05	18.9%	9.0%	0.1
2029PROJ84% MLB	30	MLBTOR	5	5	30	5.05	5.21	18.6%	9.3%	0.1

Last 3 seasons WAR 1.4 · Next 3 projected WAR 0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs31

FB Velo26

K%10

Career WAR0.0 WAR median (P10 -0.2 / P90 0.7, comp-based) · star 0% · didn't stick 94%

CompsEddie Bonine (age 28) · Zach Stewart (age 28) · Clay Condrey (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 127119vR 111

ERA4.68

FIP4.96

K%19.1%

BB%8.7%

K-BB%10.4%

Proj IP57

Value2027 · WAR

Runs saved vs league avg · 57 IP

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL5555

CMD5050

K†4545

Statcast Percentiles

FB Velo

p2692.8

Whiff%

p4023.8%

p1015.8%

xwOBA vs

p310.334

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)
2018	19	ROK MLE	DSL Blue Jays	14	14	70	279	87	12	4	100%	5.0	21.2%	5.4%	15.8%	2.0%	2.06	3.09	—
2018	19	ROK RAW	DSL Blue Jays	14	14	70	279	87	12	4	100%	5.0	31.2%	4.3%	26.9%	1.4%	2.06	1.87	—
2021	22	MIX MLE	2 levels	7	2	20	88	28	8	2	29%	2.9	22.7%	11.0%	11.7%	3.4%	2.66	4.46	—
2021	22	MIX RAW	2 levels	7	2	20	88	28	8	2	29%	2.9	31.8%	9.1%	22.7%	2.3%	2.66	2.80	—
2022	23	MIX MLE	2 levels	9	6	19	79	32	7	0	67%	2.1	27.7%	9.2%	18.5%	0.0%	3.79	1.92	—
2022	23	MIX RAW	2 levels	9	6	19	79	32	7	0	67%	2.1	40.5%	8.9%	31.6%	0.0%	3.79	0.84	—
2023	24	A MLE	Dunedin Blue Jays	28	9	76	309	103	26	3	32%	2.7	24.7%	9.9%	14.7%	1.0%	2.83	2.82	—
2023	24	A RAW	Dunedin Blue Jays	28	9	76	309	103	26	3	32%	2.7	33.3%	8.4%	24.9%	1.0%	2.83	1.93	—
2024	25	MIX MLE	3 levels	22	22	98	403	113	33	8	100%	4.5	22.3%	9.1%	13.3%	2.3%	3.29	3.64	—
2024	25	MIX MLE	3 levels	22	22	98	403	113	33	8	100%	4.5	22.3%	9.1%	13.3%	2.3%	3.29	3.64	—
2024	25	MIX RAW	3 levels	22	22	98	403	113	33	8	100%	4.5	28.0%	8.2%	19.9%	2.0%	3.29	2.87	—
2025	26	MIX MLE	2 levels	28	20	105	464	109	33	19	71%	3.7	19.8%	6.7%	13.1%	5.1%	5.93	5.10	+0.4
2025	26	MIX MLE	2 levels	28	20	105	464	109	33	19	71%	3.7	19.8%	6.7%	13.1%	5.1%	5.93	5.10	+0.4
2025	26	MIX RAW	2 levels	28	20	105	464	109	33	19	71%	3.7	23.5%	7.1%	16.4%	4.1%	5.93	4.32	+1.3
2026	27	MIX MLE	3 levels	27	5	51	210	45	23	7	19%	1.9	19.1%	10.3%	8.8%	3.8%	4.24	4.85	-0.2
2026	27	MIX MLE	3 levels	27	5	51	210	45	23	7	19%	1.9	19.1%	10.3%	8.8%	3.8%	4.24	4.85	-0.2
2026	27	MIX RAW	3 levels	27	5	51	210	45	23	7	19%	1.9	21.4%	11.0%	10.5%	3.3%	4.24	4.47	+0.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			10	0	20	92	19	10	4	0%	2.0	20.7%	10.9%	9.8%	4.3%	6.64	5.26	-0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	TOR	7	7	40	169	32	15	6	100%	5.7	19.1%	8.7%	10.4%	3.6%	4.68	4.96	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	TOR	7	7	44	185	35	17	7	100%	6.3	18.9%	9.0%	9.9%	3.7%	4.88	5.05	+0.2
2029	30	MLB MLE	TOR	6	6	36	153	28	14	6	100%	6.0	18.6%	9.3%	9.3%	3.9%	5.05	5.21	+0.1
2028	29	MLB CTX	TOR	6	6	34	144	27	13	5	100%	5.7	18.9%	9.0%	9.9%	3.7%	4.88	5.05	+0.1
2029	30	MLB CTX	TOR	5	5	30	127	23	12	5	100%	6.0	18.6%	9.3%	9.3%	3.9%	5.05	5.21	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		21	11	85	365	70	35	14	52%	4.0	19.2%	9.6%	9.7%	3.9%	5.36	4.84	+0.5
/ 200 IP	—	RAW		49	25	200	859	165	82	33	52%	4.1	19.2%	9.6%	9.7%	3.9%	5.36	4.84	+1.3
Career	—	MLE		135	78	440	1832	400	152	53	58%	3.3	21.8%	8.3%	13.5%	2.9%	3.75	3.89	+0.3
/ 200 IP	—	MLE		61	35	200	833	182	69	24	58%	3.3	21.8%	8.3%	13.5%	2.9%	3.75	3.89	+0.6

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 AAABuffalo Bisons · 36 IPFIP 4.16 → 4.52 (+0.36)K% 23.8% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.78%	—	×0.860	20.45%
BB% (unintentional) /BF	9.09%	—	×0.900	8.18%
HR / BF /BF	3.50%	÷1.000	×1.100	3.85%

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 4.16 → 4.52, 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).

2025 AAABuffalo Bisons · 97 IPFIP 4.27 → 5.10 (+0.83)K% 23.1% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.860	19.85%
BB% (unintentional) /BF	7.46%	—	×0.900	6.71%
HR / BF /BF	3.96%	÷0.847	×1.100	5.15%

Result: FIP 4.27 → 5.10, 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 AANew Hampshire Fisher Cats · 52 IPFIP 3.08 → 3.64 (+0.56)K% 25.0% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.810	20.25%
BB% (unintentional) /BF	8.64%	—	×1.100	9.50%
HR / BF /BF	1.82%	÷1.145	×1.200	1.91%

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 129).

Result: FIP 3.08 → 3.64, 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+Vancouver Canadians · 41 IPFIP 2.63 → 3.65 (+1.02)K% 32.7% → 25.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.72%	—	×0.770	25.19%
BB% (unintentional) /BF	7.41%	—	×1.150	8.52%
HR / BF /BF	2.47%	÷1.062	×1.250	2.91%

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 2.63 → 3.65, 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 ADunedin Blue Jays · 5 IPFIP 2.30 → 3.04 (+0.74)K% 23.8% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.81%	—	×0.740	17.62%
BB% (unintentional) /BF	9.52%	—	×1.180	11.24%
HR / BF /BF	0.00%	÷1.003	×1.300	0.00%

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 101).

Result: FIP 2.30 → 3.04, 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 ADunedin Blue Jays · 76 IPFIP 1.88 → 2.82 (+0.93)K% 33.3% → 24.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.740	24.67%
BB% (unintentional) /BF	8.41%	—	×1.180	9.93%
HR / BF /BF	0.97%	÷1.279	×1.300	0.99%

Result: FIP 1.88 → 2.82, 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).

2022 ADunedin Blue Jays · 15 IPFIP 0.92 → 1.92 (+1.00)K% 37.5% → 27.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.50%	—	×0.740	27.75%
BB% (unintentional) /BF	7.81%	—	×1.180	9.22%
HR / BF /BF	0.00%	÷0.916	×1.300	0.00%

Result: FIP 0.92 → 1.92, 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 ADunedin Blue Jays · 16 IPFIP 3.16 → 4.46 (+1.31)K% 30.7% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.67%	—	×0.740	22.69%
BB% (unintentional) /BF	9.33%	—	×1.180	11.01%
HR / BF /BF	2.67%	÷1.010	×1.300	3.43%

Result: FIP 3.16 → 4.46, 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).

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
Lazaro Estrada (OGILVIE)	—	—	4.96	19.1%	8.7%	3.6%	—	5.12	18.7%	9.6%	80	+0.16	—	—	—
Eddie Bonine R 2009 · 5.60 FIP	28	SW	5.60	13.1%	7.6%	4.8%	.306	4.54	8.6%	2.0%	68	-1.06	4.40	129	72
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	70
Clay Condrey R 2003 · 5.41 FIP	27	SP-	5.41	14.9%	10.1%	4.2%	.303	4.07	13.1%	7.4%	29	-1.34	3.18	250	69
Ramon Delgado R 2016 · 4.60 FIP	29	SW	4.60	13.8%	5.9%	3.5%	.332	4.31	11.2%	7.2%	74	-0.29	4.31	135	69
Alfonso Sanchez R 2016 · 5.26 FIP	28	SW	5.26	15.9%	7.4%	4.7%	.244	5.55	11.2%	2.3%	115	+0.29	4.51	224	68
Jeff Manship R 2013 · 5.11 FIP	28	SW	5.11	12.9%	7.9%	3.8%	.298	3.57	20.0%	11.7%	137	-1.54	2.83	250	68
Aldo Montes R 2017 · 4.96 FIP	27	SP-	4.96	12.4%	8.5%	3.3%	.322	4.69	18.2%	7.6%	75	-0.27	4.69	210	66
Nelson Gonzalez R 2018 · 5.03 FIP	28	SW	5.03	19.2%	8.2%	4.6%	.311	6.22	16.9%	4.6%	74	+1.19	3.42	258	66
Dustin Nippert R 2009 · 4.09 FIP	28	SP-	4.09	18.0%	9.7%	2.3%	.271	4.49	17.9%	6.1%	57	+0.40	3.83	268	66
Casey Sadler R 2018 · 3.95 FIP	28	SW	3.95	16.0%	7.8%	2.2%	.298	3.35	23.2%	16.5%	145	-0.60	2.21	385	65
Orlando Rodriguez R 2023 · 4.67 FIP	27	SW	4.67	13.7%	10.6%	2.5%	.252	—	—	—	—	—	4.40	119	65
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	64
Josh Roeder R 2019 · 4.71 FIP	26	SW	4.71	15.1%	8.7%	3.3%	.264	—	—	—	—	—	4.71	175	64
Jon Leicester R 2007 · 4.44 FIP	28	SP-	4.44	11.0%	9.0%	2.1%	.292	—	—	—	—	—	3.76	113	64
Bradin Hagens R 2018 · 4.92 FIP	29	SP-	4.92	14.9%	9.9%	3.3%	.341	5.46	13.2%	0.6%	66	+0.54	3.79	254	64
Ryan Glynn R 2004 · 5.23 FIP	29	SW	5.23	15.7%	7.9%	4.5%	.234	5.98	18.3%	9.8%	17	+0.75	5.23	226	64
Nolan Sanburn R 2017 · 4.55 FIP	26	SW	4.55	15.0%	10.4%	2.5%	.310	—	—	—	—	—	3.82	169	64
Carlos Torres R 2010 · 4.50 FIP	27	SW	4.50	18.3%	11.3%	2.8%	.438	3.89	20.1%	13.2%	139	-0.61	2.89	604	63
Christian Bergman R 2016 · 4.74 FIP	28	SW	4.74	15.3%	5.6%	4.0%	.309	4.62	15.0%	9.1%	322	-0.12	3.99	521	63
Chris Bassitt R 2017 · 3.83 FIP	28	SW	3.83	17.5%	9.8%	1.7%	.313	3.80	21.7%	14.1%	336	-0.03	2.92	1,596	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	0.8	53	19.1%	9.3%	1.47	5.07
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Scott Proctor ('11)	1.7	57	19.0%	10.9%	1.52	4.78
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Tom Dukes ('67-'72, -2 WAR*)	1.1	43	22.7%*	8.7%*	1.16*	5.37*