Curve Ball: Baseball, Statistics, and the Role of Chance in the Game

by Jim Albert, Jay Bennett

The intent of this book is to look at baseball data from a statistical modeling perspective. There is a fascination among baseball fans and the media to collect data on every imaginable event during a baseball game and to use this data to try to understand characteristics of the game. The problem is that patterns in baseball data are difficult to detect due to the inherent chance variation that is present. This book addresses a number of questions that are of interest to many baseball fans. These issues include how to rate players, predict the outcome of a game or the attainment of an achievement, making sense of situational data, and deciding the most valuable players in the World Series. This book will be directed to a general audience of baseball fans and does not assume that the reader has any prior background in probability or statistics, although a knowledge of high school abgebra will be helpful.

Genres: Baseball, Sports, Mathematics, Nonfiction

350 pages, ebook

First published January 1, 2001

About the author

Jim Albert is a Distinguished University Professor of Statistics at Bowling Green State University. His research interests include Bayesian modeling and applications of statistical thinking in sports. He has authored or coauthored several books including Ordinal Data Modeling, Bayesian Computation with R, and Workshop Statistics: Discovery with Data, A Bayesian Approach.

Reviews

[Jimmy Tarlau · Rating 3 out of 5]

I like statistics and I like baseball and know something about both subjects but this book is a stretch for most people who are not really into statistics. The topics are interesting: does the best team really win, what is a streaky hitter, are there such things as clutch hitters, and which playeres are the most important for the team. I'm not sure I learned a lot except to understand about how baseball stasticians work on the subject. A lot of what you learn is that the random chance is that probably the best team won't win a world series. One strange chapter had to do with Sammy Sosa and his probability of hitting a home run and how many home runs he would hit in the future based on what he has done in the past.....oh oh - maybe the probability had to do with steroids. Interesting but not for everyone.

[Tim Basuino · Rating 4 out of 5]

Not for the faint of heart, "Curve Ball..." looks at baseball from a probability-calculating standpoint. One of its best points is that what may be interpreted as an increase/decrease in skills may in fact be random fluctuation, a.k.a. "Noise". This could almost be a college textbook (and it certainly would have been a lot more interesting than some of the material I had to work with way back when).

[Dave · Rating 2 out of 5]

Doesn't really add anything to the statistical body of knowledge about baseball. The only redeeming feature is a discussion of tabletop baseball games and their use of probability and relative realism.

[Chris Aldrich · Rating 4 out of 5]

The original textbook for sabremetrics.