Oscar predictions (math-nerd style)
The Oscars air tonight, and I’ve updated my regression analysis predicting the Best Picture winner. Despite a few skeptics, the model correctly predicted “The Departed” winning last year. (Lucky or smart? Who knows.)
(See last year’s post for a more in-depth explanation of the regression model. http://invisiblelawstudent.blogspot.com/2007/02/predicting-best-picture-winner.html )
I’ve gone back and updated the data to include last year’s nominees. I’ve continued to only use data from the last five years. I still think this is an excellent way to account for the changing tastes of voters. (What does the behavior of voters from the 1950s really tell us about voters today?)
The updated data again confirms that that the guild awards are still the best predictors of Oscar success. The PGA is still negatively-correlated with winning an Oscar. For movies such as “Little Miss Sunshine,” “Brokeback Mountain,” and “The Aviator,” winning the PGA was essentially the kiss of death. A PGA award can be overcome, but if a film is on the bubble, don’t expect a PGA award to help its Oscar chances. The Golden Globes and box office earnings remain insignificant predictors.
Here’s the updated prediction model for this year:
Oscar Win = SAG x .423 + DGA x .757 + PGA x -.454 + ACE x .285 + -.025
Here’s how the model would predict the winners from the last five years:
Movie | SAG | DGA | PGA | ACE | Points |
| |||
The Departed | 0 | 1 | 0 | 1 | 1.017 |
| |||
Babel | 0 | 0 | 0 | 0 | -0.025 |
| |||
Letters from Iwo Jima | 0 | 0 | 0 | 0 | -0.025 |
| |||
Little Miss Sunshine | 1 | 0 | 1 | 0 | -0.057 |
| |||
The Queen | 0 | 0 | 0 | 0 | -0.025 |
| |||
Crash | 1 | 0 | 0 | 1 | 0.683 |
| |||
Brokeback Mountain | 0 | 1 | 1 | 0 | 0.277 |
| |||
Good Night and Good Luck | 0 | 0 | 0 | 0 | -0.025 |
| |||
Capote | 0 | 0 | 0 | 0 | -0.025 |
| |||
Munich | 0 | 0 | 0 | 0 | -0.025 |
| |||
Million Dollar Baby | 0 | 1 | 0 | 0 | 0.732 |
| |||
The Aviator | 0 | 0 | 1 | 1 | -0.195 |
| |||
Finding Neverland | 0 | 0 | 0 | 0 | -0.025 |
| |||
Ray | 0 | 0 | 0 | 1 | 0.26 |
| |||
Sideways | 1 | 0 | 0 | 0 | 0.398 |
| |||
Return of the King | 1 | 1 | 1 | 1 | 0.985 |
| |||
Lost in Translation | 0 | 0 | 0 | 0 | -0.025 |
| |||
Master and Commander | 0 | 0 | 0 | 0 | -0.025 |
| |||
Mystic River | 0 | 0 | 0 | 0 | -0.025 |
| |||
Seabiscuit | 0 | 0 | 0 | 0 | -0.025 |
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Chicago | 1 | 1 | 1 | 1 | 0.985 |
| |||
Gangs of New York | 0 | 0 | 0 | 1 | 0.26 |
| |||
The Hours | 0 | 0 | 0 | 0 | -0.025 |
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The Two Towers | 0 | 0 | 0 | 0 | -0.025 |
| |||
The Pianist | 0 | 0 | 0 | 0 | -0.025 |
| |||
Notice the correct prediction for Crash.
Here’s how the model predicts this year’s nominees:
Movie | SAG | DGA | PGA | ACE | Points |
There Will Be Blood | 0 | 0 | 0 | 0 | | -0.025 |
No Country for Old Men | 1 | 1 | 1 | 0 | | 0.7 |
Atonment | 0 | 0 | 0 | 0 | | -0.025 |
Juno | 0 | 0 | 0 | 0 | | -0.025 |
Michael Clayton | 0 | 0 | 0 | 0 | | -0.025 |
No surprises here – “No Country” is the clear leader. However, it's PGA win shows that it may not perfectly fit Oscar voters' tastes, and its lack of an ACE win highlights its vulnerability. It's still the most likely to win, but don't discount the chances for a "Michael Clayton" or "Juno" to sneak in.
Here’s hoping this helps you take the prize for that Oscar pool. Enjoy the show!
2 Comments:
Hi,
Your regression model is flawed. As someone previously commented, you need use a logit/probit model (more commonly known as logistical regression) in order to get the desired result. A linear regression using a binary 0/1 for an oscar winner is faulty because 0 and 1 don't have numerical values. In other words, the model is trying to predict 0 or 1, but you should be trying to predict true/false.
See the following two for reference:
http://online.wsj.com/article/SB110928974020363759.html
http://www.tuck.dartmouth.edu/pdf/pr20040225_oscars.pdf
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