The goal of this site is to help you learn all the practical steps you need to create and interpret sports analytics. You will learn how to:
- access the huge amount of sports data available on the internet;
- create charts and graphs to get insight and tell interesting stories about the data; and
- make useful sports predictions supported by the data.
Probability, statistics and machine learning are very important and useful in many fields in today’s world. Fortunately, sports analytics is a great setting to learn about these topics in a fun and practical way.
I hope you find this site helpful and informative, whether your goal is to improve your fantasy team roster, make better NCAA March Madness picks, learn about the exciting field of sports analytics or just improve your skills in math and coding. Enjoy, and please contact me with any comments and suggestions!
Read the welcome post for more about why I started this blog and what you’ll find here.
I live in New York City with my wife and children. I graduated from Princeton University with a degree in Aerospace Engineering. I also have an MBA in Analytical Finance from the University of Chicago’s Booth Graduate School of Business. I’ve worked in structured finance trading and investing for over 17 years, and was an information technology consultant prior to that.
I have always been a Yankees and a (long-suffering) Knicks fan. I am happy to say that some of my closest friends are Mets fans, and that we can all get along here in NYC. My biggest personal sports interest currently is tennis, although over the years I have enjoyed playing lacrosse, basketball and golf as well. I also enjoy playing fantasy sports with friends and family.
My fascination with sports analytics is an extension of my interest in sports (both the games themselves, as well as the business of sports). It’s also a natural application of my quantitative background, which includes years working in quantitative finance, technology and academic coursework in statistics, applied mathematics, optimization and computer science.
I decided to start this site as a way to express my growing interest in teaching, and to share what I’ve learned along the way.
I have attended the MIT Sloan Sports Analytics Conference with my older son, and have worked with my children on sports analytics projects outside of school to help motivate them to learn more advanced skills. I hope that my children’s work will make its way into future posts.
About this Site
The analyses and examples displayed on this site access publicly available data and utilize open source software.