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How Data Analytics is Being Leveraged by Professional Sports

Vincent Stokes / 3 min read.
August 10, 2017
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In the age of Big Data, the term analytics gets tossed around a lot, especially in the world of sports. Analytics insights from sports range from the truly strange, such as the fact the pro tennis player who grunts the most effectively tends to win, to the genuinely game-changing, such as NBA teams changing their season long approach to player rest. If so many sports are seen as games of inches, what might seem like a rounding error may in fact be the difference between victory and defeat. Let’s take a look at some ways data analytics as a field is being leveraged in professional sports.

Missile-Tracking in the NBA

STATS SportVu is a system that’s based on existing missile-tracking technologies, and it’s a popular choice across many North American sports leagues for recording the positions of every player and the ball. It has become especially popular in the NBA, where it is being used to track where players take their shots, how they come into the offensive or defensive zone and how likely they are to succeed or fail. Teams decide one-on-one match-ups based on this information, and the teams that process the data most effectively tend to win. It’s not an accident that the most data-centric NBA team of the modern era, the Golden State Warriors, is also the most successful.

Improving the Fan Experience

Many pro sports franchises make it point to monitor the entire fan experience. That goes far beyond tracking how fans experience their own arena or stadium. Teams use everything from social media trackers and premier web scraping software to scrub the entire internet for signs of fan discontent in order to meet it head-on. This sort of approach to public relations may allow teams to get ahead of controversies and keep their fans happy. For example, Bayern Munich of the Bundesliga in Germany has a standing agreement with SAP to handle global fan management tracking efforts. The next time you complain online about a big trade or a bond issue for a new stadium, the team might be listening a little more closely than you expect.


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Consent

Knowing When to Quit

As appalling as it might sound to fans of teams that are near the bottom of their leagues, there’s a point where it’s simply smart to give up and try to get the top pick in the draft. Fans of the Philadelphia 76ers of the NBA probably already feel like their team may have given up in recent years, but the seemingly cynical choice has all but been confirmed as an analytics-driven decision by management. Many teams now consider it worth playing the odds at the end of bad seasons in order to move up in draft lotteries, and it has become an important data-driven choice to decide to be the first team to stop trying so hard to win games.

Many see the 2017 Houston Astros team’s resurgence in MLB as proof of the validity of this approach. The Astros decided several years ago to deliberately tank their payroll spending in order to not pay for losing and instead focus on the future. As the team’s player quality has improved, the payroll has also grown. The Astros simply refused to pay to watch losing baseball.

The total volume of available information that sports teams have at their disposal makes the old days of tracking RBIs and quarterback ratings seems painfully quaint. We now live in a world where racing teams even at the dirt-track level regularly check air density information in order to decide how cars will be configured. Online gamblers are pulling advanced stats from systems like MLB’s PitchFX in order to determine whether betting lines are off. From the biggest franchises down to the smallest schools at the amateur level, everyone is checking the numbers to try to gain an edge.

Categories: Big Data
Tags: Big Data, sport analytics, sports

About Vincent Stokes

Vincent Stokes is a freelance writer for Datafloq.

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