Is big data serving the future of professional tennis?
The Wimbledon Championships is the oldest tennis tournament in the world, this year marked the 135th competition. We wanted to explore some of the data and insights from this year’s tournament and understand how data influences tennis generally.
Roger Federer missed Wimbledon for the first time in 23 years as he recovers from knee surgery; he has played 22 championships, won 1,251 matches and accumulated $130,594,339 USD in career prize money. Many questioned if the tennis ambassador’s absence would affect Wimbledon, but this year’s tournament was the most attended in history with 515,164 spectators, which suggests it didn’t.
On Sunday 10th July, Novak Djokovic defeated Nick Kyrgios to win his seventh Wimbledon title, and fourth consecutive.
Did you know:
- 55,000 tennis balls were used during the tournament
- The fastest serve at Wimbledon was by Taylor Dent (USA), who recorded 238.2 km/h (148 mph) in 2010
- Wimbledon commands a global television audience of 1.2 billion across 200 territories
- 276,291 glasses of Pimm’s and 191,930 portions of strawberries were served.
Big data in sports
You may be wondering which sports use big data?
Big data is used in many sports, including football, cricket, soccer, athletics, swimming and basketball. Sophisticated data can shape decisions and strategies that can benefit overall performance and can assist player recruitment. According to Forbes, the sports analytics market is estimated to grow to $8.4 billion USD by 2026!
After Rafael Nadal withdrew from Wimbledon due to injury, talk turned to injury prevention. Big data can be used to predict the likelihood of an injury. Nature.com shared that Alessio Rossi, a researcher at the University of Pisa, Italy uses GPS data during training sessions and soccer matches to pinpoint patterns and assess the probability of a player getting injured within the near future. Using decision-tree classifiers and machine learning techniques, his system can predict 80% of injuries.
Data and sports go hand-in-hand, this is emphasized in the successful book and subsequent film based on a true story, Moneyball. The Oakland Athletics baseball team used computer-based statistical analysis to form a competitive team of undervalued players using data and a limited budget.
Big data can also benefit sports broadcasting. The use of viewer data and data-led predictions can enable broadcasters to create a more insightful viewing experience.
How is big data currently used in tennis: does big data mean big chances?
Tennis highlights the power of big data, particularly when teamed with cutting-edge technology.
- Key factors affect tennis performance, including
- The strengths and weaknesses of a player and their opponents
- Performance patterns and trends
- The number of shots hit
- The degree of spin achieved with each stroke.
Gathering data from these factors can capture tennis big data and tennis analytics. Pinpointing patterns can result in smart predictions and actionable insights. As more data is collected, the accuracy of the analysis improves.
Big data and technology work in harmony within tennis. With many data systems available, the examples below contextualize how big data can support performance.
Golden Set Analytics works with experts to gather and extract strokes and performance data across 150 players on the ATP tennis tour. The data is consolidated and supplies information on the strengths and weaknesses of opponents. The analytics quickly identifies patterns that would otherwise take a coach several matches.
SwingVision is an app that uses A.I. to automate shot tracking and video analysis. The technology is used by players and coaches to track movements and ball trajectories. A.I. uses data to recognize trends and insights to generate instant feedback.
The Infosys Tennis Platform extracts an extensive number of data sources from multiple applications to compile and analyze data. With Stroke Summary, success from lobs, volleys and strokes can highlight what has the most impact on match performance. CourtVision uses four cameras at different angles to collect thousands of data points in real-time. Stats+ uses complex algorithms and data processing to pinpoint the key areas of play. The platform offers users detailed insight using thousands of data points.
At Wimbledon, IBM remains its technology partner after 33 years. According to IBM, they have 9.2m tennis data points recorded, and staff continue to record stats courtside. The platform converts the endless data into AI-powered analytics. Alongside the match and performance data, AI is used to collect media source data to understand the current player sentiment.
Player insights: is age just a number?
As we look into player insights, it becomes clear that tennis players are playing for much longer in their careers. Serena Williams and Roger Federer are 40 and still playing professionally, Rafael Nadal is 36, and Novak Djokovic is 35. In the past, Pete Sampras was 32 when he retired, and Andy Roddick was 30. What can the data tell us?
In 2018, a study conducted by tennishead revealed that the average age of the top 100 male and female tennis players has risen sharply in the last 10 years. “Thirty years ago, the average ages of the world’s top 100 men and women were 23.74 years and 22.56 years, respectively… In the last 10 years alone, the average ages have risen by 2.67 years among the men and by 2.14 years among the women” tennishead explained.
Although there is no clear explanation for the significant age increase, Mark Kovacs, a Performance Physiologist highlighted that “Tennis has a massive mental component as well, and over time you get better at that. In a sport where you’re alone against a single opponent (or, at most, have one partner in a doubles match), having a little extra maturity helps.”
The future of big data in tennis
Coach Craig O’Shannessy worked with Novak Djokovic for two years and said, “data changed our sport forever”.
Data sources will continue to increase, and so will the big data. The rise of artificial intelligence supports the work of big data and will help to create more conclusions that can affect decision-making and overall performance.
The future of tennis looks bright, especially with the help of growing data and technology.
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