Article "Rollerski-Weltcup 2010" in German Wikipedia has 24.7 points for quality (as of August 1, 2024). The article contains 0 references and 15 sections.
Since the creation of article "Rollerski-Weltcup 2010", its content was written by 21 registered users of German Wikipedia and edited by 21 registered Wikipedia users in all languages.
The article is cited 23 times in German Wikipedia and cited 23 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 August 1, 2024 (including revision history and pageviews for previous years).
| Best Rank | German: #398689 04.2011 |
Global: #2917002 04.2011 |
| Best Rank | German: #21045 04.2011 |
Global: #303028 04.2011 |
On 25 January 2025 in multilingual Wikipedia, Internet users most often read articles on the following topics: Donald Trump, Madison Keys, Elon Musk, Aryna Sabalenka, Melania Trump, Emilia Pérez, Abdukodir Khusanov, Pete Hegseth, Nosferatu, Karla Sofía Gascón.
In German Wikipedia the most popular articles on that day were: Marcel Mann, Mordach – Tod in den Bergen, Miriam Höller, Madison Keys, Eva Lys, Aryna Sabalenka, Alice Weidel, Anna-Carina Woitschack, Handball-Weltmeisterschaft der Männer 2025, Nina Bott.
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 August, 2024. When calculating current popularity and AI of articles data from July 2024 was taken into account. For historical values of popularity and AI WikiRank used data from 2001 to 2023... More information
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(52.11+0+0+71.43+0)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
