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Behind the victory of Djokovic against Federer, there are big data that could predict the outcome of the match and be exploited by any business.
The tennis match of the century, Djokovic vs. Federer
When I was a teenager, I was crazy about tennis to the point of almost killing my back to reproduce the serve and volley of my hero of that time, Boris Becker. His victory in 1991 at the Australian Open when he also obtained the world No. 1 ranking is still in my eyes.
Many years have passed, and everyone is now discussing what has been named as the tennis match of the century. The 2019 Wimbledon final when Novak Djokovic defeated Roger Federer 13-12 at the tie-break of the 5th set after almost 5 hours was an incredible match. However, between the age of Boris Becker and nowadays, a lot has changed in tennis not only in relation to the materials but also in the technology and data that are behind a victory.
I don’t know whether anyone had the same impression. My feeling was that Roger Federer knew that he had to win the match before the final tie-break. Otherwise, he almost certainly would have lost. He gave everything he could in the last game before the tie-break, but the tie-break itself was not so incredible as we could expect as if he knew he was going to lose.
And if you look at the official ATP statistics of the match, they seem to confirm such a conclusion. Roger had incredible statistics throughout the whole match, but when it comes to the tie-breaks,
“twenty of the 33 points (61%) in the three tie-breaks were contested with both players standing at the baseline, which played perfectly into Djokovic’s masterplan. Djokovic won 16 of the baseline exchanges, while Federer accumulated only four. Of the eight rallies that reached double digits, Djokovic won six.“.
The relevance of big data and analytics for Federer and sports
Big data were able to inform Federer that he had limited chances to win the fifth set tie-break and the predicted outcome was confirmed by the facts. The level of detail of such information is impressive if you consider that Federer has the best tie-break win rate of all time, with Novak Djokovic ranking second in this challenge though.
As it happens in most sports, big data has become an essential component of players’ preparation for not only Federer but any sportsman. They can predict the behavior of opponents and analyze what shall be improved in your game. There are several studies on the topic, and I found fascinating the creation of the so-called smart tennis courts that can give even more detailed data on players’ skills and behaviors to the point that even Novak Djokovic is investing in the technology.
Such technology can not only make more accessible the collection of data, but the main uplift derives from the analysis of data and the information that can be obtained from them.
The hidden legal issues of big data in sports
As expected, the large amount of data that are processed and exploited create legal issues. Apart from the data protection law issues, it is necessary to understand what rights can be held on data analytics and big data concerning, for instance, the top 100 tennis players of the ranking.
The matter had been assessed by the European Commission which considered (Read on the topic “How the IoT will change with new European regulations?“) whether either
- copyright protection could be applicable, but the issue could be whether there are creative elements necessary for the existence of copyrights in the mere collection of information on tennis plays; or
- database sui generis rights could be held on them if considerable investments are proven in the creation of the database; or
- there is the need for introducing a new “data producer’s right”, which, however, would create a further layer limiting the exploitation of rights on data.
The complexity of this scenario if further amplified in relation to eSports and online poker games for instance. Data on the behavior of opponents are crucial to determine the right strategy. We dealt with disputes where we had to convince courts of the cheating behavior of opponents, just relying on data relating to their playing strategy which did not make any sense and all of sudden had changed.
The changes introduced by the EU Regulation on non-personal data
The European Commission is partially trying to address the issue through the Regulation (EU) 2018/1807 on the free flow of non-personal data in the European Union which provides, among others, rules on porting of non-personal data, extending the scope of the GDPR data portability right (Read on the topic “How the privacy data portability right impacts you with the GDPR?“).
The Regulation is far from being a detailed set of rules on non-personal data. It is a step towards regulations that might change not only tennis and in general sports, but any business since they will all become part of the data economy.
My top 3 best practices on handling big data and analytics
In the current scenario of uncertainty, I believe that the top three best practices in dealing with big data and data analytics are:
- Contractually regulate the ownership of data, without relying on intellectual property laws. The scenario might rapidly evolve and renegotiating an agreement is always harder;
- If you are the individual/entity generating big data, make sure that you are adequately paid for the data you give to your supplier; and
- Provide a migration clause so that on the termination of the agreement, there is no loss of data generated during its term.
