According to experts in the video gaming industry there are currently 2.3 billion virtual gamers worldwide, with nearly 56% of those gamers engaging in online play and an expected growth to about 2.7 billion gamers worldwide by the year 2021. Whether you’re on team Xbox, Play Station, Nintendo, or a PC gamer, there is something for everyone in the world of online gaming.
For me, my time to unwind after a day of work and meetings usually involves my couch, big screen TV, and some sort of online video game. I figured that for my first e-Portfolio post I could dive into the world of online gaming and do a little research into some of the ways the industry is utilizing Big Data.
Game developers have the ability to track everything inside of their online game and they can use that information to make important decisions within the game while limiting their chances of making a decision that could hurt the game rather than improve it. Player activities such as total players online, user spikes, user decline, equipment choices, movement patterns, re-spawn locations, and elimination locations are just a few of the things that video game developers are mining in order to make data-informed decisions.
Data is analyzed and used to improve game experiences for all players. Online game developers use collected data to ensure games are balanced and character selections or map selections are as fair as possible for all players. If developers discover that something within a game is unbalanced, they can reference the data and tweak those items to improve the experience for all players. For example, in the game Halo, which is a widely popular first-person shooter, developer Bungie noticed that one of their online maps seemed to be unbalanced. They used player re-spawn and elimination data mined from their online matches to create a heat map of player activity.
By using data, Bungie realized one side of the map was easier for players on one team to eliminate players from the other team. Once this unbalanced map attribute was realized, they were able to update the map and bring balance to both teams.
Although there are many positives associated with using data to make informed changes to video games, there are some potentially negative ways that data could be used that need to be taken into consideration as well. Since the early 90’s developers have had the ability to use player data to analyze game difficulty and with basic machine learning they could change game difficulty on the fly in order to help frustrated players progress and keep them engaged inside the game. In the future could precision optimization and data analytics be used to create games that tailor entire experiences including story line and player interactions to create overly addictive games based on unique individual player motivations?