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Can BigData Win a Super Bowl

Technology is disrupting many industries and fields. But disruption isn’t limited to business or healthcare. It is altering fields we might not expect – like professional sports. Yes, even professional athletics is undergoing a digital transformation, and data is fueling this rapid shift. Increasingly data is being used to optimize athletic performance. That’s right. In the near future, data might be as critical to athletic success as practice. Teams are using data to help prevent injuries, predict a team’s highest-scoring line up, and elevate an individual’s training regime. Just as Netflix predicts what shows you might like; data is enabling coaches and athletes to predict their next pitch, play or teammate. Today, Sports Analytics is a burgeoning field. What started as a no-way-it-will-work project of baseball’s Oakland Athletics – which was featured in the book and film Moneyball – is now going mainstream. Moving forward, data will be what separates the winners from the losers.

Can a Moneyball Maven Fix the Browns? via Sports Illustrated

Can a Moneyball Maven Fix the Browns? via Sports Illustrated

Will data be the key to success for the NFL’s perennial bottom-dwellers? The franchise’s owner thinks so. The Browns recently hired Paul DePodesta, who has helped a number of Major League Baseball teams build out data operations. And although DePodesta – who was an integral character in Moneyball – hasn’t had a chance yet to use data to help the ailing Browns, this article provides an interesting history of sports analytics, starting with the Cleveland Indians video monitoring program in the 1990s.

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The Next Big Thing in Sports Data: Predicting (And Avoiding) Injuries via Fast Company

The Next Big Thing in Sports Data: Predicting (And Avoiding) Injuries via Fast Company

The idea that data can prevent injuries is still in its early stages, but a number of companies have found surprising results. For example, Catapult, a startup specializing in sports analytics, has built a program that collects in-game and practice performance data for athletes. During the 2013-2014 NBA season, the company worked with the Toronto Raptors and collected a range of data. After analyzing it, they were able to determine that a number of practice drills – like repetitive shooting, which required the player to jump up and down – put a ton of stress on their joints. After altering the way the team practiced, the Raptors had the lowest number of injuries in the league.

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How Big Data Aids Marathon Runners via SportsTechie

How Big Data Aids Marathon Runners via SportsTechie

Wearables – like the FitBit – make it possible for any athlete, from the arm-chair 5Ker to the professional marathoner, collect data. And an overwhelming majority of runners have embraced wearables. According to one survey, nearly 75 percent of runners use wearable technology to optimize their performance. And as the author notes, the technology is still emerging. In the future, it’s very likely runners will have access to a multitude of data, helping them to make tiny alternations that will help them shave minutes off their times.

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Germany’s 12th Man at the World Cup: Big Data via The Wall Street Journal

Germany’s 12th Man at the World Cup: Big Data via The Wall Street Journal

Germany’s national soccer team in the 2014 World Cup proved one thing: Data – at least in part – can help win championships. In fact, using a customized data analytics platform, the German squad was able to optimize their style of play and speed up the game. After analyzing data from previous games, Germany cut average possession time from 3.4 seconds to 1.1 seconds. This acceleration helped German fly past the competition on road to a world championship. To gain a competitive edge, the team partnered with German software giant SAP AG to create a custom match analysis tool that collects and analyzes massive amounts of player performance data.

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The NFL Is Finally Tapping into the Power of Data via Wired

The NFL Is Finally Tapping into the Power of Data via Wired

Of all the major sports, American football has been the slowest to adopt data science. Why? It’s much more difficult to track players on the football field and attribute that data to a specific outcome. As Wired notes, that’s slowly changing. The NFL is testing in-game sensors that provide advanced GPS tracking of players on the field. But that’s the easy part. Now, the big challenge – just as it is in business – will be cutting through the noise to find actionable data.

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