I find this interesting, both from a data design standpoint as well as from a socio-political standpoint.

Sometimes this guy simply outdoes himself.

After the first weekend of college bowls, here’s how my model stacks up against the actual results. 

Isn’t it taxation without representation when you put your non-voting younger generation so far into debt that you enslave their future?

As reported by Fox News and the London Telegraph, Simon Blackburn of London’s Royal Holloway College has developed a mathematical equation describing the geometry of parallel parking. Dr. Blackburn’s page (found here) has a link to his original paper.

I have developed the following college football bowl predictions based on my model of college football rankings. A few things to note: the most lopsided matchup seems to be Nevada vs SMU. The best matchups seem to be Oklahoma vs Stanford and South Carolina vs Connecticut.

Below I gave top 30 rankings based on a system I developed. Those rankings included such factors as home field advantage and point spread — factors the BCS forbids computer models from considering.

Below is another top 30 list. The rankings are based strictly on the Elo ranking system. For an excellent description of this system, see this article in Wikipedia. I take a different approach than straightforward Elo ranking, though. I first rank all games between FBS and FCS opponents. I then set each conference’s initial score to their respective division score. I then rank all out of conference games. I set each team’s initial score to their respective conference score. For the division and conference ranking I use K = 24. Next I rank each game, using K = 96. The teams are ordered by descending score (ie. highest score is ranked #1).

Here are the results through games played by December 5.