In the summer between the final two semesters of my Master’s program (spring and winter 2020), I did some analysis projects relating to Counter-Strike: Global Offensive (CS:GO), one of the more popular game for esport competitions. “Why were you spending time analyzing esports?”, you may ask.
The year of 2020 was not a great one for the world, most notably to the Coronavirus pandemic and related shutdowns. This was unfortunate for me on two fronts: 1. I was looking for work or an internship over the summer of 2020; the economic uncertainty adversely affected the prospects of that, and 2. I am an avid sports fan (see ballmart) and the shutdown resulted in many leagues suspending play.
The result? I turned my attention to one competition (not going to have the debate here about whether esports should count as a sport or not) that was ongoing: esports. I chose CS:GO since they were playing matches most days, unlike some of the other games out there, and I had played some CS:GO in the past, so I understood the general gist of the game. As I tend to do, I wondered about the statistical nature of what was preoccupying my mind at the time. This culminated in a CS:GO-related project for my final semester of school, but I also did some writings and “mini-analyses” on some CS:GO topics.
All of this is to say that those articles that I wrote on my old “blog” or personal website are going to stay there, but I’ll link them here. If you hover over the “eSports” header in the top navigation bar, there are some different sections of articles. The reason I am not reproducing the work here is because those articles actually contain some analysis code within them, and the way that the old website was designed included actually running the analysis when generating the html. That is why you get cool visualizations and tables while viewing on the github pages site (you would just see the code if I reproduced them here).
Again, link to content.