2020 WNBA Draft Analytics

PLUM Draft Model

Jesse Fischer • April 12, 2020
Photo: vpking

PLUM Draft Model

The PLUM draft model (named after Kelsey Plum) utilizes machine learning to objectively predict which players will succeed in the WNBA.

The model incorporates advanced statistics derived from college play-by-play data which are not available anywhere else (Bayesian RAPM, "Adjusted" box score stats, rate stats, etc.). These statistics isolate the impact and efficiency of a single player by controlling for playing time, pace, other players on the court (opponents, teammates), etc. The model also uses player characteristics (year in school, height). Lastly, a big improvement this year is the addition of the espnW 100 HoopGurlz high school recruiting rankings.

If you want to read more about modeling details, check out analysis from prior years such as 2018 or 2019 or reach out to me on Twitter.


2020 PLUM Rankings

Below are the Top 36 players - an extended view can be found here.

Plum 2020


Top Guards

Guards

Guards


Top Bigs

Bigs

Bigs


All Star Potential

Below are players with a >=1% WNBA All Star probability.

All Star Potential


Player Profiles

Select a player to see their draft profile:

Sabrina Ionescu

#20 | Oregon | SR | G | 5-10 | hs rank: 4 | ncaa

Statistical Profile

Playing Style Comps

Draft Model Insight

ftp, ast%, rapm_off
blk%, drb%, 3par


Actual

Actual


Mock Draft Comparison

Here is how the PLUM ranking compares with various mock drafts (bball-index, draftsite.com, espn, highposthoops, swishappeal, and wbasketballblog).

Mocks

Mocks Actual