Sports, Inc. Volume 9, Issue 2

The ILR Cornell Sports Business Society magazine is a semester publication titled Sports, Inc. This publication serves as a space for our membership to publish and feature in-depth research and well-thought out ideas to advance the world of sport. The magazine can be found in the Office of Student Services and is distributed to alumni who come visit us on campus. Issues are reproduced here with permission of the ILR Cornell Sports Business Society.https://digitalcommons.ilr.cornell.edu/sportsinc/1012/thumbnail.jp

Oblique strategies for ambient journalism

Alfred Hermida recently posited ‘ambient journalism’ as a new framework for para- and professional journalists, who use social networks like Twitter for story sources, and as a news delivery platform. Beginning with this framework, this article explores the following questions: How does Hermida define ‘ambient journalism’ and what is its significance? Are there alternative definitions? What lessons do current platforms provide for the design of future, real-time platforms that ‘ambient journalists’ might use? What lessons does the work of Brian Eno provide–the musician and producer who coined the term ‘ambient music’ over three decades ago? My aim here is to formulate an alternative definition of ambient journalism that emphasises craft, skills acquisition, and the mental models of professional journalists, which are the foundations more generally for journalism practices. Rather than Hermida’s participatory media context I emphasise ‘institutional adaptiveness’: how journalists and newsrooms in media institutions rely on craft and skills, and how emerging platforms can augment these foundations, rather than replace them

Using the Enterprise Architecture Approach to Analyse the Current Performance of Manchester United Football Club

Manchester United Football Club (MUFC) is one of the most successful football clubs in England, if not the world.  However, the football club's recent performance in domestic and European tournaments has left a lot to be desired.  The recent 2021 Europa League final failure encapsulates the football club's decade-long condition.  MUFC's days of competing seriously for trophies in every tournament open to the club are over.  MUFC came close to winning the local league in the 2017 and 2021 seasons but fell short, just like they did in the previous Europa League final in 2021.  Numerous reasons have contributed to the current poor performance streak.  This study aims to apply an enterprise architectural framework to enhance football player performance and manager-player relationships.  This study discovered that MUFC might leverage big data analytics-IT integrated systems by following easy-to-understand enterprise architectural framework phases, which streamlines the adoption process for MUF

Improving Decision Making in Ocean Race Sailing using Sensor Data

While in some sports, experiences have been gained using traditional information and decision support systems, using large sensor datasets for sports analytics is a recent phenomenon. Using sensor data to arrive at effective decision support for sports encompasses various challenges: (1) Sensor data needs to be understood, processed, cleaned and efficiently stored and (2) appropriate data analytics and visualization techniques need to be selected and evaluated with the sports professionals. Few elaborate case studies are available that report on development of decision support systems for professional sports teams. No comprehensive set of generically applicable design principles has been devised to develop analytics support for sports teams based on sensor data. We deploy a design science methodology to arrive at a sailing analytics architecture and race evaluation dashboard in close collaboration with a professional sailing team participating in an ocean race around the world

Analytics in Sport Marketing

The use of analytics has been growing throughout the sport industry. Although the concepts of analytics and big data are frequently used in the sport industry and highlighted in numerous media outlets, sport management students often do not have a strong understanding of why and how analytics are important for their future career, especially as it relates to sport marketing. This case study describes a fictitious student’s interaction with an industry professional who is an expert on Customer Relationship Management (CRM) and marketing analytics in the sport industry, and the student’s desire to be an intern in the Analytics Department at Major League Soccer (MLS). The study provides students information on how and why analytics are used in sport marketing and how data can be used to make decisions

Analysing data mining methods in sports analytics: a case study in NHL player salary prediction

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThe deployment of Internet of Things has become a systematic phenomenon around the world, leading to the exponential growth of data and data analysis practices. This particular growth is being seen within the sporting industry as new hardware and software are continuously being developed for home and professional use. Though there are several use cases of effective data usage within elite sports, there remains the notion that professional sporting organizations should expand their resources to fully cease the possibility of competitive advantage, through effective data mining techniques. This project conducts a comprehensive analysis of extensive open-sourced NHL data, utilizing SAS’s established SEMMA process. Through the SEMMA process, this project yields a predictive data-mining model, designed to predict future player salaries. With player salaries within the NHL steadily increasing, reaching upwards of $10millon per year, a predictive model with an overall average error of$150,000 and Mean absolute error of $870,000 can grant team’s unique knowledge, which if used effectively within the NHL, can lead to superior decision making. Though there remain limitations due to unquantifiable variables linked to a player’s psychology, as a whole, concrete deductions show that if effectively analyzed, sporting organizations have the power to leverage data to develop a competitive advantage. Our research indicates concludes that organizations pushing towards developing an established data science department are increasing their odds of winning

Effectiveness of Spatial-temporal Data Using GIS in America’s Professional Sports Leagues (MLS, MLB, and NFL)

This dissertation explores how information systems can improve the understanding of the home field advantage (HFA) in professional sports leagues in the United States. The literature related to the HFA conceptual framework and the game location factor—which represents four major impacts on teams (crowd, learning, travel, and rules)—led to an investigation into whether a relationship exists between game results and spatial, temporal, and stadium attributes. These stadium attributes include field surface type, roof type (i.e., open, fixed, and retractable), time zone, and field orientation (e.g., N/S, E/W, NE/SW) for U.S. professional sports such as soccer, baseball, and football. Winning percentage, winning streak, and losing streak were examined for their effect on game outcome. Collectively, all league games were examined to assess the effects of spatial, and temporal stadium attributes. A logistic regression (LR) analysis of the National Football League (NFL), Major League Soccer (MLS), and Major League Baseball (MLB) shows evidence of a significant relationship between spatial orientation, temporal, and stadium attributes and the game results. The LR model consider as an improvement over the base model, and the results vary from one sport to another. An IT artifact (dashboard) operationalized the proposed model based on these results. The dashboard provides team decision-makers with information to help them understand their opponent’s in the next home or away game. The artifact could be an integral part of the decision-making process for coaches and managers in game preparation and management

Build Your Dream (not just Big) Analytics Program

This paper reports on a panel discussion held at AMCIS 2014 and subsequent panel member research and findings. We focus on curriculum design, program development, and sustainability in business analytics (BA) in higher education. We address some of the burning questions the IS community has asked concerning the various stages of BA program building, and we elaborate challenges that institutions face in constructing successful and competitive analytics programs. Furthermore, given that the panelists have achieved outstanding accomplishments in academic and industrial leadership, we share our experiences and vision of a “dream” analytics program. We hope that our community will continue a dialog that encourages and engages faculty members and administrators to reflect on challenges and opportunities to build dream programs that meet industry needs