In this post we will try to see guage the role played by height and weight play in climber performance. Climber performance, for our purposes, will be represented by the maximum grade that a climber has climbed. The data for this analysis is sourced from a kaggle repository that scraped data from 8a.nu. After some data cleaning we have around 14500 datapoints. We dont consider routes and boulders separately here. Let’s look at how features in our data are distributed:

Data Distribution

feature-dist

age_at_start describes at what age did the user start climbing. xp defines the age at which he or she achieved the max grade defined in max_grade.

Correlations

correlation

It is interesting to note that while height and maximum grade dont seem to be correlated there is a statistically significant negative correlation (p « 0.5) between bmi and performance of a climber. This makes sense as its not the height alone that has an effect on climber performance but a combination of weight and height. As expected, climber experience is positively correlated with the maximum grade achieved.

The following visualisation depicts the gradual shift to lower bmis with higher grades

bmi-grage


The following graph shows that though the years of experience contribute to a higher maximum grade, the downward trend of bmi with performance persists across all experience ranges. grade-bmi




In conclusion we verify from the data that its not just height, but height along with weight (bmi) that plays a role in determining a climber’s performance.