Addison Russell

PosSS

B/TR/R

Born1994-01-23

Age (2027)33

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2022

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2019	25	AAACHC	119	.281/.400/.562	7	1	115	—	.232/.339/.434
2019	25	MLBCHC	241	.237/.311/.391	9	2	94	1.2
2021	27	INTLNaranjeros de…	175	.248/.326/.401	4	6	107	—
2022	28	INTLToros del Este	66	.183/.258/.233	1	0	43	—
2023	29	No MLB games played
2024	30	No MLB games played
2025	31	No MLB games played
2026	32	No MLB games played

Last 3 seasons WAR 1.2

Contract

No contract data on file.

Skills · percentileStatcast 2017-2019

Speed55

xwOBA37

Avg EV25

Barrel%21

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 these numbers are built

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2027 = full-season projection (no games played yet). 2028+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	MLB%	PA	AB	H	2B	3B	HR	BB	SO	HBP	SB	CS	AVG	OBP	SLG	OPS	ISO	BABIP	K%	BB%	wOBA	wRC+	BAT	RUN	FLD	POS	REP	WAR
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
2012	18	A	Burlington Bees	—	66	58	18	4	2	0	5	12	1	5	1	310	375	448	823	138	383	18	8	355	99	—	—	—	—	—	—
2012	18	ROK	AZL Athletics	—	121	106	44	4	5	6	14	23	1	9	1	415	488	717	1.205	302	494	19	12	516	145	—	—	—	—	—	—
2013	19	A+	Stockton Ports	—	504	429	118	29	10	17	61	116	11	21	3	275	379	508	887	233	338	23	12	388	98	—	—	—	—	—	—
2013	19	INTL	Mesa Solar Sox	—	97	85	24	8	1	1	10	15	1	5	2	282	365	435	800	153	329	15	10	354	126	—	—	—	—	—	—
2014	20	AA	Tennessee Smokies	—	262	242	73	14	1	13	17	43	3	5	4	302	355	529	884	227	323	16	6	387	107	—	—	—	—	—	—
2014	20	A+	Stockton Ports	—	18	16	3	0	0	0	2	6	0	1	0	188	278	188	465		300	33	11	228	5	—	—	—	—	—	—
2014	20	INTL	Mesa Solar Sox	—	50	46	9	1	0	2	3	13	1	1	0	196	260	348	608	152	226	26	6	274	72	—	—	—	—	—	—
2015	21	MLB	Chicago Cubs	—	523	475	115	29	1	13	42	149	3	4	3	242	308	389	697	147	324	28	8	311	94	-4	-0	+14	+2	+11	2.4
2015	21	AAA	Iowa Cubs	—	46	44	14	4	0	1	1	7	0	1	0	318	333	477	811	159	351	15	2	349	95	—	—	—	—	—	—
2016	22	MLB	Chicago Cubs	—	598	525	125	25	3	21	55	135	12	5	1	238	324	417	741	179	277	23	9	329	104	+3	+1	+16	+6	+13	4.0
2017	23	MLB	Chicago Cubs	—	385	352	84	21	3	12	29	91	4	2	1	239	304	418	722	179	289	24	8	320	96	-2	+0	+15	+4	+8	2.6
2018	24	MLB	Chicago Cubs	—	465	420	105	21	1	5	40	99	2	4	0	250	318	340	659	90	314	21	9	299	85	-8	+1	+15	+5	+10	2.3
2019	25	MLB	Chicago Cubs	—	241	215	51	4	1	9	20	58	3	2	0	237	311	391	702	153	280	24	8	312	94	-2	+0	+7	+1	+5	1.2
2019	25	AAA	Iowa Cubs	—	119	96	27	6	0	7	14	25	5	1	2	281	400	562	963	281	294	21	12	407	115	—	—	—	—	—	—
2021	27	INTL	Naranjeros de Hermosillo	—	175	157	39	8	2	4	16	27	2	6	1	248	326	401	727	153	278	15	9	326	107	—	—	—	—	—	—
2022	28	INTL	Toros del Este	—	66	60	11	0	0	1	6	12	0	0	0	183	258	233	491	50	213	18	9	232	43	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	2212	1987	480	100	9	60	186	532	24	17	5	242	314	392	706	150	299	24	8	315	99	-2	+1	+67	+19	+48	13.6
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	18	A MLE	Burlington Bees	—	66	59	16	3	2	0	4	18	1	5	1	271	328	390	718	119	370	27	6	314	99	—	—	—	—	—	—
2012	18	ROK MLE	AZL Athletics	—	121	111	36	3	4	5	9	33	1	9	1	324	380	559	939	234	415	27	7	382	145	—	—	—	—	—	—
2013	19	A+ MLE	Stockton Ports	—	504	446	102	25	7	14	44	149	11	21	3	229	313	410	724	182	304	30	9	313	98	—	—	—	—	—	—
2014	20	AA MLE	Tennessee Smokies	—	262	246	67	11	1	11	13	53	3	5	4	272	317	459	776	187	306	20	5	327	107	—	—	—	—	—	—
2014	20	A+ MLE	Stockton Ports	—	18	17	2	0	0	0	1	8	0	1	0	118	167	118	284		287	44	6	175	5	—	—	—	—	—	—
2015	21	MLB MLE	Chicago Cubs	—	523	477	115	28	1	14	40	149	3	4	3	241	304	392	696	151	324	28	8	307	94	-4	-0	+14	+2	+11	2.4
2015	21	AAA MLE	Iowa Cubs	—	46	44	12	3	0	1	1	9	0	1	0	273	289	409	698	136	321	20	2	309	95	—	—	—	—	—	—
2016	22	MLB MLE	Chicago Cubs	—	598	531	125	24	3	22	49	135	12	5	1	235	314	416	730	181	277	23	8	322	104	+3	+1	+16	+6	+13	4.0
2017	23	MLB MLE	Chicago Cubs	—	385	357	83	20	3	12	24	91	4	2	1	232	288	406	694	174	289	24	6	310	96	-2	+0	+15	+4	+8	2.6
2018	24	MLB MLE	Chicago Cubs	—	465	422	104	20	1	5	38	99	2	4	0	246	312	334	646	88	314	21	8	294	85	-8	+1	+15	+5	+10	2.3
2019	25	MLB MLE	Chicago Cubs	—	241	217	51	4	1	9	18	58	3	2	0	235	303	387	690	152	280	24	7	307	94	-2	+0	+7	+1	+5	1.2
2019	25	AAA MLE	Iowa Cubs	—	119	99	23	5	0	5	11	31	5	1	2	232	339	434	773	202	247	26	9	338	115	—	—	—	—	—	—
2012	18	ROK MLE	2 teams	—	187	170	52	6	6	5	13	51	2	14	2	306	362	500	862	194	409	27	7	358	128	—	—	—	—	—	—
2012	18	ROK RAW	2 teams	—	187	164	62	8	7	6	19	35	2	14	2	378	449	622	1.071	244	452	19	10	459	128	—	—	—	—	—	—
2013	19	A+ MLE	2 teams	—	601	532	122	30	8	17	53	178	12	26	5	229	313	412	725	182	308	30	9	313	98	—	—	—	—	—	—
2013	19	A+ RAW	2 teams	—	601	514	142	37	11	18	71	131	12	26	5	276	377	496	873	220	336	22	12	382	98	—	—	—	—	—	—
2014	20	AA MLE	3 teams	—	330	309	80	13	1	12	17	72	4	7	4	259	306	424	730	165	302	22	5	317	101	—	—	—	—	—	—
2014	20	AA RAW	3 teams	—	330	304	85	15	1	15	22	62	4	7	4	280	336	484	820	204	308	19	7	361	101	—	—	—	—	—	—
2015	21	MLB MLE	2 teams	—	569	521	127	32	1	14	41	158	3	5	3	244	303	390	692	146	321	28	7	308	94	-4	-0	+14	+2	+12	2.5
2015	21	MLB RAW	2 teams	—	569	519	129	33	1	14	43	156	3	5	3	249	310	397	707	148	327	27	8	314	94	-4	-0	+14	+2	+12	2.5
2016	22	MLB MLE	Chicago Cubs	—	598	531	125	24	3	22	49	135	12	5	1	235	314	416	730	181	271	23	8	322	104	+3	+1	+16	+6	+13	4.0
2016	22	MLB RAW	Chicago Cubs	—	598	525	125	25	3	21	55	135	12	5	1	238	324	417	741	179	277	23	9	329	104	+3	+1	+16	+6	+13	4.0
2017	23	MLB MLE	Chicago Cubs	—	385	357	83	20	3	12	24	91	4	2	1	232	288	406	694	174	280	24	6	310	96	-2	+0	+15	+4	+8	2.6
2017	23	MLB RAW	Chicago Cubs	—	385	352	84	21	3	12	29	91	4	2	1	239	304	418	722	179	289	24	8	320	96	-2	+0	+15	+4	+8	2.6
2018	24	MLB MLE	Chicago Cubs	—	465	422	104	20	1	5	38	99	2	4	0	246	312	334	646	88	309	21	8	294	85	-8	+1	+15	+5	+10	2.3
2018	24	MLB RAW	Chicago Cubs	—	465	420	105	21	1	5	40	99	2	4	0	250	318	340	659	90	314	21	9	299	85	-8	+1	+15	+5	+10	2.3
2019	25	MLB MLE	2 teams	—	360	316	75	9	1	15	29	89	8	3	2	237	317	415	732	177	275	25	8	317	101	+0	-0	+7	+1	+8	1.7
2019	25	MLB RAW	2 teams	—	360	311	78	10	1	16	34	83	8	3	2	251	340	444	784	193	284	23	9	343	101	+0	-0	+7	+1	+8	1.7
2021	27	INTL MLE	Naranjeros de Hermosillo	—	175	157	39	8	2	4	16	27	2	6	1	248	326	401	727	153	278	15	9	—	—	—	—	—	—	—	—
2021	27	INTL RAW	Naranjeros de Hermosillo	—	175	157	39	8	2	4	16	27	2	6	1	248	326	401	727	153	278	15	9	326	107	—	—	—	—	—	—
2022	28	INTL MLE	Toros del Este	—	66	60	11	0	0	1	6	12	0	0	0	183	258	233	491	50	213	18	9	—	—	—	—	—	—	—	—
2022	28	INTL RAW	Toros del Este	—	66	60	11	0	0	1	6	12	0	0	0	183	258	233	491	50	213	18	9	232	43	—	—	—	—	—	—
2012	18	ROK MLE	2 teams	—	187	170	52	6	6	5	13	51	2	14	2	306	362	500	862	194	399	27	7	358	128	—	—	—	—	—	—
2013	19	A+ MLE	2 teams	—	601	531	122	30	8	17	53	178	12	26	5	230	313	412	726	183	304	30	9	313	98	—	—	—	—	—	—
2014	20	AA MLE	3 teams	—	330	306	80	13	1	12	17	72	4	7	4	261	306	428	734	167	305	22	5	317	101	—	—	—	—	—	—
2015	21	MLB MLE	2 teams	—	569	520	127	32	1	14	41	158	3	5	3	244	303	390	693	146	324	28	7	308	94	—	—	—	—	—	—
2016	22	MLB MLE	Chicago Cubs	—	598	532	125	24	3	22	49	135	12	5	1	235	314	415	730	180	277	23	8	322	104	—	—	—	—	—	—
2017	23	MLB MLE	Chicago Cubs	—	385	354	83	20	3	12	24	91	4	2	1	234	288	410	698	175	289	24	6	310	96	—	—	—	—	—	—
2018	24	MLB MLE	Chicago Cubs	—	465	422	104	20	1	5	38	99	2	4	0	246	312	334	646	88	314	21	8	294	85	—	—	—	—	—	—
2019	25	MLB MLE	2 teams	—	360	320	75	9	1	15	29	89	8	3	2	234	317	409	727	175	269	25	8	317	101	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2212	1987	480	100	9	60	186	532	24	17	5	242	314	392	706	150	299	24	8	315	85	-2	+1	+67	+19	+48	13.6
/ 162G	—	A+C		—	650	584	141	29	3	18	55	156	7	5	1	241	315	394	709	152	297	24	8	315	85	-1	+0	+20	+6	+14	4.0
Career	—	MLE		—	3736	3375	818	162	26	107	286	912	49	72	19	242	311	401	712	159	299	24	8	294	85	-2	+1	+67	+19	+48	13.6
/ 162G	—	MLE		—	650	587	143	28	5	19	50	159	9	13	3	244	313	405	719	162	300	24	8	294	85	-1	+0	+20	+6	+14	4.0

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.

2019 AAAIowa Cubs · 119 PAwOBA .409 → .338 (−71)K% 21.0% → 26.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.01%	÷1.025	×1.290	—	—	26.44%
BB% (unintentional) /PA	11.76%	÷0.968	×0.710	—	×1.033	8.91%
HBP% /PA	4.20%	—	×0.980	—	×1.033	4.25%
Singles /BIP	19.72%	÷0.993	×0.900	×0.950	×1.033	17.54%
Doubles /BIP	8.45%	÷1.014	×0.810	×0.950	×1.033	6.62%
Triples /BIP	0.00%	÷1.029	×0.810	×0.950	×1.033	0.00%
Home runs /BIP	9.86%	÷1.050	×0.780	—	×1.033	7.56%

Factors used: league row PCL. Park (home-season share, regressed): HR 110, 1B 99, 2B 103, 3B 106, K 105, BB 94 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .409 → .338; ISO .281 → .219; BABIP .294 → .247. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2015 AAAIowa Cubs · 46 PAwOBA .347 → .309 (−37)K% 15.2% → 18.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.22%	÷1.051	×1.290	—	—	18.68%
BB% (unintentional) /PA	2.17%	÷0.996	×0.710	—	×1.050	1.63%
HBP% /PA	0.00%	—	×0.980	—	×1.050	0.00%
Singles /BIP	24.32%	÷1.008	×0.900	—	×1.050	22.81%
Doubles /BIP	10.81%	÷0.984	×0.810	—	×1.050	9.35%
Triples /BIP	0.00%	÷0.948	×0.810	—	×1.050	0.00%
Home runs /BIP	2.70%	÷0.916	×0.780	—	×1.050	2.42%

Factors used: league row PCL. Park (home-season share, regressed): HR 83, 1B 102, 2B 97, 3B 90, K 110, BB 99 — applied at half strength. Age: age 21 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (6.2 yr younger than average).

Result: wOBA .347 → .309; ISO .159 → .138; BABIP .351 → .321. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2014 AATennessee Smokies · 262 PAwOBA .376 → .327 (−49)K% 16.4% → 20.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.41%	÷0.980	×1.220	—	—	20.43%
BB% (unintentional) /PA	6.49%	÷0.948	×0.680	—	×1.050	4.89%
HBP% /PA	1.15%	—	×0.840	—	×1.050	1.01%
Singles /BIP	22.61%	÷0.958	×0.920	×0.995	×1.050	22.68%
Doubles /BIP	7.04%	÷1.140	×0.910	×0.995	×1.050	5.87%
Triples /BIP	0.50%	÷1.065	×0.880	×0.995	×1.050	0.43%
Home runs /BIP	6.53%	÷1.009	×0.800	—	×1.050	5.44%

Factors used: league row SL. Park (home-season share, regressed): HR 102, 1B 92, 2B 128, 3B 113, K 96, BB 90 — applied at half strength. Age: age 20 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (4.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.995.

Result: wOBA .376 → .327; ISO .227 → .184; BABIP .323 → .306. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2014 A+Stockton Ports · 18 PAwOBA .223 → .175 (−49)K% 33.3% → 44.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	33.33%	÷0.997	×1.340	—	—	44.81%
BB% (unintentional) /PA	11.11%	÷1.020	×0.710	—	×1.042	8.06%
HBP% /PA	0.00%	—	×0.790	—	×1.042	0.00%
Singles /BIP	30.00%	÷0.992	×0.910	—	×1.042	28.67%
Doubles /BIP	0.00%	÷1.044	×0.820	—	×1.042	0.00%
Triples /BIP	0.00%	÷1.011	×0.760	—	×1.042	0.00%
Home runs /BIP	0.00%	÷1.112	×0.920	—	×1.042	0.00%

Factors used: league row CAL. Park (home-season share, regressed): HR 122, 1B 98, 2B 109, 3B 102, K 99, BB 104 — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average).

Result: wOBA .223 → .175; ISO .000 → .000; BABIP .300 → .287. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2013 A+Stockton Ports · 504 PAwOBA .380 → .313 (−67)K% 23.0% → 29.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.02%	÷1.042	×1.340	—	—	29.61%
BB% (unintentional) /PA	12.10%	÷1.020	×0.710	—	×1.050	8.85%
HBP% /PA	2.18%	—	×0.790	—	×1.050	1.81%
Singles /BIP	19.81%	÷1.022	×0.910	×1.008	×1.050	18.65%
Doubles /BIP	9.27%	÷0.968	×0.820	×1.008	×1.050	8.31%
Triples /BIP	3.19%	÷1.095	×0.760	×1.008	×1.050	2.34%
Home runs /BIP	5.43%	÷1.129	×0.920	—	×1.050	4.65%

Factors used: league row CAL. Park (home-season share, regressed): HR 126, 1B 104, 2B 94, 3B 119, K 108, BB 104 — applied at half strength. Age: age 19 vs a level average of 22.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.008.

Result: wOBA .380 → .313; ISO .233 → .189; BABIP .338 → .304. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2012 ROKAZL Athletics · 121 PAwOBA .502 → .382 (−120)K% 19.0% → 27.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.01%	÷1.000	×1.440	—	—	27.37%
BB% (unintentional) /PA	11.57%	÷1.000	×0.620	—	×1.022	7.33%
HBP% /PA	0.83%	—	×0.720	—	×1.022	0.61%
Singles /BIP	34.94%	÷1.000	×0.820	×1.050	×1.022	30.76%
Doubles /BIP	4.82%	÷1.000	×0.720	×1.050	×1.022	3.73%
Triples /BIP	6.02%	÷1.000	×0.720	×1.050	×1.022	4.66%
Home runs /BIP	7.23%	÷1.000	×0.780	—	×1.022	5.77%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 18 vs a level average of 19.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .502 → .382; ISO .302 → .224; BABIP .494 → .415. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2012 ABurlington Bees · 66 PAwOBA .352 → .314 (−38)K% 18.2% → 26.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.18%	÷0.929	×1.360	—	—	26.60%
BB% (unintentional) /PA	7.58%	÷0.956	×0.690	—	×1.050	5.74%
HBP% /PA	1.52%	—	×0.780	—	×1.050	1.24%
Singles /BIP	26.09%	÷1.008	×0.920	×1.022	×1.050	25.54%
Doubles /BIP	8.70%	÷0.977	×0.830	×1.022	×1.050	7.92%
Triples /BIP	4.35%	÷0.971	×0.910	×1.022	×1.050	4.37%
Home runs /BIP	0.00%	÷1.014	×0.800	—	×1.050	0.00%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 103, 1B 102, 2B 95, 3B 94, K 86, BB 91 — applied at half strength. Age: age 18 vs a level average of 22.0 → +5.0% on BB/HBP/hit rates (4.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.022.

Result: wOBA .352 → .314; ISO .138 → .126; BABIP .383 → .370. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .