Over the past twelve months, the popularity of daily fantasy sports betting has grown exponentially. Naturally, this growing trend has been met with a variety of new analytics sites to help bettors get an edge over their competition. Swish Analytics is one of these sites, and one of their founders, Joe Hagen, took the time to talk with us about how his site leverages analytics.
Hagen and his team founded Swish Analytics last year as a sports betting site mainly focused on the NBA. However, they have since expanded to other sports, including the NFL, and have recently released their MLB product. Hagen explains that his baseball analytics system “updates in real time with information about lineups, weather, umpires, etc.—we’re factoring in basically every single stat that can be accounted for when making a prediction.”
This MLB analytics product can help a user greatly with their fantasy leagues. So far, the app has outperformed Vegas’s odds—at least in predicting straight up winners. But as Hagen explains, the main advantage of Swish is that it provides users a huge amount of important information for them to make their own informed betting decisions. “We’re trying to build products that provide players quantitative data which they can then apply to their own research.”
Compared with other analytics sites, Swish Analytics prides itself on its transparency. Whereas many sites would hide data of their false predictions, Swish shows the user everything. “We don’t want to hide anything behind closed doors,” explains Hagen, “we want to tell you how we are doing. For the most recent iteration of our daily fantasy product, you can see how all of our lineups perform throughout the duration of the year.” This transparency helps users form realistic expectations concerning the accuracy of these predictions. It also allows them to determine how to best use this data.
As analytics become more and more used in conjunction with sports, a lot of new data becomes available to fans. However, it can often be difficult for one to easily organize or access this vast quantity of information. Swish Analytics helps with just that—by automatically scraping many websites and sources, Swish can attain the most accurate data. “We identify Tweets that are related to what we’re looking for and then present that information in a readable/useable fashion,” explains Hagen, in regards to using Twitter to gain insight. “We’re identifying the information that actually matters.”
Swish Analytics is a new analytics platform, so it will surely grow in the upcoming year. Right now, users can access the free version of the website or a paid portion that allows more betting prediction information. The Swish team is right now focused on better injury analytics. Hagen and his team are very excited to offer a real time injury feed for their users. “If there are players with lingering injuries, we want to be able to provide our users a prediction on the likelihood that the player actually plays.” Injuries to a player in one’s lineup can be incredibly frustrating for a fantasy player. Swish hopes to stay on top of injury updates to get their users that information as quickly as possible.
In the future, Swish hopes to expand its product to include other sports. According to Hagen, “the next sport we put out is going to be soccer,” with NCAA in the near future as well. Furthermore, as new data and analytics become available to the public, sites like Swish Analytics will be better able to provide more accurate predictions. As daily fantasy sports betting becomes more popular, people will try to gain a competitive edge over their competition and analytics are a budding new method.
