Peyton Battenfield

P Albuquerque Isotopes

Age 29 RHP 6'4" / 224 lbs AAA peak 0.2 · 2028

Overview

AAASPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	24	AAACLE	28	28	154	3.63	4.23	17.0%	8.9%	—	K 15.0% · BB 9.4% · FIP 4.62
2023	25	MIX3 levels	20	19	99	5.18	5.82	14.3%	10.2%	-0.5	K 13.1% · BB 9.3% · FIP 6.16
2024	26	AAACOL	26	24	118	7.45	6.13	14.8%	8.7%	—	K 12.7% · BB 7.8% · FIP 5.98
2025	27	No MLB games played
2026	28	No MLB games played
2027PROJ	29	MLBCOL	3	3	16	5.35	5.39	15.3%	8.8%	0.0
2028PROJ37% MLB	30	MLBCOL	8	8	45	5.38	5.48	15.2%	9.0%	-0.0
2029PROJ55% MLB	31	MLBCOL	9	9	55	5.49	5.62	15.0%	9.3%	-0.1

Last 3 seasons WAR -0.5 · Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2023

K%25

FB Velo10

xwOBA vs10

CompsNate Long (age 29) · Greg Peavey (age 27) · Scott Carroll (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 136127vR 119

ERA5.35

FIP5.39

K%15.3%

BB%8.8%

K-BB%6.5%

Proj IP165

Value2027 · WAR

Runs saved vs league avg · 165 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL5050

CMD4545

K†3030

Statcast Percentiles

FB Velo

p1090.8

Whiff%

p4624.7%

p2518.5%

xwOBA vs

p100.375

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	23	MIX MLE	2 levels	21	19	103	398	131	19	11	90%	4.9	26.2%	5.3%	20.9%	3.7%	2.53	3.58	—
2021	23	MIX RAW	2 levels	21	19	103	398	131	19	11	90%	4.9	32.9%	4.8%	28.1%	2.8%	2.53	2.50	—
2022	24	AAA MLE	Columbus Clippers	28	28	154	640	109	57	17	100%	5.5	15.0%	9.4%	5.6%	2.9%	3.63	4.62	—
2022	24	AAA RAW	Columbus Clippers	28	28	154	640	109	57	17	100%	5.5	17.0%	8.9%	8.1%	2.7%	3.63	4.23	—
2023	25	MIX MLE	3 levels	20	19	99	420	60	43	20	95%	5.0	13.1%	9.3%	3.8%	5.4%	5.18	6.16	-0.8
2023	25	MIX RAW	3 levels	20	19	99	420	60	43	20	95%	5.0	14.3%	10.2%	4.0%	4.8%	5.18	5.82	-0.5
2024	26	AAA MLE	Albuquerque Isotopes	26	24	118	540	80	47	29	92%	4.6	12.7%	7.8%	4.9%	5.4%	7.45	5.98	—
2024	26	AAA MLE	Albuquerque Isotopes	26	24	118	540	80	47	29	92%	4.6	12.7%	7.8%	4.9%	5.4%	7.45	5.98	—
2024	26	AAA RAW	Albuquerque Isotopes	26	24	118	540	80	47	29	92%	4.6	14.8%	8.7%	6.1%	5.4%	7.45	6.13	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			7	6	35	146	27	12	7	86%	5.0	18.5%	8.2%	10.3%	4.8%	5.19	5.21	+0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	COL	3	3	16	68	10	6	3	100%	5.3	15.3%	8.8%	6.5%	3.8%	5.35	5.39	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	COL	20	20	122	515	79	46	20	100%	6.1	15.2%	9.0%	6.2%	3.9%	5.38	5.48	-0.1
2029	31	MLB MLE	COL	17	17	100	422	63	39	17	100%	5.9	15.0%	9.3%	5.8%	4.1%	5.49	5.62	-0.2
2028	30	MLB CTX	COL	8	8	45	190	29	17	7	100%	5.6	15.2%	9.0%	6.2%	3.9%	5.38	5.48	-0.0
2029	31	MLB CTX	COL	9	9	55	232	35	22	9	100%	6.1	15.0%	9.3%	5.8%	4.1%	5.49	5.62	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		24	23	135	568	91	51	24	96%	5.6	16.0%	8.9%	7.1%	4.2%	5.38	5.18	+0.3
/ 200 IP	—	RAW		35	34	200	844	135	76	36	96%	5.7	16.0%	8.9%	7.1%	4.2%	5.38	5.18	+0.5
Career	—	MLE		95	90	474	1998	324	162	85	95%	5.0	16.2%	8.1%	8.1%	4.3%	4.67	5.10	-0.3
/ 200 IP	—	MLE		40	38	200	843	137	68	36	95%	5.0	16.2%	8.1%	8.1%	4.3%	4.67	5.10	-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.

2024 AAAAlbuquerque Isotopes · 118 IPFIP 5.90 → 5.98 (+0.08)K% 14.8% → 12.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.81%	—	×0.860	12.74%
BB% (unintentional) /BF	8.70%	—	×0.900	7.83%
HR / BF /BF	5.37%	÷1.096	×1.100	5.39%

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 119).

Result: FIP 5.90 → 5.98, 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).

2023 AAASyracuse Mets · 57 IPFIP 6.44 → 6.72 (+0.28)K% 11.4% → 9.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	11.43%	—	×0.860	9.83%
BB% (unintentional) /BF	11.02%	—	×0.900	9.92%
HR / BF /BF	5.31%	÷1.003	×1.100	5.82%

Result: FIP 6.44 → 6.72, 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 AAAkron RubberDucks · 8 IPFIP 3.39 → 3.84 (+0.45)K% 17.2% → 14.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.24%	—	×0.810	13.97%
BB% (unintentional) /BF	13.79%	—	×1.100	15.17%
HR / BF /BF	0.00%	÷0.909	×1.200	0.00%

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 82).

Result: FIP 3.39 → 3.84, 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 AAAColumbus Clippers · 154 IPFIP 4.25 → 4.62 (+0.37)K% 17.0% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.03%	—	×0.880	14.99%
BB% (unintentional) /BF	8.91%	—	×1.050	9.35%
HR / BF /BF	2.66%	÷1.001	×1.100	2.92%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, 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 4.25 → 4.62, 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).

2021 AAAkron RubberDucks · 72 IPFIP 3.03 → 4.16 (+1.13)K% 29.1% → 23.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.08%	—	×0.810	23.55%
BB% (unintentional) /BF	4.96%	—	×1.100	5.46%
HR / BF /BF	3.19%	÷0.893	×1.200	4.29%

Result: FIP 3.03 → 4.16, 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 A+Bowling Green Hot Rods · 31 IPFIP 1.03 → 2.19 (+1.17)K% 42.2% → 32.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	42.24%	—	×0.770	32.53%
BB% (unintentional) /BF	4.31%	—	×1.150	4.96%
HR / BF /BF	1.72%	÷0.978	×1.250	2.20%

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 96).

Result: FIP 1.03 → 2.19, 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
Peyton Battenfield (OGILVIE)	—	—	5.39	15.3%	8.8%	3.8%	—	5.54	15.1%	6.0%	222	+0.15	—	—	—
Nate Long R 2015 · 4.67 FIP	29	SP	4.67	14.8%	10.6%	2.7%	.285	—	—	—	—	—	4.67	151	80
Greg Peavey R 2015 · 4.39 FIP	27	SP	4.39	11.2%	6.5%	2.6%	.289	—	—	—	—	—	4.39	147	75
Scott Carroll R 2014 · 4.35 FIP	29	SP-	4.35	11.2%	7.7%	2.2%	.296	4.52	11.9%	3.7%	248	+0.17	3.92	377	75
Cory Riordan R 2016 · 4.24 FIP	30	SP	4.24	14.3%	5.0%	3.1%	.341	—	—	—	—	—	4.24	154	75
Merrill Kelly R 2019 · 4.41 FIP	30	SP	4.41	20.3%	6.8%	4.0%	.289	3.83	21.1%	14.8%	390	-0.58	3.60	1,170	74
Scott Copeland R 2017 · 4.90 FIP	29	SP	4.90	16.9%	8.7%	3.9%	.325	4.53	16.2%	6.0%	240	-0.37	3.55	569	73
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	73
Travis Driskill R 2002 · 4.95 FIP	30	SP-	4.95	13.2%	8.0%	3.6%	.291	4.26	15.3%	12.0%	48	-0.69	4.26	181	72
Caleb Boushley R 2023 · 4.79 FIP	29	SP	4.79	16.3%	7.9%	3.8%	.294	4.15	17.0%	11.5%	211	-0.64	3.05	790	71
Miguel González R 2013 · 4.24 FIP	29	SP	4.24	16.9%	7.0%	3.0%	.257	4.24	17.3%	10.2%	460	+0.00	3.72	905	70
Caleb Clay R 2015 · 4.67 FIP	27	SP	4.67	9.9%	6.9%	2.8%	.324	—	—	—	—	—	4.67	111	70
Scott Richmond R 2009 · 5.11 FIP	29	SP	5.11	19.2%	9.5%	4.4%	.294	—	—	—	—	—	2.80	166	70
Andres Ivan Meza R 2015 · 4.45 FIP	28	SP	4.45	10.9%	5.6%	2.9%	.322	4.14	12.5%	4.0%	85	-0.31	4.14	275	69
Tim Melville R 2019 · 5.65 FIP	29	SP	5.65	18.2%	9.2%	5.3%	.297	—	—	—	—	—	3.67	471	68
Octavio Acosta R 2019 · 4.19 FIP	28	SP	4.19	14.9%	8.3%	2.4%	.364	—	—	—	—	—	3.88	333	68
Luke Irvine R 2016 · 4.31 FIP	27	SP-	4.31	13.4%	9.8%	2.0%	.302	—	—	—	—	—	4.31	104	68
David Martinez R 2017 · 4.88 FIP	29	SP	4.88	15.0%	8.2%	3.7%	.292	—	—	—	—	—	3.92	309	67
Robert Ellis R 2001 · 4.84 FIP	30	SP	4.84	9.9%	7.7%	2.9%	.287	8.08	9.0%	-2.2%	18	+3.24	4.84	110	67
Randy Wynne R 2022 · 5.07 FIP	29	SP	5.07	12.9%	6.2%	4.2%	.290	6.40	12.5%	7.4%	227	+1.33	4.35	461	67
Tyler Wilson R 2017 · 4.45 FIP	27	SP-	4.45	12.1%	7.0%	2.7%	.311	—	—	—	—	—	3.62	377	67

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	2.1	105	15.5%	8.9%	1.54	5.38
Brandon Claussen ('06)	1.6	105	16.0%	8.5%	1.37	5.04
Dan Wright ('04)	1.8	122	13.7%	10.2%	1.60	5.65
Armando Galarraga ('12)	2.7	108	14.6%	9.6%	1.56	4.78
Paul Mitchell ('75-'80, 1 WAR*)	3.1	104	16.7%*	7.1%*	1.59*	4.98*
Jerry Ujdur ('80-'84, -1 WAR*)	1.3	87	16.2%*	9.7%*	1.82*	5.05*
Ken Schrom ('80-'87, 3 WAR*)	4.5	150	13.4%*	8.1%*	1.41*	4.77*