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Veronica Burton

Golden State Valkyries · 55 games

Veronica Burton

11.6 PPG
3.8 RPG
5.3 APG
29 MPG
1.5 STL
0.6 BLK
1.5 TOV
40.1 FG%
34.1 3P%
82.9 FT%

Next-game projection

9pts
3.8reb
4.1ast

Recency-weighted, adjusted for the next opponent's pace and defense. A model estimate, not a guarantee.

Shot chart

Loading shots…

Field-goal attempts this season, both baskets folded to one half court. Descriptive, not a projection.

Isolated rankings

100th Net Impact
98th Off Impact
100th Def Impact
58th Points / 100

Impact (RAPM)

Net Impact 7.9 100
Off Impact 3.8 98
Def Impact 4.1 100

Scoring

Points / 100 20.5 58
Usage Rate 19.4% 58

Efficiency

True Shooting 53.8% 38
Effective FG 47.3% 29

Playmaking

Assists / 100 9.4 94
Assist / TO 3.62 99

Rebounding

Rebounds / 100 6.7 49

Defense

Steals / 100 2.7 94
Blocks / 100 1.1 67

Discipline

Turnovers / 100 2.6 69

Impact trend · RAPM by season

+8.4+0.0-0.9'22'23'24'25'26+7.9
Net +7.9Off +3.8Def +4.1

Percentile rank vs. all 229 qualified WNBA players this season, pace-adjusted. Impact (RAPM) measures on-court scoring margin per 100 possessions, teammate- and opponent-adjusted over recent seasons; each trend point is a trailing multi-season blend, so it reads as a trajectory rather than noisy single-season on/off. Descriptive stats, not a projection.

Game log

DateOppMINPTSREBASTSTLBLKFG3P
Oct 26vs ATL371383145-151-6
Oct 24@ ATL381335324-172-7
Oct 21@ ATL29324111-71-4
Oct 19vs ATL241172214-92-4
Oct 17vs ATL30543122-70-2
Oct 9@ LV37864113-90-2
Oct 7vs LV28813101-31-3
Oct 4vs LV18431101-60-1
Oct 2vs DAL3716106007-181-7
Sep 30@ DAL371115313-82-4
Sep 27vs DAL231035013-72-2
Sep 24@ LA291735105-121-4
Sep 22@ POR361378122-62-4
Sep 19vs SEA30944113-111-5
Sep 18vs POR26443610-30-2
Aug 30@ POR291166213-81-5
Aug 27@ NY278213103-81-4
Aug 26@ CONN201237005-91-2
Aug 24@ MIN301449506-112-4
Aug 21@ CHI181142103-81-3
Aug 19vs MIN361447404-92-6
Aug 17vs DAL321645205-113-6
Aug 12vs CHI261362105-93-6
Aug 9@ LA29707302-60-2
Aug 7@ DAL302247108-133-7
Aug 4vs TOR331287102-91-6
Aug 2vs TOR291726206-103-4
Jul 29@ PHX341535106-102-5
Jul 20vs WSH261227205-82-3
Jul 18vs WSH3311511204-82-5
Jul 15@ IND30454301-40-1
Jul 10@ CONN331736127-121-3
Jul 8@ TOR21626201-21-2
Jul 6@ WSH23733203-100-3
Jul 4@ ATL312114116-92-3
Jun 28vs NY27868003-71-1
Jun 26vs ATL221012404-100-2
Jun 24vs ATL35857203-50-1
Jun 21@ LV16231101-50-3
Jun 19vs MIN24525201-81-5
Jun 17vs DAL331185213-82-3
Jun 15vs LA301223224-122-4
Jun 12@ SEA301158213-91-5
Jun 9vs PHX372538007-152-7
Jun 6@ LV341553005-161-8
Jun 4@ MIN26823013-80-2
Jun 2vs POR231039003-52-2
May 31vs LV28735103-91-3
May 28vs IND292563157-131-3
May 25vs CONN171126004-62-2
May 22@ IND291733024-122-5
May 21@ NY271347005-143-6
May 13vs CHI361634105-152-6
May 10vs PHX3213312303-91-5
May 8@ SEA311626205-132-4

Model output · updated October 27, 2026