A data-driven approach to sport business and management
Author: Gil Fried,Ceyda Mumcu
Category: Business & Economics
The increasing availability of data has transformed the way sports are played, promoted and managed. This is the first textbook to explain how the big data revolution is having a profound influence across the sport industry, demonstrating how sport managers and business professionals can use analytical techniques to improve their professional practice. While other sports analytics books have focused on player performance data, this book shows how analytics can be applied to every functional area of sport business, from marketing and event management to finance and legal services. Drawing on research that spans the entire sport industry, it explains how data is influencing the most important decisions, from ticket sales and human resources to risk management and facility operations. Each chapter contains real world examples, industry profiles and extended case studies which are complimented by a companion website full of useful learning resources. Sport Analytics: A data-driven approach to sport business and management is an essential text for all sport management students and an invaluable reference for any sport management professional involved in operational research.
This book is the first to combine principles from analytics, complex systems theory, multi-disciplinary diagnostics and sport performance analysis. It considers athletes, teams, and sport organizations in individual and team games as complex systems, and demonstrates how complexity studies can enrich analytics and give us a more sophisticated understanding of the causalities of winning and losing in sports. Part I introduces the basic categories of analytics and their uses in elite sport. Part II presents an original conception of sport analytics both as a complex of different kinds of processes and as a complexity-adapted view of human systems acting in sport performance and management. Part III considers the main principles of complex sport analytics, expanding the prism of complexity to include all levels of a sport organization from athletes, coaches and trainers to top decision makers, and suggests practical applications and simulations for cases of both individual and team sports. This is illuminating reading for any advanced student, researcher or practitioner working in sport analytics, performance analysis, coaching science or sport management.
As the analysis of big datasets in sports performance becomes a more entrenched part of the sporting landscape, so the value of sport scientists and analysts with formal training in data analytics grows. Sports Analytics: Analysis, Visualisation and Decision Making in Sports Performance provides the most authoritative and comprehensive guide to the use of analytics in sport and its application in sports performance, coaching, talent identification and sports medicine available. Employing an approach-based structure and integrating problem-based learning throughout the text, the book clearly defines the difference between analytics and analysis and goes on to explain and illustrate methods including: Interactive visualisation Simulation and modelling Geospatial data analysis Spatiotemporal analysis Machine learning Genomic data analysis Social network analysis Offering a mixed-methods case study chapter, no other book offers the same level of scientific grounding or practical application in sports data analytics. Sports Analytics is essential reading for all students of sports analytics, and useful supplementary reading for students and professionals in talent identification and development, sports performance analysis, sports medicine and applied computer science.
A Guide for Coaches, Managers, and Other Decision Makers
Author: Benjamin C. Alamar
Pubpsher: Columbia University Press
Category: Sports & Recreation
Benjamin C. Alamar founded the first journal dedicated to sports statistics, the Journal of Quantitative Analysis in Sports. He developed and teaches a class on sports analytics for managers at the University of San Francisco and has published numerous cutting-edge studies on strategy and player evaluation. Today, he cochairs the sports statistics section of the International Statistics Institute and consults with several professional teams and businesses in sports analytics. There isn't a better representative of this emerging field to show diverse organizations how to implement analytics into their decision-making strategies, especially as analytic tools grow increasingly complex. Alamar provides a clear, easily digestible survey of the practice and a detailed understanding of analytics' vast possibilities. He explains how to evaluate different programs and put them to use. Using concrete examples from professional sports teams and case studies demonstrating the use and value of analytics in the field, Alamar designs a roadmap for managers, general managers, and other professionals as they build their own programs and teach their approach to others.
Release on 2016-11-18 | by C. Keith Harrison,Scott Bukstein
Using Data to Increase Revenue and Improve Operational Efficiency
Author: C. Keith Harrison,Scott Bukstein
Pubpsher: CRC Press
Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group. The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in: Ticket pricing Season ticket member retention Fan engagement Sponsorship valuation Customer relationship management Digital marketing Market research Data visualization. This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations. Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics.
This is a complete, practical guide to sports data science and modeling, with examples from sports industry economics, marketing, management, performance measurement, and competitive analysis. Thomas W. Miller, faculty director of Northwestern University's pioneering Predictive Analytics program, shows how to use advanced measures of individual and team performance to judge the competitive position of both individual athletes and teams, and to make more accurate predictions about their future performance. Miller's modeling techniques draw on methods from economics, accounting, finance, classical and Bayesian statistics, machine learning, simulation, and mathematical programming. Miller illustrates them through realistic case studies, with fully worked examples in both Python and R. Sports Analytics and Data Science will be an invaluable resource for everyone who wants to seriously investigate and more accurately predict athletic performance, including students, teachers, sports analysts, sports fans, physiologists, coaches, and managers of sports teams. It will also be valuable to all students of analytics who want to build their skills through familiar and accessible sports applications.
Release on 2014-08-12 | by Thomas H. Davenport,Jeanne G. Harris
Author: Thomas H. Davenport,Jeanne G. Harris
Pubpsher: Harvard Business Review Press
Category: Business & Economics
The Analytics and Big Data collection offers a “greatest hits” digital compilation of ideas from world-renowned thought leader Thomas Davenport, who helped popularize the terms analytics and big data in the workplace. An agile and prolific thinker, Davenport has written or coauthored more than a dozen bestselling books. Several of these titles are offered together for the first time in this curated digital bundle, including: Big Data at Work, Competing on Analytics, Analytics at Work, and Keeping Up with the Quants. The collection also includes Davenport’s popular Harvard Business Review articles, “Data Scientist: The Sexiest Job of the 21st Century” (2012) and “Analytics 3.0” (2013). Combined, these works cover all the bases on analytics and big data: what each term means; the ramifications of each from a technical, consumer, and management perspective; and where each can have the biggest impact on your business. Whether you’re an executive, a manager, or a student wanting to learn more, Analytics and Big Data is the most comprehensive collection you’ll find on the ever-growing phenomenon of digital data and analysis—and how you can make this rising business trend work for you. Named one of the ten “Masters of the New Economy” by CIO magazine, Thomas Davenport has helped hundreds of companies revitalize their management practices. He combines his interests in research, teaching, and business management as the President’s Distinguished Professor of Information Technology & Management at Babson College. Davenport has also taught at Harvard Business School, the University of Chicago, Dartmouth’s Tuck School of Business, and the University of Texas at Austin and has directed research centers at Accenture, McKinsey & Company, Ernst & Young, and CSC. He is also an independent Senior Advisor to Deloitte Analytics.
Release on 2019-10-16 | by Damon P. S. Andrew,Paul Mark Pedersen,Chad D. McEvoy
Author: Damon P. S. Andrew,Paul Mark Pedersen,Chad D. McEvoy
Pubpsher: Human Kinetics Publishers
Category: Sports administration
Research Methods and Design in Sport Management, Second Edition, explains research design, implementation, and assessment criteria with a focus on procedures unique to the discipline of sport management.
Match analysis in soccer has become more and more important in recent years. Nowadays, no professional soccer club plays a single match without having analyzed their own and their opponents’ matches to find the best possible match plan and maximize their success. In this book, Ian M. Franks and Mike Hughes explore soccer analyses and use the results to develop realistic, progressive practices to improve the performance of the individual players and the team. Research from human decision making and motor skill acquisition is directly applied to the coaching process and technical and tactical practices are designed to accommodate these findings. Not only is the players’ behavior during practice and matches analyzed but the coaches’ as well. This helps evaluate different coaching practices to find your ideal coaching style. Any coach reading this book will find help in developing and improving their coaching. Anyone who wishes to delve more into the science of soccer analysis will find ample material as well as a comprehensive bibliography to better understand the science of soccer!
Release on 2014-10-24 | by Peter O'Donoghue,Lucy Holmes
Author: Peter O'Donoghue,Lucy Holmes
Making sense of sports performance data can be a challenging task but is nevertheless an essential part of performance analysis investigations. Focusing on techniques used in the analysis of sport performance, this book introduces the fundamental principles of data analysis, explores the most important tools used in data analysis, and offers guidance on the presentation of results. The book covers key topics such as: The purpose of data analysis, from statistical analysis to algorithmic processing Commercial packages for performance and data analysis, including Focus, Sportscode, Dartfish, Prozone, Excel, SPSS and Matlab Effective use of statistical procedures in sport performance analysis Analysing data from manual notation systems, player tracking systems and computerized match analysis systems Creating visually appealing ‘dashboard’ interfaces for presenting data Assessing reliability. The book includes worked examples from real sport, offering clear guidance to the reader and bringing the subject to life. This book is invaluable reading for any student, researcher or analyst working in sport performance or undertaking a sport-related research project or methods course