The general market of data
The market for data analysis in sport is expected to reach $4 billion (€3.6 billion) by 2022 (source: Forbes). This growth can be attributed to the many uses that data has in the sports industry.
Here is how data analysis is becoming an increasingly significant part of the sporting world:
Help teams win
Today, the use of analysis software has developed. All sports teams (baseball being the forerunner, see the film Moneyball, , basketball, football and many others) now have a team of analysts to study statistics (attempted strikes, on-target strikes, kilometres travelled, opportunities created…to name a few) and help players progress and optimise their performances.
Monitor fan engagement
Sports organisations (clubs, federations, brands, etc.) can detect digital engagement models from their consumers, such as viewing matches online. This allows them to understand what fans are watching and when, via the analysis of connections to online platforms. Through this, they can create more immersive experiences that are adapted to their target audience, notably using augmented reality.
Reactions on social networks (e.g. likes and comments) also help to understand the feelings of fans and can be used to increase fan engagement. This data can extend to the stadium, where teams can use electronic tickets to understand fan movements.
Benefits for the entire organisational ecosystem
This data even helps teams sell more beer and reduce traffic jams in stadium car parks. All this creates an opportunity: to map the wider behaviour of a fan outside the stadium. By working with other stakeholders - telecom companies, online payment providers or retailers, sports teams can gain a broader understanding of the behaviour of supporters before they arrive at the stadium and after they leave. This can be used to target them with key messages, special offers, and so on, but also to provide valuable data on crowd control to municipalities.
Improve back-office intelligence
Analysis of all these areas can help a company to make operational improvements in areas such as purchasing, supply chain management, etc.
Using advanced analytic technology, companies can improve human resources practices, customer relationships and so on. Teams and associations can make key decisions about their core products and services to improve the customer experience and thus optimise their income.
Sport is increasingly built around partnerships, from sponsoring to trading players. In the past, teams didn’t have such in-depth information, forcing them to give way to huge margins. Equipped with data from extensive analyses on various things (fan engagement, brand image, response rate on social networks...), teams can now optimise negotiations and save millions of euros.
General presentation of the profession
A Data Analyst is responsible for the analysis of data resulting from the activity of the company. They collect and process it to make relevant recommendations. Their work aims to bring the data to life by interpreting it.
They use the information collected by different channels to facilitate the decision-making of managers.
Their role responds to the challenge of valuing the masses of data collected by companies. Their interpersonal skills allow them to interact with jobs as well as simplify technical issues. Thus, they are able to contribute a coherent vision of the company's activities. In view of the considerable increase in the amount of data collected, a Data Analyst is likely to see their position evolve in the coming years. Too much collected data means waiting for analysis and therefore it is not used. The Data Analyst's mission is to resolve this situation, which faces ever more important and varied data. Their role is to find new ways to process data with the support of new tools. Placed under the authority of a Chief Data Officer.
> Collect, process and study statistical data to produce business analyses and recommendations,
> Build and develop reports from Business Intelligence (BI) & Web Analytics to allow teams to have a coherent vision on the results of activity of the products and their good technical functioning,
> Manage analysis tools allowing internal decision-makers or customers to follow the development of their sites or products,
> Ensure the correct interpretation and dissemination of analysis reports resulting from BI & Web Analytics.
The keys to success in this job
. Knowing the overall operation of the company;
. Having knowledge of mathematics: basic statistics, modelling, data analysis (Applied Math);
. Having good general knowledge of sports, the international sphere and media.
. Having a good analytical mind;
. Demonstrating great intellectual integrity and perspective on the methods used to ensure that they fit the context of the data being processed;
. Having good organisational skills to structure your working methods and intervention plan;
. Being a good listener in order to accurately collect information and register the needs of internal and external customers in order to better satisfy them;
. Having excellent communication skills to explain and convince;
. Being curious enough to follow new trends and discover new tools;
. Being a creative force with the various company stakeholders;
. Knowing how to ask for help wisely;
. Knowing how to be content with satisfactory individual work (to make the most of the allocated resources, without seeking perfection);
. Having the ability to adapt (remain responsive to change);
. Being able to work in an unfamiliar area (out of sync with your area of expertise, but still maintaining a link); ...
To carry out their work, a Data Analyst must have particular skills, especially in computer engineering. They will be required to use tools specific to Big Data, including data processing tools such as Hadoop or Spark to transform the raw data into useful information. Computer language is no secret to them. A Data Analyst also uses a variety of statistical tools and methods to help identify trends that can lead to recommendations on strategies. Marketing skills are also required to advise the company's executives in this area. Rigour is essential to properly handle the large amount of data available.
. Mastery of statistical techniques and data mining (SAS, SPSS, VBA, ACCES) or even languages (R) of SQL databases, and Web Analytics tools,
. Legal and regulatory knowledge of data management (use, time, lifespan...),
. Mastery of statistical techniques and data mining (SAS, SPSS, VBA, ACCESS) or even languages (R) of SQL databases, and Web Analytics tools,
Currently, most opportunities are in football and rugby clubs. Departments dedicated to the global notion of "performance" in clubs with growing numbers; the FFR (Fédération Française de Rugby) has a Data Analyst on its team and Manchester United is strongly developing this approach. More and more data companies are being created. There are also opportunities to work with in-demand TV channels, as well as Paris sectors such as the Française Des Jeux Lottery Company.
In a very small, small or medium-sized enterprise, the Data Analyst will have a role that can be combined with other roles, such as the Data Miner and the Data Scientist.
In an intermediate-sized or large enterprise: the Data Analyst position will be a full-fledged job that will work in an agile team with the Data Miner and/or the Data Scientist. In this configuration, they can also take on the role of the "scrum master" (Project Manager in big data). The skills associated with agile teamwork are most sought after in companies of a certain size that have a big data team.
As a Junior, a Data Analyst can expect to earn at least €35k/year. Obviously, this remuneration can vary. Nevertheless, with many important missions dependent on their work, a Data Analyst can earn up to €80k/year once an expert.
In addition, if you become a Data Scientist afterwards, you will be able to claim a more substantial remuneration (up to €180k/year).
Senior: €55K - 65K/year,
Expert: €70K - 80K/year
EVERYONE'S TALKING ABOUT IT
As a result of his professional experience, Florian, a Grande École Programme graduate from 2015, was recruited by STATS ANALYTICS FRANCE, a data processing company based in Nice. He is on a permanent contract as a Research Analyst on Ligue 1 in the editorial department.