Where will the next ski injury occur? A system for visual and predictive analytics of ski injuries

Abstract

Ski injury is a rare event with 2 parts per thousand rate (2 injuries per 1000 skier days expected). Additionally, injuries are dispersed over a ski resort spatially and temporally, making it harder to predict where the injury will occur. In order to inspect ski-related injuries, we have developed a visual system which allows global and spatial inspection of ski lift transportation RFID data. To enrich the visual environment, we have embedded a predictive lasso regression model which predicts injury occurrence spatially and temporally over a ski resort with an AUC performance of 0.766. We propose the model which allows decision makers to make real-time decisions on allocation of rescue service capacities at a ski resort. Predictive model improves the models existing in literature as it works for various locations at a ski resort, and makes predictions of occurring injuries on an hourly basis.