Clifford Chance

The global industry recording, analysing and utilising athletes' performance data was valued at close to $1 billion in 2020 and is expected to reach $5 billion by 2026 . However, until recently, despite the data arising from athletes, it has been sport's other stakeholders who have unlocked its value.

Events over the last year, including Project Red Card and Kevin de Bruyne's new contract with Manchester City (the current English Premier League Champions), suggest that the balance between the major stakeholders in sport (including clubs, sponsors, governing bodies) and athletes is shifting.

This is particularly true under emerging tech regulation, such as the General Data Protection Regulation (EU) 2016/679 (GDPR) and its local implementing legislation, which directly empowers athletes to take control and ownership of their own performance data.

Data Analytics in Sports: the Current State of Play

Whilst basic data and statistics have always been a part of sport, over the last two decades technologies such as machine learning, advanced wireless connectivity and wearable trackers have become integral to the ways that elite athletes' performance is assessed.

Alongside this, stakeholders, including teams, clubs, leagues, broadcasters, betting companies, agencies, game developers and fantasy sports providers, have sought to utilise data analytics  in search of competitive advantages and additional opportunities for monetisation.

The ready availability of this new data, and the volume and automatic processing of it, raise important questions about the rights of athletes.

Data at Play

Traditional data: these are the basic statistics that have been in sports for decades. In football this would include statistics such as appearances, assists, goals, tackles and clean sheets.

Advanced data: these are statistics that involve more complex analysis but which are still derived from traditional data.

Biometric data: these are statistics that reflect internal body data which can include medical indicators such as pulse, blood oxygen levels, cardiovascular metrics, sleep cycles and body fat composition.

Stakeholders

Some of the traditional and new stakeholders in sports data and analytics include:

Data tracking technology developers: companies that build and develop the technology required to track athletes' performance data. This includes some of the most recognisable names in global technology, such as AWS and IBM, a host of specialised sports technology companies, such as KINEXON, and an ever-increasing number of start-ups and SMEs.

Data analytics companies: independent specialists who collect and analyse performance data to sell onto third parties.

Professional teams/clubs: purchase, collect and process data to identify ways to improve performance, on the pitch and in the transfer market, over the short, medium and long term.

Sports agencies: represent athletes or clubs and use data to promote and market their clients.

Broadcasters: process, analyse and report on data as part of the consumer viewing experience.

Gaming developers: use performance data to evaluate athletes and improve the user experience, gameplay and realism for consumers.

Fantasy sports providers: process traditional and advanced data to create a scoring system for their users.

Betting companies: process and analyse both traditional and advanced data as part of setting betting lines and odds. Additionally, they use the live data, provided by data analytics companies, to operate the relatively new market of in-play betting and cash out options.

The Value of Performance Data

The market for athlete performance data is diverse, lucrative and growing. According to Deloitte, between 2014 and 2019 there were over 3000 venture deals and funding rounds for sports technology companies.

Looking specifically at the fees paid by data analytics companies to access and distribute performance data, a recent prospectus, published by the Genius Sports Group (Genius), suggested that the fees it pays to FootballDataCO (FDC), for the exclusive rights to collect and distribute in-game data from the English Premier League, English Football League and Scottish Football League, are close to £10 million a year.

This value is being driven, at least in part, by the fact that end users are expecting greater access to performance data as part of their holistic consumption of sport (including through watching, gaming, playing fantasy sports, gambling etc.). This encourages stakeholders providing and developing these services to ensure that their access to performance data is equal to or superior to that of their competitors, or risk losing customers to them.  

Emerging Litigation

Another measure of the value of sports data is the increased litigation we are seeing in this space, including the ongoing dispute between Genius, FDC and Sportradar relating to the five year exclusivity agreement signed by Genius and FDC in 2019.

Under this agreement, Genius receives the exclusive right to capture live game data, from the English and Scottish Football Leagues, and distribute it. Both Genius and FDC have sought to maximise their exclusivity by attempting to stop other data analytics companies from collecting live data in stadiums by requiring clubs  to evict non-Genius data scouts for breach of the ticketing terms. In March 2020, Sportradar brought proceedings against Genius and FDC in the Competition Appeal Tribunal for anti-competitive behaviour and abuse of dominant position. More specifically, for refusing to grant sublicenses to other data analytics companies or allow their data scouts access to live matches.

In return, in February 2021, Genius brought proceedings in the High Court against Sportradar alleging that the consistent dispatching of Sportradar data scouts to live matches in England and Scotland was a breach of Genius' exclusivity agreement.

The cases could have significant consequences in the sports data industry. If Sportradar is successful, it will make it more difficult for sports bodies to sell exclusive sports data rights which may devalue sports data as an asset and result in a proliferation of new data companies. Conversely, if Genius and FDC are successful, it may result in further uplifts in value.

What about the participants?

Whilst the industry surrounding athletes' performance data has grown, athletes have not traditionally shared directly in the upside - until recently.

Threatened legal action is being brought by roughly 400 current and former football players, led by long term manager Russell Slade, from across the English and Scottish professional leagues, against various stakeholders processing their performance data for the commercial gain of third parties, so called "Project Red Card".  

There are parallels to be drawn in football to the famous Bosman ruling, of 1995, where the European Court of Justice held that the player transfer regulations at the time, which limited a player's ability to move club at the end of their contract by requiring the sign off of the previous club, were a restriction on the free movement of workers under Article 39 of the EC Treaty.

As such, players, including Jean-Marc Bosman, should be allowed to change club, within the EU, at the end of their contract at their own discretion. Players were given self-determination and the opportunity to leverage their value as a participant.

Similarly, whilst Project Red Card is purported to focus on the players' legal rights under the GDPR with respect to the processing of their personal data, it may also demonstrate that athletes have recognised the potential value of their personal data and are ready to leverage their legal rights to share in the profits.

Another recent, practical example of an athlete leveraging the value of their personal data is Kevin de Bruyne's contract extension with Manchester City F.C.

Reports at the time of the contract suggested that Kevin de Bruyne and his lawyers had hired a data analytics company to assist with the contract negotiations. Whilst clubs and agencies have worked with data analytics companies to gain a competitive advantage on the pitch, in the transfer market and in contract negotiations, it has so far been unheard of, publicly, for a player to deploy a data analytics company to utilise comparative analysis to demonstrate their own value to a club.

The data analytics company, Analytics FC, reportedly analysed both traditional and advanced metrics, comparing his data to that of similar players around top European football clubs, to demonstrate his importance to the club and, crucially, the comparative competitive advantage Manchester City F.C. stood to lose if he were to leave, for free, at the end of his contract.

In the past, only clubs had access to this walled garden of data and could therefore arbitrage player performance data in contract negotiations. This may encourage players and their agents to follow suit.

GDPR

Any processing of personal data within the EU, and increasingly across the world (including in India, Brazil and California, amongst others) will be subject to applicable data protection and privacy regimes. In Europe the key piece of legislation is the GDPR.

Personal Data: the GDPR defines 'personal data' as any data relating to an identified or identifiable individual (the data subject). A data subject, here the athletes themselves, will be identifiable if they can be directly or indirectly identified using this data. This definition is broad enough to include almost all types of performance data.

Controllership: the GDPR defines a 'controller' as any natural or legal body which determines the purposes and means of processing personal data. This would typically be the organisation who is collecting, storing and analysing the data for their own benefit.

Lawfulness of Processing: in order to process personal data the GDPR requires a controller to have a lawful processing ground. The most relevant justification for processing in this context (except special category data) will be legitimate interests.

It should be noted that there is a distinction between stakeholders who have direct contractual relationships with athletes, such as clubs, agencies and, in Kevin de Bruyne's case, a data analytics company, and stakeholders who do not have contractual relationships with the players, such as bookmakers, most data analytics companies and broadcasters. It is more challenging for the latter to appropriately justify the processing of an athlete's data where that athlete is not directly made aware of the processing.

Legitimate Interests: controllers who are seeking to rely on legitimate interests as the legal ground for data processing can only do so where their 'legitimate interest' does not override the interests and fundamental rights and freedoms of the data subject. This means that each stakeholder, seeking to process athlete personal data, must carry out such a balancing test.

Richard Dutton, who represents Project Red Card, has sought to point out that performance data can 'make or break careers…details of passing accuracy, their fitness, their speed, all of those things which you can see…on countless websites – that is how players are assessed now'. The implication is that processing an athlete's performance data can be fundamental to how the athlete is perceived, their career trajectory and their potential earnings and, therefore, such rights override the legitimate commercial interests of a third party in this context.  

Consent: should controllers determine that that legitimate interests is not an appropriate justification; they may seek to rely on the consent of the athletes in question. The GDPR, sets a high bar to clear and consent must be 'freely given, specific, informed and unambiguous' and can be withdrawn at any time.

It is notable that the EDPB (the independent European body whose purpose is to ensure consistent application of the GDPR and to promote cooperation among the EU’s data protection authorities) in its Guidelines published 29 January 2020, has suggested that the imbalance of negotiating power between an employer and an employee means that it is difficult to ensure and demonstrate that such consent is 'freely given'. The Guidelines go on to use, explicitly, the example of team sports where clubs may exert pressure on teams of athletes to provide consent to the monitoring of their data or risk letting their team and teammates down. It is therefore likely to be difficult for third parties (or even teams) to obtain and maintain this level of consent from participants in order to justify the processing and analytics associated with the data.

Biometric Data: under the GDPR, medical, genetic and biometric data are considered to be 'special category data'. This is important as, under the GDPR, additional safeguards are in place for the processing of this data. This means, in particular, that controllers are unable to rely on 'legitimate interests' in order to process such data and are likely to have to rely on the explicit consent (which is a higher standard than ordinary consent) of athletes, creating the same challenges as have been identified above when attempting to perform analytics on such data.

Right to erasure: the GDPR gives data subjects right to request that personal data being held by a controller is deleted in two relevant circumstances:

(i) where the data subject objects to the processing; or

(ii) where processing relies on the consent of the data subject, where the data subject withdraws that consent.

In the case of (i), as soon as the data subject objects, the controller must cease processing the personal data until it demonstrates, using the balancing test discussed above, that it has compelling legitimate grounds for processing which override the interests, rights and freedoms of the data subject.

Athletes may, therefore, see this right to delete as a means to enforce the value of their data. Gaps in any dataset as a result of a deletion will have an effect on its reliability and value - particularly in the context of sports data. Incomplete datasets would make it challenging, for example, to set accurate betting odds, evaluate comparative athlete performance or develop realistic video games. As such, there is a real risk to the companies collecting and selling this data that the value of the datasets they produce could be diminished.

Right to access: the GDPR provides data subjects qualified rights to access their personal data that a controller retains. This could be significant to athletes in contract negotiations. Should athletes follow Kevin de Bruyne in retaining the services of data analytics companies to help them negotiate contracts, they may seek to use their right to access to request clubs to handover the datasets they have compiled on the athlete which could improve the competitive negotiating position of the players.

Conclusions

Whilst the data analytics industry has boomed over the last two decades, a movement towards athlete empowerment with respect to their own data has only just started.

It is unlikely that we will see a resolution to Project Red Card in 2021 or that athletes retaining data analytics companies for contract negotiations will become widespread immediately. That said, both serve as examples that athletes and their representatives, globally, are waking up to the value of their performance data and are looking to access their share of the profits.

This trend is not limited to the EU and UK, or indeed to football. Looking globally, both the National Football League and Women's National Basketball Association, in the USA, have recently acknowledged the value of performance data to athletes in their latest collective bargaining agreements and the NFL has even gone as far as stating that 'each individual player owns his personal data collected by sensors'.

Ownership and monetisation of athlete performance data is likely to become an increasing focus of value and a therefore point of contention and negotiation between competing stakeholders for an increasingly important asset class in the context of organised sport.