40k Stoat Center: What’s in a Name?

This article is satire – please do not make any major decisions based on this article’s conclusions

Greetings fellow Warhammer 40k players!

Here at 40k Stoat Center we realize that all the good statistical variables are currently being analyzed by groups with much cooler names then us. Short of a radical redistribution of databases, we are forced to scrape by with the pickings of “useless” stats that the larger groups ignore. While it would be easy to decry these stats as “spurious”, “completely unrelated to player performance”, or simply “bad”, our goal by the end of this article is to convince you they exist.

Perhaps the most criminally under-utilized area of study is that based around a player’s first name. You might ask: “what does this have to do with performance?” And I would reply: Good question.

For this analysis I scraped through the ITC database for the first names of registered players and analyzed the results for the nascent 2021 season, alongside the 2019 and 2018 seasons (we did not include the 2020 season due to COVID virus and totally not because we couldn’t find it on the website). Below is an aggregate review of the top performing first names since 2018 (minimum of 15 appearance)

Interesting stuff, looks like the ITC is secretly being dominated by a Cabal of Johans. At the same time, it also appears the best first names have yet to fight. Let’s try and focus on the top 5 with at least 100 appearances:

One of the first things to note is the scoring change the ITC implemented after the 2018 season. Beyond that, you might also pickup that the (for the most part) as a first name shows up more it has a lower overall score, likely demonstrating the Law of Small Numbers (the smaller a population size is the more likely it is to be affected by dramatic swings in individual outcomes). But I believe that is pure speculation

One area I was particularly interested in was understanding the relationship between the number of characters in an individual’s first name and their overall performance. To that end I plotted out the following chart:

Thus, we can see there is a clear relationship. Others may say this is another example of the law of small numbers, or that the R2 value shows the model only accounts for 18% of the variance in scores, or that a p value for this chart is 0.67 meaning it’s statistically useless in almost every regard. To this I say: So what? Follow your heart! Even if it only offers a small chance of success you have nothing to lose by including as many characters as possible in the first name whenever you register for an ITC event.

Based on the above evidence we can clearly infer that GW needs to nerf Tau

Thank you for coming to my TED talk.

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