How to Tatort - tv show aired in 2020. Article "How to Tatort" in German Wikipedia has 22.1 points for quality (as of August 1, 2024). The article contains 6 references and 6 sections.
Since the creation of article "How to Tatort", its content was written by 13 registered users of German Wikipedia and edited by 13 registered Wikipedia users in all languages.
The article is cited 13 times in German Wikipedia and cited 13 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: #12463 05.2021 |
Global: #223410 05.2021 |
| Best Rank | German: #8649 12.2020 |
Global: #220801 12.2020 |
On 12 March 2025 in multilingual Wikipedia, Internet users most often read articles on the following topics: Elon Musk, 2024–25 UEFA Champions League, UEFA Champions League, Diego Simeone, Kim Sae-ron, Kim Soo-hyun, Greenland, Giuliano Simeone, Donald Trump, ChatGPT.
In German Wikipedia the most popular articles on that day were: Martin Pfister, Herstatt-Bank, Dorothee Bär, Goldjungs, Andreas Türck, Elon Musk, Peggy Parnass, Liste der größten Auslegerbrücken, Drachenläufer, Joschka Fischer.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(14.88+8.7+0+28.57+58.38)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
