# Who's #1: The Science of Rating and Ranking

• 4h 40m
• Amy N. Langville, Carl D. Meyer
• Princeton University Press
• 2012

A website's ranking on Google can spell the difference between success and failure for a new business. NCAA football ratings determine which schools get to play for the big money in postseason bowl games. Product ratings influence everything from the clothes we wear to the movies we select on Netflix. Ratings and rankings are everywhere, but how exactly do they work? Who's #1? offers an engaging and accessible account of how scientific rating and ranking methods are created and applied to a variety of uses.

Amy Langville and Carl Meyer provide the first comprehensive overview of the mathematical algorithms and methods used to rate and rank sports teams, political candidates, products, Web pages, and more. In a series of interesting asides, Langville and Meyer provide fascinating insights into the ingenious contributions of many of the field's pioneers. They survey and compare the different methods employed today, showing why their strengths and weaknesses depend on the underlying goal, and explaining why and when a given method should be considered. Langville and Meyer also describe what can and can't be expected from the most widely used systems.

The science of rating and ranking touches virtually every facet of our lives, and now you don't need to be an expert to understand how it really works. Who's #1? is the definitive introduction to the subject. It features easy-to-understand examples and interesting trivia and historical facts, and much of the required mathematics is included.

Amy N. Langville is associate professor of mathematics at the College of Charleston.

Carl D. Meyer is professor of mathematics at North Carolina State University. They are the authors of Google's PageRank and Beyond: The Science of Search Engine Rankings (Princeton).

## In this Book

• Introduction to Ranking
• Massey’s Method
• Colley’s Method
• Keener’s Method
• Elo’s System
• The Markov Method
• The Offense–Defense Rating Method
• Ranking by Reordering Methods
• User Preference Ratings
• Handling Ties
• Incorporating Weights
• “What If…” Scenarios and Sensitivity
• Rank Aggregation–Part 1
• Rank Aggregation–Part 2
• Methods of Comparison
• Data
• Epilogue
• Glossary
• Bibliography