Special Issue on Statistics in Sport Management
Guest Editors: Jess C. Dixon & Todd M. Loughead, University of Windsor, Canada
Coursework in statistics and/or research methods have long been components of the curriculum for many sport management programs. Thanks in large part to Michael Lewis’s (2003) best-selling novel Moneyball, the global sport industry has become increasingly focused on analytics and “big data” as a means for informing decisions. To this point, a great number of academic and mainstream media articles, Internet websites, books, conferences, as well as radio and television shows have been devoted to this topic in recent years. Given this trend, providing strong instruction in the area of statistics is arguably more important than ever in the field of sport management.
Many statistics courses involve a combination of lecture-based teaching and exercises that allow students to apply the statistical concepts and techniques. We propose that case studies could be utilized instead of or in conjunction with lectures and/or exercises in order to enhance student learning. With industry practitioners now more focused on using data of all shapes and sizes (e.g., survey responses, secondary datasets, demographic profiles) to solve problems facing sport organizations, case studies can be used to replicate this practice in the classroom. In this approach, once a particular statistical technique has been taught (e.g., regression or ANOVA), instructors could then utilize data-driven case studies to apply these new skills in a practical and meaningful way. This allows professors to mimic industry settings through the process of having students:
- Read a narrative of a case situation,
- Identify the case problem(s),
- Perform the appropriate statistical analyses of the data accompanying the case, and
- Make recommendations or conclusions based on the results of the statistical analyses.
The aim of this special issue is to develop a library of teaching case studies appropriate for undergraduate and graduate courses in statistics, data analytics, and/or quantitative research methods that can be used in case study pedagogy.
The scope of this special issue is broad in terms of industry context. We encourage submissions that involve, but are not limited to professional and semiprofessional sports; collegiate athletics; equipment and apparel manufacturers, wholesalers, and retailers; administrative and regulatory athletic associations (e.g., FIFA, IOC, NFL); youth sport, sport facilities and buildings; sport media; sport agencies and consulting services; and local, regional, and national sports commissions and authorities (Li, Hofacre, & Mahony, 2001).
The range of topics for this special issue is also broad and should reflect problems being faced by sport managers in their daily activities that may be addressed using various statistical analyses, including but not limited to: frequency distributions and percentiles, measures of central tendency, measures of variability, z-scores and the normal curve, correlation coefficients, linear regression, multiple regression, probability, one-sample t-test, two-sample t-test, ANOVA, MANOVA, ANCOVA, MANCOVA, repeated measures, chi-square and other non-parametric tests.
Examples of Cases: We encourage the development of original case studies written about, or in partnership with, sport organizations that rely on the use of quantitative data to inform their decision-making. Examples may include:
- The general manager of a professional sports team using performance data to select prospective players in a league entry draft,
- A local fitness club owner using survey results to recruit and retain members,
- A sport sponsor using demographic and viewership data to compare commercial advertising options,
- A ticket broker leveraging an event’s characteristics to establish ticket prices,
- A collegiate coach using in-game performance data to inform effective game strategies and tactics,
- A sponsorship director using sales metrics to identify high and low achieving employees and reward their performances accordingly,
- A sports apparel company using global sales data to identify new avenues for revenue growth,
- A national team coach using social network survey data to determine the team’s leadership core.
Notes for Prospective Authors: Submitted case studies should not have been previously published, nor be currently under consideration for publication elsewhere. All case studies are refereed through a peer review process. A guide for authors and other information for submitting case studies are available on the Instructions for Submitting page: http://journals.humankinetics.com/cssm-instructions-for-submitting. When prompted, please indicate that you would like your submission to be considered for the special issue on Statistics in Sport Management.
Important Dates: The deadline for submission is August 1, 2015.
Questions/Concerns: Questions or concerns regarding this special issue may be directed to the special issue editors:
Jess C. Dixon
University of Windsor
Todd M. Loughead
University of Windsor