Data is used in the sports industry in a myriad of ways.
Medics and coaches use data to garner insights into patterns and trends that can help enhance an athlete’s or team’s performance or develop strategies for health and improvement. Sports journalists use data to look at historical trends or talk about players’ performance. Streaming networks use real-time data to enhance the audience’s experience. And the list goes on.
As a data professional and a former tennis coach, I have a unique perspective on just how game-changing data has been for the sports industry. Below, I dive into some key observations on how data has transformed the game of tennis in recent years.
Data has Upped the Ante
Tennis has always been a highly technical sport. For example, during my tennis coaching years, I remember being taught how to string a racket by the head stringer at Wimbledon. That taught me how much thought goes into changing string tension―I learned how each racket is specially designed to complement a player’s unique needs or things like the court’s surface texture. Tiny details like that were considered even during my time in the tennis world.
But these days, the analytics capabilities are light years ahead of where they were at a few decades ago. Now, tennis has become even more strategy driven. It’s clear that there is a lot more work that goes on in the background today.
Specifically, new tools and capabilities mean that there is a lot of analysis that coaches can do, to understand the playing habits of opponents. This has boosted the level of talent and has arguably raised the level of competition in the sport.
Years ago, it would take several games to recognise a weakness. But with advanced data, you can’t hide your weaknesses anymore. Now, every detail of a player’s game is recorded. And coaches and professionals can use this information to formulate strategies. Which ultimately raises the game of tennis (in my opinion).
Some Examples of How is Data Leveraged in Tennis
Data can be commonly utilized in serving. Players will rarely take risks with their second serve, and data confirms most players win a much higher percentage of points on their first serve than on their second serve. Usually, everyone hits their first serve with power and speed, but the second serve can be slower but have greater precision, to ensure the ball lands in the lines and the point is not lost. The data on this can help players and their teams come up with strategies for the return of their opponent’s first and second serve.
Video analysis has also been popular for a while now as it can analyse the sequence of joint and limb movements so that changes can be made to improve elements of the game. The player can watch clips back to clearly understand what needs to change so that the stroke can be improved; and for the physio and sport science team – how can injuries be prevented. The proof that this works is the fact that professional tennis players are still competing at the Grand Slams at an older age than they would have, say 20 years ago.
Sports scientists can also use data and analytics to gather trends around grassroots training. For instance, data analytics have provided evidence showing how younger players in academy years will experience growth spurts and during that time, they will be more prone to injury.
This information gives coaches the opportunity to change training regimes to minimise the risk of injury.
Proper Analysis is Key
While data analytics have transformed tennis, as well as the wider sports industry, it’s important to note that the data itself can only take you so far. And what I mean by that is, data only provides information on something―it’s then up to the data professionals to take that information and translate it into something useful.
That’s why it’s so important to have data professionals in the industry who can communicate with non-data people, to ensure that their insights are aligned with a company’s business goals.
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