Abstract
Historically, sport science and medicine researchers have had difficulty obtaining adequate sample sizes, limiting their ability to make accurate generalizations to populations of athletes. To move towards better and more generalizable research, sport could look to other fields of research, and draw upon collaborative approaches for performing science. These include concepts such as big teams approaches for conducting experimental research, developing data repositories centred on a holistic inter-disciplinary view of the athlete and exploring privacy preserving meta-analytic inspired concepts such as federated analyses or pooled synthetic data. These approaches have enormous potential but do come with their own difficulties and risks. There are challenges surrounding the collection, ownership and perception of data, particularly in high-performance sport contexts. This conceptual review is a step towards presenting possible solutions, which could be tested, documented and sculpted to fit the high-performance and professional sport environment, with the aim of improving the processes underpinning scientific enquiry in sport.