Justin Perry Doyle
FindMyTeam is a full-stack website application designed to connect people together through competitive video games and statistics. Themed around League of Legends, FindMyTeam uses UI design elements from dating apps like the swipe feature, data analytics visualisation similar to applications like TrackerNetwork, pulling user statistics directly from the League of Legends API, along with liking and matching functionality and Discord API ingestion, to connect users together who want to play with one another and build high performing cohesive teams in a competitive setting.
Create a fully functional full-stack application leveraging multiple technologies allowing users to team with one another based on insights gained through data visualisation and statistics. These statistics will be ingested through the RIOT API (League of Legends developers), along with Discord API integration to allow users to connect with ease.
FindMyTeam was a vast learning experience for me, I learned Python in the context of a full stack web application which I had never done before, including the Flask framework for building a REST API. Managing a project this big was also a first for me, although I have completed other large projects none were as extensive as FindMyTeam. Through this I learned so much around project management, communication with my supervisor, planning and discipline when it comes to working consistently over a number of months to complete a singular but multifaceted goal.
I hope to work on many more similar projects in the future and throughout my Masters in UCD.
Find My Team (which will be referred to as “FMT” throughout this report) is a full stack web application, that aims to provide users with a way to connect with other players (specifically of the game League of Legends or “LoL”) and play together competitively. FMT does this by allowing users to connect their FMT account to their LoL/RIOT account (RIOT are the developers of LoL) and inherit statistics and rank that they achieve in game into FMT. These statistics are then displayed on a user card in a similar fashion to that of dating applications like Tinder or Hinge, where users may select which players to play or “match” with by liking that persons’ profile. The steps involved in developing FMT include designing a back end, front-end, and UI interface, doing research in all these areas and putting that into practice to create a functioning web application for users. Testing was carried out before, during and after implementation. The market research showed a clear desire for FMT in the landscape and that people approached FMT with familiarity after most having had experience with similar applications although centred around dating rather than gaming. To expand FMT, adding new games into the application would be the first place to start, and finding ways to integrate data analytics and machine learning into the search algorithms may be helpful and useful.
Hi, I'm Justin, I'm a graduating 4th year in Creative Computing. My journey through college has been a good one and isn't stopping here as I'm hopefully doing a Masters next year in Comp Science in UCD! My work is focused around full stack web development, with some AI machine learning and data analytics sprinkled in. I'm excited to develop my learning in this space in the future and hopefully meet some incredible people along the way.
