Zach Franklin

P Syracuse Mets

Age 28 RHP 6'1" / 198 lbs AAA peak 0.1 · 2027

Overview

AAAPROSPECT

ETA2029MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	37	0	51	3.20	1.78	36.6%	9.3%	—	K 26.4% · BB 10.9% · FIP 3.24
2025	26	MIX2 levels	48	0	56	2.40	2.50	35.3%	10.7%	—	K 29.0% · BB 11.3% · FIP 3.24
2026	27	AAANYM	46	1	61	3.69	4.40	30.4%	8.1%	—	K 26.1% · BB 7.3% · FIP 5.00
2027PROJ	28	MLBNYM	7	0	7	4.45	4.45	27.9%	10.1%	0.0
2028PROJ29% MLB	29	MLBNYM	16	0	17	4.51	4.56	27.2%	10.2%	-0.0
2029PROJ44% MLB	30	MLBNYM	22	0	23	4.63	4.72	26.6%	10.4%	-0.0

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

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.2 / P90 0.7, comp-based) · star 0% · didn't stick 93%

CompsRyan Brasier (age 28) · Matt Ramsey (age 28) · Kiko Calero (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 118110vR 101

ERA4.45

FIP4.45

K%27.9%

BB%10.1%

K-BB%17.8%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

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)
2023	24	MIX MLE	2 levels	11	0	11	54	18	6	0	0%	1.0	33.3%	11.1%	22.2%	0.0%	6.35	1.69	—
2023	24	MIX RAW	2 levels	11	0	11	54	18	6	0	0%	1.0	33.3%	11.1%	22.2%	0.0%	6.35	1.51	—
2024	25	MIX MLE	2 levels	37	0	51	205	75	19	2	0%	1.4	26.4%	10.9%	15.5%	1.8%	3.20	3.24	—
2024	25	MIX MLE	2 levels	37	0	51	205	75	19	2	0%	1.4	26.4%	10.9%	15.5%	1.8%	3.20	3.24	—
2024	25	MIX RAW	2 levels	37	0	51	205	75	19	2	0%	1.4	36.6%	9.3%	27.3%	1.0%	3.20	1.78	—
2025	26	MIX MLE	2 levels	48	0	56	224	79	24	4	0%	1.2	29.0%	11.3%	17.7%	2.1%	2.40	3.24	—
2025	26	MIX MLE	2 levels	48	0	56	224	79	24	4	0%	1.2	29.0%	11.3%	17.7%	2.1%	2.40	3.24	—
2025	26	MIX RAW	2 levels	48	0	56	224	79	24	4	0%	1.2	35.3%	10.7%	24.6%	1.8%	2.40	2.50	—
2026	27	AAA MLE	Syracuse Mets	46	1	61	247	75	20	13	2%	1.3	26.1%	7.3%	18.8%	5.8%	3.69	5.00	—
2026	27	AAA MLE	Syracuse Mets	46	1	61	247	75	20	13	2%	1.3	26.1%	7.3%	18.8%	5.8%	3.69	5.00	—
2026	27	AAA RAW	Syracuse Mets	46	1	61	247	75	20	13	2%	1.3	30.4%	8.1%	22.3%	5.3%	3.69	4.40	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	NYM	7	0	7	30	8	3	1	0%	1.0	27.9%	10.1%	17.8%	3.7%	4.45	4.45	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	NYM	57	0	60	252	68	26	10	0%	1.0	27.2%	10.2%	17.0%	3.8%	4.51	4.56	-0.0
2029	30	MLB MLE	NYM	50	0	52	220	59	23	9	0%	1.0	26.6%	10.4%	16.1%	3.9%	4.63	4.72	-0.1
2028	29	MLB CTX	NYM	16	0	17	72	20	7	3	0%	1.1	27.2%	10.2%	17.0%	3.8%	4.51	4.56	-0.0
2029	30	MLB CTX	NYM	22	0	23	97	26	10	4	0%	1.0	26.6%	10.4%	16.1%	3.9%	4.63	4.72	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		38	0	40	170	46	18	7	0%	1.1	26.8%	10.3%	16.5%	3.9%	4.58	4.27	+0.1
/ 200 IP	—	RAW		190	0	200	844	229	90	35	0%	1.1	26.8%	10.3%	16.5%	3.9%	4.58	4.27	+0.7
Career	—	MLE		142	1	179	730	202	72	23	1%	1.3	27.6%	9.8%	17.8%	3.1%	3.31	3.72	-0.1
/ 200 IP	—	MLE		158	1	200	814	225	80	25	1%	1.3	27.6%	9.8%	17.8%	3.1%	3.31	3.72	-0.2

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 AAASyracuse Mets · 61 IPFIP 4.45 → 5.00 (+0.55)K% 30.4% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.36%	—	×0.860	26.11%
BB% (unintentional) /BF	8.10%	—	×0.900	7.29%
HR / BF /BF	5.26%	÷1.000	×1.100	5.79%

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 4.45 → 5.00, 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 AABirmingham Barons · 42 IPFIP 2.08 → 3.15 (+1.07)K% 36.1% → 29.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.14%	—	×0.810	29.28%
BB% (unintentional) /BF	10.84%	—	×1.100	11.93%
HR / BF /BF	1.20%	÷0.784	×1.200	1.84%

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 57).

Result: FIP 2.08 → 3.15, 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).

2025 AAACharlotte Knights · 14 IPFIP 3.54 → 3.48 (−0.06)K% 32.8% → 28.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.76%	—	×0.860	28.17%
BB% (unintentional) /BF	10.34%	—	×0.900	9.31%
HR / BF /BF	3.45%	÷1.320	×1.100	2.87%

Result: FIP 3.54 → 3.48, 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+Winston-Salem Dash · 41 IPFIP 2.05 → 3.24 (+1.19)K% 34.3% → 26.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.32%	—	×0.770	26.43%
BB% (unintentional) /BF	9.47%	—	×1.150	10.89%
HR / BF /BF	1.18%	÷0.817	×1.250	1.81%

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 63).

Result: FIP 2.05 → 3.24, 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 AABirmingham Barons · 10 IPFIP 0.17 → 1.03 (+0.86)K% 47.2% → 38.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	47.22%	—	×0.810	38.25%
BB% (unintentional) /BF	8.33%	—	×1.100	9.17%
HR / BF /BF	0.00%	÷0.935	×1.200	0.00%

Result: FIP 0.17 → 1.03, 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).

2023 AKannapolis Cannon Ballers · 8 IPFIP 1.86 → 2.73 (+0.87)K% 29.3% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.27%	—	×0.740	21.66%
BB% (unintentional) /BF	9.76%	—	×1.180	11.51%
HR / BF /BF	0.00%	÷0.861	×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 72).

Result: FIP 1.86 → 2.73, 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
Zach Franklin (OGILVIE)	—	—	—	—	—	3.7%	—	4.63	26.9%	16.6%	112	+0.18	—	—	—
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	87
Matt Ramsey R 2018 · 3.78 FIP	28	SU	3.78	24.9%	8.8%	3.0%	.276	2.42	21.7%	12.6%	34	-1.36	2.42	125	87
Kiko Calero R 2003 · 3.54 FIP	28	SU	3.54	31.5%	11.1%	3.1%	.273	3.11	26.1%	18.9%	159	-0.43	2.27	298	85
Michael Flynn R 2024 · 3.99 FIP	27	SU	3.99	27.6%	8.3%	3.9%	.277	4.68	16.2%	3.7%	50	+0.69	3.89	168	83
Jason Stoffel R 2016 · 3.49 FIP	27	SU	3.49	27.2%	8.0%	3.0%	.293	—	—	—	—	—	3.49	103	83
Fernando Rodriguez Jr. R 2012 · 3.90 FIP	28	SU	3.90	25.2%	8.7%	3.3%	.299	3.34	26.5%	16.9%	75	-0.56	3.34	335	83
Dayan Díaz R 2017 · 3.45 FIP	28	SU	3.45	25.1%	8.7%	2.5%	.358	3.96	29.4%	19.3%	16	+0.51	3.08	205	82
Scott Atchison R 2004 · 3.61 FIP	28	SU	3.61	27.1%	9.0%	3.0%	.309	4.55	19.1%	11.5%	31	+0.94	2.52	340	80
Jon Edwards R 2015 · 3.40 FIP	27	SU	3.40	31.7%	13.1%	2.4%	.264	2.40	30.3%	22.6%	30	-1.00	2.40	132	80
Zach Putnam R 2015 · 3.47 FIP	28	SU	3.47	30.2%	9.0%	3.2%	.287	2.94	26.3%	17.5%	27	-0.53	2.91	131	80
Matt Pushard R 2024 · 3.87 FIP	26	SU	3.87	24.1%	8.9%	3.0%	.242	3.29	22.2%	14.0%	115	-0.58	2.84	220	80
Jason Bulger R 2008 · 4.60 FIP	29	SU	4.60	27.4%	12.3%	4.1%	.293	3.94	25.1%	13.3%	90	-0.66	3.78	106	80
Al Alburquerque R 2014 · 3.62 FIP	28	SU	3.62	26.7%	8.5%	3.1%	.267	3.27	21.8%	11.6%	147	-0.35	1.73	391	79
Trent Harris R 2024 · 3.45 FIP	25	SU	3.45	26.9%	9.5%	2.6%	.258	3.36	24.7%	16.7%	121	-0.09	3.06	198	78
Peyton Gray R 2021 · 4.27 FIP	26	SU	4.27	29.2%	14.1%	3.4%	.307	—	—	—	—	—	3.62	160	78
Steve Delabar R 2012 · 3.82 FIP	29	SU	3.82	33.6%	9.1%	4.4%	.234	3.44	26.9%	15.9%	139	-0.38	2.43	229	78
Taylor Cole R 2018 · 3.70 FIP	28	SU	3.70	25.4%	10.4%	2.6%	.291	3.49	22.0%	13.9%	72	-0.21	3.49	433	78
Brooks Kriske R 2021 · 4.95 FIP	27	SU	4.95	28.6%	12.1%	5.0%	.261	4.27	30.0%	17.8%	88	-0.68	3.09	246	78
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	78
Brooks Pounders R 2019 · 4.16 FIP	28	SU	4.16	24.5%	8.0%	3.9%	.276	—	—	—	—	—	3.34	307	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	0.9	60	27.3%	10.2%	1.48	4.52
Noé Ramirez ('22)	1.5	59	24.8%	9.4%	1.42	4.21
Colin Poche ('25)	1.1	54	26.7%	10.2%	1.32	4.01
Robert Stephenson ('25)	1.9	62	25.9%	10.1%	1.54	4.59
Buddy Schultz ('75-'79, 2 WAR*)	1.2	60	27.4%*	8.5%*	1.21*	4.14*
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*
Pete Ladd ('79-'86, 0 WAR*)	1.4	72	24.6%*	7.8%*	1.53*	4.42*