The use of data in professional sport has grown significantly in recent years. In football, the volume of data available to teams is expanding exponentially. It is increasingly difficult to capture all of the relevant data points available and distill the complex information contained in those millions of data points per game into a series of simple representations. These representations then have to be quickly absorbed, tailored and shared to enhance teams’ performances and win more games.
The adage that big data provides big insights has never been more important, while also being increasingly more difficult to achieve. Sports analysts rely on data to do their jobs, collating and clipping information from training sessions and competitive matches, which helps manage squads, deal with injuries and help coaches make the decisions that matter.
Sports data intelligence is an exploding industry due to the sheer value behind the data. Player monitoring and tracking technologies have been in place for some time, but without timely and relevant context the numbers simply do not add up. Finding the context behind each situation is crucial for data analysts to get immediate answers they can rely upon to make informed decisions.
The power of machine learning and artificial intelligence is being harnessed by blue-chip businesses looking to amplify human potential. The same is happening in professional sport. Behind the scenes new technologies are maximising the value of data – so important in a complex football match with thousands of events per game translating into millions of data points. Machine learning is helping players and their sports science teams come up with objective measures and spot scenarios impossible to the human eye.
Artificial Intelligence can simulate such a quantity of events that it allows a data scientist to translate the insights, and make recommendations as to what will happen on the pitch. This arms coaches to make informed decisions on individual players and is vital in preparing for a game. The added insight can influence which players are selected in team sports and be helpful with a tight turnaround between games such as is the case with football. Beyond individual training schedules that should be organised, it can aid in determining tactics based on the opposition’s playing style.
When imagining a sports scientist or analyst, you often envisage a room full of screens, spending time analyzing footage (akin to Billy Beane’s assistant in Moneyball). Machine learning is improving this time-intensive role to enable faster and better-decision making. So using actionable insight, as opposed to a series of numbers that have no relevant context, helps those in this role get quicker, deeper analysis and add even greater value to the coaching staff.
The technology is only getting better. Artificial Intelligence is quickly being implemented in our everyday lives with digital assistants on our phones and in our homes. And it’s here to stay. By applying technology to sport where marginal gains are vital, we’re seeing effective analysis allowing football clubs and players get ahead.
Sport creates some of the greatest human achievements and holds such an inspiring emotional connection for fans around the world. It’s fascinating to see the relationship between artificial intelligence and team performance. In celebrating the peak of human or team performance and emotion, it’s machines that provide data for insights to be drawn. As machine learning algorithms evolve and become further sophisticated, they hold great potential to unlock performance on the sports field.