In The Crunch, Bruce Nash provides analysis of the numbers underlying the film industry.
Do you have an interesting movie numbers question? Send it to email@example.com and Bruce will consider it for The Crunch.
November 13, 2013
On Tuesday we launched The Numbers Bankability Index, a new service to help assess the value that different people bring to the industry, from actors and actresses to directors, screenwriters, producers, and anyone else involved in the creative process of making a movie. In this article, I'll look more deeply into how the Index is compiled, and how we use the tools behind it to analyze questions about people in movies.
If you haven't already, now's a good time to look at our announcement video, and the November Edition of the Worldwide Bankability Index.
November 12, 2013
September 22, 2013
Top-grossing people in technical roles
Last week I unveiled our new People Records section and talked about some of top performers across different types of acting, from the blockbusting superstars to the unsung heroes, to the cameo kings and queens. We've added some more charts to the record section this week, this time covering technical roles, and once more there's a lot of data to be mined.
September 14, 2013
Top-grossing actors and actresses in leading roles
Over the past two or so years, we've been working on one of the biggest projects we've ever undertaken: building out our database of acting and technical credits to include complete information on every acting role and significant technical credit for movies for which we have box office information. While work on this vast task continues (and will, of course, continue as long as films are being made), we have enough coverage of the industry now to start doing some serious analysis. Over the next month or two, I'll be looking at some of the things we've found and we'll be rolling out new features at The Numbers that take advantage of the dataset. This week, I'll look into how we are categorizing acting roles, and discuss the first charts in our new People Records section.
August 24, 2013
After a fairly extended Summer break, there's quite a lot of catch-up to do. I have a few posts already in the pipeline, including the second part of my series on Medium Data (the second article has grown big enough that it might turn into a mini-series of its own). I also have a lot more movie analytics work coming down the pike. First though, I have a big list of articles and web sites I've been meaning to share.
May 1, 2013
We live in a world that is being transformed by Big Data. The ability to gather and process vast amounts of information, and the development of analytical tools to find meaning in it all, promises to change business, science and social practices.
It's already changing the way companies like Target and WalMart do business and how the CDC plans for 'flu season. It's a hot topic for good reason. But it also has its limitations and problems, which are becoming more apparent as Big Data becomes more widely used. Ultimately, the solution to these problems will lead us to a new way of looking at analytical work -- a more focused and rigorous approach. Medium Data.
February 24, 2013
Voting is closed in our annual Predict the Academy Awards contest, and Argo is the clear favorite to pick up the Best Picture award, based on the opinion of nearly 500 entrants. Ben Affleck's thriller took an impressive 80% of the vote, more than six times the score of Lincoln, which took second place in the poll. Coincidentally, the contest has predicted the winner of the Best Picture Oscar 80% of the time in the 15 years we've been running it. Quite a few other categories have strong favorites, but there are also some really close calls, and it looks as though the awards will be shared by several films tonight.
- Votes in Each Category
- Predicted Winners in Each Category
January 19, 2013
Creative Commons image courtesy of redjar
We've been publishing our video sales charts for a little over five years now. In that time, I've made various tweaks to the algorithms and introduced Blu-ray sales tracking. We're starting 2013 with an overhaul of the tracking system, designed to increase the number of films we track on a weekly basis as well as to enhance the accuracy of the charts. In this article, I'll dig a little into how our tracking works, and what's new with the overhaul.
December 6, 2012
Leonardo DiCaprio plays Jack Dawson and Kate Winslet plays Rose DeWitt Bukater in Titanic, from Paramount Pictures and Twentieth Century Fox.
Anyone who's ever written fiction will know the challenge of finding a good name for a character. Many articles have been written and hours spent on the subject over the years, and the challenge always remains: how to come up with a name that captures the character without distracting the audience with something too unusual.
I thought it might be interesting to look at our database, which contains over 80,000 acting credits, to see what the most common character names are. The results show not only some of the most common first names, but also the bit parts that show up again and again and again. They also reveal that movie writers generally stick to the rule of never having a character's name end with the letter S -- there's only a single instance in the top 100.
See below the fold for the list...
November 6, 2012
I'm live blogging election night results as they come in and offering analysis on how the evening is going for each candidate.
12.25pm ET/9.45pm PT There are still a huge number of votes to count in many states, so it's too early to get a complete picture of why the election was called much earlier than I predicted. But among the states with 90% or more of the votes counted, it looks as though the winner (regardless of whether it's Obama or Romney) has outperformed the polls.
For example, Romney is currently ahead by 14% in South Carolina, versus a 13% margin predicted by 538, 34% in Oklahoma versus 32%, 20% in North Dakota versus 15%, 42% in Wyoming versus 37%, and 11% in Indiana versus 9% predicted. Meanwhile, Obama is up by 17% in Illinois versus a predicted 20%, 18% in New Jersey versus 12%, and 6% versus 6% in Pennsylvania. So, on average, Mitt Romney is up by 3% in the states that he has won, while the president-elect, Barack Obama is up by 1% on average in the states he has won. (Note that this is based on a small sample... I'll dig deeper tomorrow.)
With that said, it also looks as though the networks called the races considerably earlier than in previous years. CNN was among the last to call many of the races, but was still quicker than the model predicted. That actually continues something of a trend: 2008 was generally called earlier than 2004, although I suspected at the time that that was because the race wasn't quite as close. Maybe there are other factors at play (like better analysis by the networks, and faster counting by the states).
As I say, I'll take a closer look at all of these things tomorrow and over the next few days. For now, much earlier than I was expecting, I'll be signing off the evening.
November 1, 2012
In a break from our usual programming, here is my election night prediction for 2012.
Rather than predicting the result in each state, my prediction focuses on something slightly different: when each state will be called by CNN on election night. This is useful information, I think, for political junkies who are curious if and when they'll feel comfortable enough with the results to go to bed on Tuesday (or the early hours of Wednesday!). Since we're in for a close election, it also might tell us something about how likely it is we'll end election day without a clear winner, and if that will set us up for a long legal battle over who will emerge triumphant.
Click the video below to see the presentation, and see the full article below the fold for links to download the spreadsheets on which model is based.
August 30, 2012
A common area of debate for independent film-makers revolves around the question of the "ideal" production budget. Depending on who you talk to, and when, you'll hear that it's impossible to make money in the industry with a film budgeted at under $2 million, or over $10 million, or less than $20 million (or some other number). Producers who attend panels at conferences and film festivals often come back to me afterwards and ask if their $8 million project is doomed because a speaker declared that "no-one in their right mind would make an independent film for more than $5 million," or something similar.
This debate prompts a question: Is there an ideal budget for a feature film -- some budget level that will produce greater-than-expected returns for the film-maker?
July 25, 2012
Thanks to everyone who sent feedback on last week's article, "Are We Entering the Age of the Super-Blockbuster?". In this week's notes and feedback column, I share some of the best comments and suggestions, and also note a couple of articles that have popped up online in the last week. While the media and industry seems to be off and running with the "super-blockbuster/uber-hit" idea, our readers point out some ways that we need to do more work to pin down exactly what's going on.
July 19, 2012
Christian Bale as Bruce Wayne in Warner Bros. Pictures' and Legendary Pictures' action thriller "The Dark Knight Rises," a Warner Bros. Pictures release. TM & © DC Comics.
Steven Zeitchik recently posted an interesting article on the L.A. Times web site that discusses the possibility that we have entered the age of what he calls the "uber-hit ... movies that go beyond modest success to dominate the multiplex, often leaving other contenders far behind."
Statistical analysis can provide us with some insight into whether there really has been a sea change in the industry.
Bruce Nash is the Founder and President of Nash Information Services, LLC and Publisher of The Numbers.
As well as running Nash Information Services, LLC, he provides consulting and analytical services on the movie industry to major financial institutions and
media companies, as well as helping independent production companies finance their films.
Since 1997, he has developed the company's Movie Industry Model, a sophisticated tool for analyzing the past and future performance of movies, including ancillary revenue through
DVD and Blu-ray sales and rentals, TV sales, and foreign revenues.