Article "2022年の日本競馬" in Japanese Wikipedia has 76 points for quality (as of November 1, 2023). The article contains 1553 references and 53 sections. The article also contains quality flaw template, which reduce quality score.
In October 2023 the article "2022年の日本競馬" was edited by 4 authors in Japanese Wikipedia (7972nd place) and written by 4 authors in all languages.
Since the creation of article "2022年の日本競馬", its content was written by 31 registered users of Japanese Wikipedia and edited by 31 registered Wikipedia users in all languages.
The article is cited 155 times in Japanese Wikipedia and cited 155 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 November 1, 2023 (including revision history and pageviews for previous years).
| Best Rank | Japanese: #31186 12.2022 |
Global: #381749 12.2022 |
On 14 April 2024 in multilingual Wikipedia, Internet users most often read articles on the following topics: Iran, Bayer 04 Leverkusen, Israel, Fallout, Iron Dome, Xabi Alonso, Max Holloway, Fallout, YouTube, Bundesliga.
In Japanese Wikipedia the most popular articles on that day were: 菊池こころ, 藤岡康太, アンチヒーロー (テレビドラマ), 水原一平, 長谷川博己, 藤原道長, 怪獣8号, 蜻蛉日記, 松井秀喜, 花咲舞が黙ってない.
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 November, 2023. When calculating current popularity and AI of articles data from October 2023 was taken into account. For historical values of popularity and AI WikiRank used data from 2001 to 2023... More information
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(100+100+0+100+100)-4$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
