Predicting Box Office Success a Year in Advance from Ranker Data

April 22nd, 2013 by Ravi Iyer

A number of data scientists have attempted to predict movie box office success from various datasets. For example, researchers at HP labs were able to use tweets around the release date plus the number of theaters that a movie was released in to predict 97.3% of movie box office revenue in the first weekend. The Hollywood Stock Exchange, which lets participants bet on the box office revenues and infers a prediction, predicts 96.5% of box office revenue in the opening weekend. Wikipedia activity predicts 77% of box office revenue according to a collaboration of European researchers. Ranker runs lists of anticipated movies each year, often for more than a year in advance, and so the question I wanted to analyze in our data was how predictive is Ranker data of box office success.

However, since the above researchers have already shown that online activity at the time of the opening weekend predicts box office success during that weekend, I wanted to build upon that work and see if Ranker data could predict box office receipts well in advance of opening weekend. Below is a simple scatterplot of results, showing that Ranker data from the previous year predicts 82% of variance in movie box office revenue for movies released in the next year.

: Predicting Box Office Success from Ranker Data

The above graph uses votes cast in 2011 to predict revenues from our Most Anticipated 2012 Films list. While our data is not as predictive as twitter data collected leading up to opening weekend, the remarkable thing about this result is that most votes (8,200 votes from 1,146 voters) were cast 7-13 months before the actual release date. I look forward to doing the same analysis on our Most Anticipated 2013 Films list at the end of this year.

– Ravi Iyer