Last month, I posted a review of a new book titled “Who’s #1?” on the mathematics of ranking and rating – if you’re interested, you can purchase a copy via the Amazon sidebar on the right. Today I’d like to study the San Francisco Giants with one of the techniques used in this book: the offense-defense rating method.
Why the Giants? It’s really just a personal preference. For the non-Giants fan, though, it’s worth pointing out that the Giants won the World Series in 2010, but failed to even make the playoffs in 2011. Let’s try to investigate why this is the case. Baseball fans may have their own explanations for this observation, but for a moment let’s focus on the math.
Let's go Giants!
As the name suggests, the offense-defense rating method rates a team’s offensive and defensive capabilities. Of course, these two things are highly interdependent – if a baseball team . . . → Read More: Were the San Francisco Giants #1?
In an earlier post, I closed by hinting at the mathematics of ranking. In this modern era, the topic is particularly relevant: the ranking algorithms are hard at work whenever you type something into a search engine, rate a movie on Netflix, or look at a product on Amazon. It’s also a popular area of study among sports enthusiasts, for whom accurate rankings of the relative strengths of teams can make all the difference in a fantasy league or a betting pool.
Because of all of these accessible applications, it should come as no surprise that the mathematics of ranking is the subject of a new book, titled Who’s #1? The Science of Rating and Ranking. Written by applied mathematicians Amy N. Langville and Carl D. Meyer, the book tackles a variety of methods used to extract ratings or rankings given some collection of input data.
This book is chock full . . . → Read More: Math in Books: Who’s #1?