# THE META REPORT NAME IS TOO LONG, TOO DAMN LONG (n°27)

Patch 2.17 - Week 1 - Patch next week. So that Sion won’t dominate anymore… So that Sion won’t dominate anymore, right?

Valentino (Legna) Vazzoler
10-13-2021

# Data

Number of (Ranked) matches analyzed 56800 or 113600 games.

Last Update: 2021-10-14 18:00

Note : following my recent analysis the following decks:

• Akshan / Sivir (IO/SH)

• Sivir / Zed

• Akshan / Sivir / Zed

Have been aggregated into a single archetype: “ASZ - Sivir Ionia”

In addition a quick fix to account for the Rubin-baits (burn decks that pretend to be other archetypes) decks have been applied and they are called:

• RubinBait - Draven / Ezreal

• RubinBait - Draven / Sion

• RubinBait - Caitlyn / Draven - not make from Rubin but same logic

Patch 2.17 - Week 1 - by the Numbers
Characteristic All Games Ranked
N = 143,1041 N = 56,8002
Status
Other 81,756 (57%)
Ranked 56,799 (40%)
Friendly 4,549 (3.2%)
Server
americas 63,412 (44%) 24,075 (42%)
asia 24,783 (17%) 10,746 (19%)
europe 54,909 (38%) 21,979 (39%)

1 Metadata from Friendly Matches (that aren't Bo3) is not recoverable, the value may not be perfect since I lack the starting time of the game. The amount of Games to still scrap is also an estimation based on the 'position' of the game

2 n (%)

# Regions

## Play Rate

### Plot

The Gini Index is a measure of heterogeneity so, in this case and in simpler terms, how much the play rates are similar. The Index goes (when normalized like here) $$in$$ [0,1] and it’s equal to 1 when there’s a single value with 100% play rate or 0 when all play rates are equal. Of course a Gini Index of 1 needs to be avoided but it’s not like the aim should be 0. As said, it’s just to add some additional tools.

### Table

Region Play Rate
Relative Frequencies by Inclusion Rate of a Region
Region Freq Shard
America Asia Europe
BandleCity 20.94% 20.74% 23.25% 20.03%
Noxus 14.93% 15.35% 13.92% 14.96%
Piltover 13.35% 13.60% 13.36% 13.08%
Bilgewater 9.94% 10.48% 9.72% 9.44%
Shurima 7.41% 7.58% 5.64% 8.08%
MtTargon 6.86% 6.86% 6.54% 7.02%
Demacia 6.71% 6.22% 6.93% 7.14%
Ionia 5.61% 5.91% 5.62% 5.27%
Freljord 5.56% 5.10% 5.57% 6.06%
Patch 2.17 - Week 1 Ranked games from 2021-10-06 21:00:00 UTC to 2021-10-13 21:00:00 UTC. Metadata of games collected with RiotGames API

## Play Rate by number of Cards

Note: currently all dual region cards have only their main region as possible value assigned. The same problem also apply to the card’s inclusion rates, with Lulu being the most notable case affected by this.

### Table

Region Play Rate
Relative Frequencies by number of times a Card within a Region is included in a Deck
Region Freq Shard
America Asia Europe
BandleCity 25.39% 25.24% 27.96% 24.30%
PnZ 12.66% 12.79% 12.91% 12.39%
Noxus 11.80% 11.96% 11.22% 11.90%
Bilgewater 10.97% 11.26% 10.94% 10.66%
Shurima 8.18% 8.45% 6.14% 8.89%
MtTargon 7.23% 7.23% 6.83% 7.42%
Demacia 6.02% 5.60% 6.15% 6.41%
Ionia 5.74% 5.99% 5.50% 5.59%
Freljord 4.07% 3.76% 4.38% 4.27%
Patch 2.17 - Week 1 Ranked games from 2021-10-06 21:00:00 UTC to 2021-10-13 21:00:00 UTC. Metadata of games collected with RiotGames API

# Champions Combinations

## Day by Day

Highlisting the top10 most played decks (at the moment of the last game played).

## Win Rates

Tie games are excluded

### Meta Decks

Win rates of the most played combination of champions. Play Rate >= 1% in at least one of the servers.

### Underdog

Top Win rates of the top10 best performing least played combination of champions. Play rate $$\in$$ [0.1%,1%)1

# Match Ups

Note : Regarding MU, this is not the most accurate estimation you can get from my data. If you want a better picture of the current meta it would be better to look at the dedicated MU-page where I use all “Ranked” games with the current sets of buffs and nerfs. While one may object I don’t account for optimizations and differences in skills acquired during the weeks, the overall number of games / sample size makes them a better source of information. So, in case, pls refer to the MU - page for a better “meta-investigation”.

## Match-up Grid

The win rates on the grid are among the 15 most played champion combination.

 MatchUps Draven/Sion (NX/PZ) Poppy/Ziggs (BC/NX) Senna/Veigar (BC/SI) Nami/Zoe Fizz/Poppy (BC/NX) Gangplank/Sejuani Akshan/Sivir (DE/SH) Pyke/Rek'Sai Gangplank/Twisted Fate (BC/BW) Lee Sin/Zoe Ezreal/Vi (BC/PZ) Lulu/Poppy (BC/DE) Caitlyn/Teemo (BC/PZ) Poppy/Zed (DE/IO) Elise/Vi Draven/Sion (NX/PZ) 66% 49% 37% 54% 51% 72% 70% 52% 30% 47% 64% 55% 55% 78% Poppy/Ziggs (BC/NX) 34% 49% 59% 50% 63% 58% 55% 49% 42% 65% 52% 66% 52% 33% Senna/Veigar (BC/SI) 51% 51% 55% 27% 46% 42% 49% 57% 68% 45% 31% 54% 34% 46% Nami/Zoe 63% 41% 45% 57% 49% 44% 40% 66% 59% 45% 40% 68% 35% 27% Fizz/Poppy (BC/NX) 46% 50% 73% 43% 54% 43% 50% 23% 73% 58% 41% 54% 41% 41% Gangplank/Sejuani 49% 37% 54% 51% 46% 61% 60% 47% 45% 67% 49% 65% 43% 37% Akshan/Sivir (DE/SH) 28% 42% 58% 56% 57% 39% 47% 44% 58% 57% 42% 56% 53% 67% Pyke/Rek'Sai 30% 45% 51% 60% 50% 40% 53% 43% 59% 58% 44% 58% 39% 60% Gangplank/Twisted Fate (BC/BW) 48% 51% 43% 34% 77% 53% 56% 57% 40% 61% 47% 75% 42% 20% Lee Sin/Zoe 70% 58% 32% 41% 27% 55% 42% 41% 60% 44% 44% 54% 55% 50% Ezreal/Vi (BC/PZ) 53% 35% 55% 55% 42% 33% 43% 42% 39% 56% 40% 65% 63% 48% Lulu/Poppy (BC/DE) 36% 48% 69% 60% 59% 51% 58% 56% 53% 56% 60% 64% 61% 48% Caitlyn/Teemo (BC/PZ) 45% 34% 46% 32% 46% 35% 44% 42% 25% 46% 35% 36% 34% 40% Poppy/Zed (DE/IO) 45% 48% 66% 65% 59% 57% 47% 61% 58% 45% 37% 39% 66% 13% Elise/Vi 22% 67% 54% 73% 59% 63% 33% 40% 80% 50% 52% 52% 60% 87%

# Decks of the week

Another week another way to abuse Bandle

## Deckcodes

- Play rate: How often a card is included in this class of decks / the table is order by this column.
- 3/2/1 is the relative and absolute frequency of the number of copies in the decks that plays them
- Frequencies from 50% to 100% are colored from shades of green to white to identify more easily the highest values

# LoR-Meta Index (LMI)

• Tier0 with LMI >= 97.5

• Tier1 with LMI $$\in$$ [85,97.5)

• Tier2 with LMI $$\in$$ [60,85)

• Tier3 or lower with LMI < 60

Note: Hovering over a circle will display a deck values.

The LMI 2 3 is an Index I developed to measure the performance of decks in the metagame. For those who are familiar with basic statistical concept I wrote a document to explain the theory behind it: , it’s very similar to vicioussyndicate (vS) Meta Score from their data reaper report. The score of each deck is not just their “strength”, it takes in consideration both play rates and win rates that’s why I prefer to say it measure the “performance”. The values range from 0 to 100 and the higher the value, the higher is the performance.

Top3 Players (or more in case of ties) from each server that had the highest amount of consecutive wins with the same archetype. The provided deckcode is the one played in the last win found.

# Cards Presence

## Play Rate

It seems that not even Twin Disciple can beat Sharsight

## Forgotten Cards

Cards that couldn’t find place even in a meme deck.

 Region BC BW DE IO NX PZ SH SI 1 Heroic Charge Plunder Poro Kadregrin the Infernal Nimble Poro Savage Reckoner Hextech Transmogulator Ricochet Sinister Poro 2 Keeper’s Verdict Wise Fry Sown Seeds Affectionate Poro Eminent Benefactor 3 Shadow Flare Wrathful Rider Unstable Voltician 4 The Empyrean

# Legal bla bla

This content was created under Riot Games ‘Legal Jibber Jabber’ policy using assets owned by Riot Games. Riot Games does not endorse or sponsor this project.

1. Min number of games 50, during the times a meta/ladder just changed.↩︎