Sport organizations strive to become data driven businesses. Over the last few years, there has been an increasing demand for data in order to inform players and coaches and facilitate decision making both prior and during sporting events. Analytics is largely becoming an arms race where the tools and improved outcomes are a competitive edge over other teams as well as to improve the fan experience since sports teams compete against a dominating world of varying entertainment.
Sports Analytics in Practice with R illustrates basic analytical concepts in a fun and engaging manner, presenting case studies with coding examples and data sets for readers to work alongside the explanations. This book endeavours to teach basic analytics for sports related use cases from cricket to baseball, from basketball to tennis, from football (soccer) to sports gambling. Analytics can be applied to player personnel decisions, marketing, business operations and even on field decision making.
This book offers the reader the ability to execute R code and obtain public sports data for analysis and the understanding of how data can be applied to sports decisions, such as:
- player evaluations
- what team level statistics specifically improve the probability of a win
- how to make compelling visualizations
- how to perform sentiment analysis to gauge fan experience
- what a “slump” looks like in data
- how to build a basic predictive model for sports gambling, and many more
Sports Analytics in Practice with R is aimed at students and professionals in the sports management field. This book is accessible to those with limited knowledge of R or programming skills.
