# THE SEASONAL REPORT IS VAST (n°2)

Seasonal Tournament - Beyond the Bandlewood - Open Rounds

Valentino (Legna) Vazzoler
10-08-2021

# Data

Number of (Ranked) matches analyzed 13064 or 26128 games.

Last Update: 2021-10-10 16:42

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

Seasonal Open Rounds - by the Numbers
Players coverage reached regarding the Seasonal Tournament - Beyond the Bandlewood - Open Rounds
Server Players Games
Asia 218/(?) 3142
Europe 916/1024(?) 11302
Americas 926/1024(?) 11684
Source: Source: Metadata of games collected with RiotGames API

### Missing Games

The following data is related to the the number of games missing to recreate a match.So when I could only collect either a win or a loss or both a win and a loss but not the remaining game. It is not the total number of missing games as it doesn’t account for the cases where I lack all games but that value can’t be known as it’s impossible to know whenever the round was played or not.

During the partial results is the graph is lacking I recovered all games I could up until that moment.

### Matches Coverage

Seasonal Open Rounds - by the Numbers
Match coverage reached regarding the Seasonal Tournament - Beyond the Bandlewood - Open Rounds
America1 Asia1 Europe1
round
1 840 218 852
2 730 218 666
3 696 218 674
4 586 218 570
5 526 218 512
6 410 218 404
7 326 218 346
8 322 218 312
9 298 218 282
Source: Source: Metadata of games collected with RiotGames API

1 n

# Decks

As this is the Seasonal Tournament let’s start with the decks/archetype informations

This is also the moment of the meta where the classification Archetype = Champion+Region shows its biggest limitation as there are an increase in tech champions (usually in single copy)

# Deck's Stats

## Seasonal Tournament - Beyond the Bandlewood - Open Rounds

Relative frequencies from all data or only lineUps with full information Source: Metadata of games collected with RiotGames API

• Ban Rate: ratio between the number of bans and the number of matches of a deck.

$$$BanRate = \frac{\#ban}{\#match}$$$

Example: 2 Line-Ups contained a Teemo/Ezreal deck, both played all 9 matches and Teemo/Ezreal was banned respectively 3 and 6 times; the ban rate would be $$\frac{(3+6)}{(9+9)} = 50\%$$

• PlayRate: ratio between the number of times a deck appears among all lineUps (both including or not incomplete lineUps data) and the number of all decks in all lineUps.

# LineUp's Playrates

## Seasonal Tournament - Beyond the Bandlewood - Open Rounds

Data from only full Line-Ups. Source: Source: Metadata of games collected with RiotGames API FALSE

# 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 1 2 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.

# 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 18.79% 18.60% 19.71% 18.75%
Noxus 18.16% 18.17% 20.36% 17.61%
Bilgewater 12.17% 12.93% 10.02% 11.92%
Piltover 11.97% 11.76% 14.38% 11.58%
MtTargon 8.44% 8.69% 6.30% 8.72%
Demacia 7.03% 6.88% 7.27% 7.13%
Shurima 5.87% 5.71% 3.96% 6.51%
Ionia 5.78% 6.08% 5.98% 5.41%
Freljord 4.91% 4.72% 5.01% 5.07%
Source: Source: Metadata of games collected with RiotGames API

# Top Player(?) Champions of Choice

This section is done before the release of the official top32 list from Riot.

• For the Asia shard it displays those who reached at least 7 matches wins (not counting bye)

• For the America and Europe shard it displays those who reached at least 8 matches wins (not counting bye)

When partial results are being published, it’s not limited to the top32 but the current highest performing players collected at that point. As there are “Bye” that I can’t track the final results will never be perfect. 3

### Table - All Server & Deckcodes

Remember that as I can’t collect “bye” the true top list may differ buy a lot.

# Top Players' Deckcodes

## Seasonal Tournament - Beyond the Bandlewood - Open Rounds

Source: Source: Metadata of games collected with RiotGames API

# The Meta and the Seasonal

This Seasonal was much more “predictable” than what I expected. Probably because of the less try-harding many players approached the tournament simply with the “strongest” decks as they would in the ladder.