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 | ||
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.
Figure 1: Uncomplete Matches Distribution
| 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 | |||
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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=#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 (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 ∈ [85,97.5)
Tier2 with LMI ∈ [60,85)
Tier3 or lower with LMI < 60
Note: Hovering over a circle will display a deck values.
The LMI
1 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. 2
Regions
Play Rate
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.
| 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% |
| ShadowIsles | 6.88% | 6.45% | 7.03% | 7.29% |
| 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.
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.
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