Given a pattern x of length m and a text y of length n, both over an ordered alphabet, the order-preserving pattern matching problem consists in finding all substrings of the text with the same relative order as the pattern. The OPPM, which might be viewed as an approximate variant of the well known exact pattern matching problem, has gained attention in recent years. This interesting problem finds applications in a lot of fields as from time series analysis, like share prices on stock markets or weather data analysis, to musical melody matching. In this paper we present two new filtering approaches which turn out to be much more effective in practice than the previously presented methods by reducing the number of false positives up to 99%. From our experimental results it turns out that our proposed solutions are up to 2 times faster than the previous solutions.