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Dr. Jim Albert: Emeritus Professor of Mathematics and Statistics, Bowling Green State University


How did you get into being a statistician? Can you tell us a bit about your career?

When I was growing up in the Philadelphia area, I was a sports fan (playing basketball and tennis and following all professional sports) and was good in math. I was a math major at Bucknell although I didn't understand at first how I was going to apply my math knowledge. Fortunately, I was able to take several courses in Statistics as an undergraduate and that led to me to pursue a doctorate at Purdue. My thesis was relatively theoretical, but I seized the opportunity to use sports examples in my papers. I was a professor at Bowling Green State University for 41 years. One joys of being a professor is that one is able to work on problems that you are passionate about, and that led to me to write papers addressing baseball questions from a statistical perspective.


What is your favorite stat to work with?

I have always been interested in so-called situational stats that describe how a baseball player performs in different situations. These situations could be home vs away, how they take advantage of a hitter's count, and how they perform against pitchers of different arms. Also, I have been fascinated in streaky performances, both by teams and individuals.


Which stat do you think is most useful in baseball?

The most useful stats are the ones that are useful in prediction. For example, a pitcher's FIP (fielding independent pitching) measure is more useful than a pitcher's ERA since two seasons of FIP stats have a higher correlation than two seasons of ERA. Teams focus on statistics that are helpful in predicting future performance.


What is your favorite moment from your career so far?

The publication of my first baseball book Curve Ball (joint authored with Jay Bennett) was one of my favorite moments since we were able to read a larger group of quantitatively oriented baseball fans.


What advice would you give, regarding stats, to a young kid trying to get into the sports world?

I started by playing simulation baseball games and following teams, focusing on the new statistical measures. No matter what one's major is, it is helpful to take a lot of math and learn a coding language like R or Python. Start doing your analyses that address some interesting baseball question of interest. This is a great time to do little projects given the ready availability of free baseball data.

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