Statistical modelling and sports business analytics
Author(s)
Bibliographic Information
Statistical modelling and sports business analytics
(Routledge frontiers of business management)
Routledge, 2020
- : hbk
Available at 4 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references and index
Description and Table of Contents
Description
This book introduces predictive analytics in sports and discusses the relationship between analytics and algorithms and statistics. It defines sports data to be used and explains why the unique nature of sports would make analytics useful. The book also explains why the proper use of predictive analytics includes knowing what they are incapable of doing as well as the role of predictive analytics in the bigger picture of sports entrepreneurship, innovation, and technology.
The book looks at the mathematical foundations that enhance technical knowledge of predictive models and illustrates through practical, insightful cases that will help to empower readers to build and deploy their own analytic methodologies.
This book targets readers who already have working knowledge of location, dispersion, and distribution statistics, bivariate relationships (scatter plots and correlation coefficients), and statistical significance testing and is a reliable, well-rounded reference for furthering their knowledge of predictive analytics in sports.
Table of Contents
1. Statistical Modelling and Sport Business Analytics 2. On the Use of Quantitative Data in the Sport Context 3. Big Data and Business Intelligence in Sport 4. Social Media Marketing and Network Analysis in Sport 5. Sport Companies using Analytics and Statistics 6. Relationship between Support for Sports Policy and Political Ideology in the Host Community's Perception of the Impacts of a Major Sporting Event 7. What is a Sports Club in the 21st Century? Social Enterprise and Social Entrepreneurship 8. Identification of Weight Control Behaviors in Members of Polish Amateur Sports Clubs for Gender and Sexual Minorities 9. The Effects of Turkish Football Federation's Penalties Upon The Sportive Success Of Super League Teams: Ordered Logit Regression Analysis 10. Corporate Social Responsibility in the Field of Sports Marketing: A Study applied to SC Braga 11. Deal's Completed? An Exploratory Case Study about the Role of Players' Agents in the Football Industry 12. The Experience, Perception and Meanings Attributed to Latin Dances: A Business Analytics Approach 13. Statistical Analysis of Outdoor Adventure Facilitation Efficacy in Kenya 14. The Future of Sport Data Analytics
by "Nielsen BookData"