Stefan Szymanski is an economist whose research focuses primarily on sports. He has published more than 100 papers in peer reviewed journals and written ten books, including the international bestseller Soccernomics (with Simon Kuper). He was born in Nigeria to a Polish father and English mother, lived most of his life in London, until moving to Michigan in 2011.
Coursera
Discover the art and science of forecasting in professional sports with our 'Prediction Models with Sports Data' course. Master the use of Python to model past game results and accurately predict future outcomes, all while learning about logistic regression techniques applied to team performance analysis.
Coursera
Dive into the world of sports analytics with our beginner-friendly course. Using Python, explore how to represent and analyze sports data, focusing on regression analysis for team and player performance across major leagues like NFL, NBA, NHL, EPL, and IPL. Gain valuable skills in extracting meaningful insights from sports data.
Coursera
Dive into the world of sports analytics with 'Moneyball and Beyond', a course that explores the transformative power of data-driven decision-making. Uncover the secrets behind the Moneyball phenomenon and learn to apply advanced statistical methods using Python programming. This course is perfect for enthusiasts, students, and professionals looking to understand how data has reshaped professional sports.