Sports analytics has emerged as a field of research with increasing popularity propelled, in part, by the real-world success illustrated by the best-selling book and motion picture, Moneyball. Analysis of team and player performance data has continued to revolutionize the sports industry on the field, court, and ice as well as in living rooms among fantasy sports players and online sports gambling.
Drawing from real data sets in Major League Baseball (MLB), the National Basketball Association (NBA), the National Hockey League (NHL), the English Premier League (EPL-soccer), and the Indian Premier League (IPL-cricket), you’ll learn how to construct predictive models to anticipate team and player performance. You’ll also replicate the success of Moneyball using real statistical models, use the Linear Probability Model (LPM) to anticipate categorical outcomes variables in sports contests, explore how teams collect and organize an athlete’s performance data with wearable technologies, and how to apply machine learning in a sports analytics context.
This introduction to the field of sports analytics is designed for sports managers, coaches, physical therapists, as well as sports fans who want to understand the science behind athlete performance and game prediction. New Python programmers and data analysts who are looking for a fun and practical way to apply their Python, statistics, or predictive modeling skills will enjoy exploring courses in this series.
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.
Coursera
Dive into the world of Wearable Technologies and Sports Analytics to understand how modern gadgets are transforming athletic performance analysis. This course explores the use of wearable technology in capturing detailed data about athletes' stress, recovery, and overall performance throughout entire seasons. Discover how these insights can lead to new strategies for injury prevention and optimizing training routines.
Coursera
Dive deep into the world of sports analytics with our Introduction to Machine Learning in Sports Analytics course. Gain expertise in applying machine learning techniques using Python's scikit-learn toolkit on real-world athletic datasets. Explore various algorithms and learn how to predict outcomes in professional sports, enhancing your understanding and skills in data analysis.