R-trees do not historically guarantee good worst-case performance, but generally perform well with real-world data.

Is the specification typical or worst-case performance?

Average performance and worst-case performance are the most used in algorithm analysis.

Many problems with bad worst-case performance have good average-case performance.

It is particularly useful because it guarantees worst-case performance rather than making assumptions about the state of the program.

Using such a tree, the algorithm has an O(n log(n)) worst-case performance, thus being degree-optimal.

Pivot selection along the lines of the worst-case linear time selection algorithm could be used to get better worst-case performance.

In sorting n objects, merge sort has an average and worst-case performance of O(n log n).

In a clocked CPU, the clock can go no faster than the worst-case performance of the slowest stage.

Variations of the algorithm improve worst-case performance by using better-performing sorts such as quicksort or recursive flashsort on classes that exceed a certain size limit.