Multiclass Classification with Decision Trees: Why do we calculate a score and apply softmax?
Depending on the parameters you used for your model, it may not be calibrated in probabilities. That is, your model output a score, that is helpfull to give a relative order between your instance, but the score may not reflect the real % chance of the output happening. 

Softmax, will at least garanty that your output are between 0 and 1 and sum to one. This will give you an output that is nearer to a probability (but that may not be enough to be calibrated to 'historical' probabilities).  

PS: I don't think there is a link with xgboost, unless you have very specific options.