Walking and cycling are increasingly promoted as sustainable and health-enhancing modes, yet rising volumes in shared urban spaces intensify interactions and perceived conflict potential. While numerous studies show that pedestrian–cyclist interactions rarely result in safety-critical incidents, behavioural adaptations, such as speed reduction and crash avoiding manoeuvres, plays a key role in mitigating risk and increasing perceived safety. As most existing research relies on data-intensive methods such as video observations or simulations, this paper explores the potential of large-scale GPS cycling data to analyse conflict potential and behavioural adaptation in areas shared spaces used by pedestrians and cyclists. Considering the pedestrian zone ‘Prague Street’ in Dresden, Germany, as a case study, we combine GPS trajectories from the 2024th CITY CYCLING campaign with a time-based proxy data for pedestrian density. The results show clear behavioural adaptation: during periods of high pedestrian activity, cyclist do not only use other routes, but cycling volumes decrease and average speeds are reduced by approximately 5–8 km/h. The findings confirm established relationships between density, speed, and conflict mitigation, while highlighting both the opportunities and limitations of GPS based approaches. The study demonstrates that such data can serve as a scalable screening tool for assessing behavioural adaptation and potential risk in shared spaces. We further propose a model considering most relevant data to comprehensively analyse risk potential in near future.