This week our featured book is Sports Analytics: A Guide for Coaches, Managers, and Other Decision Makers, by Benjamin C. Alamar, with a foreword by Dean Oliver. Today, the last day of our book giveaway, we have an excerpt from a couple of print interviews with Ben Alamar on his book, the use of statistics in organizations, and how one should prepare for a career as a sports statistician. The first of these two interviews can be found in its entirety on the Sports Analytics Blog, and the second at STATtr@k.
Sports Analytics Blog Interview
SA Blog: What made you decide to switch from “Corporate America” (where you worked for PwC) to the sports industry?
Ben: I switched careers as soon as I realized that I might be able to create a career in sports for myself. I grew up as a sports junky, but not a baseball fan, so it was not until after I had finished graduate school that I became aware of Bill James and the use of statistical analysis in baseball. Once I saw what was happening in baseball, and I had the good fortune of working with Aaron Schatz, Roland Beech and Jeff Ma at Protrade, I was sold. The possibility to apply these tools in football and basketball were too exciting to me to pass up.
SABlog: Can you talk a little about the Journal of Quantitive Analysis in Sports which you founded? What does it entail and what inspired you to start it?
Ben: When I decided to work in sports, I also wanted to pursue an academic career. Professors have to publish their research in academic journals in order to progress in their careers. I knew that there was really no field of sports statistics in academia, thought there were researchers all of the world that had done a paper or two in the area. I started the journal to provide a consistent place to publish high level statistical analysis of sport. I needed the journal myself and I felt that others would appreciate the outlet for their work as well.
SABlog: What advice would you give to students and young professionals trying to break into the industry?
Ben: Develop skills in statistics and data management, and then spend some time trying to determine questions that coaches and general managers would want to know the answers to. Once you can identify these questions, answer them analytically and find a way to present them that makes the results clear and engaging to people who don’t have your training in statistics but know a lot more about the sport than you do.
JA: When were you first interested in statistics applications in sports?
BA: I wrote my first paper on modeling the probability that an NFL team would make the playoffs during my third quarter in graduate school. I liked the paper, but never got it published. I didn’t return to stats in sports until I was a post doc at UCSF. I did some consulting work for a start-up company in the field and decided that it was the area I wanted to concentrate on.
JA: Are there specific statistical tools or topics that you find especially helpful in your work? If a person had to take, say, three courses in statistics to help them in your work, what courses would they be?
BA: Some important tools include basic regression analysis, logistic regression, Monte Carlo simulation, classification, and hierarchical regression. Just as important as the technical tools though is the skill of effectively communicating the analysis to nontechnical audiences.
JA: Is there specific statistics or data-management software that you find helpful?
BA: R and SQL are very useful.
JA: What are the first steps in entering the sports industry as a statistician?
BA: There is no clear path. I recommend that aspiring sports analysts try to answer a question they think a general manager or coach would find interesting, then find a way to get that work into the hands of people who might be interested. There is no shortage of people interested in working in the field, but there is a shortage of people who have actually done good work in the field.
JA: In “Moneyball,” there was some resistance to the use of statistical methods to learn about players, especially by people who were not part of the baseball establishment. Do you think there is a similar resistance to the use of statistical methods in basketball?
BA: I would not classify it as resistance, but I think there is a natural skepticism of employing any new tool when you have had success previously without it. As decisionmakers gain more exposure to information that analysis can provide, they tend to become more interested.
JA: Do you think there will be an increasing demand for statisticians in your particular sport?
BA: Yes, I do. Data sets are becoming more complex (motion capture technology is being used to track everything that moves on the court 25 times a second) and the general concept of using statistics is gaining more acceptance; these factors will lead to more teams employing large analytics groups.