What's new?

June 2008 - After a long delay (and a bit of downtime), sportvis.com is on a new server. In the near future, I plan to convert this site to a blog format, making it easier to post more often.

January 18, 2007 - I've started posting data to my sister site, Crashing the Dance, where we use machine learning techniques to predict the selection and seeding choices of the NCAA Tournament selection committee based on their historical behavior.

October 29, 2006 - I'll be in Baltimore this weekend for InfoVis 2006 If you're at the conference, stop by and see my poster Monday night at the poster session.

August 3, 2006 - I just learned that my poster submission for the 2006 IEEE Symposium on Information Visualiizaton (a.k.a., InfoVis 2006) has been accepted! InfoVis is the leading conference in the field, so this is pretty exciting. Thanks to John Stasko, my infovis professor and master's project advisor.

July 1, 2006 - Today I'm giving a presentation at the Society of American Baseball Research (SABR) convention in Seattle. I will be talking about using information visualization (infovis) with baseball statistics by giving a brief infovis tutorial and showing the work I did at Georgia Tech.

I will post slides and references from my talk shortly. I would like to post a version of the visualization tool I built, but I need to get it to a point where I feel comfortable releasing it to the public.

About SportVis

SportVis will try to capture and publicize use of information visualization (infovis) with sports statistical data. More importantly, we will help push further integration of sports and infovis.

Major American sports generate substantial amounts of numerical data that lend themselves to statistical analysis. Primarily through the work of Bill James and the availability of data on the Internet, advanced baseball statistical analysis (typically called Sabermetrics) has gained substantial traction. More recently, other sports, including basketball (e.g., Dean Oliver, Ken Pomeroy) and professional football (e.g., Football Outsiders) have received analytical treatment. However, there is still a resistance among the general sports fan to embrace this new lens through which to view the game.

Some of this may be attributed to the often unsophisticated presentation of complex information, something to which information visualization is particularly suited. Unfortunately, there has been surprisingly little substantial application of information visualization to sports statistics. Presentations of general information visualization systems (e.g., Spotfire) and techniques (e.g., treemaps) frequently use sports data as examples. There is a dearth of tools (the visualization of a tennis match is one notable exception) to help users with tasks specific to analyzing sports. Such tools could not only enhance the enjoyment of fans, but also assist media coverage and team officials decision making.

More to come soon...