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- All Subjects: API Scripting
- All Subjects: SaaS
- Creators: Clark, Joseph
DescriptionThe thesis will study price optimization techniques, SaaS industry pricing structures, A/B testing, and then build a unique framework to optimize price and maximize revenue. The ultimate goal of the thesis research is to create a framework that identifies the best pricing structure and price points for a SaaS company.
ContributorsRyu, Kibaek (Author) / Clark, Joseph (Thesis director) / Granberry, Chase (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Information Systems (Contributor)
Created2014-05
Description
League of Legends is a popular multiplayer online battle arena (MOBA) developed by Riot Games. Each team consists of 5 players who each control a single character (champion) which they select at the beginning of each game. In order to win the match, a team has to destroy the Nexus (the central structure) in the opponent's base. League of Legends has grown rapidly since its release in 2009 and has over 70 million registered players. Several community websites have been created that track the performance of players and show detailed statistics for just about every aspect of the game. This project focuses on exploring the applicability of predictive analytics within League of Legends, by predicting the outcome of any given ranked match at the start of the game. It resulted in a model with accuracy of 58% using decision trees. An additional contribution of the project is a solution to a data collection anomaly that has biased previous studies.
ContributorsNeumann, Alexander (Author) / Clark, Joseph (Thesis director) / Simon, Alan (Committee member) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12