Buck Farmer

P Louisville Bats

Age 36 RHP 6'4" / 243 lbs AAA peak 0.3 · 2027

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	32	MLBCIN	71	0	75	4.20	4.30	22.7%	9.4%	0.2
2024	33	MLBCIN	61	1	71	3.04	3.38	23.4%	7.7%	1.0
2025	34	MIX2 levels	48	0	52	4.47	3.42	21.6%	11.2%	—	K 18.7% · BB 11.8% · FIP 4.03
2026	35	No MLB games played
2027PROJ	36	MLBCIN	17	0	18	4.21	4.46	21.2%	10.0%	0.0
2028PROJ	37	MLBCIN	109	0	114	4.60	4.86	20.1%	10.6%	-0.4
2029PROJ	38	MLBCIN	78	0	82	5.02	5.30	19.0%	11.3%	-0.7

Last 3 seasons WAR 1.2 · Next 3 projected WAR -1.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

K%57

xwOBA vs45

FB Velo25

CompsKeiichi Yabu (age 36) · Juan Sandoval (age 36) · Zack Segovia (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 115107vR 98

ERA4.21

FIP4.46

K%21.2%

BB%10.0%

K-BB%11.2%

Proj IP175

Value2027 · WAR

Runs saved vs league avg · 175 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p2592.7

Whiff%

p5526.1%

p5723.4%

xwOBA vs

p450.317

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)
2014	23	MLB MLE	Detroit Tigers	4	2	9	46	11	5	2	50%	2.3	23.9%	10.9%	13.0%	4.3%	11.57	4.84	+0.1
2014	23	MLB RAW	Detroit Tigers	4	2	9	46	11	5	2	50%	2.3	23.9%	10.9%	13.0%	4.3%	11.57	5.14	+0.0
2015	24	MIX MLE	2 levels	30	21	127	554	100	40	16	70%	4.2	16.4%	7.4%	9.0%	3.2%	5.17	4.41	+1.5
2015	24	MIX RAW	2 levels	30	21	127	554	100	40	16	70%	4.2	18.1%	7.2%	10.8%	2.9%	5.17	4.11	+1.9
2016	25	MIX MLE	2 levels	34	21	129	557	120	47	15	62%	3.8	19.5%	8.7%	10.9%	3.2%	4.11	4.29	+1.7
2016	25	MIX RAW	2 levels	34	21	129	557	120	47	15	62%	3.8	21.5%	8.4%	13.1%	2.7%	4.11	3.84	+2.4
2017	26	MIX MLE	2 levels	32	32	172	738	163	50	18	100%	5.4	20.2%	7.0%	13.3%	2.6%	4.72	3.68	+3.6
2017	26	MIX RAW	2 levels	32	32	172	738	163	50	18	100%	5.4	22.1%	6.8%	15.3%	2.4%	4.72	3.44	+4.1
2018	27	MLB MLE	Detroit Tigers	66	1	69	308	57	40	6	2%	1.1	18.5%	13.0%	5.5%	2.0%	4.15	4.30	+0.2
2018	27	MLB RAW	Detroit Tigers	66	1	69	308	57	40	6	2%	1.1	18.5%	13.0%	5.5%	1.9%	4.15	4.31	+0.2
2019	28	MLB MLE	Detroit Tigers	73	1	68	288	73	22	8	1%	0.9	25.3%	7.6%	17.7%	2.9%	3.72	3.52	+0.8
2019	28	MLB RAW	Detroit Tigers	73	1	68	288	73	22	8	1%	0.9	25.3%	7.6%	17.7%	2.8%	3.72	3.45	+0.9
2020	29	MLB MLE	Detroit Tigers	23	0	21	89	14	5	3	0%	0.9	15.7%	5.6%	10.1%	3.5%	3.80	4.42	+0.0
2020	29	MLB RAW	Detroit Tigers	23	0	21	89	14	5	3	0%	0.9	15.7%	5.6%	10.1%	3.4%	3.80	4.32	+0.1
2021	30	MIX MLE	2 levels	60	0	62	280	59	30	10	0%	1.0	20.1%	10.9%	9.2%	3.8%	5.25	4.85	-0.2
2021	30	MIX RAW	2 levels	60	0	62	280	59	30	10	0%	1.0	21.1%	10.7%	10.4%	3.6%	5.25	4.75	-0.1
2022	31	MIX MLE	2 levels	64	0	69	291	88	34	6	0%	1.1	28.8%	11.8%	17.0%	1.8%	3.76	3.16	+1.1
2022	31	MIX RAW	2 levels	64	0	69	291	88	34	6	0%	1.1	30.2%	11.7%	18.6%	2.1%	3.76	3.16	+1.2
2023	32	MLB MLE	Cincinnati Reds	71	0	75	309	70	29	11	0%	1.1	22.7%	9.4%	13.3%	3.3%	4.20	4.19	+0.3
2023	32	MLB RAW	Cincinnati Reds	71	0	75	309	70	29	11	0%	1.1	22.7%	9.4%	13.3%	3.6%	4.20	4.30	+0.2
2024	33	MLB MLE	Cincinnati Reds	61	1	71	299	70	23	7	2%	1.2	23.4%	7.7%	15.7%	2.2%	3.04	3.29	+1.1
2024	33	MLB MLE	Cincinnati Reds	61	1	71	299	70	23	7	2%	1.2	23.4%	7.7%	15.7%	2.2%	3.04	3.29	+1.1
2024	33	MLB RAW	Cincinnati Reds	61	1	71	299	70	23	7	2%	1.2	23.4%	7.7%	15.7%	2.3%	3.04	3.38	+1.0
2025	34	MIX MLE	2 levels	48	0	52	232	50	26	3	0%	1.1	18.7%	11.8%	6.9%	1.8%	4.47	4.03	—
2025	34	MIX MLE	2 levels	48	0	52	232	50	26	3	0%	1.1	18.7%	11.8%	6.9%	1.8%	4.47	4.03	—
2025	34	MIX RAW	2 levels	48	0	52	232	50	26	3	0%	1.1	21.6%	11.2%	10.3%	1.3%	4.47	3.42	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			417	22	514	2245	486	223	71	5%	1.2	21.6%	9.9%	11.7%	3.2%	4.71	4.31	+1.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	CIN	17	0	18	76	16	8	2	0%	1.1	21.2%	10.0%	11.2%	2.8%	4.21	4.46	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	CIN	109	0	114	483	97	51	15	0%	1.1	20.1%	10.6%	9.5%	3.2%	4.60	4.86	-0.4
2029	38	MLB MLE	CIN	78	0	82	345	65	39	12	0%	1.0	19.0%	11.3%	7.7%	3.6%	5.02	5.30	-0.7
2028	37	MLB CTX	CIN	109	0	114	481	97	51	15	0%	1.0	20.1%	10.6%	9.5%	3.2%	4.60	4.86	-0.4
2029	38	MLB CTX	CIN	78	0	82	346	66	39	13	0%	1.1	19.0%	11.3%	7.7%	3.6%	5.02	5.30	-0.7
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		604	22	710	3073	649	313	99	4%	1.2	21.1%	10.2%	10.9%	3.2%	4.73	4.37	+1.5
/ 200 IP	—	RAW		170	6	200	866	183	88	28	4%	1.2	21.1%	10.2%	10.9%	3.2%	4.73	4.37	+0.4
Career	—	MLE		566	79	925	3991	828	358	111	14%	1.6	20.7%	9.0%	11.8%	2.8%	4.41	4.01	+0.3
/ 200 IP	—	MLE		122	17	200	863	179	77	24	14%	1.6	20.7%	9.0%	11.8%	2.8%	4.41	4.01	+0.1

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.

2025 AAALouisville Bats · 44 IPFIP 3.76 → 4.03 (+0.27)K% 21.7% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.72%	—	×0.860	18.68%
BB% (unintentional) /BF	13.13%	—	×0.900	11.82%
HR / BF /BF	1.52%	÷0.901	×1.100	1.85%

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 80).

Result: FIP 3.76 → 4.03, 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 ROKACL Reds · 8 IPFIP 1.36 → 1.92 (+0.56)K% 20.6% → 14.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.59%	—	×0.680	14.00%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
HR / BF /BF	0.00%	÷1.252	×1.400	0.00%

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 150).

Result: FIP 1.36 → 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).

2022 AAALouisville Bats · 22 IPFIP 3.60 → 3.70 (+0.10)K% 37.0% → 32.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.96%	—	×0.880	32.52%
BB% (unintentional) /BF	9.78%	—	×1.050	10.27%
HR / BF /BF	4.35%	÷1.282	×1.100	3.73%

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 156).

Result: FIP 3.60 → 3.70, 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 AAARound Rock Express · 26 IPFIP 3.06 → 3.40 (+0.34)K% 20.2% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.18%	—	×0.880	17.76%
BB% (unintentional) /BF	9.17%	—	×1.050	9.63%
HR / BF /BF	0.92%	÷0.958	×1.100	1.05%

Result: FIP 3.06 → 3.40, 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).

2017 AAAToledo Mud Hens · 124 IPFIP 2.93 → 3.23 (+0.31)K% 22.0% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.97%	—	×0.880	19.33%
BB% (unintentional) /BF	5.78%	—	×1.050	6.07%
HR / BF /BF	1.73%	÷1.049	×1.100	1.82%

Result: FIP 2.93 → 3.23, 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).

2016 AAAToledo Mud Hens · 100 IPFIP 3.51 → 4.09 (+0.58)K% 21.8% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.83%	—	×0.880	19.21%
BB% (unintentional) /BF	6.57%	—	×1.050	6.90%
HR / BF /BF	2.58%	÷0.899	×1.100	3.16%

Result: FIP 3.51 → 4.09, 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).

2015 AAAToledo Mud Hens · 87 IPFIP 3.11 → 3.55 (+0.44)K% 20.7% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.65%	—	×0.880	18.17%
BB% (unintentional) /BF	6.79%	—	×1.050	7.13%
HR / BF /BF	1.63%	÷0.911	×1.100	1.97%

Result: FIP 3.11 → 3.55, 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
Buck Farmer (OGILVIE)	—	—	—	—	—	2.8%	—	5.04	19.7%	8.7%	196	+0.58	—	—	—
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	55
Juan Sandoval R 2017 · 3.42 FIP	36	SU	3.42	16.7%	7.2%	1.5%	.298	5.41	15.9%	8.7%	57	+1.99	3.24	225	52
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	49
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	49
Francisco Del Rosario R 2017 · 4.15 FIP	36	SU	4.15	16.4%	10.0%	2.1%	.267	6.35	11.9%	-0.6%	77	+2.20	3.93	194	49
Pete Walker R 2005 · 4.79 FIP	36	SU	4.79	12.0%	9.2%	2.8%	.261	4.45	19.6%	11.6%	30	-0.34	4.45	327	48
Daniel Guerrero R 2019 · 5.59 FIP	34	SW	5.59	14.7%	11.1%	4.2%	.353	—	—	—	—	—	4.61	269	45
Erubiel Gonzalez R 2015 · 3.43 FIP	36	SU	3.43	12.4%	6.0%	1.1%	.328	3.26	14.8%	10.4%	69	-0.17	2.99	119	43
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	43
Daniel Bard R 2021 · 3.62 FIP	36	SU	3.62	26.3%	11.5%	2.3%	.337	3.64	24.6%	10.3%	110	+0.02	2.56	456	42
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	42
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	41
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	40
Jesus Adrian Castillo R 2019 · 5.13 FIP	35	SU	5.13	13.1%	7.8%	3.9%	.319	—	—	—	—	—	2.23	173	39
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	39
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	37
Matt Bush R 2022 · 3.73 FIP	36	SU	3.73	30.3%	6.6%	4.3%	.224	3.79	26.2%	17.5%	36	+0.06	2.87	249	36
Masato Yoshii R 2001 · 4.64 FIP	36	SW	4.64	12.8%	4.9%	3.6%	.281	4.15	13.4%	8.0%	131	-0.49	4.15	757	35
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	34
Brian Sweeney R 2010 · 4.63 FIP	36	SU	4.63	9.5%	3.4%	3.5%	.226	—	—	—	—	—	3.03	108	33

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	4.4	68	21.1%	10.5%	1.21	4.63
Jay Witasick ('07)	3.7	73	19.6%	11.0%	1.19	4.64
Chris Stratton ('25)	3.1	69	21.0%	9.5%	1.02	4.64
Dustin McGowan ('17)	3.3	65	19.2%	9.9%	1.08	4.50
Ed Farmer ('71-'83, -2 WAR*)	3.1	69	21.3%*	12.2%*	1.03*	4.71*
George Frazier ('78-'87, 2 WAR*)	3.4	68	21.6%*	10.5%*	0.92*	4.42*
Pete Mikkelsen ('64-'72, 1 WAR*)	3.3	73	20.1%*	9.3%*	1.12*	4.15*