In this post, we will take a look at rock climbing ascents recorded in the 8a.nu data (or to be more precise their grades). This post is about approximately 2.7 m ascents, often multiple ascents by one climber (we will look in a future post at the maximum climbing performance of climbers).
The following graph shows the French grade distribution of all ascents:
What is immediate obvious is that the distribution is not symmetric. First, there are few ascents below the French grade of 6a. We second find a remarkable uniform number of records between 6c and 6c+. The most number of entries is for 7a (or 5.11d) routes. Most 8a.nu user climber probably rather well and are reluctant to enter ascents below 7a in the database.
Here the same plot truncated below 7a and with percentages of ascents (7a and higher).
Interestingly, there are more French 8a routes recorded than 7c+, and a noticeable drop from 8a to 8a+. A possible explanation is that the French 8a grade could constitute a reference. Climbers might put more effort and try more 8a routes than either 7c+ or 8a+ (and perhaps are first ascenders more willing to grade a route 8a). This would also explain the large share of 7a routes compared to 7a+ (and perhaps 6c+). But perhaps there are other explanations I am not aware of? It is also worth mentioning that there is no spike at 9a, perhaps because of greater scrutiny?
Data science, statistics and visualization of rock climbing and bouldering related aspects. E.g. what is the role of height and weight in climbing? How much harder is onsighting vs redpointing? Is machine learning relevant for rock climbing?
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