NGO and charity committed to reducing injury in sport

Multi-Sport Injury Data Collection Programme

Unique data collection programme and platform, fuelling research and enabling long-term, holistic oversight

  • The Podium data collection platform consists of 4 key areas: 


    One of Podium’s ambitions is to build the single most comprehensive repository of high-quality, sensitive, reliable youth sports injury information and for it to become the go-to resource for all sports injury-related stakeholders. The Podium Digital Platform allows us to collect data about sports injuries from a variety of sources to build a rich picture of each injury, through the use of intuitive apps for teachers, coaches, parents and players, the integration with other platforms such as wearables and other devices, and the use of machine learning in the collection of video and audio footage from injuries. 

    The Podium apps are built using the leading-edge, low-code application development environment, Outsystems, which allows Podium to build highly engaging, secure mobile apps in a rapid, iterative manner, meaning that we can be highly responsive and adapt to the needs of the teacher, the coach, the parent and the pupil. This environment also allows us to co-design mobile apps and experiences with our intended audiences. We will be working with young people in schools and colleges to help them help us design apps that they wish to engage with, in hackathons and as part of their curriculum in design and information technology. 

  • Manage

    High-quality data is a crucial element in Podium’s mission to reduce the incidence and impact of sports injury in young people. Our research is predicated on the quality of our data. This is achieved through collection methods but also through excellent data management which entails matching and cleansing the data using a number of tools and technologies to ensure it is of the highest quality. 

    Podium is implementing technologies that continuously monitor the quality of the data and self-correct it, and we are able to stratify the data with different levels of confidence and quality. For example, some data is collected by medically-qualified physios and doctors who can provide a diagnosis, whereas other data is collected by parents, teachers, and volunteers. This latter data is still useful but only for certain kinds of analysis. Once matched, data is anonymised for use downstream in reports, dashboards and analytics available to schools, clubs, National Governing Bodies and Government Agencies. It is also prepared for academia so that high-quality research can be undertaken on high-quality data.   

  • Harness

    Harnessing the data is where the magic happens. Podium will leverage advanced data analytics, artificial intelligence and machine learning to create meaningful insight into our data through the use of analytics, dashboards, reports, and visualisations. Delivering actionable insight to our many different audiences in ways that are useful to them in the context and situation in which they find themselves is Podium’s challenge. For example, apps for data visualisation and analysis for teachers to use in the classroom and tools and bite sized learning for use at the pitch side. 

  • Store and secure

    All of the data that we collect lands in the Podium Data Lake which is at the core of the Podium Digital Platform. Here it is securely stored, matched, cleansed, and anonymised before being made available for use in reports, dashboards and analytics for our various stakeholders. 

    The whole platform is protected by our ISO27001 compliant Security Operations Centre who monitor access and behaviour of our networks, systems and data 24x7, blocking unauthorised access and scanning for abnormal and unexpected activity and usage patterns. In addition to these security controls, we employ ontological rules to ensure that the data can only be used for the purposes for which it was collected, and we further protect the anonymity of our data subjects by implementing ontologies that prevent deanonymisation.