# THE META REPORT NAME IS TOO LONG, TOO DAMN LONG (n°22)

Patch 2.14 - Week 2 - Requiem for Akshan/Sivir

Valentino (Legna) Vazzoler
09-8-2021

# Data

Number of (Ranked) matches analyzed 29117 or 58234 games.

Last Update: 2021-09-21 07:08 1

by the Numbers
Patch 2.14 second week / Master players1,2
Characteristic N = 40,3603
Status
Ranked 29,117 (72%)
Other 8,238 (20%)
Friendly 3,005 (7.4%)
Server
americas 16,331 (40%)
asia 7,771 (19%)
europe 16,258 (40%)

1 Max datetime recovered: 2021-09-08 20:59:38 UTC from 2021-09-01 21:00:00 to 2021-09-08 21:00:00 UTC

2 EU Master players in the ladder: 497 while number of possible Master players recovered is: 497

NA Master players in the ladder: 562 while number of possible Master players recovered is: 559

ASIA Master players in the ladder: 252 while number of possible Master players recovered is: 251

3 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

# 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
Noxus 19.72% 16.95% 21.82% 21.36%
BandleCity 16.45% 18.53% 18.90% 13.56%
PnZ 15.26% 15.37% 16.29% 14.74%
Bilgewater 14.10% 12.88% 9.95% 16.94%
Demacia 7.66% 8.05% 7.09% 7.55%
Shurima 7.50% 9.40% 6.40% 6.23%
MtTargon 7.34% 6.69% 6.40% 8.32%
Ionia 4.61% 4.47% 5.48% 4.38%
Freljord 3.12% 3.36% 3.18% 2.88%

## Play Rate by number of Cards

Note : currently all dual region cards have only their main region as possible value assigned. It’ll be fixed in time for the next report but currently it makes so that BandleCity playrate is overestimated. 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 20.72% 21.87% 24.34% 18.17%
PnZ 15.82% 16.22% 16.46% 15.19%
Noxus 15.65% 13.42% 16.76% 17.21%
Bilgewater 13.92% 12.59% 9.88% 16.80%
Shurima 8.76% 10.90% 7.63% 7.28%
MtTargon 8.15% 7.51% 6.76% 9.30%
Demacia 6.56% 6.87% 5.95% 6.54%
Ionia 4.93% 4.76% 5.86% 4.71%
Freljord 2.07% 2.39% 2.50% 1.59%

# 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%)2

# Match Ups

Note : While these are indeed the Match-Ups win-rates that one can extract from last week games I need to point out that 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 MU-page where I use all games with the current sets of buffs and nerfs. While it’s that there I don’t account for optimization and difference in skills acquired during the weeks the overall number of games / sample size makes them a much safer source of information. While I’ll continue to release the weekly data, 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 Akshan / Sivir (DE/SH) Caitlyn / Draven Caitlyn / Teemo (BC/PZ) Draven / Sion (NX/PZ) Fizz / Lulu / Poppy (BC/NX) Fizz / Poppy (BC/NX) Gangplank / Miss Fortune (BW/NX) Gangplank / Sejuani Lulu / Poppy (BC/DE) Lulu / Poppy (DE/IO) Nami / Zoe Poppy / Zed (DE/IO) Pyke / Rek'Sai Senna / Veigar (BC/SI) Xerath / Zilean (BC/SH) Akshan / Sivir (DE/SH) 34% 48% 27% 45% 54% 47% 53% 56% 44% 55% 47% 48% 74% 59% Caitlyn / Draven 66% 52% 25% 43% 49% 33% 48% 64% 70% 52% 61% 52% 43% 52% Caitlyn / Teemo (BC/PZ) 52% 48% 39% 53% 44% 27% 39% 24% 26% 31% 29% 30% 54% 78% Draven / Sion (NX/PZ) 73% 75% 61% 48% 54% 60% 51% 64% 60% 35% 64% 66% 50% 60% Fizz / Lulu / Poppy (BC/NX) 55% 57% 47% 52% 61% 53% 64% 45% 41% 48% 49% 39% 73% 55% Fizz / Poppy (BC/NX) 46% 51% 56% 46% 39% 50% 48% 41% 49% 45% 46% 50% 70% 57% Gangplank / Miss Fortune (BW/NX) 53% 67% 73% 40% 47% 50% 44% 41% 39% 67% 45% 59% 38% 71% Gangplank / Sejuani 47% 52% 61% 49% 36% 52% 56% 56% 41% 43% 59% 58% 51% 75% Lulu / Poppy (BC/DE) 44% 36% 76% 36% 55% 59% 59% 44% 39% 57% 43% 53% 57% 50% Lulu / Poppy (DE/IO) 56% 30% 74% 40% 59% 51% 61% 59% 61% 62% 40% 67% 61% 68% Nami / Zoe 45% 48% 69% 65% 52% 55% 33% 57% 43% 38% 39% 40% 46% 62% Poppy / Zed (DE/IO) 53% 39% 71% 36% 51% 54% 55% 41% 57% 60% 61% 64% 55% 75% Pyke / Rek'Sai 52% 48% 70% 34% 61% 50% 41% 42% 47% 33% 60% 36% 60% 53% Senna / Veigar (BC/SI) 26% 57% 46% 50% 27% 30% 62% 49% 43% 39% 54% 45% 40% 45% Xerath / Zilean (BC/SH) 41% 48% 22% 40% 45% 43% 29% 25% 50% 32% 38% 25% 47% 55%

# Deck Structure of the week

Usually I don’t take a meta-deck for this section, but the underdog decks are either “old decks” or with just too few games. Next weeks I’ll more for some “hidden gem”.

## Lulu / Poppy (BC/DE)

- 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)

The LMI 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.

# 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.