Methodology for driving score(behavior)
Since you do not have labelled data, you'll have to use a lot of domain knowledge. Also, predicting a class (poor, bad, normal, good, perfect) might be easier than predicting a score (0-100). The approach you could use is:

Apply clustering on your dataset.
Try to find the optimal number of clusters for your dataset using the Elbow Method. Suppose you get 3 optimal clusters.
Now comes the part for applying domain knowledge. Try to analyse the clusters by picking up individual examples from the cluster and using domain knowledge identify which category (here, good, bad, average) you can classify them into.
After analysing some examples from the clusters, you can assign the label you get to the entire clusters as the examples within a cluster are similar.

The above method makes some assumptions but can be an interesting experiment for your dataset.