You may call James R. Ashburn and Paul M. Colvert football maniacs. Or researchers with too much time on their hands. Or statisticians looking to apply data analysis everywhere they look. Or all of this at the same time.
Nevertheless, they have written a paper called A Bayesian Mean-Value Approach with a Self-Consistently Determined Prior Distribution for the Ranking of College Football Teams (currently in preprint). Behind this long title, hides a quite classical application of statistics.
We introduce a Bayesian mean-value approach for ranking all college football teams using only win-loss data. This approach is unique in that the prior distribution necessary to handle undefeated and winless teams is calculated self-consistently. Furthermore, we will show statistics supporting the validity of the prior distribution. Finally, a brief comparison with other football rankings will be presented.
If you want to know how far a stastistician can go on a semi-serious subject using a serious tone, read the article linked above, it can get pretty interesting, despite being 31 pages long!
The NCAA football matches is a dataset frequently used by statisticians to develop and test some algorithms and it has made the object of many studies with such esoteric titles as ” A Penalized Maximum Likelihood Approach for the Ranking of College Football Teams Independent of Victory Margins“, “Random Walker Ranking for NCAA Division I-A Football” and “Hybrid Paired Comparison Analysis, with Applications to the Ranking of College Football Teams“.
July 26th, 2006 | General Science | 1 comment
When Huygens came to rest on the surface of Titan on 14 January 2005, it survived the impact and continued to transmit to the Cassini mothership, orbiting above. Part of that radio signal ‘leaked’ downwards and hit the surface of Titan before being reflected back up to Cassini. On its way up, it interfered with the direct beam.