• The Royal Spanish Athletics Federation and Telefónica Tech join forces to generate a positive boost to Spanish sport through new trends adapted to high performance.
  • Improved performance is achieved by applying IoT and Big Data solutions to athletes' training sessions through the advanced analysis of selected parameters and metrics, and their management, evaluation and interpretation through Artificial Intelligence (AI) solutions.
  • These data are extracted from wearable sensors attached to the athlete or their equipment, which can be consulted in real time to adapt workloads to these results.

Madrid, 20 October 2021. The first Olympic sport and Telefónica Tech are joining forces to launch a global project for innovation in sports performance. This project represents an evolution within the top level, a new approach based on shared values, sport innovation and technology as fundamental pillars in the creation of new advanced training methods for the preparation and performance improvement of elite athletes.

The Royal Spanish Athletics Federation and Telefónica Tech are launching a project in which a customised technological solution is being developed to improve the performance of athletes. The solution acquires data from sensors attached to the athletes' bodies in order to provide relevant technical assistance to them and their coaches during their training sessions, giving them a legal competitive advantage.

This collaboration also symbolizes the evolution and progress of sport through an intelligent and collaborative model of development. An alliance between federated sport and the technology industry that opens up new avenues for the future and contributes to positioning the "Spain Sport" brand at the forefront of global sports innovation, actively promoting the emergence of new markets and international opportunities.

Telefónica Tech transfers to the sports industry its experience with other organizations in advising on the process of transformation to Data. The key lies in applying advanced data analysis to Sports Science with the latest advances in Big Data, Artificial Intelligence and Machine Learning, with the aim of improving training and creating analytical tools that provide additional knowledge of the performance of the athlete and the team.

The various methodologies that currently exist for analyzing technique are slow to perform, costly and difficult to access, as they require specialized and individualized biomechanical studies. Athletes and their technical staff can rely on this new technology, which, thanks to IoT solutions and Big Data, democratizes access, achieving results in real time and accessible from any device.

Incorporating immersive and digitised technology in training sessions

Through wearable sensors and applications, solutions are developed for the extraction of performance indicators such as speed, ranges or angles. The hundreds of data per second that are generated are stored and processed without affecting the athlete's performance and being fully compliant. The data is processed on an analytical platform to be able to access the information, developed in a cloud environment, guaranteeing secure storage of all the information collected.

Using artificial intelligence algorithms, the raw data obtained from the athlete's sensors are processed and translated into explanatory performance factors. The platform will learn after each training session, obtaining relevant and accurate information previously agreed by the athlete and the coach, including indications or advice to improve the result. This information can be consumed from smartphones, tablets and smart watches, allowing it to be analysed in real time and in situ.

Gonzalo Martín-Villa, CEO of Telefónica IoT & Big Data Tech, says: "It is currently the case that the teams or athletes who rely on data are the ones who are achieving the best results. This fact is changing sport itself and the way in which training sessions are planned and monitored, as well as the physical condition of the athletes themselves and their possible injuries. At Telefónica Tech we apply to sport the experience acquired in advanced data analysis with other organizations, positioning ourselves in a preferential position in the redefinition of the athlete's experience".

Raúl Chapado, President of the Royal Spanish Athletics Federation, says: "A new model, for a new era, with a high potential for growth and international expansion that through proactive interaction explores new horizons and formats in elite sports performance. This alliance represents a new dimension of sports preparation for elite athletes interconnected through the use of technology and a digital environment that incorporates artificial intelligence and Big Data to improve performance".

About Telefónica Tech

Telefónica Tech is the leading company in digital transformation. The company offers a wide range of services and integrated technology solutions in Cybersecurity, Cloud, IoT, Big Data and Blockchain. For more information, please visit: https://tech.telefonica.com/

About Real Federación Española de Atletismo - The Royal Spanish Athletics Federation

The Royal Spanish Athletics Federation, constituted on 27 February 1918, is a non-profit making private association whose aim, through the integration of regional federations, athletes, coaches, judges, clubs and other interested groups involved in athletics, is to promote, develop and organize athletics in Spain, in which it is the exclusive representative of the International Athletics Federation (World Athletics) and the European Athletics Association (EAA), the development and organization of athletics in Spain, in which it is the exclusive representative of the International Athletics Federation (World Athletics) and European Athletics (European Athletics) and which, in addition to its own attributions, exercises, by delegation, public functions of an administrative nature.

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Telefónica SA published this content on 20 October 2021 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 20 October 2021 09:10:02 UTC.