Challenges in collecting athlete data. What problems do their agents face?
Sports clubs and marketing agencies process vast amounts of information about athletes daily. In theory, it sounds simple: data collection is Sports clubs and marketing agencies process vast amounts of information about athletes daily. In theory, it is simple: data collection is possible. In practice, collecting and transforming it into actionable insights is a daunting task, requiring time, resources, and the right tools. What specific problems do specialists encounter? In practice, collecting and transforming it into actionable insights is a daunting task, requiring time, resources, and the right tools. What specific problems do specialists encounter?
Sports are not just about talent and hard work but also effective information analysis. Collecting data related to athletes can support:
- effective player recruitment,
- optimal training sessions,
- continuous improvement of club strategies.
Through sports data analysis, clubs and agencies can help their athletes achieve better results and improve athlete performance, building a competitive edge in the team sports industry. Such an approach not only enhances overall outcomes but also ensures a systematic method for analyzing data. It’s the future of sports, opening doors to new opportunities for growth and the success of the entire club. However, it also brings numerous challenges that must be addressed.
Data is everywhere but hard to find
The first issue for those collecting athlete is its fragmentation. Athlete information is published on league websites, in databases, sports services, and on social media. Each source has its own format and method of tracking and presenting the data collected, making it difficult to search efficiently.
A scout, talent hunter, or recruiter might spend an entire day gathering a complete set of information about one athlete. Sometimes, it’s necessary to combine data from several sources to get a coherent picture. For sports clubs and agencies, this means not only a substantial workload but also costs associated with hiring additional personnel.
Challenges in processing data
Even when big data is accessible, transforming it into a “workable” version is often so challenging that it becomes impractical. Much of the data is presented in various formats. Before it can be used, it must undergo additional processing. Statistics for one athlete might be presented as numerical sets, while information about their transfers might be descriptive. Compiling all this into one readable database requires significant effort.
Low-quality data
Performance data quality is crucial for effective decision-making. Low-quality, incomplete, outdated, or incorrect data can lead to faulty analyses and decisions. In extreme cases, such data can become useless or even harmful.
Data is ephemeral and changes quickly
Match results, player statistics, rankings and performance indicators are regularly updated and overwritten with new data. What is available today may disappear or change tomorrow.
Clubs and agencies aiming to track players’ progress over time must not only collect data but also regularly update and archive it. Without the right tools, this becomes virtually impossible on a larger scale.
Poor data filterability
Access to data is one thing, but effectively filtering and selecting it is another. Athlete-related data often spans different periods, entire leagues, various countries, or even continents. Meanwhile, clubs and agencies need real-time or specific information narrowed down to particular groups of athletes, such as those playing in a certain club or in a specific position.
For example, a football club may need data only on its players in selected ranking lists but ends up receiving nationwide data instead. Filtering out irrelevant information and finding what matches the club’s individual needs takes hours.
Summary
Recruiting new athletes is essential for a club’s growth and performance improvement. However, sports organizations face many challenges in collecting and analyzing athlete data. The fragmentation of information, its ephemeral nature, filtering issues, and the lack of a unified platform for integration make efficient data management impractical without the right tools.
If these challenges sound familiar, learn more about our solution that helps collect and process athlete data effectively.