The Library is Opening: All Stars 3

It’s that time again! RuPaul’s Drag Race is starting a new season of All Stars. I’ve previously used machine learning to try to predict the outcome of regular seasons of Drag Race. Since All Stars has traditionally had a different format (paired queens in season 1 and lip sync for your legacy in season 2), I don’t have the data to train machine learning algorithms for All Stars seasons. However I can try to predict how the queens will do based on their performances in their original seasons. This is a brief post, so to learn more about how all this works, read the first post. Based on the queens that have officially been announced (so this doesn’t include the mystery 10th queen that will be revealed on tonight’s premier), the outcome of All Stars Season 3 is predicted to be:


So based on the algorithms, Aja will be heading home first. BenDeLa, Shangela, and Kennedy will be our top three, with BenDeLa taking home the crown.

Obviously with a new format and a different mix of competitors, how a queen did in their original season isn’t a great predictor of how they will do in All Stars. Still, it’s fun to see what the data says.

I’m looking forward to what will hopefully be a great season of All Stars! To the queens:

The GitHub repo for this project

The Library is Open: Season 9

Season 9 of RuPaul’s Drag Race has started! Drag Race is a reality competition show hosted by the legendary drag queen RuPaul to find the next drag superstar. Each season, between 12 and 14 queens compete in challenges, which could consist of sewing together new looks for the runway, acting in parody scenes of gay cult classics, singing, or dancing. At the end of the episode, one queen is named the winner of the challenge and the two queens who fall in the bottom must lip-sync for their lives. They perform a lip-sync to a pre-chosen song on the runway for RuPaul, and whoever impresses most gets to stay, while the other is asked to sashay away.

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The Library is Open

Season 8 of RuPaul’s Drag Race premiered on March 7. As the season airs, Drag Race fans enjoy speculating who will make it to the top three, rooting for their favorites. I’ve been diving into machine learning recently, and one of the biggest uses of machine learning is for prediction, and I thought it would be fun to try to apply a few machine learning algorithms to data about the 100 queens who have appeared on Drag Race to try to predict how season 8 might progress. This is inspired in no small part by Alex Hanna’s excellent survival analysis of season 5, and I use the data she collected, adding in seasons 6-8. If you haven’t read Alex’s posts about season 5, and are fans of both Drag Race and statistical analysis, I recommend checking it out before reading on.

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