How Successful Sports Careers Are Built Using Data Analytics


The data analytics field is expanding its horizons every day. Today, sports analytics have become a vital cog in both individual and team sports. A decade or earlier, players and coaches reviewed video footage of the game and modified their strategies accordingly. Today, in every sport, teams or individuals look at the video footage with a new sense with the help of embedded data analytics. Previously, data analysts were kept at a distance by coaches and staff members.

But today, it’s almost the opposite, and data analysts are considered core staff members and are used in developing every strategy and improving player performance. As players and coaches strive for any statistical edge they can see, the role of sports analytics is growing like never before. So, let’s learn more about the use of data analytics in building successful sports teams and careers.

Data analytics transforming sports

Impact of Data Analytics on Sports

Data analytics’ use in improving sports performance

Data analysts help the sports fraternity in various ways. Across the globe, these number-driven professionals have transformed how sports management personnel approach every task. Big data is crucial for improving both the on field and off field performances of players and coaching staff.

  • On-Field Performance

Various sports franchises and athletes utilize data analytics to enhance their on-field performance. A football team can use analytics to get a solution on which type of play is best to run in specific situations. Tennis players can trace their reaction time and try to improve it. Soccer teams can utilize data analytics and cutting-edge camera systems to track the motion of each player on the pitch, calculating who uses their movements most effectively, who’s landing the best passes, and who has the best impact on possession.

  • The Sports Business

Sports business professionals frequently use data to improve fan engagement, drive ticket sales, and get a better understanding of the successes and failures of their marketing efforts. Ex: Marketing executives can track how merchandise, jerseys, and sales correlate with wins and later modify prices to elevate consumer interest and improve game spending. Additionally, a ticketing executive uses data analytics to get a clear idea of which parts of a stadium are most popular for seating and runs more promotions to sell less popular spots so that they get filled and generate more revenue.

  • Healthcare and Rehabilitation

At the intersection of healthcare, technology, and athletics, there are several devices that offer assistance in monitoring the health and vital statistics of an athlete. Also, there are a number of programs that put all the data points together and show where there are problems. Ex: Heart monitors plot and track each athlete’s heart rate right throughout a workout, practice, and game. Brain and heart health are two significant areas where sports clubs utilize data analytics. Sports professionals also make use of devices like FitBits to trace various data points.

Popular Sports Teams and their Data Analytics Partner

  • Real Madrid & Microsoft: Probably the greatest football club ever, Real Madrid utilizes Microsoft technology to better its performance, operations, fitness, and relationships to cater to its 500 million global fans.
  • Manchester United and Aon: Similar to thousands of companies across the world, the Manchester United soccer franchise depends on Aon as their big-time advisor to come up with innovative solutions that enable them to stay relevant and ahead of the competition.

Sports Data Analytics Use case

Injury reduction

The toughest task for most athletes and teams is to predict when playing or practicing conditions increase the risk of injury. For the players, it means having data that can help them prolong their careers and thereby increase their earnings. For teams, it means more victories and higher revenue. Predicting possible injuries effectively needs measures that assist in balancing exertion and strain with the proper recovery time and sleep. A study estimated that the NFL had lost more than $500 million in 2019 alone due to injuries. So, it shouldn’t be a surprise that the NFL and Amazon Web Services recently worked together to use machine learning (ML) and computer vision (CV) technologies, along with multiple different data sets, to learn more about how to predict injuries.


For a long time, players and coaching staff used their experience and gut feelings to churn out victories for their teams. Most of the decisions and strategies were made based on video footage with limited information. But with data analytics, huge amounts of information can be sorted and shown to you in a matter of seconds. You have to just use them effectively and create the best scenario to win more matches and reach new heights in your sports career, making the team victorious more times than not.

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