2020 WNBA Draft Analytics: The PLUM Model
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Have you entered our 2020 WNBA Draft Challenge yet? Predict the order of the first round of the WNBA Draft and compete against your friends. There will be prizes for the top 5 entries!
As the WNBA Draft approaches on Friday, teams are evaluating players from every angle. Staffs are debating constantly, watching game tape, talking to coaches and teammates, interviewing players, and reviewing their notes from scouting trips this season. Of course, they’re also reviewing the stats summarizing how each player performed.
We all know past performance is no guarantee of future results. There are many factors that need to be considered – opponents faced, athleticism, playing style, and more. Scouts do this from observation and weighting the different factors as they see fit, typically in their heads to form their “board.”
However, that’s not the only approach. Machine learning techniques can be used to develop what analysts refer to as a “draft model” that predicts WNBA player performance based on historical information. Jesse Fischer, the draft modeling guru behind tothemean.com, started building NBA draft models in 2014. In 2017, he created the PLUM WNBA Draft Model (named in honor of Kelsey Plum), the first publicly available WNBA Draft Model we’re aware of at Her Hoop Stats.
The model utilizes data from the box score and play-by-play as well as player characteristics such as height and year in school. Fischer has continually improved the PLUM model over time and this year it incorporates espnW high school recruiting rankings. High school rankings have been shown to add value to NBA draft models since talent can be hidden by an NCAA team's system. In professional leagues, players can have the opportunity to unleash their skills. No model is perfect, but it’s a great way to look at players and see if there’s something the scouts should investigate further.
Who’s number one this year? You won’t be surprised to hear that Sabrina Ionescu is at the top of the PLUM model draft board. Lauren Cox ranks second as she gets the benefit of ranking first in her high school class. Since the model considers performance over the last three years weighted by minutes played, Cox is also helped by her strong sophomore and junior seasons.
Satou Sabally, the consensus No. 2 pick, ranks seventh overall in the model. She’s a little lower than the scouts have her largely because of her relatively low block rate (66th %ile among all Division I players) and entering college as the 36th-ranked recruit. However, the PLUM model does predict that she is a prospect with a high floor, as she has the fourth-lowest chance of being a WNBA “bust” among all players.
The PLUM model is more optimistic than consensus that the games of UConn standouts Crystal Dangerfield and Megan Walker will translate well to the WNBA. They rank third and fourth with Walker having the third-highest chance of developing into an All-Star. While Chennedy Carter has the potential to be an offensive star in the W, she rates a little lower than expected due to her predicted defensive contribution.
The top 36 players appear below alongside their probability of being a star, a starter, a role player, or a “bust” in the WNBA. Those percentages are a reminder of how hard it is to be a productive player in a league with only 144 possible roster spots. Head on over to the 2020 WNBA Draft Analytics blog post on tothemean.com for even more details on the prospects, including statistical growth across all college seasons and comparisons to WNBA picks with similar playing styles.
Thanks for reading the Her Hoop Stats Newsletter. If you like our work, be sure to check out our stats site, our podcast, and our social media accounts on Twitter, Facebook, and Instagram. You can also buy Her Hoop Stats gear, such as laptop stickers, mugs, and shirts!
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