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An analysis on the question whether Riot buffs champions which get a new skin

giantZorg·5/8/2019, 9:29:38 AM·68 votes·19,090 views

Tl,dr: No if you look at winrate, but it's way more likely for them to show up in patch notes.

Introduction:

Hello all. I made a nice analysis on whether Riot buffs champions which get a new skin that I posted on reddit, but I also want to make it available here. Please use the reddit version to get all the working links to the data and code if you want to use it.

This post is inspired by u/PriagDE's post found here which tried to answer whether Riot buffs champions which will get a new skin. It is a separate post as it has a completely different method and covers a wider array of questions.

To me as a person, I'm a data scientist working in the retail business with a low number of projects at the time so I used this opportunity to train a little my webscraping skills. I post the results here as I find them interesting and hope you do too.

You can find all the data, scripts and figures here if you want to use the data for your own analysis or scrape something else from the patch notes.

Table of contents:

  • Webscraping of data from leagueofgraphs and the official patch notes
  • Overview on the number of champion changes per patch and skins released
  • Relation between the number of champion changes and skins released
  • Relationship between released skins and winrate changes
  • Final words

Webscraping of data from leagueofgraphs and the official patch notes

The first part I needed to do was gather data. To decide whether a champion got buffed when he gets a new skin, I will take the difference between the winrate 20 days before and 20 days after the patch got released. The 20 days are chosen in order to let the winrate settle a bit after patch changes.

This means I need to gather the patch notes history as well as the winrate of all champions. As mentioned by u/PriagDE, upcoming skins were only included from patch 4.8 on, so I gathered the patch notes starting from 4.8. This matches nicely the available history on the winrate on leagueofgraphs which starts at the moment approximately at the beginning of season 4. The script which I made to do so is this: lol_skins_winrate.py. Feel free to use it if you want to do something else with it. It is by no means optimized, but works also behind a proxy. You will need to get a copy of geckodriver to use Firefox as is done in the script.

I also collected the data on popularity and banrate if someone is interested. The saved data files used in the second step are these: lol_champions_bannrate.csv, lol_champions_beliebtheit.csv, lol_champions_winrate.csv and lol_patch_daten.csv containing the ban rate, popularity, win rate and patch data (which patch was released when with which champion getting changes and which new skins).

Take note that I didn't include the champion changes in 8.23(?) where they changed the runes system and changed base values for all the champions. In addition, I make no difference between skins and chromas released as Riot has an incentive to sell both to you. The skin list should be complete with the exception of some Urgot chromas (I think).

Overview on the number of champion changes per patch and skins released

The complete analysis script can be found here: lol_skins_nach_patches.R. Again, feel free to use to change it to answer your own questions if you want. It is again not optimized for speed, but for quick development (to all R users, I know there are too many for loops, but they do the job and I wanted to get it done quickly).

So the first question I wanted to get an answer is how match each champion shows up in the patch notes. This is not completely fair of course as newer released champs have less chances to appear in them, so keep this in mind. The table looks like this:

https://i.redd.it/uaoadd5m7yw21.png

We can see our favorite problem childs Azir and Ryze showing up in the patch notes a lot. Given that the total number of considered patches is 121, Azir shows up in more than a quarter of them. On the other end of the scale, with have champions like Diana, Blitzcrank or Nami which remain rather stable over the whole time.

The following two graphs show the number of champion changes over the patches as well as the number of skins/chromas released over the patches. The red line is calculated using a cubic spline smoother with the degrees of freedom determined by cross validation:

https://i.redd.it/jkyfwjea8yw21.png https://i.redd.it/7p953kdc8yw21.png

In the upper plot, we can see that Riot actually slowed down a bit starting in season 7 and does less changes per patch. In the lower plot, we see that the number of released skins/chromas remained fairly constant for quite some time. One might argue that the second half of season 8 and season 9 so far is higher, but the evidence for this is weak.

One thing not considered here is the amount of work that was necessary when champion reworks were made. The data consideres this as one skin due to the way the data is scraped, but the effort which was necessary by the skin team could have been higher, resulting in less skins published as a result. But in reworks, the also don't need to find a theme for the skins, so they can also be faster than with other skins. Just wanted to mention this as it's a possible source of error.

In addition, I had a look at the cross correlation between the number of champion changes and the skins released. This comes about that I thought I could see some anticorrelation in the two lines in the graphs above. I will explain below what that exactly means. The cross correlation graph looks like this:

https://i.redd.it/8fs0zunx9yw21.png

The lag is the difference in number of patches considered for the correlation. E.g. the positive value at lag 7 means that if a high number of champion changes is present this patch, the is a tendence for a high number of released skins/chromas 7 patches later. There is also considerable anticorrelation for a lag -5 and -6 which means that if 6 patches ago there were a lot of skins released, this patch has a tendence to have little champion changes.

I have little explanation of these values, only maybe that there a less skins on season start/mid-season/end-of-season as manpower is needed to get mid season right or worlds ready. But it's also only a tendence, the correlations are significant but not too big.

Relation between the number of champion changes and skins released

Here I had a look whether champions who get a skin released also got champion changes within the last 1 to 3 patches. I remember some comment in Meddlers quick gameplay thoughts where some Rioter wrote that working on a skin puts attention on said champion, making it more likely to get some work (even if only quality of life changes) on them done. Here are the results:

https://i.redd.it/h6vlbyykbyw21.png

We can see that considering the patch a skin/chroma gets released as well as the last 3 patches, there is a 42% chance of a champion getting changes. This is way higher that the average which is somewhere around 10% if we would assume that the champions selected for changes would happen randomly.

So this is confirmation that getting a skin/chroma comes with a strong connection to being changed in the patch notes. Remember here that correlation does not imply causation, so we cannot say whether skins/chromas have a causal link to being changed in the patch notes. But there is a strong suggestion that it might be the case.

Relationship between released skins and winrate changes

And finally, we will have a look whether a champion receiving a skin/chroma gets buffed. I will define getting buffed not by appearance in the patch notes, but by comparing the winrate of the corresponding champion 20 days before and 20 days after the patch release for any given skin/chroma. We can debate whether 20 days is a good time period, and maybe I should also consider a longer window before, but I think we can get some good results with 20 days. I excluded release skins for this analysis.

I define getting buffed this way as it also consideres everything that happens in a patch which also includes item changes or systemic jungle changes, where it can be that a champion gets a (compensation) buff on paper, but actually drops in winrate due to core items being changed for example.

I made one boxplot combining all the data available and one separating by season:

https://i.redd.it/c10wzto1eyw21.png https://i.redd.it/suh6xxsbeyw21.png

We can clearly see that there is no significant change in winrate when a champion gets a skin/chroma. I also put the data in the following table:

Minimum: -8.11 25% Quantile: -0.83 Median: 0.02 75% Quantile: 0.76 Maxim: 10.3 Mean: -0.02

We also see in the second graph that this remains fairly constant over the seasons, with season 7 actually being that champions which got new skins decrease in winrate.

Final words

Thank you for reading until here. I hope this has been an interesting read as it was interesting for me to do the analysis. If you have other interesting questions that you think could be answered with this data, write it in the comments and I try to answer them with the data. I don't have too much spare time at the moment anymore, so my answer might be a bit delayed, but I will try to get to them.

Have a good day :) [sona-playing]

Edit: So the graphs are working after all. Removed an apology for them not working.

34 Comments

Wyrin5/8/2019, 12:01:51 PM12 votes

Jesus dude... good job

DuskDaUmbreon5/8/2019, 12:22:45 PM10 votes

So...Analysis of the tl;dr:: Skins bring champions into the spotlight more by reminding people that they exist, thereby increasing the chances the balance team gives them attention. Would you say this sounds like an accurate conclusion?

Also, your post does bring up interesting things. I didn't realize that Diana got the least patch notes over that period - I'd have thought it'd have been Warwick or someone like that, not Diana.

HopeStartsWithU5/8/2019, 2:13:34 PM5 votes

Since nobody mentioned it (or I skipped it): A Rioter sometimes (a long while ago actually) ago mentioned that when a skin comes up the balance team usually takes a look on said champion. Not because they want to get those sale numbers up but because said champion falls off their radar and the new skin is just a reminder for them "hey bud, is me, ya boi."

It's not because of winrate or money, as you proved in your text, so: Insanely well done analysis man. That's what I love to see on these boards!

RipReviveFkRito5/8/2019, 10:46:05 AM4 votes

This seems like a rather insane analysis which I'm too lazy to read. Would be nice to get a TL;DR

HateDaddy5/8/2019, 2:35:57 PM3 votes

Question:

If you define buff as change in winrate, don’t you have concerns there? I mean, a winrate Can totally increase as a result of other things not related to direct champion buffs. I realize analyzing that would be a nightmare, but the complaint or notion of buffs for newly released skins doesn’t imply performance improvement, it’s that riot buffs champions to increase skin sales. I just find that definition a bit concerning, because generally buffs are noted in patch notes as specific buffs to improve poor performance.

Also, as far as the strong correlation with skins and champion changes, I’d say to some extent just the novel effect makes champion changes more likely. Also, it’s likely that skins release increase play rates of champions, so it’s reasonable to think that to some extent it gives riot a larger sample size to work with. That said, there’s usually several explanations for strong correlations.

Cool stuff nevertheless

PhDs Nuts5/8/2019, 1:45:28 PM3 votes

Why use win rate if you have access to patch notes and can just see if they were buffed? When a skin is released, people that dont play the champion often are more likely to play them, making win rate a poor variable to use.

If buffs make a champion 2% stronger but a bunch of inexperienced players drop the expected win rate by 1 point, it will show no change (50% win rate to 49% is a 2% change, and a 2% buff brings it back to ~50%).

LuxannaVeritas5/8/2019, 11:34:28 PM3 votes

YAY DATA SCIENCE!

Thanks for running the analysis on this set of data! I recognized a good portion of the methods you used in R so that's really neat.

WrÆth5/8/2019, 7:45:01 PM2 votes

Hey, big ups for A.) taking the time to make the most quality content I've seen on the boards in a while and B.) not reposting something you found on the league subreddit or someone else's art you found.

T2K Baka5/8/2019, 12:48:16 PM1 votes

Great job dude. But i dont think Katarina is getting a buff anytime soon

Sir Saltarin5/8/2019, 12:10:58 PM1 votes

This is really useful but you also have to understand how to read how this stats translate into the game

What matters the most is the intensity of the buffs-nerfs because that's what actually affects the game

Hilsun5/8/2019, 4:13:24 PM1 votes

I think that this effort is wonderful, and the detail to each aspect of the study is meticulous: the only thing I would like to see included in the study is a breakdown of this correlation specifically with buffs and nerfs, whereas your study focuses on any changes at all. Still, fantastic work!

zammea5/8/2019, 6:37:03 PM1 votes

There should be a relation b/n people playing the champ and the likelihood of skin being produced. Then how much of this people are willing to spend money for second skin. And is the relationship b/n enforced meta and line of skins being in work. Good job on the data analysis however for me personally you missed the essential questions " why this skin and is it cash grab or not". Yes the correlation b/n win rate and skin is low and that is to be expected. After all they want you to buy the skin and come for more WILLINGLY. If you force a person to do something against himself he will hate you for it.

Sorry mate.

Eleshakai5/8/2019, 9:40:10 PM1 votes

Wait... don't the patch notes include the names of the skins coming out that patch? In which case, isn't it pointless to scan patch notes for the champ's name? Or did I miss a provision in your analysis accounting for that?

ModThe Djinn5/10/2019, 12:52:48 PM1 votes

This is fantastic data.

So this is confirmation that getting a skin/chroma comes with a strong connection to being changed in the patch notes. Remember here that correlation does not imply causation, so we cannot say whether skins/chromas have a causal link to being changed in the patch notes. But there is a strong suggestion that it might be the case.

I think it's reasonable to suggest that a champion tends to see adjustments in the patches immediately before or after a skin release. Internal champion testing would reasonably focus on that champion to test the skin, meaning that champion's gameplay is likely front-and-center in a way it's normally not. The same may be seen after a popular skin release, where the increased community attention to that champion raises concerns about a champion's balance.

iiGazeii5/9/2019, 5:37:16 AM1 votes

I think a possible issue with using winrate to judge a champions strength is that releasing a skin invites players who are already good with a champion to play more often. The people who are more likely to buy a skin are the people who play a champion a lot, so by getting them to come in and play on that patch, a champion's winrate might be inflated.

However, you can't just use them getting buffed or nerfed as a good judge either, since many things affect how well a champion does. Item buffs, rune changes, counterpicks getting nerfed, etc., all have an effect on how well a champion performs. To make a truly accurate model of a champions strength in relation to its skins, all these interactions would need to be taken into account.

Clone Is Friend5/10/2019, 11:11:39 AM1 votes

shaco got an announcement for a skin and suddenly riot is starting to fix bugs and give some quality of life to shaco... after the assassin rework 3 years ago. took them 3 years to fix many bugs and get some quality of life and the second that shaco is getting a skin they are like "Lets buff shaco so the players actually dont be mad about the bugs and maybe buy the skin"

Predatorator5/8/2019, 12:51:17 PM1 votes

wonderful job! love the effort

OtakuBurrito5/10/2019, 12:01:24 PM1 votes

Someone hire this man as a data analysis at Riot.

The23rdGamer5/8/2019, 12:56:48 PM1 votes

Really interesting stuff, thank you!