top of page
This site was designed with the
.com
website builder. Create your website today.Start Now

Resources

Scroll down for datasets, relevant Washington University courses, and recommended readings.

To access our sports analytics internship and job opportunities list, email washusportsanalytics@gmail.com from your WUSTL email.

Datasets

https://tinyurl.com/washusportsdata

If you need help collecting another dataset, contact us at washusportsanalytics@gmail.com.

Relevant WashU Courses

  • Business of Sports Society: Another club worth checking out, visit their website here!

​​

  • Sports Business Analytics (Olin Business School; MGT 460I): Part of Olin's Business of Sports Minor, this course touches on the analytics side of the business of sports by teaching business analytics through sports-themed applications.

  • Managerial Statistics I, II (Olin Business School; DAT 120, DAT 121): A two-course sequence focused on the business applications of statistics, covering topics including probability, linear regression and forecasting.

  • Data Analytics in Python* (Olin Business School; OSCM 400C): An introduction to data science using Python, assuming no previous programming knowledge. The first half of the course consists of learning the basics of Python as a programming language, while the second half focuses on its data analytics applications including using examples from the sports industry.

  • Introduction to Computer Science (McKelvey School of Engineering; CSE 131): An introduction to computer science and programming in Java.

  • Introduction to Data Science (McKelvey School of Engineering; CSE 207A): An introduction to data science and machine learning taught in Python.

  • Introduction to Statistics* (College of Arts and Sciences; Math 1011): Basic concepts of statistics including data collection, data organization, and statistical inference.

  • Elementary Probability and Statistics (College of Arts and Sciences, Math 2200): An introduction to statistics, reasoning and data analysis. Students learn basic R commands. We recommend Math 2200 over Math 1011.

  • Elementary to intermediate Probability and Statistics (College of Arts and Sciences; Math 3200): Similar to Math 2200 with more use of R. Recommend instead of 2200 to students pursing higher level statistics courses.

  • Bayesian Statistics* (College of Arts and Sciences; Math 459): An introduction to the Bayesian approach to statistical inference including stochastic simulation (Markov chain Monte Carlo).

  • Multivariate Statistical Analysis* (College of Arts and Sciences; Math 460): Multivariate statistics concepts including clustering, model selection and evaluation, cross-validation, classification, and more. Uses R.

  • Probability* (College of Arts and Sciences; Math 493): Mathematical theory and application of probability at the advanced undergraduate level.

  • Mathematical Statistics* (College of Arts and Sciences; Math 494): Theory of numerous advanced statistical concepts.

  • Stochastic Processes* (College of Arts and Sciences; Math 495): Content varies, past topics have included random walks, Markov chains, Gaussian processes, empirical processes, and more.

 

* not offered every semester

All above-100-level courses (excluding Math 2200, 3200) have prerequisites. This list is not exhaustive.

Complete course descriptions available on WebSTAC.

Our Favorite Sports Analytics Books

  • Moneyball: The Art of Winning an Unfair Game, Michael Lewis (2004): In this best-seller turned blockbuster feature film, Michael Lewis follows the low-budget Oakland Athletics, their larger-than-life general manger, Billy Beane, and the strange brotherhood of amateur baseball enthusiasts. Michael Lewis has written not only "the single most influential baseball book ever" (Rob Neyer, Slate) but also what "may be the best book ever written on business" (Weekly Standard).

  • Astroball: The New Way to Win it All, Ben Reiter (2019): A perfect sequel to Michael Lewis's Moneyball, this best-seller summarizes how, in less than half a decade, the Houston Astros went from being the worst team in baseball to World Series Champions. The book describes how the organization discovered and utilized new metrics so similarly to how the Athletics did only 15 years before.

  • Scorecasting: The Hidden Influences Behind How Sports Are Played and Games Are Won, Tobias Moskowitz and L. Jon Wertheim (2012): Published in early 2012, University of Chicago (boo) behavioral economist Tobias Moskowitz and Sports Illustrated writer L. Jon Wertheim were some of the first to question and eventually disprove some of the most known truisms in sports. The authors discovered the influence of umpires and referees on homefield advantage as well as other aspects of they games they call, the authors address whether or not defense win championships, and they statistically examine the hot hand fallacy and more.

bottom of page