Over the past few years, analytics has become the hottest buzzword in wide world of sports. A game-changing type of analysis built on the backbone of spreadsheets and fantasy sporting leagues around the world, analytics, much to the chagrin of old-school traditionalists, has revolutionized the way both fans and team management interact with the sports they love, exemplified by the over-saturation of seemingly inconsequential and complex statistics that everyone seems to be looking at these days. Although the true power of analytics in traditional sports has been hotly debated among the talking heads of the sporting world, it seems the numbers are here to stay, as everyone chases after their own Moneyball-esque glory.
Arguably the greatest challenge data analysts have had to overcome in yearning for acceptance in the traditional sports world, is the reputation of hogwash the old-school sporting society have deemed analytics to be. The great Charles Barkley, the NBA hall of famer and one of analytics’ loudest critics, famously once said, “Analytics don’t work… All these guys who run these organizations, who talk about analytics, they have one thing in common. They a bunch of guys who ain’t never played the game, and they never got the girls in high school, and they just want to get in the game.”
This push back from threatened sport-purists has been common, because analytics has been trying to revolutionize sports that have remained relatively the same for more than a century. But eSports on the other hand, is just beginning to enter the global consciousness. Fractured across numerous popular titles, dozens of new leagues and competitive s
cenes are forming every year. Analytics has the opportunity to grow with eSports from its very beginning, and it can affect a lasting impression among the younger, more technophile groups that run and participate in these competitions.
Zach Fine, Evan Spellman, and Jordan Lavatai are three data analysts that are hoping to be at the forefront of the eSports-analytics boom with the wonderful website: https://statspy.us/. Currently getting their feet wet by analyzing the immensely popular Counter Strike: Global Offensive scene, the gentlemen at StatSpy recently launched their website, full of charts and analysis for CS:GO enthusiasts to our over. I recently sat down for an interview with the StatSpy team to get their opinions on eSports, analytics, and why both are vital to each other.
For those that may not know, what is analytics, and what is its relevance towards eSports?
Zach, Evan, & Jordan (ZE&J): Analytics in the broadest sense of the term is the usage of past data to predict upcoming trends, or how a system of data might react to certain changes. In a more limited area like eSports, analytics is the use of data to predict the result of teams playing each other, or to identify the key aspects of a team or players game that can have the biggest aspect on their chances of winning. These predictions can do everything from helping the casual fan understand a more nuanced area of the game to assisting a professional team in their preparations for a match.
How have you gone about finding proper data for your analysis? What kind of questions are you hoping to answer with your data?
(ZE&J): One great thing about eSports is that due to the online nature of more games, the resulting data is also online. For Counter Strike (CS:GO) we gather data from various professional league websites, and also directly from replays of the games themselves. The biggest questions that we want to answer right now are what trackable in-game data sources have the biggest impact on a team or player’s performance in future games. Through this we can begin to more accurately model both the predictive side of our analysis but also create a greater understanding of what makes a great player or team.
How can current eSports organizations utilize analytics to help themselves?
(ZE&J): In every sport, electronic or not, analytics plays a huge role in team improvement and preparation. Teams can use analytics to identify their biggest weaknesses and their greatest strengths, which allows them to make adjustments to their play accurately. They can also use these same data sets to better understand their competitor and prepare for them in a more meaningful and pointed way.
It’s not just teams that can be assisted by these analytics, it’s everyone. Game producers can use analytics to have a more complete understanding of their own game, what is working, what isn’t, where their users gravitate towards be that a specific strategy on a map, or a certain build of a champion, or an item path, there are endless amounts of things to be taken from advanced analytics.
One of the things we would like to see is professional eSports programming, for tournaments and such, be more engaged in using advanced statistics at the desk. Perhaps even a ticker at the bottom of matches. There’s so many ways they could use it that would benefit the viewers greatly.
What was the motivation in creating StatSpy? Where did the idea come from?
Zach: For as long as I can remember I have been a math guy. As a result, I always had an affinity for numbers and statistics over words and opinions. I was a huge fan of fantasy sports growing up, and always was looking a box scores of football games and player stat breakdowns of basketball players. I think I realized that I could contribute to the world of analytics after my freshman year of college, where I started to build the foundation of my programming skill, and saw that I could create my own analysis. Once I realized that I didn’t have to just look at the analysis of others and could create my own, I went for it!
Tell me a little about the entire team. What drew you personally to the world of big data and analytics ?
Zach: The original idea for StatSpy started about 8 months ago when I got into the Counter-Strike: Global Offensive scene. I had been a long time League of Legends player and was burned out with the game and wanted to try something new. A friend of mine suggested I try CS:GO and I was immediately a huge fan. After playing CS:GO for a couple of months I was introduced to fantasy eSports and eSports betting. Having been a big fantasy sports fan I was naturally drawn to those type of games, however when I started doing my research when playing, I realized that amount of statistical data available was almost nothing compared to that of mainstream sports. It was at that point that I decided to really pursue creating a website devoted to statistical analysis of eSports. I enlisted the help of Jordan, my roommate and fellow developer, and Evan, my good friend and someone who has bounced around the eSports scene in his own right and here we are!
Ideally, where do you want to see StatSpy and yourselves in a few years from now?
Zach: My goal is for StatSpy to be the premier place that people go to, to do their own analytic research for eSports, whether it be a casual player trying to improve themselves, an amateur or pro team trying to step their game up to the next level, or someone looking to get ahead in fantasy eSports or betting. We all plan to be in this for the long haul as we are trying to create an amazing site and grow it until we are synonymous with eSports. However long that takes, we’ll be here!
Why choose Counter Strike as your first eSport to analyze? What does analytics tell you about the Counter Strike Scene?
Zach: We chose Counter Strike for a few different reasons. Primarily, Counter Strike had the most basic data to analyze out of the 3 big eSports (DOTA2, LoL, CS:GO), which meant that we could get the ball rolling and develop basic analysis of professional teams and matches more easily than any other game. Secondly, CS:GO has a thriving betting/fantasy eSports scene which offers the biggest potential market for us as an analytics company. Finally, CS:GO is the game I have played the most personally and my favorite eSport, so I had a personal connection to the game kind of. As for the analytics, I think one of the biggest things that we’re taking away right now is that the volatility of professional teams in CS:GO is one of the hardest things for the betting public to grab ahold of. Between the roster changes, natural ups and downs of teams, different favored maps, trying to pin down consistent odds and rankings is much harder than it is for other eSports.
Any other games you hope to expand into soon? How do you guys try to decide which scene to try to enter next?
(ZE&J): Our goal is to enter every major eSports at some point in the future, but the one we are looking at getting into right now is League of Legends. When making these decisions the biggest factors we look at are the size of the competitive community, the future potential of the game, and the difficulty of gathering/analyzing data from the game. League looks great from all of those standpoints since it’s the biggest eSport around, is only growing, and has replay technology that can adapted for analytics.
What are a few things you hope audiences can learn from analytics when following their favorite competitors?
Zach: I think the biggest thing people will learn about their favorite teams are the strengths and weaknesses of that team. Often times we are left making assumptions about a player, or a team, or a strategy based on what we are seeing, but we’ve learned that our flat assumptions don’t always coincide with the numbers. For me personally the ability to adapt my general knowledge and beliefs about game alongside the analytics has improved my understanding greatly. Even if you’re not a great player, you can still understand the game at its highest level.
In your opinion, what are the one or two main insights that you want your readers to understand from analytics, StatSpy, or your work?
Zach: By far the biggest thing I want people to understand from analytics is that it’s very easy to get caught believing things that have a basis in reality, and as I mentioned in the question above, sometimes those beliefs don’t coincide with the analytics. It’s important as a player, a competitor, or a viewer to be able to have a well-rounded understanding of a game. Through the insights we can give people through our analysis, and a reader’s general knowledge of the game, they should be able to start to reinforce or negate their beliefs through evidentiary means!
What do you see as the future of eSports? And where do you hope to see big data in eSports in the future?
Zach: In my opinion, the future of eSports is about as bright as it gets! More and more people are starting to follow eSports, and we are seeing some crazy viewer turnouts at the big international tournaments. Major US television networks are beginning to broadcast eSports leagues, viewership online is higher than ever, and people like Mark Cuban and Rick Fox are bridging the gap between traditional sports and eSports. There is no doubt that we are about to see an explosion of popularity in eSports.
I think big data will exist in the realm of eSports in the same way it does in normal sports. Fans of sports love to compare players, teams, numbers, so there is an inherent place for big data in eSports as well. As time goes on there will be a shift in how serious eSports will be taken, not only by the public, but by organizations as well. This will create a place where analytics will be devoted to improving professional teams, and a lot devoted to predicting the outcome of matches for fantasy/betting purposes as well. It is our belief that the growth of eSports will mirror the growth of traditional sports, and that is a great thing.
ESports has already generated considerable buzz in the analytics world, as the MIT Sloan Sports Analytics Conference, the largest sports analytics conference in the world, has devoted entire panels to the subject recently. Unlike traditional sports leagues, which were established long before analytics were invented, eSports is growing and maturing during the analytics era. Even though individual talent playing these games is arguably just as important as in traditional sports, analytics will have a place from the beginning as teams and leagues begin forming around the hundreds of competitive games that will be coming out over the next few decades. And due to eSports’ inherently analytical and tech savvy background, I do not think we will find very many Charles Barkley-esque traditionalists decrying the value of analytics in the eSports industry anytime soon. And StatSpy is poised to be one of the best in the industry. Break out the spreadsheets, it’s time to go crunch some more numbers.