<h1>About Dataset</h1>

<h2>🏃 Context</h2>

<p>

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.

</p>

<h2>🏃 Content</h2>

<p>

This dataset consists of detailed training logs from a Dutch high-level running team over a period of seven years (2012–2019). It includes data from <strong>middle- and long-distance runners</strong> competing in events from 800 meters to the marathon. These groups were chosen for their shared endurance-based training characteristics.

</p>

<ul>

  <li>Collected from: 74 athletes (27 women, 47 men)</li>

  <li>Average duration on team: 3.7 years</li>

  <li>Competition level: Mostly national, some international</li>

  <li>Head coach remained the same during the study period</li>

</ul>

<p>

This study complies with the Declaration of Helsinki and was approved by the ethics committee of the institution affiliated with the second author.

</p>

<h2>🏃 Acknowledgements</h2>

<p>

If you use this dataset, please cite the following work:

</p>

<blockquote>

S. Lovdal, Ruud J. R. Den Hartigh, G. Azzopardi, <em>“Injury Prediction in Competitive Runners with Machine Learning”</em>, International Journal of Sports Physiology and Performance, 2020 (in press).

</blockquote>

<pre>

@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}

}

</pre>

<p>

<strong>📦 Source of Dataset:</strong> <a href="https://doi.org/10.34894/UWU9PV" target="_blank">https://doi.org/10.34894/UWU9PV</a>

</p>

<hr>

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