WARNING: NOT MOBILE FRIENDLY Data Ahead!
As promised here's the data for ALL of
Flat Track Stats info I've been working on. I've broken this up into a couple of Dashboards you can visit or you can go
here to view the whole book as a collection.
Dashboard 1: The Whip It Effect
The first Dashboard shows League Type by Start Date (not filtering for leagues that no longer exist). Note the LARGE increase from 2009-2010.
Whip It came out September 13, 2009 and was a large boon for the roller derby community obviously as numbers shot up FAR faster than in previous years or since.
The second part of the dash shows Bouts by Type over time and just shows exactly how many bouts and how exponentially it grew in the first few years of the sport to now having over 4500 bouts on average for the last 3 years! This is an area you can filter to see how many bouts there are comparitively between juniors, women, coed, and men's leagues by checking the boxes to the right.
Lastly you'll find the number of tournaments by type (most being labelled obviously as "Invitational") but it's interesting to see how many more Seeded Bracket tournaments have been held in the last few years.
Dashboard 2: Home Team Winners
This dashboard I've filtered by default the teams that will be competing this weekend in the WFTDA Championships. You can click "All" on the Filter at the right, click it again to basically clear "All" and then type in your team name if you're interested how your team (or your league) is doing at home.
The left half of this dashboard are score differentials over time for all bouts (above the median line and in green means they won, below the median and going towards red means a loss). The trend lines show how those selected teams have done over time at home and if they're doing better or worse (hint: most teams are doing better and better with home field advantage even when normalized for total score, which this is not).
The right half of this dashboard is all the games that the selected teams have had at home. Again red is a loss, green is a win with the point difference at the end of the bar. This is just to kind of see how a team has performed over time and gives you a quick glance at who they've played and how they've done against them.
Dashboard 3: Where did all these derby people COME FROM!?
If you haven't watched the fancy video I made I'll go ahead and imbed that again here:
The data itself looks like Dashboard 3 where you'll see the totals for different types and can click around to sort by genus of league (again, coed, junior, men, women's and all).
Bonus Viz: How Popular is Roller Derby Where You Live?
Finally I wanted to see, based on state population where derby was "most popular" by capita. I took 2013 State Population Estimates from
http://www.data.gov/ and ran that against the states teams were located in. This data is based on all ACTIVE teams (teams with a "Disbanded Date != Null" were removed). Since I don't have the number of players per team I decided to multiply the numbers up a bit so we could see how many roller derby team per 1 Million people there were in each particular state. What I found was really interesting and will require more research but seems to point to the fact that larger states (regardless of population) tend to have more teams. The ultimate conclusion though is if you want to know where has the most derby per capita. Wyoming. No kidding gang!
The top number on each state is the number of teams (again only Active teams) that are in that state. The bottom number is the number of teams per 1 million people in that state's population. Play around, sort out just junior leagues or just look at your state in particular. All maps in these visualizations are zoomable so go nuts!
I hope you enjoyed these graphs and if you want to talk more about it hit me up via email
here or at twitter
@wjking0 to talk to me about more data nerd stuff I've been working on. Thanks again to Flat Track Stats for having an AWESOME data set to work with and I look forward to doing more in the future (penalty info anyone!?)! Much derby love! <3 -Jack Flash
So I got thinking about where fun places to buy things are. I've recently fallen desperately in LOOOOOVE with Import.io. I'd been playing with a few little data scrapes but I finally decided to put it through some real paces now that I understood better how to train it and analyze the data after-the-fact.
