The aim of this study is to describe a tracking methodology for a Trail Running (TR) athlete during five years through the capture of data from digital devices, associating the race pace and speed with the terrain slope. The trajectories generated by the global positioning system (GPS) were obtained from the Strava platform. From this information, measurements of horizontal distance, elevation gain, slope, horizontal speed, and vertical speed are made. In order to analyze the entire data spectrum the Tobler model was calibrated using a quantile regression. For each training week data from 8 previous weeks was used, and model parameters were extracted for each decile, P0: minimum rhythm; m1: critical angle, C + (relative cost of running uphill) and C-(relative cost of running downhill). We conclude that capturing daily data through digital devices is a useful way to obtain information on the association between race pace and slope. A quantile regression model could be useful for the design of training programs for a TR athlete.