THE META REPORT NAME IS TOO LONG, TOO DAMN LONG (n°60)

Patch 3.8 - Week 1 - Burn API burn edition!

Valentino (Legna) Vazzoler
06-01-2022

Data

Number of (Prev) Seasonal Players used: 2415

Number of (Ranked) matches analysed 175794 or 351588 games.

Last Update: 2022-06-02 08:46

Games

Patch 3.8 - Week 1 - by the Numbers1
Characteristic All Games2 Ranked2
N = 313,7753 N = 175,7943
Status
Ranked 175,794 (56%)
ThePathOfChampions 103,561 (33%)
Other 31,344 (10.0%)
Friendly Bo3 3,076 (1.0%)
Server
Americas 133,543 (43%) 74,846 (43%)
Apac 93,121 (30%) 48,551 (28%)
Europe 87,111 (28%) 52,397 (30%)
1 Max datetime recovered: 2022-06-01 17:59:53.28824 UTC from 2022-05-25 18:00:00 to 2022-06-01 18:00:00 UTC
2 Games from 2415 players who attended the previous Seasonal Tournament As the API is currently bugged there is lack of games from the EU server since the 31th of May
3 n (%)

Account

Shard/Server Total
Americas Apac Europe
Player Rank
Seasonal 946 (39%) 654 (27%) 815 (34%) 2,415 (100%)
Total 946 (39%) 654 (27%) 815 (34%) 2,415 (100%)

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
Freq Shard
America Apac Europe
Regions
Noxus 16.06% 16.03% 15.54% 16.57%
Bilgewater 13.19% 13.34% 13.20% 12.96%
Demacia 9.21% 9.63% 8.73% 9.05%
Piltover 8.53% 8.99% 8.08% 8.29%
Shurima 8.06% 8.15% 9.10% 6.99%
MtTargon 6.71% 7.28% 6.42% 6.18%
Freljord 6.30% 6.04% 6.53% 6.46%
Ionia 5.36% 4.72% 5.38% 6.25%
BandleCity 3.38% 3.82% 3.65% 2.49%
Runeterra
Bard 7.76% 6.50% 7.91% 9.44%
Jhin 5.94% 5.68% 5.86% 6.38%
total 13.70% 12.18% 13.77% 15.82%
Patch 3.8 - Week 1 Ranked games from 2022-05-25 18:00:00 UTC to 2022-06-01 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-06-02 06:45:28.9844

Play Rate by number of Cards

Table

Region Play Rate
Relative Frequencies by number of times a Card within a Region is included in a Deck
Freq Shard
America Apac Europe
Regions
Noxus 14.86% 14.81% 14.26% 15.49%
Bilgewater 13.32% 13.45% 13.39% 13.07%
Runeterra 11.49% 10.50% 11.65% 12.76%
Demacia 10.00% 10.32% 9.70% 9.82%
Shurima 8.72% 8.88% 9.96% 7.36%
Piltover 8.54% 9.07% 8.01% 8.28%
MtTargon 7.02% 7.43% 6.42% 6.98%
Ionia 6.78% 5.71% 6.74% 8.35%
Freljord 6.78% 6.51% 6.80% 7.13%
BandleCity 3.70% 4.16% 4.27% 2.52%
Patch 3.8 - Week 1 Ranked games from 2022-05-25 18:00:00 UTC to 2022-06-01 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-06-02 06:45:28.9844

Champions Combinations

Play Rates

Table

Source: Metadata of games collected with RiotGames API. Last Update: 2022-06-02 06:47:50.762275 FALSE

Day by day

It’s been months since the meta has been truly dominated by a couple of decks at most. Sure we had decks stronger than the mean but overall no GoHard or Nasus/Thresh and Azir/Irelia.

This makes the overall visualization a bit more tricky not because it’s harder or anything but I think the nuances are being lost. Of couse right at the start of a new meta each change will be most likely easier to see but overall the meta tends to sort of stabilise quite fast.

Because of this I’m going to experiment with two more visual: Stacked games and play-rates. Both plots aggregate the data at each hour.

Stacked Playrates

Each playrate is stacked upon the other with the decks with the highest overall play-rate (the written value) being at the bottom.

Stacked Playrates

Similar to the previous version this one use the absolute number of games. While overall it’s less useful compared to the stacked play-rates this one can answer the weekly question?

“iS LoR dying? If So, wHY isN’t RiTO dOing As OnNLy I know hOw to rEstoRe tHe GaME?”

So, it gives a better idea about how many games are being played. Of course with an increasing number of master players it would be better to adjust its values but as this week the data is from a closed population without changes, this is fine.

Game by game

The “old” version that I’ll most likely deprecate in the future unless I find a better way to improve it. It’s not wrong of anything but since a few months I’m dissatisfied by how it can convey its data and how badly it shows changes when using a long timeframe.

Win Rates

Meta Decks

Win rates of the most played combination of champions. Play Rate $$\geq 1\%$$ in at least one of the servers.

Underdog

Top Win rates of the top10 best performing least played combination of champions. Play rate $$\in [0.1%, 1%)$$ [^Min number of games 50, during the times a meta/ladder just changed]

Match Ups

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, please refer to the MU - page for a better “meta-investigation”.

Match-up Grid

The win rates on the grid are among the 10 most played champion combination.

Annie/Jhin Lissandra/Taliyah Annie/Ezreal Bard/Zed Illaoi/Jarvan IV Maokai/Nautilus Pyke/Rek'Sai Illaoi/Lux Pantheon/Yuumi Elise/Viego
Annie/Jhin
NA
NA
58.5%
(56.2% - 60.8%)
42.3%
(39.6% - 45.0%)
57.9%
(55.7% - 60.1%)
34.2%
(31.3% - 37.0%)
45.1%
(42.4% - 47.8%)
45.3%
(41.9% - 48.7%)
36.9%
(33.6% - 40.3%)
59.3%
(55.7% - 62.9%)
45.4%
(40.7% - 50.2%)
Lissandra/Taliyah
41.5%
(39.2% - 43.8%)
NA
NA
66.6%
(63.8% - 69.2%)
47.4%
(44.4% - 50.4%)
36.4%
(33.4% - 39.6%)
54.9%
(51.5% - 58.3%)
51.1%
(47.0% - 55.1%)
46.8%
(42.5% - 51.1%)
48.9%
(44.7% - 53.2%)
46.9%
(42.5% - 51.3%)
Annie/Ezreal
57.7%
(55.0% - 60.4%)
33.4%
(30.8% - 36.2%)
NA
NA
55.9%
(52.8% - 59.1%)
49.5%
(46.1% - 52.9%)
42.5%
(38.8% - 46.3%)
53.4%
(49.1% - 57.7%)
51.5%
(46.7% - 56.2%)
61.2%
(56.5% - 65.7%)
56.2%
(51.1% - 61.3%)
Bard/Zed
42.1%
(39.9% - 44.3%)
52.6%
(49.6% - 55.6%)
44.1%
(40.9% - 47.2%)
NA
NA
55.3%
(51.7% - 58.9%)
48.0%
(44.5% - 51.6%)
52.7%
(47.9% - 57.4%)
55.9%
(51.3% - 60.4%)
40.3%
(35.4% - 45.3%)
40.4%
(34.0% - 47.2%)
Illaoi/Jarvan IV
65.8%
(63.0% - 68.7%)
63.6%
(60.4% - 66.6%)
50.5%
(47.1% - 53.9%)
44.7%
(41.1% - 48.3%)
NA
NA
61.6%
(57.4% - 65.6%)
46.7%
(41.6% - 51.9%)
49.2%
(43.9% - 54.4%)
31.3%
(26.7% - 36.2%)
34.5%
(29.2% - 40.1%)
Maokai/Nautilus
54.9%
(52.2% - 57.6%)
45.1%
(41.7% - 48.5%)
57.5%
(53.7% - 61.2%)
52.0%
(48.4% - 55.5%)
38.4%
(34.4% - 42.6%)
NA
NA
41.9%
(36.9% - 47.1%)
45.1%
(40.0% - 50.3%)
41.6%
(36.3% - 47.0%)
44.7%
(38.3% - 51.1%)
Pyke/Rek'Sai
54.7%
(51.3% - 58.1%)
48.9%
(44.9% - 53.0%)
46.6%
(42.3% - 50.9%)
47.3%
(42.6% - 52.1%)
53.3%
(48.1% - 58.4%)
58.1%
(52.9% - 63.1%)
NA
NA
50.8%
(44.5% - 57.1%)
44.8%
(38.5% - 51.2%)
43.0%
(35.2% - 51.1%)
Illaoi/Lux
63.1%
(59.7% - 66.4%)
53.2%
(48.9% - 57.5%)
48.5%
(43.8% - 53.3%)
44.1%
(39.6% - 48.7%)
50.8%
(45.6% - 56.1%)
54.9%
(49.7% - 60.0%)
49.2%
(42.9% - 55.5%)
NA
NA
35.7%
(29.9% - 41.9%)
36.4%
(27.4% - 46.1%)
Pantheon/Yuumi
40.7%
(37.1% - 44.3%)
51.1%
(46.8% - 55.3%)
38.8%
(34.3% - 43.5%)
59.7%
(54.7% - 64.6%)
68.7%
(63.8% - 73.3%)
58.4%
(53.0% - 63.7%)
55.2%
(48.8% - 61.5%)
64.3%
(58.1% - 70.1%)
NA
NA
36.6%
(29.0% - 44.8%)
Elise/Viego
54.6%
(49.8% - 59.3%)
53.1%
(48.7% - 57.5%)
43.8%
(38.7% - 48.9%)
59.6%
(52.8% - 66.0%)
65.5%
(59.9% - 70.8%)
55.3%
(48.9% - 61.7%)
57.0%
(48.9% - 64.8%)
63.6%
(53.9% - 72.6%)
63.4%
(55.2% - 71.0%)
NA
NA
MatchUp values from Ranked games of the player who attended the last Seasonal Tournament Order of the Archetypes based on the playrate. Source: Metadata of games collected with RiotGames API

LoR-Meta Index (LMI)

Note: Games from Master Rank only

Tier0 with LMI $$\geq$$ 97.5 Tier1 with LMI $$\in [85, 97.5)$$ Tier2 with LMI $$\in [60, 85)$$ Tier3- with LMI $$<$$ 60

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.

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.

Top3 Biggest Win Streak by Server
Cumulative wins with the same Archetype
Player Result Archetype Deck Code
Americas
Makantor 14 Viego (SI/SH)
Da Tank Buster 13 Annie/Ziggs
M14 de terno 13 Lissandra/Taliyah
Ronomon 13 Jayce/Lux
Apac
BLCK EIDETIKER 16 Lissandra/Taliyah
END fluorine 15 Bard/Zed
초고속 모드 14 Lissandra/Taliyah
Europe
friendlynihilist 18 Annie/Ziggs
Groxec 16 Pyke/Rek'Sai
Vinz 16 Maokai/Nautilus
Games from all Master are collected each hour adding up to the last 20 matches. Unlikely but possible to miss games in case of high frequency games. Metadata of games collected with RiotGames API

Cards Presence

Forgotten Cards

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

Not-Standard Archetype Names

Names and rules for the “non standard archetypes” which are not defined by Champion+Regions

Archetype ~Fix
Deck Source
ASZ - Sivir Ionia Akshan/Sivir (IO/SH) or Sivir/Zed or Akshan/Sivir/Zed
BandleTree 3 copies of BandleTree
Dragons (DE/MT) (DE/MT) Decks with *at least* Shyvana and ASol
Marauder (NX/FR) Two to Three copies of Both Legion Marauder and Strength in Numbers
Mistwraith Allegiance Three copies of both Mistwraith and Wraithcaller
Pirates (BW/NX) BW/NX deck with Miss Fortune and any of Twisted Fate, Gangplank
RubinBait - <Champ> Burn Deck using <Champ> to bait mulligan
Sentinel Control PnZ/SI deck any combination of Elise/Jayce/Vi
Kindred Control PnZ/SI deck any combination of Elise/Jayce/Vi AND Kindred
SunDisc Mono Shurima with 1+ Sun Disc - without Rek'Sai
Tri-Beam (NX/PZ) (NX/PZ) deck with at least 2 copies of Tri-Beam
Viktor - Shellfolk Viktor + at least one of Curious Shellfolk/Mirror Mage + at least 2 Trinket Trade

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