The NFL and NBA is in full swing with events taking place all over the country each week. These events continue to become more competitive each year.

Professional athletes continue to have more and more pressure put on them to compete at above average levels day in and day out. As statistical analytics continue to grow as well, athletes and coaches find new ways to integrate big data into their workflow.

Forbes recently reported on how soccer teams in the United Kingdom have been using big data to help inform their soccer clubs. Arsenal, the Premier League soccer team has invested in additional camera equipment to track motions from the players.

Forbes also noted that football players and other athletes wear sensors to track inquiries. ‘In American football or rugby for example, injury levels have been reduced in the professional game due to wearable sensors that monitor the intensity of activity and impact of collisions, and compare this to historical data to determine when a player might be in danger of overexerting or injuring themselves.’

Machine learning and data crunching continues to provide insight for coaches and players to see what is working more often in different situations. It can be noted that each situation in a sporting event may be more unique than others. A Reddit thread discusses how NFL has more variables in each play compared to baseball.

“I’m investing a lot in machine vision.” – Mark Cuban

Mark Cuban, owner of the Dallas Mavericks and entrepreneur, discusses the importance of machine learning in the YouTube video below. Tune in to the minute mark at 46:00.

MIT Technology Review goes into detail on how big data takes resources and financial backing to collect and manage the data. With the inequality between teams, it is hard to track how well the data is being used across the board.