Statsgasm Returns

Our friend Marshall Flores wasn’t able to devote as much time to walking us through his Stasgasm process as thoroughly as he did last year. But I was really glad to hear that he could spare us a few hours of his time to apply his regression models to the data he gathered for the 2015 nominees.  If you missed Marshall’s Statsgasm series in 2014, I’ll link to those detailed posts on the next page.  But here are the basic charts that show the final results of his predictive analytics. What do the percentages represent? Those are the probabilities of each possible outcome, based on the available data. The Statsgasm numbers seek to predict the likelihood of each nominee winning. In my own simplest dumb-guy terms: for example, Patricia Arquette has a 96% chance of winning Best Supporting Actress Sunday night; Bennett Miller has a 1.25% chance of winning Best Director (which is barely any better than his chance of winning Best Supporting Actress).

Statsgasm 2015
by Marshall Flores

Best Picture

Best Director

Best Actress

Best Actor

Best Supporting Actress

Best Supporting Actor

Best Original Screenplay

Best Adapted Screenplay

Best Cinematography

Best Editing

Best Foreign Language Film

Best Feature Documentary

Best Animated Feature

Best Score

Best Song

Best Production Design

Best Costumes

Best Sound Editing

Best Sound Mixing

Best Visual Effects

Best Hair & Makeup

What sorcery is this?
Complete explanation from 2013-2014:

Pilot episode of AwardsDaily’s Statsgasm
Statsgasm – Week Two – Regression!
Statsgasm – Week Three
Statsgasm Episode 4: Best Picture Nomination Voting Simulation (Pt. 1)
Statsgasm Episode 4: Best Picture Nomination Voting Simulation (Pt. 2)
Statsgasm Episode 5: the Art of Prediction
Statsgasm: Final Predictions for the 86th Academy Awards, Pt 1
Statsgasm: Final Predictions for the 86th Academy Awards, Pt 2