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Analyzing Baseball Data with R (Chapman & Hall/CRC The R Series) Paperback – October 29, 2013

ISBN-13: 978-1466570221 ISBN-10: 1466570229

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Product Details

  • Series: Chapman & Hall/CRC The R Series (Book 14)
  • Paperback: 352 pages
  • Publisher: Chapman and Hall/CRC (October 29, 2013)
  • Language: English
  • ISBN-10: 1466570229
  • ISBN-13: 978-1466570221
  • Product Dimensions: 1 x 6 x 9 inches
  • Shipping Weight: 1 pounds (View shipping rates and policies)
  • Average Customer Review: 4.7 out of 5 stars  See all reviews (23 customer reviews)
  • Amazon Best Sellers Rank: #116,400 in Books (See Top 100 in Books)

Editorial Reviews


"If you are interested in statistics, especially baseball statistics, you will find this book fascinating and very useful. It provides many details. websites, and useful descriptions for using the R programming environment. This is not only a book on statistics; there are many references to famous player statistics, making this a very enjoyable book to read. And even if you don’t like baseball but still find statistics very exciting, then this book provides a great introduction to R that can be used for any other type of statistical data set."
IEEE Insulation Magazine, November/December 2014

"I have spent most of the past decade working in baseball as a statistical analyst for the New York Mets. … This type of employment can be highly valued, especially among quantitatively inclined college students who are coincidentally passionate baseball fans. It is from these students from whom I am most frequently asked, ‘what book would you recommend for someone who wants to get started in sabermetrics?’ Invariably, my response has been [Jim Albert and Jay Bennett’s] Curve Ball. I have a new response. …
I always felt that Curve Ball was the best place for a budding sabermetrician to start … However, it later dawned on me that while Curve Ball provided a sound framework for thinking probabilistically about baseball, I devoted a huge proportion of my time at work to computer programming. …
In their new book, Albert and Max Marchi, a native Italian who now works for the Cleveland Indians, have closed the loop by offering the aspiring sabermetrician a blueprint. … The reader who digests this book alongside her keyboard will emerge as a practicing sabermetrician—having knowledge of the key ideas in sabermetric theory, a historical understanding of from whence those ideas came, and the practical ability to compute with baseball data. It is a sabermetric workshop in paperback."
—Ben S. Baumer, International Statistical Review (2014), 82

About the Author

Max Marchi is a baseball analyst with the Cleveland Indians. He was previously a statistician at the Emilia-Romagna Regional Health Agency. He has been a regular contributor to The Hardball Times and Baseball Prospectus websites and has consulted for MLB clubs.

Jim Albert is a professor of statistics at Bowling Green State University. He has authored or coauthored several books and is the editor of the Journal of Quantitative Analysis of Sports. His interests include Bayesian modeling, statistics education, and the application of statistical thinking in sports.

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Customer Reviews

4.7 out of 5 stars
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Long story short, I got whipped.
Mike Byrne
Instructions on where and how to download the code and data used in the tutorials are also in the book.
I Wanna Be A Pepper Too
I purchased the kindle edition, which I am reading though my iPad.
Mark Conrad

Most Helpful Customer Reviews

11 of 11 people found the following review helpful By JULIEK on January 26, 2014
Format: Paperback Verified Purchase
I'm admit am not really into baseball analytics. However, I have been slowly getting into analytics for other sports, and really wanted to start using R to explore my data. I am pretty new to R, so I had no idea what to do with 200+ variables had collected in excel, in Rstudio. So I turned to texts and other books but struggled. A majority of the time the books I read used business data etc for examples which didn't really help me personally, grasp how I could replicate the same commands using my sports data. Trying to find a book that has programing and sports in it is like finding a needle in a haystack. This book was the only book that came up in search results when I entered sports + analytics. When I stumbled upon it, despite it being about baseball, I bought it immediately after I recognized Jim Alberts name (from JQAS), and I am so glad I did. For those sports data lovers out there who want to understand how to use R to analyze your datasets rejoice! because this is only book you will probably need!!!!

Prior to using this book had no programming background except a few seminars on python and since then have self taught myself further with code academy etc. As for R, I have been to 2 "intro" free seminars, and admit I only grasped the fundamentals of commands in the R console because the commands follow very similar structure those in a python terminal. However, in terms of R as it applies to sports, how and what commands I enter/use to answer various questions about my data I had trouble grasping without any examples to help me, a visual learner, learn from. Prior to this book no other book I've come across has provided examples with R being applied to sports. Thus this book has been a godsend.
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14 of 15 people found the following review helpful By J. Mills on November 1, 2013
Format: Kindle Edition Verified Purchase
This will be essential reading for those looking to learn R as it specifically relates to baseball analytics. The book explores various datasets, explains with clarity how they are designed, and discusses how they can be utilized to do baseball specific analytics. Easily the most comprehensive resource available for the aspiring baseball analyst as it compiles much of the work previously located in hidden corners of the blogosphere into one easily understandable and accessible book. A must buy.
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6 of 7 people found the following review helpful By Devon on January 26, 2014
Format: Paperback Verified Purchase
Probably unlike most people who will buy this book, I am more well versed in R than I am Sabermetrics. I bought this book to teach me more about baseball statistics, and I figured it would be worth it considering Jim Albert's involvement.

I have taken formal classes in R in graduate school, and let me tell you this book was a dynamite review and I think even better at teaching basic coding and packages than some of the books solely dedicated to R out there. It also directed me to some databases I was unfamiliar with and where to find specific datasets, which is amazing.

This is a must buy for those looking to conduct statistical analyses on their favorite team while utilizing free software.

Looking forward to next season.
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2 of 2 people found the following review helpful By Dimitri Shvorob on December 26, 2013
Format: Kindle Edition
I confess to having no interest in baseball - why check out the book then? For the chance of finding a nice, transferable statistical analysis or visualization - but if you do, "Analyzing baseball data with R" is an excellent learning aid, offering wealth of information and effectively teaching R via a sequence of substantial data-exploration exercises. I like the book's attention to its datasets and data sources - note also the sections on parsing online data and storing data in MySQL database - and give extra points for good coverage of "ddply", "lattice" and "ggplot2" R packages.
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1 of 1 people found the following review helpful By Jerry Saperstein HALL OF FAMETOP 500 REVIEWERVINE VOICE on September 24, 2014
Format: Paperback Vine Customer Review of Free Product ( What's this? )
R is an open source programming language intended for statisticians and data miners. Applying R to processing baseball statistics is a brilliant move. Even if you have no interest in baseball or the vast body of statistics surrounding it, the data will be familiar: Babe Ruth and Hank Aaron, homeruns, hits and so on. Even non-fans will have some familiarity with baseball.

The authors apply R to a variety of statistical analyses of baseball statistics. I knew that there were people who followed baseball closely, but I was frankly surprised by just how seriously so many people take analysis of baseball statistics. There’s even a name for the pursuit: sabermetrics. (As Explained on Wikipedia: “the empirical analysis of baseball, especially baseball statistics that measure in-game activity. The term is derived from the acronym SABR, which stands for the Society for American Baseball Research. It was coined by Bill James, who is one of its pioneers and is often considered its most prominent advocate and public face”.)

The book has a very different structure than most programming tutorials. No time is spent preparing you with fundamentals: the authors just dump you into analyzing baseball statistics with R. Boom. Open the book and you’re there. If you are aready a programmer, it’s a good approach – but if you’re not, I think you’ll possibly encounter problems.

I use Excel for data analysis and mining, can brute force my way through several dialects of Basic and sort of hold my own with Python.

With this book, picking up a basic working knowledge of R is not only easy, but fun and interesting.

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