It can be worse. A O(n log n) algorithm might be slower than a O(n^2) algorithm for all practical values of n.
Also, one should be careful what to count. Sorting strings, for example, is not quite O(n log n); average string length/expected offset of first difference/whatever should also be in that O().
Along the same line, for many algorithms, cache-locality is more important than number of CPU cycles. So, counting cache misses rather tha cycles can be the better way to judge an algorithm.