Applied Sports Analytics

Course Description

Since Michael Lewis’s Moneyball, there is huge interest in using analytical methods in sports. Professional sport organizations are using analytics to make better decisions on team formation, playing strategy etc. Enthusiasts use analytics to predict the outcome of the sport event and to try to quantify reasons that make team win. We are going to look at the basic models for predicting the game outcome, such as Poisson regressions, Bradley-Terry models, Elo ratings, and analyzing match results.

Course topics

Sports Analytics, Predictive modeling, Regression.

Course tools

R.

Prerequisites

Basics of Probabilities, Probability distributions, regressions, working with dataframes in R.

Lecturer

Habet Madoyan Visiting lecturer at American University of Armenia, CEO at Datamotus Habet Madoyan is teaching several courses at the American University of Armenia such as Sports Analytics, Data Mining, Design and Analysis of Experiments and Applied Statistics. He is also co founder of myChoice LLC (http://mychoicesurveys.com/) (Singapore), a platform for automated design and analysis of conjoint experiments. Habet is also CEO of the boutique data analytics consulting company ‘Datamotus’, operating in Armenia. Fields of interests: Data Mining, Sports Analytics, Applied Statistics, Machine Learning, Statistical Analysis, Business Analytics. Contacts: madoyan.h@gmail.com www.linkedin.com/in/habetmadoyanmba/ github.com/Habet/