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

Sandro Radovanovic (), Boris Delibasic (), Milija Suknovic () and Dajana Matovic ()
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Sandro Radovanovic: University of Belgrade
Boris Delibasic: University of Belgrade
Milija Suknovic: University of Belgrade
Dajana Matovic: University of Belgrade

Operational Research, 2019, vol. 19, issue 4, No 7, 973-992

Abstract: Abstract Ski injury is a rare event with 2‰ 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.

Keywords: Ski injury prediction; Data visualization; Lasso logistic regression (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s12351-018-00449-x

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