6 143 GENERAL DISCUSSION GENERAL CONCLUSION This thesis showed that personalised data, machine learning, advanced statistics, and a causal roadmap in combination with a causal model could help to reduce the data analytics gap between physical activity and physical performance data and the ability to extract meaningful insights and predictions. While reducing the data analytics gap, we showed the potential of data analytics to gain meaningful insights and predictions on physical activity, physical performance, or injuries, enabling more informed interventions in physical activity. These results provide a foundation for future research to reduce the data analytics gap even more. PRACTICAL IMPLICATIONS AND OUTLOOK The practical implications of using data in coaching and training are significant. One approach could be to develop rich datasets that combine individual and contextual data, using systems that collect data frequently and consistently. To achieve this, collaborating with data experts who can help interpret this data would be helpful. Another approach could be to put together a multidisciplinary team of data experts who work together with coaches and trainers. By fostering a structural collaboration between science and practice, teams can develop effective strategies and predictive monitoring systems using data to improve coaching and training outcomes. With the correct data and data analytics possibly combined with automated data processing, coaches and trainers can gain valuable insights and predictions into their athletes’ performance, training methods and recovery, enabling timely interventions leading to better overall results. Moreover, establishing a structural collaboration between science and practice can improve virtual coaching strategies and virtual coaching systems by generating data from the continuous monitoring of individuals in their daily lives. The process of continuous monitoring could make it possible to generate personalised valuable insights, predictions and recommendations. As a result, individuals can make real-time adjustments based on these insights to optimize their performance and overall well-being.
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