Data Preparation for Injury Prediction
I have recently wrote a technical note (actually a video) for Sport Performance and Science Reports journal regarding Data Preparation for Injury Prediction. Both data and R core are available on GitHub repository. The purpose of this technical note is to showcase one particular way of preparing (and engineering) data for injury prediction tasks, as well as start the discussion with fellow sport scientist. As always, any feedback is highly welcome.
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Wonderful article.
I will try to implement this approach with me team.
One thing: on your opinion, which will be the best solution to implement gps data if I have only 10 gps? I will use gps data only on some athlete (that are several every training) or it will be better to use average values and apply them to the whole team?Thank a lot again!
Marco
Hi Marco,
Glad you found it useful. Regarding only having 10 units – I think the BEST use might be to create a list of exercises/drills you do and have a certain ranges of values (e.g. HSD per min od drill, # Hard Acceleration per minute of drill, etc). You can rotate athletes to get a glimpse, as well note the position of the athletes (to also see if there are any differences).
Having this drill database makes you more ‘precise’ in ‘predicting’ the load. This is by far not perfect, but beteer than nothing.
As for injury prediction with only 10 units? Hmm… Having 30 unitsts, injury prediction is still pipe dream, so don’t need to worry about it. What can be done is to use the drills database to ‘estimate’ individual loads (using position and minutes played in a given drill) or as you say ‘average’ (although then you are predicting for a TEAM, not individual).
Hope this all make some sense 🙂
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