![]() ![]() What about R to analyze data in other sports, in the whole world and, specifically, in Italy? In the third millennium, working with a guy who lives more than 4,000 miles away is not so difficult: we frequently exchanged emails, and we had a couple of videochats along the way. From my perspective it was the perfect match: it was the first time I was writing a book, and I definitely needed an expert guide (just look at Jim’s body of work!). Well, John asked me if I would be fine if they gave me Jim as a teammate. Can you believe that was the first book I read on the subject? It happened that the editor of the series, John Kimmell had been the editor for the book Curve Ball, also co-authored by Jim, back in 2003, a very successful book on statistics applied to baseball. Well this is one of the great turns of luck that happen once in a while. While writing the introduction I surveyed people working as analysts inside front offices of Major League Baseball teams, and most of them mentioned R as one of their tools. Some of them told me they were thinking about learning R, so a book featuring baseball examples is just what they were looking for. I believe many of the guys doing baseball data analysis have more an IT than a statistician background, thus a lot of them use languages not directly related to stats, such as SQL, Python, etc. And then, a couple of years ago, a big movie was made about that (based on a best-seller book), starring Brad Pitt.Īnd is R popular for analyzing baseball data? What software is most often used to analyze sport data? A long history of data collection, a season consisting of 162 games per teams, and the games progressing in discrete events, making its analysis easier. Well, baseball features what is probably the perfect combination for a data analyst. In fact, data analysis is very popular in baseball. I definitely wasn’t thinking about selling copies in Italy, but I thought the book could be of some interest to baseball fans in the United States, especially those wanting to wet their toes in a field that is growing in popularity. ![]() At the same time, baseball is not very popular in Italy and only few people know it. R is very popular among statisticians but it’s not such a widespread programming language like Java or C. The examples they suggested were biology, epidemiology, genetics, engineering, finance, and the social sciences. They were accepting suggestions for books (for their R Series) on three main themes, one of which was “Applications of R to specific disciplines”. Some time ago CRC Press sent a call for proposals to several mailing lists. Last time you wrote for us a series of articles about maps with R. ![]() Max is the author, with Jim Albert, of the book “ Analyzing baseball data with R“. This week, the post is an interview with Max Marchi. ![]()
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