As more nations are eliminated and the drama of the World Cup increases, loyal fans and bandwagoners alike are jumping in on the action. World Cup coverage has dominated both sports and social media.
Such massive interest has led to a wave of statistical analysis and predictions. Fans want to know about their team, the chances of winning, how past performance affects the next game, and everything in between. As interested observers consume more information, sports journalists and analysts are finding new ways to break through the noise with unique presentations.
New trends in big data and data analysis are driving this change in information intake, and forward-thinking media outlets are showing just how useful these tools can be. By utilizing the resources available for analysis and visualization, these journalists are illustrating how data can provide new insight. Below, we’ve highlighted a few of the data-driven ways sites have covered the World Cup so far.
One of the most shared graphics of US interest in the World Cup is a Twitter volume map of World Cup related activity after John Brooks’ 86th minute goal in the US-Ghana match. As the six-second video shows, twitter erupted in activity across the United States as fans celebrated the unexpected goal from the 19 year-old substitute. This map was created using Cartodb, a cloud-based solution for creating maps based on user data. By calibrating the map to display small dots for any tweet related to the USA-Ghana game, Michael Katz of SB Nation was able to visualize the country’s reaction in real-time. Instead of simply listing statistics or ratings, Michael was able to utilize mapping technology to show US interest in international soccer in a way never before seen.
One day before the World Cup started, the New York Daily News posted an article with a interactive map for finding the best places to watch each game in New York City, tailored to each team. By utilizing Mapbox’s open source platform, the graphic allows fans to find the name, location, and description of a selected venue. To create the popular map, The New York Daily News simply collected existing data and delivered it in a novel, useful way.
Fans are always looking for accurate ways to predict the outcome of a sporting event before it happens. During the 2010 World Cup, a common octopus named Paul made several accurate predictions on match winners, bringing him worldwide attention as an animal oracle. While we no longer have Paul to help us predict the winner of this World Cup (RIP), many sports journalists are utilizing predictive analytics to forecast match outcomes (and generate site traffic).
Before the start of the World Cup, bettingexpert hosted a World Cup Prediction Competition where users made picks on who would win each match and ultimately the World Cup. Bettingexpert analyzed the more than 40,000 submissions in a World Cup Prediction Stats post, where they broke down each teams odds of winning the cup based on public opinion. With relatively simple statistical analysis, bettingexpert drew in huge amounts of site traffic, along with positive press coverage.
FiveThirtyEight, a polling aggregation website and blog created by Nate Silver, has created some of the most popular and informative predictive posts regarding World Cup matches. One day before the start of the World Cup, FiveThirtyEight released a World Cup prediction post including the outcome of every previous World Cup. Performing analytics based on the Elo ratings of each World Cup team before the start of the tournament, Silver’s post shows how this prediction method would have performed compared to the actual outcome for each of the previous World Cups, along with a full analysis of this year’s prediction.
In addition to their initial predictions, FiveThirtyEight created an interactive dashboard where fans can see real time odds of their team advancing in each stage of the World Cup, including the chances of each game ending in a win, loss, or draw. By utilizing data from ESPN’s Soccer Power Index (SPI), FiveThirtyEight is able to calculate the odds of each outcome with probabilities based on 10,000 simulations. Through this post, FiveThirtyEight has made the otherwise overwhelming data accessible to fans, exemplifying the power of visualization.
Companies use these same tactics as well, albeit for different purposes. Applications such as Pentaho and QlikView specialize in predictive analytics, which help companies predict future scenarios, decrease their risk, and increase competitive insight. Pentaho helps businesses discover meaningful patterns inside data sets, much like FiveThirtyEight helps fans see the trends in past World Cup matches. QlikView offers tools for assembling data on the fly to create visualizations and analysis, which function similarly to the interactive game-odds on FiveThirtyEight.
Sporting events like the World Cup contain a wealth of accessible, interesting data. By using tools that turn such data into actionable analysis, journalists increase their competitive advantage and often attract substantial followings. In the same way that businesses can gain competitive market advantages with business intelligence, media outlets are turning towards towards data and visualization to gain their own edge.
See any examples of great data-driven journalism that we missed? Let us know in the comments.