APPLIED BUSINESS INTEL FRAMEWORKS IN SPR
APPL BUS INTEL FRAMEWORKS
This course will build on the topics and tactics covered in Business Intelligence in Sports to create a real-life learning lab where students can apply key concepts and expand their techniques against real data from a partner professional sports team. More advanced skills around SQL, Tableau, and R will be developed and applied to relevant scenarios using available data such as customer demographics, behaviors, tickets, attendance, social media, marketing, surveys, and sponsorships. Students will leave the class prepared to join a team’s business intelligence department and make immediate contributions.
- W 8:10 p.m.-10 p.m.
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Instructor:
Charlie Sungho Shin
Info - 3 points
EMERGING AND NICHE SPORTS LEAGUES
EMERGING & NICHE SPORTS L
The creation and maintenance of sports leagues is a nuanced and complex endeavor. This course examines the format, hierarchy, membership, governance, and operational efficiencies of several sports leagues that have been launched with varying levels of success. Through a combination of lectures, case studies and guest speakers, students will learn about the ideation, funding, legal aspects, marketing, media strategy and monetization of these businesses, both domestically and globally. Students will gather data about emerging sports leagues of the past and present and conduct research on the leagues of their choice. The culminating project in this course will be an original proposal by student groups of a new sports league, addressing all of the aforementioned dimensions in a formal presentation to potential ‘investors.’ Students will present their proposal via online video conference for instructor feedback following the block week. This course is ideal for students who have an interest in the structural and operational decisions that affect the success and sustainability of sports leagues and their members.
This is an elective course for the M.S. program in Sports Management; students in the program may take this course when allowed by their curriculum requirements. Students outside of the Sports Management program may take this course upon approval of the Academic Program Director.
- MTWRF 9 a.m.-5 p.m.
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Instructor:
Scott Rosner
Info - 3 points
BASKETBALL ANALYTICS
In this course, students will develop a working knowledge of the practical application of analysis and models used to make management decisions within an organization and a professional league. Basketball Analytics will explore the use of data and statistics to inform decision making in the National Basketball Association (NBA). Utilizing data made available through the NBA and other publicly available resources, students will learn to use analytics to ask and answer the right questions and provide best practice solutions through critical thinking.
- M 8:10 p.m.-10 p.m.
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Instructor:
Joshua Orenstein
Info - 3 points
INTERNATIONAL SPORTS MANAGEMENT
- MTWRF 9 a.m.-5 p.m.
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Instructor:
Cataldo Ruta
Info - 3 points
SPORTS REVENUES STRATEGIES & ANALYSIS
Digital, social, and mobile media continue to heavily impact every aspect of sports business, often in profound and unanticipated ways, particularly in managing and optimizing revenue streams. All revenue line items are fully intertwined and integrated with each other, media, sponsorship, ticketing, hospitality, concessions and licensing, etc. Students of this course will learn to analyze and optimize the ecosystem of sports business including content rights, ticketing, sponsorship, merchandising, marketing, etc., as well as make business analytics decisions by leveraging business analytics software to run scenario analysis.
- T 6:10 p.m.-8 p.m.
- 3 points
INTERCOLLEGIATE ATHLETICS ADMIN
- MTWRF 9 a.m.-5 p.m.
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Instructor:
Adam Neuman
Info - 3 points
SUPERVISED PROJECT IN SPORTS MANAGEMENT
SUPERVISED PROJ IN SPORTS
Projects are research intensive and vary according to partners and specialty.
Advanced standing in the Sports Management program, with at least 12 points/credits (4 courses) completed is required. A student may not exceed 6 points/credits (2 courses) of Supervised Projects, or take more than 3 points/credits (1 course) per semester.