“Social Sports is an application which facilitates the environment fans need to support their teams, in doing so our application aids hospitality businesses market their events and brings business during their downtime. Social Sports allows businesses to market their sports screening events to fans and supporters. Fans and supporters using Social Sports are able to see the percentage of supporters/fans on each side and decide which bar or restaurant to go watch the game. Social Sport’s mission is to connect sports fans with other like minded passionate fans and enable community formation and allow sports fans around the world to socialize with much ease.”

Sports analytics refers to the implementation of data science and analytics techniques within the sports industry. Several sports analysts and team managers have utilized analytical tools to boost overall team and player performance, often through the analysis of historical data. One of the most common techniques employed in sports analytics is that of data mining–the extensive practice of analyzing data in order to extract and deliver insights and findings. Data mining projects are frequently guided with the six-step Cross Industry Standard Process for Data Mining (CRISP-DM) framework. One such sport that has extensively used data science and analytics, and data mining specifically, is that of Formula One (F1). Given the sports’ reliance on technology, race engineers working for F1 constructors often develop statistical models analyzing historical race performance to derive insight of drivers’ success. For the purposes of this project, the perspective of a race engineer working for the F1 constructor McLaren was considered. As the constructor is seeking to gain a competitive advantage for the upcoming F1 season, race performance data concerning previous seasons was collected and analyzed as part of a larger data mining project utilizing the CRISP-DM framework. Statistical models, such as linear regression and random forest, were developed to predict the number of points scored by McLaren racers and the variables most strongly contributed to such scored points. The final results point to specific lap times having to be aimed for as the most important variable in determining the number of points gained, although specific locations also seem prone to McLaren race success. These results in turn will be utilized to develop race strategies for the upcoming season to ensure McLaren has high efficiency against its competitors.

Former NFL player Colin Kaepernick began protesting during the national anthem in 2016. This research addresses the impacts that Kaepernick and his protests had on himself, the NFL, and the issues he was protesting. The research finds that Kaepernick was blackballed out of the NFL and that hundreds of other NFL players joined him in protest, which caused the league to ban the action before eventually becoming more political as a league. Additionally, the protests brought greater awareness to the issues and prompted some to become more politically active. In addition to providing a new framework for researching examples of politics in sports, this project concludes that athlete-activists can sacrifice themselves to provide more freedom for future athletes to be activists.