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Applied Sport Business Analytics With HKPropel Access

$109.00 USD

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Book with online resource
$109.00 USD

ISBN: 9781492598534

©2023

Page Count: 216


Applied Sport Business Analytics With HKPropel Access provides a practical explanation of the use of data analytic metrics in sport, exploring selected techniques and tools as well as addressing fundamental applications of analytics within modern sports organizations. Current and aspiring sport managers will develop their understanding of how analytics can be used strategically to make data-informed decisions by selecting and translating data into evidence and meaningful metrics.

The text begins with an introduction to the world of analytics, exploring the social, economic, and business foundations that form the history of data analytics. Different strategies used to make data-driven decisions are discussed to demonstrate the importance of analytics in a modern sport context. The text explains terms and methods that are typical in sport analytics, bridging the gap between sport managers and sport analysts to help them understand the perceptions and needs of one another.

The text’s focus on quantitative statistical analysis—with its exploration of modeling, predictive analytics, and forecasting—helps students learn how to analyze data and make use of it. Students will then learn to turn data into visual representations such as cluster diagrams to reveal clear results. With practical exercises that utilize five included datasets and are heavily support by related video tutorials delivered through HKPropel, even those without programming experience will learn how to program and transform complex statistical data into easy-to-understand visuals.

Case studies exploring real-world scenarios—including player position analysis in women's professional basketball, esport player popularity and market analysis, and prospective player evaluation for the NFL draft—examine managerial implications to help develop understanding of what questions to ask, how to interpret data, and how to use data to make informed decisions. Finally, an in-depth look at how cutting-edge analytics mechanisms were used to analyze over one million tweets associated with the NBA over an entire season will illustrate how to successfully work with large amounts of data to achieve results.

Concepts throughout the book are made easy to understand through exercises, datasets, and video lectures on key topics, all accessible through HKPropel. These tools combine to provide valuable experience and practical understanding. Interview With a Professional sidebars offer additional real-world glimpses into the use of analytics by practitioners in sport business.

Applied Sport Business Analytics will provide a broader and deeper knowledge of the use of sport analytics for aspiring sport managers, data analysts, and practitioners alike. It will prepare them to translate metrics in a useful way that allows them to make data-informed and data-driven decisions to achieve desired outcomes in their organization.

Note: A code for accessing HKPropel is included with all new print books.

Audience

Text for upper-level undergraduate courses in sport management and sport business; reference for academic libraries and researchers in sport management and sport business analytics.
Chapter 1. Foundations of Analytics for Sport Managers
A Brief History of Analytics in Sport
Evolution of Sport Analytics and the MIT Sloan Sports Analytics Conference
Data and Decision-Making
Systems and Analytics
Emerging Applications of Sport Analytics
Summary
Online Activities
References

Chapter 2. Working With Quantitative Data in R
R Basics
Exploring Datasets
Isolating Variables With Brackets, c(), and Operators
Descriptive Statistics
Inferential Statistics
Summary
Online Activities
References

Chapter 3. Plotting Data in R
Base Plotting Structures in R
Setting and Mapping Plot Elements
Plotting Data With ggplot2()
Map Plots
Summary
Online Activities
References

Chapter 4. Data-Driven Decision-Making
Machine Learning Analysis: WNBA Players’ Positions Analytics Application
Esport Analytics Application
European Football Analytics Application
NFL Player Evaluations Analytics Application
Comparative Analysis of Male and Female Prize Monies and Salaries Analytics Application
Online Activities
References

Chapter 5. Natural Language Processing and Text Mining
Language as Object Classes and Strings
Basic Text Processing Workflow
Identify Text Sources, Preprocessing, and Feature Extraction
Analytics
Insight and Recommendations
Summary
Online Activities
References
Christopher Atwater is an assistant professor of sport management in the School of Hospitality, Sport, and Tourism Management at Troy University. He teaches analytics courses at the graduate and undergraduate levels.

Robert Baker is a professor and the director of the Center for Sport Management at George Mason University. He is a former president of the North American Society for Sport Management (NASSM), a founding board member of the World Association for Sport Management (WASM), and a founding commissioner of the Commission on Sport Management Accreditation (COSMA). He has conducted numerous presentations and produced articles on sport analytics.

Ted Kwartler earned his MBA from Notre Dame. He is an instructor at Harvard University. He has conducted many presentations and written articles on sport analytics. He also authored a popular book entitled Text Mining.

All ancillaries are free to adopting instructors through HKPropel.

Instructor guide. Includes datasets (in .csv file format), answer guides for online exercises and assessments, and a link to video tutorials maintained by author Chris Atwater.

Chapter quizzes. Contains ready-made quizzes (10 questions each) to assess student comprehension of the most important concepts in each chapter. Each quiz may be downloaded or assigned to students directly through HKPropel. The chapter assessments are automatically graded, and instructors can review student scores in the platform.

Instructors also receive access to all student materials in HKPropel. For Applied Sport Business Analytics, this includes a key term activity, links to 36 videos maintained by author Chris Atwater, and five datasets with accompanying exercises and assignments.

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Christopher Atwater,Robert E. Baker,Ted Kwartler

Applied Sport Business Analytics With HKPropel Access

$109.00 USD
Applied Sport Business Analytics With HKPropel Access provides a practical explanation of the use of data analytic metrics in sport, exploring selected techniques and tools as well as addressing fundamental applications of analytics within modern sports organizations. Current and aspiring sport managers will develop their understanding of how analytics can be used strategically to make data-informed decisions by selecting and translating data into evidence and meaningful metrics.

The text begins with an introduction to the world of analytics, exploring the social, economic, and business foundations that form the history of data analytics. Different strategies used to make data-driven decisions are discussed to demonstrate the importance of analytics in a modern sport context. The text explains terms and methods that are typical in sport analytics, bridging the gap between sport managers and sport analysts to help them understand the perceptions and needs of one another.

The text’s focus on quantitative statistical analysis—with its exploration of modeling, predictive analytics, and forecasting—helps students learn how to analyze data and make use of it. Students will then learn to turn data into visual representations such as cluster diagrams to reveal clear results. With practical exercises that utilize five included datasets and are heavily support by related video tutorials delivered through HKPropel, even those without programming experience will learn how to program and transform complex statistical data into easy-to-understand visuals.

Case studies exploring real-world scenarios—including player position analysis in women's professional basketball, esport player popularity and market analysis, and prospective player evaluation for the NFL draft—examine managerial implications to help develop understanding of what questions to ask, how to interpret data, and how to use data to make informed decisions. Finally, an in-depth look at how cutting-edge analytics mechanisms were used to analyze over one million tweets associated with the NBA over an entire season will illustrate how to successfully work with large amounts of data to achieve results.

Concepts throughout the book are made easy to understand through exercises, datasets, and video lectures on key topics, all accessible through HKPropel. These tools combine to provide valuable experience and practical understanding. Interview With a Professional sidebars offer additional real-world glimpses into the use of analytics by practitioners in sport business.

Applied Sport Business Analytics will provide a broader and deeper knowledge of the use of sport analytics for aspiring sport managers, data analysts, and practitioners alike. It will prepare them to translate metrics in a useful way that allows them to make data-informed and data-driven decisions to achieve desired outcomes in their organization.

Note: A code for accessing HKPropel is included with all new print books.

Audience

Text for upper-level undergraduate courses in sport management and sport business; reference for academic libraries and researchers in sport management and sport business analytics.
Chapter 1. Foundations of Analytics for Sport Managers
A Brief History of Analytics in Sport
Evolution of Sport Analytics and the MIT Sloan Sports Analytics Conference
Data and Decision-Making
Systems and Analytics
Emerging Applications of Sport Analytics
Summary
Online Activities
References

Chapter 2. Working With Quantitative Data in R
R Basics
Exploring Datasets
Isolating Variables With Brackets, c(), and Operators
Descriptive Statistics
Inferential Statistics
Summary
Online Activities
References

Chapter 3. Plotting Data in R
Base Plotting Structures in R
Setting and Mapping Plot Elements
Plotting Data With ggplot2()
Map Plots
Summary
Online Activities
References

Chapter 4. Data-Driven Decision-Making
Machine Learning Analysis: WNBA Players’ Positions Analytics Application
Esport Analytics Application
European Football Analytics Application
NFL Player Evaluations Analytics Application
Comparative Analysis of Male and Female Prize Monies and Salaries Analytics Application
Online Activities
References

Chapter 5. Natural Language Processing and Text Mining
Language as Object Classes and Strings
Basic Text Processing Workflow
Identify Text Sources, Preprocessing, and Feature Extraction
Analytics
Insight and Recommendations
Summary
Online Activities
References
Christopher Atwater is an assistant professor of sport management in the School of Hospitality, Sport, and Tourism Management at Troy University. He teaches analytics courses at the graduate and undergraduate levels.

Robert Baker is a professor and the director of the Center for Sport Management at George Mason University. He is a former president of the North American Society for Sport Management (NASSM), a founding board member of the World Association for Sport Management (WASM), and a founding commissioner of the Commission on Sport Management Accreditation (COSMA). He has conducted numerous presentations and produced articles on sport analytics.

Ted Kwartler earned his MBA from Notre Dame. He is an instructor at Harvard University. He has conducted many presentations and written articles on sport analytics. He also authored a popular book entitled Text Mining.

All ancillaries are free to adopting instructors through HKPropel.

Instructor guide. Includes datasets (in .csv file format), answer guides for online exercises and assessments, and a link to video tutorials maintained by author Chris Atwater.

Chapter quizzes. Contains ready-made quizzes (10 questions each) to assess student comprehension of the most important concepts in each chapter. Each quiz may be downloaded or assigned to students directly through HKPropel. The chapter assessments are automatically graded, and instructors can review student scores in the platform.

Instructors also receive access to all student materials in HKPropel. For Applied Sport Business Analytics, this includes a key term activity, links to 36 videos maintained by author Chris Atwater, and five datasets with accompanying exercises and assignments.

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