T.J. McFarland

P Athletics

Age 38 LHP 6'3" / 200 lbs MLB

Overview

MLBRP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	34	MIX2 levels	47	0	64	2.38	2.62	24.9%	9.7%	1.5	K 21.7% · BB 8.8% · FIP 2.84
2024	35	MLBOakland Athle…	79	0	57	3.81	3.28	16.6%	5.1%	0.9
2025	36	MIX2 levels	28	0	17	7.02	5.02	10.3%	3.8%	-0.1	K 9.5% · BB 4.1% · FIP 4.34
2026	37	No MLB games played
2027PROJ	38	MLBOAK	47	0	49	4.37	4.53	17.5%	7.5%	0.0
2028PROJ	39	MLBOAK	29	0	30	4.72	4.96	16.4%	8.2%	-0.1

Last 3 seasons WAR 2.3 · Next 2 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo10

K%10

xwOBA vs10

CompsHisanori Takahashi (age 37) · Juan Sandoval (age 38) · Keiichi Yabu (age 39)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 103111vR 119

ERA4.37

FIP4.53

K%17.5%

BB%7.5%

K-BB%10.0%

Proj IP49

Value2027 · WAR

Runs saved vs league avg · 49 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1087.3

Whiff%

p1017.1%

p109.5%

xwOBA vs

p100.359

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)
2013	24	MLB MLE	Baltimore Orioles	38	1	75	331	58	23	7	3%	2.0	17.5%	6.9%	10.6%	1.9%	4.22	3.55	+0.9
2013	24	MLB RAW	Baltimore Orioles	38	1	75	331	58	23	7	3%	2.0	17.5%	6.9%	10.6%	2.1%	4.22	3.69	+0.8
2014	25	MLB MLE	Baltimore Orioles	37	1	59	255	34	11	2	3%	1.6	13.3%	4.3%	9.0%	0.7%	2.76	2.91	+1.2
2014	25	MLB RAW	Baltimore Orioles	37	1	59	255	34	11	2	3%	1.6	13.3%	4.3%	9.0%	0.8%	2.76	2.95	+1.1
2015	26	MIX MLE	2 levels	46	9	93	398	57	27	4	20%	2.0	13.4%	7.0%	6.4%	0.9%	3.77	3.35	+1.3
2015	26	MIX RAW	2 levels	46	9	93	398	57	27	4	20%	2.0	14.3%	6.8%	7.5%	1.0%	3.77	3.30	+1.4
2016	27	MIX MLE	5 levels	29	8	59	265	26	17	9	28%	2.0	7.4%	6.8%	0.6%	3.1%	5.76	5.03	-0.3
2016	27	MIX RAW	5 levels	29	8	59	265	26	17	9	28%	2.0	9.8%	6.4%	3.4%	3.4%	5.76	5.06	-0.3
2017	28	MIX MLE	2 levels	50	1	65	280	38	15	4	2%	1.3	12.0%	4.6%	7.5%	1.6%	4.43	3.56	+0.8
2017	28	MIX RAW	2 levels	50	1	65	280	38	15	4	2%	1.3	13.6%	5.4%	8.2%	1.4%	4.43	3.42	+0.9
2018	29	MLB MLE	Arizona Diamondbacks	47	0	72	292	42	19	4	0%	1.5	14.4%	6.5%	7.9%	1.4%	2.00	3.51	+0.9
2018	29	MLB RAW	Arizona Diamondbacks	47	0	72	292	42	19	4	0%	1.5	14.4%	6.5%	7.9%	1.4%	2.00	3.45	+0.9
2019	30	MIX MLE	2 levels	54	0	60	266	42	16	7	0%	1.1	14.0%	6.0%	8.0%	2.5%	4.80	4.07	+0.3
2019	30	MIX RAW	2 levels	54	0	60	266	42	16	7	0%	1.1	15.8%	6.0%	9.8%	2.6%	4.80	4.02	+0.4
2020	31	MLB MLE	Oakland Athletics	23	0	21	92	9	5	5	0%	0.9	9.8%	5.4%	4.3%	6.0%	4.35	6.24	-0.4
2020	31	MLB RAW	Oakland Athletics	23	0	21	92	9	5	5	0%	0.9	9.8%	5.4%	4.3%	5.4%	4.35	6.10	-0.4
2021	32	MIX MLE	2 levels	60	0	70	276	55	14	6	0%	1.2	18.4%	5.2%	13.3%	2.4%	3.49	3.53	+0.8
2021	32	MIX RAW	2 levels	60	0	70	276	55	14	6	0%	1.2	19.9%	5.1%	14.9%	2.2%	3.49	3.24	+1.1
2022	33	MIX MLE	2 levels	45	0	51	217	31	15	7	0%	1.1	13.5%	7.0%	6.5%	3.4%	5.68	4.74	-0.1
2022	33	MIX RAW	2 levels	45	0	51	217	31	15	7	0%	1.1	14.3%	6.9%	7.4%	3.2%	5.68	4.56	-0.0
2023	34	MIX MLE	2 levels	47	0	64	277	69	27	2	0%	1.4	21.7%	8.8%	12.9%	0.8%	2.38	2.84	+1.3
2023	34	MIX RAW	2 levels	47	0	64	277	69	27	2	0%	1.4	24.9%	9.7%	15.2%	0.7%	2.38	2.62	+1.5
2024	35	MLB MLE	Oakland Athletics	79	0	57	235	39	12	4	0%	0.7	16.6%	5.1%	11.5%	1.9%	3.81	3.37	+0.8
2024	35	MLB MLE	Oakland Athletics	79	0	57	235	39	12	4	0%	0.7	16.6%	5.1%	11.5%	1.9%	3.81	3.37	+0.8
2024	35	MLB RAW	Oakland Athletics	79	0	57	235	39	12	4	0%	0.7	16.6%	5.1%	11.5%	1.7%	3.81	3.28	+0.9
2025	36	MIX MLE	2 levels	28	0	17	78	8	3	3	0%	0.6	9.5%	4.1%	5.4%	2.8%	7.02	4.34	+0.0
2025	36	MIX MLE	2 levels	28	0	17	78	8	3	3	0%	0.6	9.5%	4.1%	5.4%	2.8%	7.02	4.34	+0.0
2025	36	MIX RAW	2 levels	28	0	17	78	8	3	3	0%	0.6	10.3%	3.8%	6.4%	3.8%	7.02	5.02	-0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			460	3	546	2370	325	140	49	1%	1.2	13.7%	5.9%	7.8%	2.1%	4.18	3.84	+4.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	38	MLB	OAK	47	0	49	207	36	16	6	0%	1.0	17.5%	7.5%	10.0%	2.9%	4.37	4.53	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	39	MLB MLE	OAK	28	0	30	126	21	10	4	0%	1.1	16.4%	8.2%	8.2%	3.3%	4.72	4.96	-0.1
2028	39	MLB CTX	OAK	29	0	30	127	21	10	4	0%	1.0	16.4%	8.2%	8.2%	3.3%	4.72	4.96	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		488	3	576	2496	346	150	53	1%	1.2	13.8%	6.0%	7.8%	2.1%	4.21	3.86	+4.7
/ 200 IP	—	RAW		170	1	200	866	120	52	18	1%	1.2	13.8%	6.0%	7.8%	2.1%	4.21	3.86	+1.6
Career	—	MLE		583	20	761	3262	473	201	64	3%	1.3	14.5%	6.2%	8.3%	2.0%	3.94	3.73	+4.4
/ 200 IP	—	MLE		153	5	200	857	124	53	17	3%	1.3	14.5%	6.2%	8.3%	2.0%	3.94	3.73	+1.5

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.

2023 AAANorfolk Tides · 63 IPFIP 2.62 → 2.84 (+0.22)K% 25.2% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.19%	—	×0.860	21.66%
BB% (unintentional) /BF	9.77%	—	×0.900	8.80%
HR / BF /BF	0.75%	÷0.995	×1.100	0.83%

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 99).

Result: FIP 2.62 → 2.84, 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 AAAMemphis Redbirds · 18 IPFIP 3.57 → 3.89 (+0.32)K% 20.8% → 18.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.83%	—	×0.880	18.33%
BB% (unintentional) /BF	5.56%	—	×1.050	5.83%
HR / BF /BF	2.78%	÷1.048	×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 110).

Result: FIP 3.57 → 3.89, 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 AAAMemphis Redbirds · 31 IPFIP 2.75 → 3.24 (+0.49)K% 25.8% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.76%	—	×0.880	22.67%
BB% (unintentional) /BF	4.55%	—	×1.050	4.77%
HR / BF /BF	2.27%	÷0.949	×1.100	2.64%

Result: FIP 2.75 → 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).

2017 AAAReno Aces · 11 IPFIP 2.45 → 2.75 (+0.30)K% 23.1% → 20.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.880	20.31%
BB% (unintentional) /BF	10.26%	—	×1.050	10.77%
HR / BF /BF	0.00%	÷1.044	×1.100	0.00%

Result: FIP 2.45 → 2.75, 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 AAANorfolk Tides · 26 IPFIP 4.51 → 5.25 (+0.74)K% 9.6% → 8.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	9.65%	—	×0.880	8.49%
BB% (unintentional) /BF	6.14%	—	×1.050	6.45%
HR / BF /BF	2.63%	÷0.776	×1.100	3.73%

Result: FIP 4.51 → 5.25, 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 AAANorfolk Tides · 53 IPFIP 2.70 → 2.89 (+0.19)K% 14.8% → 13.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.76%	—	×0.880	12.99%
BB% (unintentional) /BF	6.67%	—	×1.050	7.00%
HR / BF /BF	0.00%	÷1.097	×1.100	0.00%

Result: FIP 2.70 → 2.89, 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
T.J. McFarland (OGILVIE)	—	—	—	—	—	2.9%	—	4.96	16.4%	8.2%	30	+0.43	—	—	—
Hisanori Takahashi L 2012 · 4.04 FIP	37	SU	4.04	24.5%	6.1%	4.1%	.295	—	—	—	—	—	3.50	240	59
Juan Sandoval R 2019 · 5.41 FIP	38	SU	5.41	15.9%	7.2%	5.0%	.273	—	—	—	—	—	3.24	225	36
Keiichi Yabu R 2008 · 3.48 FIP	39	SU	3.48	15.9%	9.3%	1.0%	.269	—	—	—	—	—	3.48	126	35
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	35
Hector Navarro R 2017 · 3.53 FIP	37	SU	3.53	11.5%	5.6%	1.3%	.283	—	—	—	—	—	2.30	126	34
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	32
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	32
Brian Sweeney R 2010 · 4.63 FIP	36	SU	4.63	9.5%	3.4%	3.5%	.226	—	—	—	—	—	3.03	108	31
Erubiel Gonzalez R 2017 · 3.51 FIP	38	SU	3.51	13.3%	2.5%	2.2%	.388	—	—	—	—	—	2.99	119	30
Billy Taylor R 2000 · 4.53 FIP	38	SU	4.53	21.0%	11.3%	3.2%	.275	—	—	—	—	—	2.94	323	30
Tony Pena Jr. R 2017 · 3.43 FIP	36	SU	3.43	10.9%	4.3%	1.3%	.312	—	—	—	—	—	2.80	128	29
Yoshihisa Hirano R 2020 · 5.02 FIP	36	SU	5.02	17.5%	12.7%	3.3%	.381	—	—	—	—	—	3.45	132	27
Jonathan Castellanos R 2019 · 5.24 FIP	37	SW	5.24	11.0%	9.0%	3.5%	.348	—	—	—	—	—	3.40	394	19
Logan Duran R 2019 · 3.66 FIP	37	SP-	3.66	15.5%	8.9%	1.4%	.427	—	—	—	—	—	3.42	187	14

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	3.1	48	14.1%	7.4%	0.85	4.22
Buddy Groom ('05)	3.7	52	15.3%	8.1%	0.89	4.64
Brandon Lyon ('13)	3.4	62	15.8%	7.5%	0.91	4.16
Shawn Camp ('14)	3.0	59	15.6%	6.8%	0.99	4.41
Juan Agosto ('81-'93, 1 WAR*)	3.1	63	15.0%*	9.2%*	0.59*	4.52*
Dave Tomlin ('72-'86, -2 WAR*)	2.6	64	18.0%*	8.6%*	0.87*	4.57*
Tony Castillo ('88-'98, 4 WAR*)	2.6	59	18.5%*	7.3%*	0.98*	3.76*