Keiji Monma - Japanese baseball coach. Article "門馬敬治" in Japanese Wikipedia has 25.2 points for quality (as of August 1, 2024). The article contains 25 references and 5 sections. The article also contains quality flaw template, which reduce quality score.
Since the creation of article "門馬敬治", its content was written by 17 registered users of Japanese Wikipedia and edited by 17 registered Wikipedia users in all languages.
The article is cited 11 times in Japanese Wikipedia and cited 11 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 | Japanese: #4167 03.2024 |
Global: #90471 08.2022 |
| Best Rank | Japanese: #11371 02.2019 |
Global: #436940 09.2022 |
On 12 November 2024 in multilingual Wikipedia, Internet users most often read articles on the following topics: Donald Trump, Marco Rubio, Elon Musk, Song Jae-lim, 2024 United States presidential election, Megan Fox, Melania Trump, Gladiator II, ChatGPT, deaths in 2024.
In Japanese Wikipedia the most popular articles on that day were: 福田和子, 玉木雄一郎, 松山刑務所事件, 松山ホステス殺害事件, 八代亜紀, 小泉深雪, 穐田誉輝, 岩城直也, 九里亜蓮, Perfume.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(9.58+9.33+0+16.13+97.55)-1.33$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
