Chapter 22 of David Barber's "Bayesian Reasoning and Machine Learning" (he makes it available online) does a nice (perhaps brief) job of explaining the progression through the Rasch model, the Bradley-Terry-Luce model and Elo.
As an aside, the way they chesstempo generate the exercises is also cute. The tactical chess problems are positions taken from high level (human) games fed into a chess engine which identifies blunderous moves where there is a single distinctly best way to respond. The challenge is to find that best move. Because they are taken from real games, they have the appearance and feel of real positions, which is important; many people believe pattern recognition is an important part of chess mastery. Apparently they've built up nearly 40000 such tactical exercises.