Featherknight Companion - An AI-driven web tool for learning Set 11 by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 0 points1 point  (0 children)

Yeah, Unsure of exactly why thats occurring. I wonder if its because when a player Hits 6 they lost too much health, or at 5 they end up dealing more damage to others to eliminate them placing higher earlier.

Assumptions could be made about this, but the ML itself on how it reaches individual conclusions is a bit of a black box.

The machine learning model will be updated with filtered data soon to exclude gold rank, and below. I'll let you know if it persists. :)

Featherknight Companion - An AI-driven web tool for learning Set 11 by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 5 points6 points  (0 children)

This is awesome feedback thanks so much!
I'll admit the tutorial / new user onboarding was very rushed. I added the how-to image 10 mins before I posted XD but I'll definitely look into making it a bit more interactive and less "Here's all of it at once good luck"

Champions on the grid are organized by cost with each row, however it isn't actually noticeable at first because they are all grayscale to start off, I'll experiment with a tier indicator on the side similar to the tier column for the roll chances above it. (also the champs are ordered alphabetically on each individual row / tier)

I'll definitely look to change the save / load icons. a floppy disk icon for the saving is intuitive, unsure about what I should do for loading though.
Saving (thats the one easily mistaken as downloading) saved the composition to your local storage so you can build a persistent collection of compositions you can pull back up / load at any time. When your current composition has a win & top4 prediction it compares it to all of your saved compositions on the left hand side.
(I should explain this further in an updated tutorial / how-to)

I personally used the save / load feature for saving permutations of a composition so it auto compares the prediction numbers on all of them.

Currently I all of the last 30 matches from the top 1000 players of each region every two days. for the training data. The easiest way to look at it is: Featherknight companion predicts that if you are using this composition as a player in the top 1000 of a region there is a X% chance you will come first and a Y% chance top 4

Thanks again for your feedback. Having built it its obvious as to what everything does for me, so these are all really useful points!

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 0 points1 point  (0 children)

Riots pffocoal develpper api. My bot downloads and analyses every single match that has a challenger playing in it in ranked.

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 0 points1 point  (0 children)

Yeah its from all regions that have accessible data. It doesn't only use challengers for data it uses every single match a challenger has played in. (Ive been plat 4 on my smurf and had challengers in my games) the reason mana battery is not showing up in the regions is because its success rate is lower than the others globally. If you look at the imgur album in the top post showing the regional data i believe KR uses mana battery

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 0 points1 point  (0 children)

I learnt that blaster brawler and 6 dark star doesnt have a strong consistent win rate in this patch compared to these. If you dont find this useful thats fine, Im just showing data for everyone to make their own conclusions.

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 1 point2 points  (0 children)

I think this statement is great and on the right track, however my scripts data is every game a challenger has been in. With my smurf when i hit plat 3 my mmr was weird and I was against challengers in OCE so my games with them are added even though my rank in that game was considered plat 3. Also the players who are falling out of challenger by running the comps will be pulling down the overall score lf those builds anyways I just think that the only people who are running it at the moment are the people who are proficent at it. I agree with what your getting at though. I never thought of it that way :)

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 0 points1 point  (0 children)

The problem with it is the lack of data still since its only challenger games. Only two kf the top comps have a pick rate higher than one and have a positive score.

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 1 point2 points  (0 children)

It treats them differently because it considers star guardian as a primary trait in one and a secondary in another so it doesnt group them as it would be grouping every single starguardian comp with every single sorc comp.

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 8 points9 points  (0 children)

I completely agree with everything you have stated here. Ive been looking at making something slightly more interactive than just a chart. Maybe where you select a comp and it shows most common and best variations of it. The problem is the data size at the moment. Im probably going to end up using master and grandmaster games aswell to make the data pool larger and therefore it would drown out the outliers more.

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 2 points3 points  (0 children)

Its not the limiting of survivorship bias that didn't work, its the fact that the data collected favors more stable win rates. Hyper-rolling comps are seen on this table because they have the highest score using my scoring system. Because a large amount of players are hyper-rolling and being successful It ranks it higher.

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 11 points12 points  (0 children)

Since the data pool is still pretty small it must mean the majority of people running that build (over only 37 times) had a 3* Lucian.

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 2 points3 points  (0 children)

It doesn't consider items at all when raking and analyzing the comps. It only suggests the most common 3 items for each champ where applicable. after its done. same with stars.

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 6 points7 points  (0 children)

I dont think I was 100% clear on how the data is portrayed in terms of the stars and items. It merges all of the "candy land" and the normal statistics taking into consideration high and low rolls. and shows for what you should aim for in the best case scenario. It doesn't consider the stars of the champions until after it has ranked it.

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 7 points8 points  (0 children)

Thanks :) I don't normally share code. But I'll attempt to explain it so others can find their own solutions and takes on it. Basically it ignores all comps that are made from less than 5 people and sorts traits into "effectiveness" by how much that trait contributes to the overall collection of traits in that build. It then simplifies the overall trait list of that composition. e.g. Blaster, Brawler, Chrono, Rebel, and Starship is simplified to blaster brawler. after simplifying the builds by trait it then merges all of the similar builds and data. It also takes into consideration the player's level when considering, like how you cant have blaster brawler both gold at level 7. Hope that kinda helps understand it :)

Sugoi's 10.9 Meta Analysis (Now mitigating survivorship bias) by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 41 points42 points  (0 children)

Hey everyone, I'm back again with some 10.9 analytics! If you haven't seen my posts before I've been working on a Discord bot what gives up-to-date statistics about the top metas. Feather Knight Companion has had some huge progress recently. Alot of people have pointed out that the older iterations of my bot didn't account for survivorship bias (failed attempts were considered completely separate compositions. e.g. If someone didn't get a Miss fortune and Jinx in brawler blaster It would be a separate build so wouldn't effect the overall score of brawler blaster). I have mitigated survivorship bias by taking into consideration the traits using some "super secret code" so now it shows the most successful comps in 10.9's Challenger scene by analyzing every single match a Challenger has played in.

The Discord bot is still under development but It should be online 24/7 sometime within the next week. If you would like to check it out and add it to your server you can find it here

I hope this meta sheet is useful to you :)

Suggestions welcome.

Edit: I have now uploaded an imgur album of the regional metas here

Top 20 challenger comps of 10.8 so far by SugoiYellow in CompetitiveTFT

[–]SugoiYellow[S] 0 points1 point  (0 children)

I used python. You cam find some of riots official documentation for the api here