In order to get a better understanding of the subject, it’s useful to analyze the title of my master’s thesis.
Designing live data visualisations for the new spectator sport:video games
We can differentiate three major themes, namely live streaming, data visualisation and esports. Let’s break them down a bit.
Live streaming
The act of directly live streaming sport is inherently easier for video games as a sport than it is for ordinary physical sports due to the need of special equipments for the latter. You’d need atleast one camera, someone capable of operating them correctly, a computer and a reliable internet connection which may not be that easy to obtain at diverse locations. Yet, it has become somewhat easier as smartphones usually provide these functions.
Since video games already take place in a virtual world created by a computer, it’s not that difficult to configure the computer to share your view of that virtual world with everyone else around the world. The prerequisites for playing competitive video games and being able to live stream are mostly the same: a powerful enough computer and a stable internet connection. Therefore, it isn’t surprising at all that most live streams today are about video games.
While most enthusiasts follow traditional sports on television, esports are almost exclusively live streamed on the internet instead of broadcasted on television. Both media reach a different kind of audience and provide a distinct viewing experience. Television is more often watched in group, while live streams are usually consumated individually. Live streaming on the other hand allows all kinds of interaction between distant spectators which may strengthen their affiliation with the community, while television feels more secluded.
Data visualisation
Thanks to the information age, we got access to data about practically anything. Making sense of this data is another thing though. The amount can get impracticable rather fast for humans whereas computers with their more reliable and far larger storage capabilities struggle less. They, however, have a harder time abstracting the data and deducing relevant conclusions. In this context, machine learning is used to detect certain patterns in the data.
Evolution pushed visual pattern recognition capabilities of humans to the limit. If we present data in a more visual way instead of just plain numbers, humans are able to get an understanding of the data in the fraction of a second. The way in which data is visualised can further enhance this effect. The objective of data visualisation is thus to abstract a bunch of plain data in meaningful, workable visual representations thereof and to fully exploit the pattern recognition capabilities of humans.
Esports
In my previous blog post I have already given a brief introduction of esports and why they can be considered real sports. Competition was already introduced in the earliest popular video games since it’s almost instinctive to humans. We always feel the need to compare, for without comparisons there would be no measure of success.
In traditional sports, there’s a mix between physical competence and mental strategies. As a player, the physical skills are often the most important to gain success while the strategies can be worked on with a coach. If we look at chess though, there’s absolutely no need for physical skills, except for being able to move pieces around the board for several hours. The strategy aspect though is far more complex than any traditional physical sport most would argue. Most esports can be situated in between these more extreme positions. They require some physical skill from the players: a swift reaction time and some pretty slick eye-hand coordination, often called mechanics. But even players who possess those skills aren’t guaranteed to have success. As a competitive player you need to have a deeper understanding about the game, desirable moves and the ability to adapt while in game without interference from a coach. While there’s only a handful of rules in soccer and the only state of the game is the position of the ball and the players, the number of variables players need to take into account in esports are often far greater.
With prize pools for esports competitions exceeding 20 million dollars and the peak concurrent viewership surpassing 10 million spectators at the most popular esports competitions, we can safely say esports is becoming an industry on its own.