The Union of European Football Associations (UEFA) is working on an online tool that should show the various football fields available in Europe. Once populated, the tool could help national associations in identifying areas with a shortage in infrastructure as well as prioritizing areas for investment.
The tool, which can be accessed here, is currently being developed with the input of the member associations. However, as some keep good data and others do not, UEFA intends to also use artificial intelligence and data from other resources to populate the database.
The European football governing body estimates that there are approximately 40,000 full-size football pitches in Europe. A UEFA spokesman says that the database is 85% accurate at present, but that they strive for an accuracy of 98% at least.
Various selection options
Searches can be narrowed for several types of the game (11-a-side, 7-a-side, 5-a-side or “other”), the various surface options (grass, artificial turf, hard surface, clay, “other”), and the sites where the fields are situated.
The database distinguishes between schools, football complexes (both large and small), single pitches, football hubs and stadiums.
Essential in developing and protecting
The need for data became evident in 2018 when the European Commission started investigating the use of polymeric infills in artificial turf. When asked how many artificial turf fields had been installed throughout Europe and how much polymeric infill migrates out of the field every year, neither the industry nor the collective national football associations managed to produce adequate data.
As a result, the EC adopted data that, in hindsight, turned out, by far, to not accurately reflect the actual situation, yet the damage had been done.
As UEFA will redistribute EUR 3.5 billion in grassroots football and the sustainability of the game until 2028 through its UEFA Hattrick programme, the tool will also be helpful in identifying football gaps and hotspots throughout Europe, particularly when data is drawn from other resources, e.g., weather stations, to determine local climate conditions or socio-economic resources to predict how the population will develop in the coming years.