Pedro Garcia

P Lakeland Flying Tigers

Age 25 RHP 6'1" / 190 lbs A

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	22	MIX2 levels	18	10	59	5.34	3.74	23.2%	13.8%	—	K 16.1% · BB 16.8% · FIP 5.04
2025	23	MIX2 levels	23	0	44	2.86	4.12	14.8%	8.5%	—	K 10.2% · BB 10.5% · FIP 5.52
2026	24	MIX2 levels	36	0	58	6.21	5.31	18.8%	15.3%	—	K 13.9% · BB 17.9% · FIP 6.03
2027PROJ	25	MLBDET	—	—	0	5.75	5.75	16.0%	15.4%	—
2028PROJ43% MLB	26	MLBDET	15	0	16	5.55	5.52	17.7%	14.7%	-0.2
2029PROJ63% MLB	27	MLBDET	19	0	20	5.46	5.47	18.1%	14.4%	-0.2

Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsAndrew McInvale (age 25) · Jeremy Guthrie (age 27) · Clate Schmidt (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 142134vR 126

ERA5.75

FIP5.75

K%16.0%

BB%15.4%

K-BB%0.6%

Proj IP37

Value2027 · WAR

Runs saved vs league avg · 37 IP

Grades · Contract

Scouting Grades

K†3045

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)
2022	20	ROK MLE	DSL Tigers 2	13	10	51	202	46	11	5	77%	3.9	15.5%	6.8%	8.7%	3.7%	3.16	4.69	—
2022	20	ROK RAW	DSL Tigers 2	13	10	51	202	46	11	5	77%	3.9	22.8%	5.4%	17.3%	2.5%	3.16	3.22	—
2023	21	MIX MLE	2 levels	12	8	38	176	39	18	8	67%	3.2	14.9%	12.6%	2.3%	7.2%	5.40	7.37	—
2023	21	MIX RAW	2 levels	12	8	38	176	39	18	8	67%	3.2	22.2%	10.2%	11.9%	4.5%	5.40	5.19	—
2024	22	MIX MLE	2 levels	18	10	59	276	64	38	4	56%	3.3	16.1%	16.8%	-0.7%	2.1%	5.34	5.04	—
2024	22	MIX MLE	2 levels	18	10	59	276	64	38	4	56%	3.3	16.1%	16.8%	-0.7%	2.1%	5.34	5.04	—
2024	22	MIX RAW	2 levels	18	10	59	276	64	38	4	56%	3.3	23.2%	13.8%	9.4%	1.4%	5.34	3.74	—
2025	23	MIX MLE	2 levels	23	0	44	176	26	15	4	0%	1.9	10.2%	10.5%	-0.2%	3.6%	2.86	5.52	—
2025	23	MIX MLE	2 levels	23	0	44	176	26	15	4	0%	1.9	10.2%	10.5%	-0.2%	3.6%	2.86	5.52	—
2025	23	MIX RAW	2 levels	23	0	44	176	26	15	4	0%	1.9	14.8%	8.5%	6.3%	2.3%	2.86	4.12	—
2026	24	MIX MLE	2 levels	36	0	58	287	54	44	8	0%	1.6	13.9%	17.9%	-3.9%	3.4%	6.21	6.03	—
2026	24	MIX MLE	2 levels	36	0	58	287	54	44	8	0%	1.6	13.9%	17.9%	-3.9%	3.4%	6.21	6.03	—
2026	24	MIX RAW	2 levels	36	0	58	287	54	44	8	0%	1.6	18.8%	15.3%	3.5%	2.8%	6.21	5.31	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	DET	—	—	0	—	—	—	—	—	—	16.0%	15.4%	0.6%	3.0%	5.75	5.75	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	DET	35	0	37	157	28	23	5	0%	1.1	17.7%	14.7%	3.0%	3.0%	5.55	5.52	-0.4
2029	27	MLB MLE	DET	30	0	32	134	24	19	4	0%	1.1	18.1%	14.4%	3.7%	3.1%	5.46	5.47	-0.3
2028	26	MLB CTX	DET	15	0	16	68	12	10	2	0%	1.1	17.7%	14.7%	3.0%	3.0%	5.55	5.52	-0.2
2029	27	MLB CTX	DET	19	0	20	84	15	12	3	0%	1.1	18.1%	14.4%	3.7%	3.1%	5.46	5.47	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		34	0	36	151	27	22	5	0%	1.1	17.9%	14.5%	3.4%	3.1%	5.50	5.11	-0.2
/ 200 IP	—	RAW		190	0	200	844	151	123	28	0%	1.1	17.9%	14.5%	3.4%	3.1%	5.50	5.11	-1.3
Career	—	MLE		102	28	251	1117	160	152	42	27%	2.5	14.3%	13.6%	0.7%	3.8%	4.67	5.67	-0.7
/ 200 IP	—	MLE		81	22	200	891	128	121	33	27%	2.5	14.3%	13.6%	0.7%	3.8%	4.67	5.67	-2.2

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 ALakeland Flying Tigers · 56 IPFIP 4.84 → 6.03 (+1.18)K% 18.8% → 13.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.82%	—	×0.740	13.93%
BB% (unintentional) /BF	15.13%	—	×1.180	17.85%
HR / BF /BF	2.58%	÷1.000	×1.300	3.36%

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 100).

Result: FIP 4.84 → 6.03, 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 ROKFCL Tigers · 28 IPFIP 4.11 → 5.62 (+1.51)K% 16.5% → 11.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.53%	—	×0.680	11.24%
BB% (unintentional) /BF	8.26%	—	×1.250	10.33%
HR / BF /BF	2.48%	÷0.880	×1.400	3.94%

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 76).

Result: FIP 4.11 → 5.62, 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 ALakeland Flying Tigers · 16 IPFIP 4.33 → 5.28 (+0.95)K% 10.9% → 8.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	10.91%	—	×0.740	8.07%
BB% (unintentional) /BF	9.09%	—	×1.180	10.73%
HR / BF /BF	1.82%	÷0.864	×1.300	2.74%

Result: FIP 4.33 → 5.28, 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 ROKFCL Tigers · 45 IPFIP 3.42 → 4.97 (+1.55)K% 25.4% → 17.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.38%	—	×0.680	17.26%
BB% (unintentional) /BF	10.66%	—	×1.250	13.32%
HR / BF /BF	2.03%	÷0.952	×1.400	2.99%

Result: FIP 3.42 → 4.97, 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 ALakeland Flying Tigers · 14 IPFIP 4.33 → 5.21 (+0.88)K% 17.7% → 13.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.72%	—	×0.740	13.11%
BB% (unintentional) /BF	21.52%	—	×1.180	25.39%
HR / BF /BF	0.00%	÷1.099	×1.300	0.00%

Result: FIP 4.33 → 5.21, 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 ROKFCL Tigers · 36 IPFIP 5.12 → 7.37 (+2.25)K% 21.9% → 14.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.89%	—	×0.680	14.89%
BB% (unintentional) /BF	10.06%	—	×1.250	12.57%
HR / BF /BF	4.73%	÷0.924	×1.400	7.17%

Result: FIP 5.12 → 7.37, 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).

2022 ROKDSL Tigers 2 · 51 IPFIP 3.23 → 4.69 (+1.47)K% 22.8% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.77%	—	×0.680	15.49%
BB% (unintentional) /BF	5.45%	—	×1.250	6.81%
HR / BF /BF	2.48%	÷0.933	×1.400	3.71%

Result: FIP 3.23 → 4.69, 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
Pedro Garcia (OGILVIE)	—	—	5.75	16.0%	15.4%	3.0%	—	5.50	17.9%	3.3%	69	-0.25	—	—	—
Andrew McInvale R 2022 · 5.15 FIP	25	SU	5.15	17.6%	15.9%	2.8%	.324	6.44	24.5%	10.0%	23	+1.29	4.92	103	84
Jeremy Guthrie R 2006 · 4.92 FIP	27	SU	4.92	15.1%	15.1%	2.1%	.349	4.57	14.8%	8.1%	566	-0.35	4.08	1,834	83
Clate Schmidt R 2019 · 5.66 FIP	25	SU	5.66	13.5%	13.9%	3.5%	.290	—	—	—	—	—	3.51	160	81
Hayden Snelsire R 2024 · 5.10 FIP	23	SU	5.10	18.9%	13.8%	3.4%	.272	4.28	20.0%	13.7%	135	-0.82	3.83	178	81
Stephen Johnson R 2016 · 5.15 FIP	25	SU	5.15	16.7%	12.7%	3.4%	.268	—	—	—	—	—	3.12	141	81
Ryan Vogelsong R 2001 · 5.34 FIP	24	SU	5.34	14.6%	11.6%	3.7%	.287	4.78	14.9%	5.7%	155	-0.56	3.14	1,184	80
Haden Erbe R 2024 · 5.28 FIP	25	SU	5.28	18.4%	16.5%	3.0%	.320	5.19	17.8%	0.5%	40	-0.09	5.19	116	80
Jordan Brink R 2016 · 5.96 FIP	23	SW	5.96	18.3%	19.2%	3.6%	.233	—	—	—	—	—	3.99	132	80
Austin Amaral R 2024 · 5.94 FIP	22	SU	5.94	12.1%	14.4%	3.7%	.254	3.55	18.6%	6.3%	113	-2.39	3.53	136	79
Cole Hillier R 2024 · 4.64 FIP	23	SU	4.64	16.9%	14.7%	2.0%	.297	4.45	18.1%	4.5%	111	-0.19	3.80	169	79
Fernando Cruz R 2015 · 5.29 FIP	25	SU	5.29	15.6%	12.2%	3.6%	.284	—	—	—	—	—	2.50	371	79
Jake Gilbert R 2022 · 4.65 FIP	25	SU	4.65	18.2%	16.2%	1.9%	.331	—	—	—	—	—	4.14	103	79
Kender Villegas R 2017 · 4.70 FIP	24	SU	4.70	13.3%	13.3%	1.9%	.269	—	—	—	—	—	3.26	131	79
Yordy Cabrera R 2016 · 4.99 FIP	25	SU	4.99	15.8%	17.2%	1.9%	.321	4.17	13.7%	2.7%	140	-0.82	3.43	159	78
Julian Arballo R 2015 · 5.13 FIP	27	SU	5.13	15.1%	13.8%	2.8%	.335	4.46	12.6%	0.6%	116	-0.67	4.45	214	78
Vanny Valenzuela R 2015 · 6.82 FIP	27	SW	6.82	12.4%	14.8%	5.3%	.314	4.29	15.8%	4.6%	70	-2.53	3.26	118	78
Cooper Adams R 2024 · 5.42 FIP	24	SW	5.42	13.0%	12.2%	3.4%	.275	4.32	21.7%	10.4%	141	-1.10	3.05	221	78
Juan Paniagua R 2015 · 4.69 FIP	25	SU	4.69	15.7%	11.9%	2.6%	.262	4.63	16.2%	1.8%	93	-0.06	4.57	151	78
Reece Karalus R 2018 · 4.73 FIP	24	SU	4.73	15.4%	11.9%	2.6%	.299	—	—	—	—	—	4.73	149	78
Tyler Burch R 2023 · 4.92 FIP	25	SU	4.92	15.0%	12.6%	2.7%	.285	—	—	—	—	—	4.56	119	77

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	0.5	35	17.2%	14.9%	1.18	5.59
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Doug Bochtler ('00)	1.3	65	18.6%	14.4%	1.25	4.57
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Doug Creek ('05)	1.4	58	22.2%	15.1%	1.52	5.32
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*