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.