Alex Makarewich

P Great Lakes Loons

Age 25 RHP 6'0" / 185 lbs A+

Overview

A+PROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	22	MIX2 levels	17	10	32	9.28	5.38	25.9%	21.3%	—	K 19.7% · BB 26.7% · FIP 6.15
2025	23	MIX2 levels	41	0	44	3.07	3.03	36.8%	24.0%	—	K 27.9% · BB 27.7% · FIP 4.26
2026	24	A+LAD	34	0	39	4.89	5.04	32.1%	27.8%	—	K 24.7% · BB 32.0% · FIP 6.17
2027PROJ	25	MLBLAD	—	—	0	5.39	5.39	24.8%	20.0%	—
2028PROJ43% MLB	26	MLBLAD	12	0	13	5.27	5.26	24.8%	18.9%	-0.1

Next 2 projected WAR -0.1Projected 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 0.7, comp-based) · star 0% · didn't stick 99%

CompsZane Russell (age 24) · Maikel Cleto (age 25) · CJ Weins (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 136127vR 119

ERA5.39

FIP5.39

K%24.8%

BB%20.0%

K-BB%4.7%

Proj IP23

Value2027 · WAR

Runs saved vs league avg · 23 IP

Grades · Contract

Scouting Grades

K†6060

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)
2024	22	MIX MLE	2 levels	17	10	32	174	45	37	4	59%	1.9	19.7%	26.7%	-7.0%	2.4%	9.28	6.15	—
2024	22	MIX MLE	2 levels	17	10	32	174	45	37	4	59%	1.9	19.7%	26.7%	-7.0%	2.4%	9.28	6.15	—
2024	22	MIX RAW	2 levels	17	10	32	174	45	37	4	59%	1.9	25.9%	21.3%	4.6%	2.3%	9.28	5.38	—
2025	23	MIX MLE	2 levels	41	0	44	204	75	49	0	0%	1.1	27.9%	27.7%	0.2%	0.0%	3.07	4.26	—
2025	23	MIX MLE	2 levels	41	0	44	204	75	49	0	0%	1.1	27.9%	27.7%	0.2%	0.0%	3.07	4.26	—
2025	23	MIX RAW	2 levels	41	0	44	204	75	49	0	0%	1.1	36.8%	24.0%	12.7%	0.0%	3.07	3.03	—
2026	24	A+ MLE	Great Lakes Loons	34	0	39	187	60	52	3	0%	1.1	24.7%	32.0%	-7.3%	2.0%	4.89	6.17	—
2026	24	A+ MLE	Great Lakes Loons	34	0	39	187	60	52	3	0%	1.1	24.7%	32.0%	-7.3%	2.0%	4.89	6.17	—
2026	24	A+ RAW	Great Lakes Loons	34	0	39	187	60	52	3	0%	1.1	32.1%	27.8%	4.3%	1.6%	4.89	5.04	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	LAD	—	—	0	—	—	—	—	—	—	24.8%	20.0%	4.7%	2.7%	5.39	5.39	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	LAD	28	0	29	123	31	23	3	0%	1.0	24.8%	18.9%	5.9%	2.7%	5.27	5.26	-0.2
2028	26	MLB CTX	LAD	12	0	13	55	14	10	1	0%	1.1	24.8%	18.9%	5.9%	2.7%	5.27	5.26	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		12	0	13	53	13	10	1	0%	1.0	24.8%	18.9%	5.9%	2.7%	5.27	4.88	-0.0
/ 200 IP	—	RAW		190	0	200	844	207	159	16	0%	1.1	24.8%	18.9%	5.9%	2.7%	5.27	4.88	-0.8
Career	—	MLE		92	10	115	565	137	163	8	11%	1.2	24.3%	28.8%	-4.5%	1.4%	5.42	5.47	-0.2
/ 200 IP	—	MLE		160	17	200	985	240	284	14	11%	1.2	24.3%	28.8%	-4.5%	1.4%	5.42	5.47	-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 A+Great Lakes Loons · 39 IPFIP 4.79 → 6.17 (+1.37)K% 32.1% → 24.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.09%	—	×0.770	24.71%
BB% (unintentional) /BF	27.81%	—	×1.150	31.98%
HR / BF /BF	1.60%	÷1.000	×1.250	2.01%

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 100).

Result: FIP 4.79 → 6.17, 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).

2025 A+Great Lakes Loons · 31 IPFIP 3.85 → 4.98 (+1.13)K% 31.6% → 24.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.58%	—	×0.770	24.32%
BB% (unintentional) /BF	26.97%	—	×1.150	31.02%
HR / BF /BF	0.00%	÷0.992	×1.250	0.00%

Result: FIP 3.85 → 4.98, 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 ARancho Cucamonga Quakes · 13 IPFIP 0.66 → 2.15 (+1.49)K% 51.9% → 38.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	51.92%	—	×0.740	38.42%
BB% (unintentional) /BF	15.38%	—	×1.180	18.15%
HR / BF /BF	0.00%	÷1.055	×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 111).

Result: FIP 0.66 → 2.15, 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 ARancho Cucamonga Quakes · 27 IPFIP 4.82 → 6.15 (+1.34)K% 26.7% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.67%	—	×0.740	19.73%
BB% (unintentional) /BF	22.67%	—	×1.180	26.75%
HR / BF /BF	2.00%	÷1.072	×1.300	2.43%

Result: FIP 4.82 → 6.15, 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 ROKACL Dodgers · 5 IPFIP 5.21 → 7.28 (+2.07)K% 20.8% → 14.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.83%	—	×0.680	14.17%
BB% (unintentional) /BF	12.50%	—	×1.250	15.62%
HR / BF /BF	4.17%	÷0.942	×1.400	6.19%

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 88).

Result: FIP 5.21 → 7.28, 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).

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
Alex Makarewich (OGILVIE)	—	—	5.39	24.8%	20.0%	2.7%	—	5.26	24.8%	5.9%	29	-0.13	—	—	—
Zane Russell R 2024 · 4.95 FIP	24	SU	4.95	22.7%	18.3%	2.6%	.314	5.36	18.2%	6.7%	71	+0.41	4.63	108	89
Maikel Cleto R 2014 · 4.24 FIP	25	SU	4.24	23.2%	15.2%	2.1%	.256	3.45	25.4%	14.5%	106	-0.79	2.59	185	85
CJ Weins R 2024 · 4.55 FIP	23	SU	4.55	24.7%	15.9%	2.8%	.276	5.77	16.2%	-4.4%	76	+1.22	4.55	117	85
Fernando Baez R 2017 · 5.37 FIP	25	SU	5.37	24.3%	21.2%	3.0%	.271	—	—	—	—	—	3.45	129	84
Caleb Simpson R 2017 · 5.37 FIP	25	SU	5.37	23.7%	17.2%	3.8%	.263	3.93	23.5%	5.1%	71	-1.44	3.57	197	84
Kyle Wilcox R 2019 · 5.16 FIP	25	SU	5.16	25.1%	21.2%	2.7%	.310	5.57	25.1%	-1.5%	13	+0.41	2.78	310	84
LJ McDonough R 2024 · 4.54 FIP	24	SU	4.54	22.6%	16.7%	2.3%	.385	4.85	20.0%	2.8%	90	+0.31	4.16	127	83
Evan Johnson R 2022 · 4.64 FIP	25	SU	4.64	23.6%	17.6%	2.4%	.284	—	—	—	—	—	4.42	103	83
Christopher Troye R 2024 · 5.46 FIP	25	SU	5.46	24.2%	17.0%	4.1%	.282	5.61	19.1%	-3.8%	30	+0.15	3.42	158	82
Kevin Kopps R 2022 · 4.56 FIP	25	SU	4.56	20.2%	15.1%	2.3%	.278	4.40	16.3%	4.0%	182	-0.16	3.45	237	82
Cody Scroggins R 2022 · 4.50 FIP	25	SU	4.50	20.5%	16.2%	2.0%	.351	3.78	14.2%	4.6%	18	-0.72	3.78	108	82
Conor Grammes R 2022 · 4.64 FIP	25	SU	4.64	28.6%	16.8%	3.3%	.293	4.52	20.8%	1.1%	128	-0.12	4.11	171	81
Jose De La Torre R 2013 · 5.22 FIP	27	SU	5.22	28.3%	18.9%	3.9%	.308	3.87	17.6%	6.6%	110	-1.35	2.64	141	81
Dakota Mekkes R 2019 · 4.58 FIP	24	SU	4.58	23.1%	15.4%	2.7%	.290	4.85	16.7%	1.8%	70	+0.27	2.94	246	81
Tyler Davis R 2024 · 6.02 FIP	25	SU	6.02	21.0%	18.8%	4.2%	.317	3.78	21.9%	10.2%	111	-2.24	3.20	137	81
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	81
Carter Loewen R 2024 · 4.26 FIP	25	SU	4.26	23.1%	15.0%	2.2%	.312	4.16	20.0%	11.9%	23	-0.10	2.67	145	80
Hudson Leach R 2024 · 5.37 FIP	22	SU	5.37	20.5%	20.0%	2.7%	.261	4.54	20.9%	3.1%	71	-0.83	2.77	101	80
Conor Larkin R 2024 · 4.82 FIP	25	SU	4.82	24.4%	16.7%	3.0%	.233	4.66	17.9%	5.2%	90	-0.16	2.40	179	80
Ryan Jensen R 2023 · 4.61 FIP	25	SU	4.61	20.9%	17.0%	2.0%	.329	4.12	24.4%	7.6%	107	-0.49	3.92	311	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	0.3	26	24.8%	19.4%	1.04	5.32
Brian Bruney ('12)	1.3	43	21.2%	15.8%	0.94	4.68
Doug Creek ('05)	1.4	58	22.2%	15.1%	1.52	5.32
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Armando Almanza ('05)	1.1	54	24.4%	14.3%	1.43	4.82
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*