Big data in sports has become big business, with companies racing to compile, analyze and extract valuable information, which in turn can be used to enhance performance and outcomes in big games. But only recently is sports data becoming ‘biggish’ data, and it’s growing quickly.
In a game like football, which has typically low scores, but large amounts of ‘hidden’ data, the idea of mining it is enticing. Data such as the players’ heart rates, distance run, etc. can help pinpoint the contributing factors that lead up until the moment a goal is scored. This gives coaches a better opportunity to manage their teams more effectively on the field, and ultimately ensuring a higher goal rate.
Sport is one of the few areas that the public can really see big data in action and there are plans to make this data more interactive, especially in the world of football. But big data in football extends beyond a player’s value on the field. It is also linked to their popularity in bringing crowds into the stadiums, viewership on TV and retailing of merchandise.
Sport Has Evolved Into More than Just a Game
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Big data and analytics have the potential to further enhance a football team’s performances and their relationships with their fans.
Just this past May at a football conference in Qatar, Mark Sear, CTO for Big Data at EMC made an announcement that one of the leading English League teams planned to allow its supporters to vote for player substitutions during U-21 matches. Fans would be able to view real-time performance data from all the players’ on the pitch via wearable technology. The crowd can then weigh in and vote for their choice in player substitution via an app on their smartphones.
This interactive concept is bridging the gap between competitive sports and the emerging trend of virtual reality gaming. Launching at U-21 games will increase the appeal for fans to attend games, and thus boost ticket revenue. “It actually makes it very similar to Football Manager (a popular football management simulation game) because you judge people off their numbers,” Sear said. “It makes it a fascinating experience.”
Big data can also be further linked to football fans’ reactions and sentient on social media, including how they interact with their team and devices during games. According to Sear, up to 70% of football fans use their smartphones while watching a game at a stadium.
Going beyond the pitch (or court, or field), sports analytics uses big data to analyze what a player means for the club’s bottom line. Therefore his performance and data essentially determines their net value and worth as a professional sportsman. New developments in big data for football could have a massive impact on the transfer prices of players between clubs. Currently players do not have a fixed price associated to them; and instead it is between the two clubs to negotiate and agree on a price for the player in question.
Although sports data is not something new, it has dramatically evolved from being manually recorded and analyzed by pen and paper on the side of the field. Today this data has increased exponentially and is now processed by high tech computers and data scientists in almost real-time. We can already see the impact that big data is having in other sports such as tennis, F1 and baseball. But as big data analytics continues to evolve, we can expect more and more teams to find creative ways to embrace technology and we look forward to seeing how football embraces and implements this trend.
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