Wimbledon: Data and Analytics In Tennis

The sports data analytics market is expected to reach a record value of $4.5 billion by 2025.

Thanks to its capabilities through technologies such artificial intelligence (AI) and machine learning (ML), sports data analytics has opened a wealth of opportunities to teams across all sports games to perfect their strategies and tactics, understand who their best players are and why, as well as analyse risk factors such as injuries.  

One sport which regularly uses sports data analytics is tennis, and with Wimbledon currently gripping the nation, there seemed like no better time to deep dive into the use of analytics in Britain’s most historic and most-loved game.

The History of Wimbledon

Wimbledon is the oldest tennis tournament in the world, with the first championship taking place nearly 150 years ago in 1877. While it was only Men’s Singles played at the inception of the game, a few years later in 1884, Ladies’ Singles and Men’s Doubles were introduced. The final matches, Ladies’ Doubles and Mixed Doubles, were introduced in 1917. Despite its long-term presence in the UK, its popularity has only grown – especially via television audiences. Indeed, the two-week tournament held in 2021 attracted a cumulative audience of 15.5m from the BBC’s coverage.

The History of Data at Wimbledon

Sport Data Analytics arrived at centre court in 1991 after more than a century of players and coaches simply needing to guess what was working and what wasn’t working. While the use of metric measurement emerged at a very basic level for tennis, the understanding and use of its abilities grew rapidly alongside the incredible advancements of available technology. In 2015, IBM – for the first time – shared rally data which consequently provided game-changing insights into the optimum way to practice through mathematical equation. Not only did this information allow for more efficient practice, but it ensured players weren’t being overworked unnecessarily for very little return.

What Else is Measured Through Tennis Data?

There are numerous data sets collected during tennis, both in matches and in practice. Some devices within a competitive match enable more accurate refereeing, such as supervision of balls landing on the lines, similar to technology such as VAR which is found on the football pitch, video replays, and fan engagement. During practices, players may opt to use wearable devices on their bodies and racquets so that coaches and teams can see where both their strengths and weaknesses lie throughout the game. This then enables the creation of tailored practice strategies to help them improve their performance.

Data Analysis within tennis can also give a good indication of patterns of performance, facilitating strategic gameplay from players. A good example of this can be found in this Towards Data Science article which explores the importance of the first serve in tennis and whether it can guarantee success in a game.

Not all players embrace data in tennis, however. According to tennis.com, Federer – while beginning to use data after his injury comeback – remains cautious of its value. Nadal embraces racquet sensors but chooses not to delve into the stats of the game at all. On the other side of the coin however, Djokovic was the first player to fully implement data insights into his game, employing a data analysis consultant as part of his team.

But whether you’re for the use of data in the game or not, there’s no denying that its value in the market is creeping up slowly but surely. We’re likely to see more adoption of its use over the coming years and Wimbledon 2022 is undoubtedly going to be fraught with insights before, during and after matches.

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