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A finite mixture latent trajectory model for modeling ultrarunners' behavior in a 24-hour race

Authors: 

Francesco Bartolucci, Brendan Murphy

Publication Type: 
Refereed Original Article
Abstract: 
A mixed latent trajectory model is developed to study the performance and strategy of runners in a 24-hour long ultra running race. The model facilitates clustering of runners based on their speed and propensity to rest and thus reveals the strate- gies used in the race. Inference for the mixed latent trajectory model is achieved using an expectation-maximization algorithm. Fitting the model to data from the 2013 World Championships reveals three clearly separated clusters of runners who exhibit di erent strategies throughout the race. The strategies show that runners can be grouped in terms of their average moving speed and their propensity to rest during the race. The e ect of age and gender on the probability of belonging to each cluster is also investigated.
Digital Object Identifer (DOI): 
10.1515/jqas-2014-006
Publication Status: 
Published
Publication Date: 
01/07/2015
Journal: 
Journal of Quantitative Analysis in Sports
Institution: 
National University of Ireland, Dublin (UCD)
Open access repository: 
Yes
Publication document: