Have you ever been mind-boggling blown away by statistics? Perhaps you’ve felt severe heart palpitations at the sight of numbers so shocking, so unexpected?
Hardcore stat-junkies may have swiftly answered ‘YES!’ to both scenarios, but more often than not statistics are subtle things that make their way into our lives to fill broadcast time and lend gentle insight into an area of focus.
Though it sometimes relies on slightly incomplete or under-populated data sets, the Global Starcraft II League has recently introduced tournament-specific statistics that gives fans of Starcraft II new insight into how players perform on specific maps in specific match ups on the biggest eSports stage in the universe. While these flashes of information are new, fun, and educational, they are largely used to fill down-time during the live, unscripted broadcast. Beyond the surface of this entertainment method, there lies a unique opportunity to apply methods of statistical analysis to a larger, more purposeful movement.
For those unfamiliar with the concept of ‘Big Data’, the term “loosely describes data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time.” (Google ‘Big Data’ for more information!)
The best way to visualize the overall concept of ‘Big Data’ is to think of Google, the world’s largest, fastest search engine and one of the most successful multinational tech corporations the world has ever seen. Data is at the core of Google’s business operations – without it they simply wouldn’t exist. Google gathers information, organizes it, and packages it into a user-friendly application that then displays queried results. Millions upon millions of searches are conducted each day on Google, not because it is the only site of its kind, but because it does a fantastic job of analyzing why a user queries for specific data and provides that user with targeted, meaningful results.
Now to interpret how this concept of ‘Big Data’ renders into the realm of sports, consider ESPN, the worldwide leader in sports broadcasting. ESPN covers nearly every sport, year in and year out, and is able to produce statistics based on storied histories of past and present major league seasons/events/etc. These statistics lend insights into the game that casual fans then use to predict how to best manage their fantasy rosters, how to bet on upcoming events, and how to arm themselves with an array of back-pocket statements that can be used to disprove rival fans at bars and restaurants across the globe. ESPN has no copycats – it is the premier source for sports data and information. Would the fan’s experience be lessened without ESPN’s statistical analysis of their sport? Probably not – but at the end of the day, statistics make the overall experience that much richer for everyone involved.
Analytical statistics are slowly blending into eSports in the same fashion a baseball, basketball, or football broadcaster announces information before, during, and after a professional game. While this is great for the casual fan and live broadcasting, it leaves something to be desired for players and coaches trying to analyze patterns in meta-game shifts or for teams who need to analyze which players are more likely to win on a Friday than a Monday. With ‘Big Data’, answering these questions is not only possible – it becomes the only way to stay on top.
Companies like Google and ESPN don’t just use ‘Big Data’ – they rely on it and leverage it for every competitive advantage possible. If an organization possesses insights that others do not, a lead emerges – organizations that recognize where they can take the lead and how to take it will outperform organizations that lag behind and refuse to innovate and expand.
This is why the emergence of ‘Big Data’ in eSports is so exciting – there are so many different games, so many different possible moves, and so many ways to win – the possibilities are endless!
But remember, statistical analysis does not have to be confined to how a game is played – values can be assigned to practice regiments, travel habits, or sleeping patterns. Individual gamers can track their day-to-day to find which activities enhance their eSports success and which do not. Professional teams can analyze which players are trending upwards or downwards in popularity on social media sites and adjust their marketing strategies accordingly.
When I say the possibilities are endless, I mean it – if an organization begins taking a statistical method of approach to their business and strategic operations, they are only limited by brain power and financial resources (and with the emergence of cloud-based distributed computing, the price to pay for these services is as cheap as it ever has been – but that’s for a different article…). There’s a whole host of data available out there – it’s just a matter of collecting it and analyzing it correctly and effectively.
Will eSports ever reach its ‘Big Data’ potential? Is there enough capital out there to be gained to consider these initiatives worth it? Should players and teams focus solely on playing the game first and worry about the data later?
I guess we’ll have to wait and see who first decides to become the “nerdiest” nerds of all by arming themselves with ‘Big Data’ at their side. Organizations can certainly make strong impacts in their respective fields with this approach, but must always remember – the data may talk to you, but on the eSports battlefield it is you who does the talking.