After an entire month of collective cheering (and agonizing), billions around the globe are now eagerly anticipating the 2014 FIFA World Cup final on July 13th in Brazil. Both the German and the Argentinian teams have effectively exploited any type of edge over each of their opponents to earn their respective spots in the finals.
One very effective way to stay one step ahead is by leveraging the massive amounts of data for a competitive advantage. As an InformationWeek post on the topic points out, each kick, pass, steal, and goal represents just one in a series of 2,000 “events” that occur in each match.
Coaches and other officials for national soccer teams can utilize data that’s generated from sensors, video cameras, social media feeds, and other outlets in tandem with data analytics to analyze the tendencies, strengths, and shortcomings of rival teams and craft strategies based on those insights.
Some teams are using emerging tools such as goal line and ball tracking technologies to measure the tendencies of players in very specific situations.
In addition, unstructured data in the form of video analytics can be used along with keywords to identify and collect specific audio and video events from game videos that coaches and other decision-makers can use to analyze key game activities and player/team tactics.
“Teams can crunch the data to discover that more goals are scored from in-swinging corners and adapt their play accordingly – just as Manchester City did when they won the English Premier League in the 2011/2012 season,” according to the InformationWeek article.
With interest in the World Cup at a fever pitch, TIBCO Spotfire worked with Perkin Elmer Informatics to develop a demo that illustrates how TIBCO Spotfire’s data visualization tools and dashboards can be used to discover deeper insights.
- Check out the demo to explore data points from a very memorable World Cup, including information on teams, players’ ages, positions, and other statistics.
- Try Spotfire and start discovering meaningful insights in your own data.