Running is a popular form of exercise, recreation, and sport across all age groups. Done properly, it contributes to improved physical fitness, coordination, emotional development, and personal achievement. However, running under adverse conditions or without proper equipment can result in injuries and physical strain.
This dataset consists of detailed training logs from a Dutch high-level running team over a period of seven years (2012β2019). It includes data from middle- and long-distance runners competing in events from 800 meters to the marathon. These groups were chosen for their shared endurance-based training characteristics.
This study complies with the Declaration of Helsinki and was approved by the ethics committee of the institution affiliated with the second author.
If you use this dataset, please cite the following work:
S. Lovdal, Ruud J. R. Den Hartigh, G. Azzopardi, βInjury Prediction in Competitive Runners with Machine Learningβ, International Journal of Sports Physiology and Performance, 2020 (in press).
@misc{lovdal2021injury, author = {Lovdal, Sofie and den Hartigh, Ruud and Azzopardi, George}, title = {Replication Data for: Injury Prediction In Competitive Runners With Machine Learning}, publisher = {DataverseNL}, year = {2021}, version = {V1}, doi = {10.34894/UWU9PV}, url = {https://doi.org/10.34894/UWU9PV} }
π¦ Source of Dataset: https://doi.org/10.34894/UWU9PV
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