Visualisation of Sport Ratings

University of Amsterdam, Fall 2014
Research project proposal for Bachelor Artifical Intelligence (AI), Honours Programme
Supervisor: Christian Schaffner (ILLC / email)

Motivating Problem

In American Football, the 120 top US-college teams each play a season of roughly 15 games against some geographically close opponents. Given the outcomes of all these games, determine the top two teams that deserve to play in the national college super bowl.

The standard way of ranking teams based first on number of wins and then on goal difference might work rather poorly in this case, because not a full Round Robin has been played. Also, this system does not take into account the strengths of the opponents. Sport rating systems analyze the results of sports competitions to provide objective ratings for each team.

The problem with these systems is that they are mathematically not as easy to understand as "getting 3 points for a win, and 1 point for a draw". Hence, we want to use modern visualisation techniques in order to illustrate how the rating system works to the mathematical outsider.

Research Objectives


Number of students

2 is preferred, 3 is possible.


Introductory Presentation for the students