Following their first article on data management, which highlighted the main challenges faced by professional clubs, Six Sports Management and Alexis Barat are now looking at how to organise a performance analysis department. What is the added value of such a department? How should it be structured to maximise its impact?
WHY HAVE A PERFORMANCE ANALYSIS DEPARTMENT?
Data Analytics (the analysis of data with the aim of extracting meaningful insights) has become an essential, and even crucial, component for most sports teams over the past few years. The statistical analysis of matches, training sessions and other aspects of team life has a significant impact on results in the short, medium and long term. Indirectly, improved results enable clubs to generate more revenue (marketing, ticketing, sponsorships, etc.), which is often the key driver for professional clubs.
This is why Data Analytics can be used to identify the performance levers that lead to better results. It is part of a continuous improvement and performance optimisation process. Data Analytics can be applied to several areas within a club: the French Rugby Federation, for example, uses it in an attempt to reduce injury risk, while football clubs such as Toulouse use it to optimise recruitment, with data helping to identify players whose performances are undervalued by the market.
A very large amount of data is generated within a club on a daily basis. To make the best possible use of this data, it is necessary to create a separate department, independent from the coach and under the authority of the club’s management, with one of its key objectives being long-term sustainability. Indeed, the various analyses and recommendations produced by the department must be aligned with long-term objectives, without the departure of one of its employees disrupting the organisation.
CREATING A DEPARTMENT IS NOT ENOUGH TO MAKE IT EFFECTIVE
According to Dan Pelchen, founder of Traits Insights, the fundamental issue surrounding data is making “Analytics” accessible — meaning desired and used at every level of the organisation.
The first and most important step in adopting data analysis as a central component of performance is the willingness of decision-makers to leverage data. The decision-maker (coach, manager, sporting director, etc.) can be viewed as an internal client, or user. If they are reluctant to use it, it will be difficult to leverage the work of the performance analysis department. Raising awareness and securing the buy-in of stakeholders across the club are therefore fundamental to making the most of a data analysis department.
It is necessary to foster a data culture among the various teams responsible for performance and implement a “data-driven” strategy across the entire club. In other words, decisions should be guided by tangible facts and analyses derived from raw information (commonly referred to as raw data).
First, the department must be able to identify, combine and manage different data sources before it can build complex data analysis models. These can be descriptive (describing past events), diagnostic (helping to understand why past events occurred), predictive (helping to predict what may happen) or prescriptive (indicating possible actions to take).
Finally, beyond simply producing data, the department must be capable of transforming the organisation as a whole in order to extract value from these models and support decision-making. This “data-driven” approach should not be viewed as replacing the performance analysts already present within clubs (video analysts, strength and conditioning coaches, etc.), but rather as a means of providing additional support to the decision-making process.
HOW SHOULD A PERFORMANCE ANALYSIS DEPARTMENT BE STRUCTURED?
As with the creation of any new activity, two phases can be distinguished when structuring this type of department: a design/organisation phase and a run phase.
To build this department, it is important to draw on external expertise. Initially, technical profiles capable of implementing a global data architecture should be brought in, covering the entire process from collection to transformation and from distribution to consumption.
New data sources are constantly emerging within clubs thanks to new technologies, such as IoT (Internet of Things) data generated by GPS devices. A coherent data architecture therefore helps ensure the security, quality and lifecycle management of data originating from completely different sources.
The involvement of Data Engineers capable of building data collection and storage systems (data lakes, data warehouses, data pipelines) is therefore essential. Data Scientists can support them in developing predictive models or complex analytical models.
Secondly, the involvement of Data Analysts makes it possible to transform, interpret and distribute data so that it can be visualised and used as effectively as possible in day-to-day operations. These Data Analysts are often also involved during the run phase, producing data and insights for the coaching staff.
Depending on the club’s budget, Data Analysts may be supported by — or make way for — Sports Scientists, who carry out the day-to-day analysis (video analysts, GPS data analysts, strength and conditioning coaches, etc.). They form the direct link with the field and with the “internal clients” or “end users”, and most often hold a master’s degree in sports science.
In its day-to-day operations, the department needs a project manager or Head of Performance (often referred to as a Chief Performance Officer), an individual with a cross-functional view of the department who ensures effective communication between “user” requirements and analysts (data and sports scientists).
THE DELICATE ISSUE OF DATA MANAGEMENT
The department must establish appropriate data governance. This means a set of processes, roles, rules, standards and parameters that ensure information is used effectively and efficiently to help the department achieve its objectives, by defining procedures that guarantee data quality and security, as well as the actions to be taken. Data governance must, in particular, ensure compliance with GDPR regulations.
For example, the processing of medical data can be a particularly sensitive issue that requires careful consideration. Data access rights must be defined in advance according to the different roles within the organisation.
Furthermore, communication challenges are inherent to teamwork, regardless of the field or project. Interactions between individuals within a performance department are critical to the smooth functioning of the organisation and to meeting decision-makers’ needs as effectively as possible.
On the one hand, the Sports Scientist is responsible for understanding the decision-makers’ requirements; on the other, the Data Analyst is responsible for obtaining the appropriate data to address them. The Chief Performance Officer is responsible for communication between all these stakeholders and for ensuring the successful delivery of the various projects.
Today, and for cost reasons, some clubs are seeing the emergence of a hybrid role combining the responsibilities of a Data Analyst and a Sports Scientist. Unfortunately, there is not yet any established academic training specifically designed for such a role, and these professionals most often develop their skills over time through practical experience.
Knowledge transfer and training are also necessary to ensure the long-term sustainability of such a department. If an employee leaves the department, continuity of ongoing projects must be ensured.
This requires transparent technical and functional documentation of processes. Similarly, the various stakeholders must be given dedicated time for training, allowing team members to develop their skills internally and learn how to use new and more effective tools.
It is the responsibility of the department head — or, failing that, the General Manager — to ensure that all these elements are in place, provide team members with the necessary tools, and initiate change management when required.
Investing in a performance analysis department means investing in a team capable of addressing both current and future needs through the use of data. It also means ensuring access to descriptive, predictive and prescriptive analyses, as well as having the ability to interpret them.
With the right resources, the department can be structured to handle the organisation’s analytical requirements and generate value. Working with an external provider to support the structuring of the department is an investment that can significantly improve day-to-day performance through an effective data infrastructure.
That being said, if such a department remains a support function for decision-makers, enabling them to analyse facts and information, the key assets will always be human: the athletes.
As a result, human and psychological factors will always require the knowledge and judgement of experienced individuals, such as Scouts, who are increasingly supported by data analysis but by no means replaced by it.
By distinguishing between the design and run phases, we want to highlight that such departments can exist in clubs with “almost” any level of budget. In our next article, we will explain how to proceed in practical terms depending on the available budget, and how to finance the creation of such departments at a lower cost.