Esports has been an explosive business especially with the current pandemic situation, it is rising to unparalleled levels of popularity as everything is going digital, Riot Games’ League of legends, which is considered one the most played video games right now with 27+ Million players per day and 115 Million over a month, checks many boxes where value can be obtained.[12] The general idea is that the game has a ranked ladder system, where players are evaluated by their win to lose ratio which is influenced by their skills in-game, each individual game performance counts towards the win or lose outcome. When looking at the general distribution of league of legends players, we will find that out of 9 available ranked divisions in the game, only 13.373% of the players are in the top 4 divisions, the remaining 87% is in the remaining divisions.[13] This is what we’re essentially looking into, and in order to do that we will go through the game data which includes compiling it first through API calls to Riot public endpoints, once the data is compiled, cleaning and pre-processing will commence, the expectation here is to have a data set ready to analyze that enables us to look for attributes that decisively tell us what is causing the winner to win and the loser to lose and finally applying an appropriate model to predict the outcome of the games.

Publication Date


Document Type

Master's Project

Student Type


Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research (Dubai)


Sanjay Modak

Advisor/Committee Member

Ehsan Warriach


RIT Dubai