Enterprise Systems and Data Analytics: A Fantasy Football Case Study

Literature Review

According to Alamar (2013), sport organizations are more likely to consider the use of data analytics tools in order to be competitive. Schumaker et al. (2010) highlight the vast amount of raw sport data that is typically collected on individual players, teams and game-related events. Furthermore, Schumaker et al. (2010) proposed a number of tiers in which sport-related data can be grouped based on the ways it can be used. At the simplest level, sports data can be collected around the operational aspects of a game as a means of keeping records of events or performance. Local and community-based sporting groups would typically fall under the realm of collecting sport data in this way (Bingley 2011). Other ways sport organizations might use data is to assist with sport decision making processes— where historical data or raw statistics are pre-cursors that allow people to be better informed about a particular sport situation. At the most advanced level, sport-related data can be analyzed so as to improve the activities that operate within a sport be they at an individual, team or organizational level which provides a new viewpoint or understanding of a situation (Schumaker et al. 2010).