Olymp Bezner - German clothing manufacturer. Article “Olymp Bezner” in German Wikipedia has 36.3 points for quality (as of July 1, 2025). The article contains 15 references and 8 sections.
Since the creation of article “Olymp Bezner”, its content was written by 44 registered users of German Wikipedia and edited by 44 registered Wikipedia users in all languages.
The article is cited 14 times in German Wikipedia and cited 14 times in all languages.
The highest Authors Interest rank from 2001:
The highest popularity rank from 2008:
There is 1 language version for this article in the WikiRank database (of the considered 55 Wikipedia language editions).
The quality and popularity assessment was based on Wikipédia dumps from July 1, 2025 (including revision history and pageviews for previous years).
| Best Rank | German: #14357 07.2019 |
Global: #238131 07.2019 |
| Best Rank | German: #3100 04.2025 |
Global: #126886 04.2025 |
On 10 February 2026 in multilingual Wikipedia, Internet users most often read articles on the following topics: Jeffrey Epstein, Ghislaine Maxwell, Ilia Malinin, Bad Bunny, 2026 Winter Olympics, Epstein files, Jutta Leerdam, Jake Paul, Puerto Rico, Little Saint James.
In German Wikipedia the most popular articles on that day were: Jeffrey Epstein, Julia Taubitz, Philipp Raimund, Ghislaine Maxwell, Bad Bunny, Emma Aicher, Olympische Winterspiele 2026, Gil Ofarim, Lindsey Vonn, Epstein-Akten.
The WikiRank project is intended for automatic relative evaluation of the articles in the various language versions of Wikipedia. At the moment the service allows to compare over 44 million Wikipedia articles in 55 languages. Quality scores of articles are based on Wikipedia dumps from July, 2025. When calculating current popularity and AI of articles data from June 2025 was taken into account. For historical values of popularity and AI WikiRank used data from 2001 to 2025... More information
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(14.7+21.43+7.14+38.1+100)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
