Andrew Heaney

P Los Angeles Dodgers

Age 36 LHP 6'2" / 200 lbs MLB peak 1.2 · 2027

Overview

MLBSP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	32	MLBTEX	34	28	147	4.15	4.30	23.6%	9.4%	1.9
2024	33	MLBTEX	32	31	160	4.28	3.73	22.9%	5.8%	3.2
2025	34	MIX2 levels	31	27	132	5.17	5.01	17.3%	7.4%	0.6	K 16.0% · BB 7.5% · FIP 5.15
2026	35	No MLB games played
2027PROJ	36	MLBLAD	19	19	116	4.55	4.49	19.9%	6.4%	1.2
2028PROJ	37	MLBLAD	11	11	68	4.75	4.89	18.9%	7.0%	0.4
2029PROJ	38	MLBLAD	6	6	36	5.09	5.32	17.7%	7.7%	0.0

Last 3 seasons WAR 5.7 · Next 3 projected WAR 1.7Projected 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

CompsTsuyoshi Wada (age 34) · Mauricio Lara (age 36) · Arturo Lopez (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 110118vR 126

ERA4.55

FIP4.49

K%19.9%

BB%6.4%

K-BB%13.6%

Proj IP116

Value2027 · WAR

Runs saved vs league avg · 116 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1090.1

Whiff%

p1219.9%

p1016.0%

xwOBA vs

p100.362

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	Miami Marlins	7	5	29	126	20	7	6	71%	4.2	15.9%	5.6%	10.3%	5.0%	5.83	5.21	+0.1
2014	23	MLB RAW	Miami Marlins	7	5	29	126	20	7	6	71%	4.2	15.9%	5.6%	10.3%	4.8%	5.83	5.11	+0.1
2015	24	MIX MLE	2 levels	32	32	184	792	152	52	11	100%	5.8	18.1%	6.7%	11.3%	1.4%	4.01	3.19	+5.0
2015	24	MIX RAW	2 levels	32	32	184	792	152	52	11	100%	5.8	19.2%	6.6%	12.6%	1.4%	4.01	3.07	+5.4
2016	25	MLB MLE	Los Angeles Angels	1	1	6	25	7	0	2	100%	6.0	28.0%	0.0%	28.0%	8.0%	6.00	5.13	+0.0
2016	25	MLB RAW	Los Angeles Angels	1	1	6	25	7	0	2	100%	6.0	28.0%	0.0%	28.0%	8.0%	6.00	5.10	+0.0
2017	26	MIX MLE	3 levels	11	11	49	213	56	14	14	100%	4.5	23.0%	7.7%	15.3%	8.2%	4.56	6.63	-0.7
2017	26	MIX RAW	3 levels	11	11	49	213	56	14	14	100%	4.5	26.3%	6.6%	19.7%	6.6%	4.56	5.37	+0.0
2018	27	MIX MLE	2 levels	31	31	186	771	186	46	27	100%	6.0	24.0%	6.0%	18.0%	3.5%	4.06	3.77	+3.7
2018	27	MIX RAW	2 levels	31	31	186	771	186	46	27	100%	6.0	24.1%	6.0%	18.2%	3.5%	4.06	3.73	+3.8
2019	28	MIX MLE	2 levels	19	19	100	425	128	30	20	100%	5.2	28.9%	7.1%	21.8%	4.8%	4.70	4.19	+1.4
2019	28	MIX RAW	2 levels	19	19	100	425	128	30	20	100%	5.2	30.1%	7.1%	23.1%	4.7%	4.70	4.04	+1.6
2020	29	MLB MLE	Los Angeles Angels	12	12	67	279	70	18	9	100%	5.6	25.1%	6.5%	18.6%	3.2%	4.46	3.53	+1.5
2020	29	MLB RAW	Los Angeles Angels	12	12	67	279	70	18	9	100%	5.6	25.1%	6.5%	18.6%	3.2%	4.46	3.56	+1.5
2021	30	MLB MLE	New York Yankees	30	23	130	558	150	41	29	77%	4.3	26.9%	7.3%	19.5%	4.9%	5.83	4.43	+1.5
2021	30	MLB RAW	New York Yankees	30	23	130	558	150	41	29	77%	4.3	26.9%	7.3%	19.5%	5.2%	5.83	4.64	+1.1
2022	31	MIX MLE	5 levels	21	19	93	386	139	20	18	90%	4.4	35.5%	6.1%	29.4%	4.3%	3.11	3.26	+2.4
2022	31	MIX RAW	5 levels	21	19	93	386	139	20	18	90%	4.4	36.0%	5.2%	30.8%	4.7%	3.11	3.27	+2.4
2023	32	MLB MLE	Texas Rangers	34	28	147	641	151	60	23	82%	4.3	23.6%	9.4%	14.2%	3.3%	4.15	4.13	+2.2
2023	32	MLB RAW	Texas Rangers	34	28	147	641	151	60	23	82%	4.3	23.6%	9.4%	14.2%	3.6%	4.15	4.30	+1.9
2024	33	MLB MLE	Texas Rangers	32	31	160	693	159	40	23	97%	5.0	22.9%	5.8%	17.2%	3.1%	4.28	3.59	+3.5
2024	33	MLB MLE	Texas Rangers	32	31	160	693	159	40	23	97%	5.0	22.9%	5.8%	17.2%	3.1%	4.28	3.59	+3.5
2024	33	MLB RAW	Texas Rangers	32	31	160	693	159	40	23	97%	5.0	22.9%	5.8%	17.2%	3.3%	4.28	3.73	+3.2
2025	34	MIX MLE	2 levels	31	27	132	571	99	42	25	87%	4.3	16.0%	7.5%	8.6%	4.5%	5.17	5.15	+0.4
2025	34	MIX MLE	2 levels	31	27	132	571	99	42	25	87%	4.3	16.0%	7.5%	8.6%	4.5%	5.17	5.15	+0.4
2025	34	MIX RAW	2 levels	31	27	132	571	99	42	25	87%	4.3	17.3%	7.4%	10.0%	4.4%	5.17	5.01	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			230	208	1137	4865	1156	335	199	90%	4.9	23.8%	6.9%	16.9%	4.1%	4.57	4.23	+15.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	LAD	19	19	116	490	98	31	17	100%	6.1	19.9%	6.4%	13.6%	3.4%	4.55	4.49	+1.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	LAD	11	11	68	288	54	20	11	100%	6.2	18.9%	7.0%	11.8%	3.8%	4.75	4.89	+0.4
2029	38	MLB MLE	LAD	6	6	36	153	27	12	7	100%	6.0	17.7%	7.7%	10.0%	4.3%	5.09	5.32	+0.0
2028	37	MLB CTX	LAD	11	11	68	287	54	20	11	100%	6.2	18.9%	7.0%	11.8%	3.8%	4.75	4.89	+0.4
2029	38	MLB CTX	LAD	6	6	36	152	27	12	7	100%	6.0	17.7%	7.7%	10.0%	4.3%	5.09	5.32	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		247	225	1241	5307	1237	367	217	91%	5.0	23.3%	6.9%	16.4%	4.1%	4.59	4.25	+16.8
/ 200 IP	—	RAW		40	36	200	855	199	59	35	91%	5.0	23.3%	6.9%	16.4%	4.1%	4.59	4.25	+2.7
Career	—	MLE		261	239	1283	5480	1286	378	205	92%	4.9	23.5%	6.9%	16.6%	3.7%	4.45	4.05	+16.1
/ 200 IP	—	MLE		41	37	200	854	200	59	32	92%	4.9	23.5%	6.9%	16.6%	3.7%	4.45	4.05	+2.6

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 AAAOklahoma City Comets · 10 IPFIP 0.69 → 1.05 (+0.37)K% 37.1% → 31.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.14%	—	×0.860	31.94%
BB% (unintentional) /BF	5.71%	—	×0.900	5.14%
HR / BF /BF	0.00%	÷0.956	×1.100	0.00%

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 91).

Result: FIP 0.69 → 1.05, 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 AAAOklahoma City Dodgers · 7 IPFIP -0.28 → 0.13 (+0.41)K% 40.0% → 35.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.00%	—	×0.880	35.20%
BB% (unintentional) /BF	0.00%	—	×1.050	0.00%
HR / BF /BF	0.00%	÷0.997	×1.100	0.00%

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 99).

Result: FIP -0.28 → 0.13, 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).

2018 A+Inland Empire 66ers · 6 IPFIP 1.37 → 1.99 (+0.62)K% 27.3% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.27%	—	×0.770	21.00%
BB% (unintentional) /BF	4.55%	—	×1.150	5.23%
HR / BF /BF	0.00%	÷0.978	×1.250	0.00%

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 1.37 → 1.99, 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 AAASalt Lake Bees · 17 IPFIP 3.70 → 4.12 (+0.42)K% 20.0% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.880	17.60%
BB% (unintentional) /BF	5.71%	—	×1.050	6.00%
HR / BF /BF	2.86%	÷0.989	×1.100	3.18%

Result: FIP 3.70 → 4.12, 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 ROKAZL Angels · 10 IPFIP 0.39 → 1.43 (+1.04)K% 35.7% → 24.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.71%	—	×0.680	24.29%
BB% (unintentional) /BF	2.38%	—	×1.250	2.98%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 0.39 → 1.43, 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 AAASalt Lake Bees · 78 IPFIP 2.54 → 2.83 (+0.29)K% 20.9% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.90%	—	×0.880	18.40%
BB% (unintentional) /BF	7.06%	—	×1.050	7.42%
HR / BF /BF	0.56%	÷0.980	×1.100	0.63%

Result: FIP 2.54 → 2.83, 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
Andrew Heaney (OGILVIE)	—	—	—	—	—	3.4%	—	5.04	18.5%	11.2%	105	+0.55	—	—	—
Tsuyoshi Wada L 2015 · 3.66 FIP	34	SP	3.66	16.8%	7.1%	2.0%	.307	—	—	—	—	—	3.60	188	63
Mauricio Lara L 2015 · 3.62 FIP	36	SP	3.62	13.9%	6.9%	1.5%	.310	3.69	12.1%	5.1%	220	+0.07	3.62	444	59
Arturo Lopez L 2019 · 5.46 FIP	36	SP	5.46	12.2%	6.8%	4.6%	.320	—	—	—	—	—	4.34	445	57
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	53
Marlon Arias L 2019 · 4.83 FIP	34	SP	4.83	19.8%	11.2%	3.6%	.273	—	—	—	—	—	3.73	154	53
Francisley Bueno L 2017 · 4.44 FIP	36	SP	4.44	11.7%	8.4%	2.3%	.351	—	—	—	—	—	2.43	188	53
Jorge Castillo L 2017 · 4.97 FIP	35	SP	4.97	11.2%	6.7%	3.6%	.337	4.91	19.6%	11.5%	119	-0.06	4.50	408	48
Jason Lane L 2015 · 5.56 FIP	38	SP	5.56	8.4%	6.2%	4.3%	.307	—	—	—	—	—	5.56	164	47
Kenshin Kawakami R 2010 · 4.06 FIP	35	SP	4.06	15.1%	5.6%	2.8%	.293	—	—	—	—	—	3.97	244	35
Yasutomo Kubo R 2019 · 3.98 FIP	38	SP	3.98	20.4%	4.7%	3.6%	.327	—	—	—	—	—	3.98	152	31
Jarrett Grube R 2017 · 4.41 FIP	35	SP	4.41	15.8%	8.1%	3.0%	.296	—	—	—	—	—	3.75	393	31
Austin Bibens-Dirkx R 2021 · 4.20 FIP	36	SP-	4.20	15.8%	5.6%	3.1%	.333	—	—	—	—	—	3.97	567	30
Jorge Martinez R 2019 · 3.71 FIP	34	SP	3.71	16.3%	5.7%	2.3%	.348	—	—	—	—	—	3.53	214	30
Jose Oyervides R 2017 · 5.38 FIP	35	SP	5.38	18.0%	6.3%	5.5%	.254	5.66	16.3%	5.1%	115	+0.28	3.01	407	29
Yoanner Negrin R 2019 · 3.87 FIP	35	SP	3.87	17.5%	8.1%	2.2%	.280	—	—	—	—	—	3.15	485	29
Walter Silva R 2015 · 4.15 FIP	38	SP	4.15	14.8%	7.4%	2.5%	.311	3.91	10.4%	3.7%	209	-0.24	3.67	453	28
Jesse Estrada R 2019 · 4.34 FIP	35	SP-	4.34	14.4%	6.6%	2.9%	.312	—	—	—	—	—	3.80	257	28
Hiroki Kuroda R 2011 · 3.64 FIP	36	SP	3.64	19.2%	5.1%	2.8%	.282	3.50	18.2%	13.3%	620	-0.14	2.96	1,319	28
Frankie De La Cruz R 2019 · 4.38 FIP	35	SP-	4.38	16.2%	8.0%	3.0%	.322	—	—	—	—	—	2.87	262	28
Chris Smith R 2017 · 5.08 FIP	36	SP-	5.08	15.6%	7.5%	4.3%	.286	—	—	—	—	—	3.79	477	26

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	6.8	97	23.0%	6.9%	1.56	4.59
Drew Smyly ('24)	5.7	104	23.1%	7.7%	1.49	4.20
Chase Anderson ('24)	5.5	101	19.7%	8.1%	1.48	4.41
Mark Leiter ('90-'01, 5 WAR*)	5.9	118	20.7%*	7.8%*	1.36*	4.61*
Derek Holland ('21)	7.3	113	19.7%	8.4%	1.35	4.62
Doug Bird ('73-'83, 10 WAR*)	6.1	110	20.3%*	5.8%*	1.41*	4.43*
Scott Bankhead ('86-'95, 10 WAR*)	4.5	100	21.2%*	7.3%*	1.36*	4.16*