Aggregating and statistical reasoning with ranked data are tasks that arise in a number of applications from analyzing political elections to modeling user preferences over a set of items. Representing distributions over rankings, however, can be daunting due to the fact that the number of rankings of n items scales factorially. Moreover, it is crucial for probabilistic models over rankings to ...

We investigate the sensitivity of the Colley Matrix (CM) rankings—one of six computer rankings used by the Bowl Championship Series—to (hypothetical) changes in the outcomes of (actual) games. Specifically, we measure the shift in the rankings of the top 25 teams when the win-loss outcome of, say, a single game between two teams, each with winning percentages below 30%, is hypothetically switch...