How to get started with rating and ranking based on pairwise competition data? I'm interesting in learning about how to rate and rank individuals in a group who only interact/compete in a pairwise fashion (i.e., systems like the ELO rating system for chess). 


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*Are there are any go-to methods or more accurate and advanced methods out there? 

*Are there any R packages that make implementation easy? 

*Are there methods that can use auxiliary information as well as the outcome of a match/game? 

*Are there methods that can better use the information of winning margin as opposed to dichotomous win/lose?

*What should I be looking for in the literature?

 A: I just finished a pretty good book on that subject. It discusses ELO as well as many other ranking methods like Massey, Colley, and Keener's. Most of the methods in the book use sports matches as the example and use both win/loss and margin of victory as inputs.
A: Since asking this question, I've found I've had lots of success with the PlayerRatings package for R. It makes creating ELO/Glicko and the authors own method of performance ratings very easy.
A: This book does not work with margins but provides the theory of rank teams based on paired comparisons. The Method of Paired Comparison by Herbert A. David http://www.amazon.com/Method-Paired-Comparisons-Statistical-Monograph/dp/0852640137/ref=sr_1_1?s=books&ie=UTF8&qid=1340424897&sr=1-1&keywords=The+method+of+paired+comparisons
Regarding victory margins I beleive some of the computer methods used for the BCS combine paired comparison methods such as the Bradley-Terry model with victory margins.
A: Regarding "how to do it in R", the prefmod  package http://cran.r-project.org/web/packages/prefmod/index.html  is meant for preference analysis with paired comparisons, rankings and ratings. It fits Bradley-Terry models and pattern models with object and subject covariates. See my answer here How to fit Bradley–Terry–Luce model in R, without complicated formula? for a short intro, or this paper http://www.jstatsoft.org/v48/i10 for more info. 
