My plan with this blog is to do occasional rundowns of articles I find interesting, particularly ones that involve the study or analysis of e-sports. That’s an area that will only grow as time goes on – while e-sports is still a (relatively) new phenomenon, there are already people dedicated to studying it. And obviously that will only continue; e-sports and the online culture in general will have a huge influence on the culture and even economics of future generations.
With that stated, theringer.com just posted an interesting article looking at analytics in e-sports. In general, I’m not a sports analytics guy; I find the application of statistics to sports intriguing, but I’m not good enough with math to do it on my own. Nevertheless, e-sports seems to me like it has a math-based element that should lend itself naturally to advanced analytics. With other upcoming sports, like Ultimate frisbee, for example, the analytics learning curve comes as people learn (1) what statistics to measure, and (2) how to measure them. With e-sports, the “how-to” part is built in. The games are online, and on computers, where everything is measured and stored. The how-to is already there.
That leaves the what, and as Ben Lindbergh explains, that’s where the difficulty is. There’s no exact parallel with physical sports; e-sports, particularly MOBAs, have baseball’s individual stats (deaths, kills, assists, etc.) but also soccer’s constant motion, and added to that the different roles that a sport like football has. An offensive lineman many never score a touchdown, but may be crucial to winning the game. When I play Gazlowe in Heroes of the Storm, I might not make many kills; and yet I know that I can influence the game one way or the other.
Definitely lots of room for improvement, and it will be interesting to see how the field develops. Read the article . . . great stuff there.e-sport analytics