Only 16% of 4,700 club bookings were women

but who's surprised

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In November the Chicago-based comedy journalist Zach Freeman released the Comedy Club Database, a resource tracking comedy club bookings by gender and ethnicity. He collaborated with a group of comics and one of his former students—he used to teach computer science at the University of Chicago—to make sense of thousands of bookings at 55 comedy clubs from September through December 2019. The top-line results were stark:

Maria Bamford @mariabamfoo
New Comedy club database now available at
projectccdb.com. Shows last 3 months of bookings at 55 clubs across the US with 16% women and 6% women of color.

Freeman will be the first to tell you that the study is incomplete. He and his collaborators gathered their data from clubs’ websites: if a given show did not list its features or openers, these bookings were not included in the data. The same goes for showcase-style shows whose lineups may not have been listed or were incompletely listed. Freeman emphasizes that when it comes to headliners, however, the project has data for every club in its dataset.

It should also be emphasized that the project tracked bookings rather than people. If Kurt Metzger performed six gigs at Zanies Rosemont on a given weekend in September, this would be counted as six male bookings rather than one. If Ali Wong and Maria Bamford each performed three gigs, this would be counted as six female bookings rather than two. And so on. 

I spoke to Freeman by phone yesterday about the project, the results, and the response he’s received from comics. This interview has been edited and condensed for clarity. 


Could you talk a bit about how this project came into being?

I write about comedy for the Chicago Tribune, and I was at a show, and I was talking to some comedians after the show, and they were talking about bookings—that some clubs seem to book predominantly male, predominantly white comics. They had talked about that with each other a lot, but they were like, “Is this just our bias? Are we just thinking that that's a thing and we don't know?” And one of them said, “I wish someone could build a database that could track this, and we could see if that's true or if that's just us thinking that we're being left out.” I'm paraphrasing—that's not their exact quote.

I'm also a programmer, and at the time I was teaching a class at the University of Chicago, in the Master's Program in Computer Science. A databases class, specifically. The students learn about designing and building a database. And I always get them to pick a project that they want to focus on and build around. So it was weird, because what [the comics] were describing was pretty much exactly what I would get a lot of students to build for class. And I told them how I could probably build a system that could track that pretty easily.

The spring of last year was the last time I taught. Since I had a little more time, I decided to build this project. I worked with one of the students that I had in the spring. We worked together and kind of designed the database and built the system, then the front end. Then we picked the timeframe. We asked the group of comedians which clubs should we track and what should we track—openers, features, and headliners, or just headliners, how should we do it? Like I said, I'm a programmer and I write about comedy, but I'm not a person who designs longitudinal studies or anything like that.

We picked a three-month time period to try to get a pretty substantial amount of data and not just say, "look at this one month," or "look at this one club," or "look at this one area." They picked clubs across the country, and we used the club's websites. Everything that they had listed there—openers, features, and headliners—we put all of that in the database. And then I built reports using Tableau. I built reports to pull that data out of the database to show the trends we were looking at. 

We broke it down in a bunch of different ways. I think the most interesting would be the total bookings by percent and by number. Just to show that percentages can say one thing, but if you don't know how much you're looking at, it doesn't really say much. So to see that in 4,700 bookings, 16% were female—again, it's as close to an objective scientific study as I think you could get, but we are trying to just objectively get all the data. 

I'm not trying to prove something. It just came out of that conversation. They said, "I wish someone could build the database and look at this." And so I did.

Were you surprised by the results? Did they line up with your experiences writing about comedy?

I was a little surprised. I think in writing about comedy, maybe I hadn't thought about that as much. I think I noticed there's more men, but I didn't necessarily think it would be that stark of a contrast. The female comedians I was talking to about this weren't at all surprised. So that's my blind spot as a man. The female comedians I talked to were like, “Yeah, that sounds right, 16 percent.” 

What else struck you about the results, other than that one imbalance?

From early on when we were entering the data, that was about the percentage. It seems pretty clear, across clubs, across time, that that's a pretty close percentage of bookings in general. Because as we were entering data, we didn't see a big jump from it being like, “Oh, it was 25%, and now it's ten, and now it's 15,” or whatever. Obviously there's variation among clubs, but they kind of consistently balanced each other out at about that percentage.

You can see on our reports that we can filter based on headliners, features, and openers. And if you look at all of them or if you look at just one of them, they still stay pretty close to that percentage. If you just filter by headliners, it's a little bit lower: 14.63%. 

Some of the pushback that we got when we put this out, on Twitter, was that we didn't have all of the features and openers. And that that is true. Some people were saying that we did that on purpose, to try to skew the numbers. But what we used was the clubs' websites. And some clubs list all their lineups: if they have an opener, feature and headliner, they'll list all three of them. Or if they have like a lineup night, maybe they'll list ten comedians for that night. If clubs had that, we would enter it. And if they didn't, then we didn't, because we were covering 55 clubs and we were just using their websites. 

So I think that is a fair criticism. Our data is, I would say, incomplete in terms of the openers and features, just based on how we gathered the data. But if you look at the headlining numbers, I know that we have all the headliners from all 55 clubs across three months, and that number is even a little bit lower. 

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I think that we're looking at maybe trying to do it again and trying to get a more complete set of data, or to go the other direction and just do headliners. I don't know if us trying to be as complete as possible maybe had the opposite effect—that people were like, "Oh, well, you didn't get all the data." But we were trying to get all the data we could. Again, I didn't build this to make some kind of point, but just to actually look at what the trends were. So if we just do headliners, maybe it's clearer, regardless of what you think of the results, these are accurate objective results. 

And like I said, if you filter by headliner now, that's exactly what it is. There's no missing data. These are the numbers.

Have you spoken to any club owners about the results? Or bookers, producers?

No, I haven't. I would definitely be interested to hear what they think. I know this is probably a sensitive spot for a lot of people, and I didn't build it to try to make anyone look bad. But I haven't talked to anybody. I would be interested to hear what they would say about these numbers. If they would say, “Yeah, that seems right,” or, “We're looking to improve that,” or, “This is a nonissue.”

What other reactions from comics have you gotten?

For the most part, just online, it seemed like comedians, especially female comedians, were very excited to have this information out there. That was the main reaction I saw, both publicly and in private messages. Like, “Thank you for doing this, this is a great resource, thank you for putting this together so we can actually see these numbers.” And then just a few comedians, like I said, pointing out that we didn't have all the openers, the features, that kind of thing. 

And again, I'm not trying to point fingers or make somebody look bad, but just literally gather the data. But it had some of the reactions that I kind of expected when you do something like that, of people being a little more upset than you might think, just based on looking at the data.

Anything else you'd want to say about it that I may have missed?

People have pointed out what we're missing, and we're looking at maybe doing another round of this to try to make it clearer that we're just trying to gather the data and get it as complete as we can. We're not trying to make some kind of point. The fact that the database exists came from somebody bringing that up and discussing it, but I'm just the programmer that built it. I'm not trying to build it based on my own biases, or enter data based on my own biases. That's the main thing. Whether people like it or don't like it, I don't want people to dismiss it just because they don't like those numbers. The numbers are real.


If you would ever like to talk to me about your experiences working in comedy, please feel free to email me back here or DM me on Twitter.

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