Rate view · points per 100 possessions on each side of the ball · 2022 regular season · RS+PS solve
Production
7.5PTS
5.0REB
3.1AST
1.4TOV
2.13A/TO
1.5STL
0.4BLK
Shooting
51.2TS%
52.02P%
25.73P%
77.8FT%
zTS−4.8
ROLE−1.9
RTS−3.0
zTS = ROLE + RTS
VVPM impact
points / 100
Offense plus positive-good defense.
−80+8
League density for the active node · selected player marked in pink · defense is positive = good
OOffensive impact
adds to O-VPM
How the player helps possessions survive, score, and continue.
77thO-VPM+1.11
−5.00+5.0
DDefensive impact
positive = good
How the player ends possessions and suppresses scoring value.
83rdD-VPM+0.71
−2.50+2.5
Impact waterfall
points / 100
Each factor's value stacks left to right into the side's VPM total — the dashed line tracks the running sum.
Four-factor detail is published for the 2026 regular-season solve only — historical seasons carry O-VPM and D-VPM without the factor split.
eFG zones
freqfg
−0.40 / −0.10Rim
+0.30 / +0.30Mid
+0.23 / +0.34Three
Off
−0.20−0.20
−0.14+0.44
−0.00+0.23
Def
−0.05−0.05
+0.07+0.23
+0.01+0.33
rim + mid + three = eFG · freq + fg = zone value · off / def · up = good
Signal chain
prior → lineups
Box prior
+1.22
raw box model
Effective prior
+1.88
×1.5, centred
Lineup update
+0.26
2026 possessions
VPM
+2.14
prior + update
prior source2026 boxupdate+0.26 on 3,550 poss
Team mix
lineup-weighted VPM sum · click to filter
Each strip is 5 × the possession-weighted mean VPM of the players currently listed on that roster (pts / 100 poss). Traded players carry all their possessions to their current team.
About
VPM is databallr's WNBA player impact in points per 100 possessions: a single-season prior-centred ridge over 2026 lineups, where each factor's prior is a public box-score model trained only on 2022–2025. Offense + defense = VPM; defense is positive-good.
Offense and defense each split exactly into four factors — eFG (rim + mid + three shot value), FT, TOV (turnover value, positive = fewer / cheaper turnovers), and 2nd chance. The eFG zones module is the rim / mid / three drill-down of the eFG bar.
Player contextShot profile and role rates for the selected season
Shot diet
FT = 0.44 × FTA
RIM37%
MID29%
3P27%
FT8%
Share of FGA + 0.44 × FTA
Shot profile
2022 regular season
below avgabove avgFT8% freqleague avg
VOL2.5 FTA/100−2.1lg 4.5
2.5 FTA/100 (−2.1)
4.5 FTA/100
EFF77.8% FT%−1.6%lg 79.4%
77.8% FT% (−1.6%)
79.4% FT%
RIM37% freqleague avg
VOL5.2 FGA/100+0.3lg 5.0
5.2 FGA/100 (+0.3)
5.0 FGA/100
EFF66.7% FG%+3.9%lg 62.8%
66.7% FG% (+3.9%)
62.8% FG%
MID29% freqleague avg
VOL4.2 FGA/100−2.2lg 6.5
4.2 FGA/100 (−2.2)
6.5 FGA/100
EFF33.8% FG%−4.5%lg 38.3%
33.8% FG% (−4.5%)
38.3% FG%
3P27% freqleague avg
VOL3.8 3PA/100−1.8lg 5.6
3.8 3PA/100 (−1.8)
5.6 3PA/100
EFF25.7% FG%−8.8%lg 34.6%
25.7% FG% (−8.8%)
34.6% FG%
frequency beside each zone is its share of FGA + 0.44 × FTA · volume is attempts per 100 of the player’s own on-floor offensive possessions · the league column pools that same ratio over every player, i.e. team attempts per 100 divided by five · volume bars share the season’s 5th–95th percentile gap axis · efficiency bars show sample-qualified within-zone percentile distance from league average; fewer than 20 attempts (8 in playoffs) leaves the bar unranked
Role & playstyle
four box-score reads · not impact
01
Offensive roleSpecialist usage
Usage and creation burden
17.2Usageplays / 10014th pct
37.2%Self-createdmade-FG pts75th pct
14.3Assist creationpts / 10080th pct
02
Shot selectionMixed shot diet
Where her attempts come from
39.5%At rimof FGA69th pct
31.7%Midrangeof FGA40th pct
28.8%From threeof FGA41st pct
03
Possession pressureLow-event possession role
Fouls, extra chances, lost balls
2.8Fouls drawn/ 10020th pct
2.3Off. rebounds/ 10064th pct
0.6Ball securitylost-ball / 10041st pct
04
Defensive activityElite steal activity
Stops, disruption, and cleanup
3.7%STOP%def. possessions—
2.9Steals/ 10093rd pct
0.7Blocks/ 10053rd pct
7.4Def. rebounds/ 10064th pct
Rates use the player’s own on-floor possessions. Percentiles compare the same season and split; higher means more, not better. Ball security is reversed so higher means fewer lost-ball turnovers. STOP% = steals + offensive fouls drawn + recovered blocks per 100 defensive possessions.
Season historyCompare the same player across the available WNBA seasons
Career log
5 regular seasons
Production · per game
Shooting
VPM impact
Season
Team
GP
MPG
PTS
AST
REB
STL
BLK
TOV
3P%
TS%
TS+
Off
Def
VPM
2026
GSV
37
24.8
14.3
2.2
3.3
1.6
0.2
1.6
34.6
51.0
−5.0
+0.11
+2.03
+2.14
2025
SEA
44
31.5
11.6
4.2
4.3
2.3
0.5
1.9
30.5
50.8
−3.4
−0.17
+2.47
+2.30
2024
SEA
12
29.0
10.3
3.7
4.0
1.7
0.3
1.4
32.3
55.2
+1.6
−0.06
+0.61
+0.55
2023
SEA
10
28.5
8.4
3.8
3.6
1.5
0.4
2.2
21.7
42.1
−12.0
−1.49
+0.71
−0.78
2022
SEA
36
25.6
7.5
3.1
5.0
1.5
0.4
1.4
25.7
51.2
−3.0
+1.11
+0.71
+1.82
Career
—
139
27.7
10.9
3.3
4.1
1.8
0.3
1.7
29.8
50.7
−3.8
+0.13
+1.61
+1.74
poor elite · cell tint = percentileclick a season to load it above
the career log spans 2022–2026, the reach of this repo’s WNBA box cache — earlier seasons are absent, not zero · TS+ = TS% − league TS% that season, in percentage points — it is not databallr’s role-adjusted RTS, and not this repo’s rTS/zTS chain · per 75 and per 100 use the average of on-floor offensive and defensive possessions · the career line pools totals and recomputes the rates, and its VPM is possession-weighted · 2022–2025 VPM is the RS+PS solve, 2026 is regular season to date