THE META REPORT NAME IS TOO LONG, TOO DAMN LONG (n°33)

Patch 2.19 - Week 2 - BETWEEN WORLDS - Seasonal Tournament Open Rounds Waiting Room

Valentino (Legna) Vazzoler
11-24-2021

Data

Number of (Ranked) matches analysed 42325 or 84650 games. / Master

Number of (Ranked) matches analysed 105200 or 210400 games. / ~Plat+

Last Update: 2021-11-24 18:46

Patch 2.19 - Week 2 - by the Numbers1
Characteristic3 Current Master2 Last-Season Master2
N = 85,6504 N = 42,3254 N = 216,9324 N = 105,2004
Status
Ranked 42,325 (49%) 105,200 (48%)
Other 41,071 (48%) 108,434 (50%)
Friendly 2,254 (2.6%) 3,298 (1.5%)
Server
americas 35,410 (41%) 16,696 (39%) 97,169 (45%) 45,638 (43%)
asia 18,635 (22%) 8,188 (19%) 38,072 (18%) 16,613 (16%)
europe 31,605 (37%) 17,441 (41%) 81,691 (38%) 42,949 (41%)

1 Max datetime recovered: 2021-11-24 17:07:19 UTC from 2021-11-17 18:00:00 to 2021-11-24 18:00:00 UTC

2 EU Master playerDecks in the ladder 512 while number of possible Master playerDecks recovered is 505, Number of Last-Season EU Master used 1509 NA Master playerDecks in the ladder 533 while number of possible Master playerDecks recovered is 532, Number of Last-Season NA Master used 1733 ASIA Master playerDecks in the ladder 227 while number of possible Master playerDecks recovered is 226, Number of Last-Season ASIA Master used 600

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

4 n(%) took from the number of matches. When the data is analysed the size is double since we account each different player

Regions

Switching back to Master as this report is supposed to be

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 14.39% 13.31% 16.71% 14.33%
Bilgewater 12.26% 13.46% 11.56% 11.45%
Noxus 11.84% 10.26% 12.53% 13.02%
Freljord 11.32% 11.97% 9.87% 11.39%
Demacia 11.20% 11.04% 10.98% 11.46%
Ionia 10.54% 11.14% 10.12% 10.16%
Piltover 10.12% 10.59% 9.95% 9.76%
Shurima 8.19% 9.10% 9.03% 6.93%
ShadowIsles 6.77% 5.56% 6.73% 7.94%
MtTargon 3.36% 3.56% 2.54% 3.56%
Patch 2.19 - Week 2 Ranked games from 2021-11-17 18:00:00 UTC to 2021-11-24 18:00:00 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.

Plot

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
Bilgewater 17.17% 18.26% 15.81% 16.76%
BandleCity 16.21% 14.47% 19.26% 16.45%
PnZ 11.08% 12.02% 9.88% 10.75%
Demacia 10.23% 9.93% 10.29% 10.48%
Ionia 10.00% 10.47% 9.59% 9.73%
Noxus 9.86% 8.79% 9.80% 10.90%
Shurima 8.90% 9.88% 10.01% 7.45%
Freljord 7.07% 7.51% 6.96% 6.69%
ShadowIsles 6.36% 5.29% 6.26% 7.44%
MtTargon 3.12% 3.37% 2.14% 3.35%
Patch 2.19 - Week 2 Ranked games from 2021-11-17 18:00:00 UTC to 2021-11-24 18:00:00 UTC Metadata of games collected with RiotGames API

Champions Combinations

Note: I know I have to add some aggregations especially for Bandle (sorry Dr.LoR)

Archetype ~Fix
Deck Source
ASZ - Sivir Ionia Akshan/Sivir (IO/SH) or Sivir/Zed or Akshan/Sivir/Zed
RubinBait - <Champ> Burn Deck using <Champ> to bait mulligan
Dragons (DE/MT) (DE/MT) Decks with *at least* Shyvana and ASol
SunDisc Mono Shurima with 1+ Sun Disc

Play Rates

Plot

from Last-Season Master

Data from Last-Season Master Only. Source: Source: Metadata of games collected with RiotGames API FALSE

from Current Master

Data from Current Master Only. Source: Source: Metadata of games collected with RiotGames API FALSE

Day by Day

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

Win Rates

Tie games are excluded / only games from ‘Old’ Master

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:: only games from Last-Season Master

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 15 most played champion combination. The upper value is from all the Last-Season Masters, the bottom one only from the current Current Masters. MU with less than 30 games are not included.

Poppy/Zed (DE/IO) Gangplank/Sejuani Poppy/Ziggs (BC/NX) Pyke/Rek'Sai Draven/Sion (NX/PZ) Senna/Veigar (BC/SI) Lissandra/Taliyah Swain/Teemo (BC/NX) Jayce/Lux Akshan/Sivir (DE/SH) Lee Sin/Zoe Gangplank/Twisted Fate (BC/BW) Heimerdinger/Jayce (BC/PZ) Fizz/Poppy (BC/NX) Sentinel Control
Poppy/Zed (DE/IO)
NA
(NA)
57.2%
(55.9%)
46.3%
(47.9%)
63.0%
(65.4%)
49.1%
(49.6%)
67.0%
(67.7%)
71.6%
(72.2%)
43.4%
(43.6%)
51.2%
(50.4%)
52.5%
(50.3%)
66.5%
(66.9%)
43.4%
(43.5%)
55.3%
(53.4%)
53.5%
(51.5%)
41.9%
(41.8%)
Gangplank/Sejuani
42.8%
(44.1%)
NA
(NA)
50.0%
(49.1%)
54.6%
(51.3%)
55.5%
(58.1%)
55.2%
(52.3%)
40.6%
(41.0%)
64.8%
(67.4%)
58.5%
(63.4%)
58.7%
(62.4%)
43.5%
(45.4%)
52.0%
(50.5%)
60.2%
(63.3%)
48.4%
(53.2%)
52.0%
(52.8%)
Poppy/Ziggs (BC/NX)
53.7%
(52.1%)
50.0%
(50.9%)
NA
(NA)
60.4%
(59.6%)
40.4%
(37.3%)
44.9%
(46.6%)
68.1%
(60.8%)
63.2%
(66.7%)
62.9%
(68.6%)
48.8%
(51.4%)
33.9%
(29.1%)
39.1%
(37.9%)
62.6%
(57.8%)
46.2%
(48.6%)
32.8%
(31.6%)
Pyke/Rek'Sai
37.0%
(34.6%)
45.4%
(48.7%)
39.6%
(40.4%)
NA
(NA)
36.7%
(36.7%)
52.9%
(48.0%)
57.8%
(59.8%)
54.0%
(53.1%)
55.9%
(67.7%)
43.5%
(42.7%)
52.0%
(53.2%)
41.2%
(43.3%)
46.5%
(54.7%)
42.6%
(45.2%)
52.8%
(55.4%)
Draven/Sion (NX/PZ)
50.9%
(50.4%)
44.5%
(41.9%)
59.6%
(62.7%)
63.3%
(63.3%)
NA
(NA)
42.0%
(43.2%)
39.6%
(37.8%)
45.0%
(47.0%)
60.5%
(54.8%)
65.2%
(61.8%)
30.5%
(31.4%)
41.5%
(41.0%)
44.0%
(41.4%)
66.9%
(58.5%)
58.0%
(54.3%)
Senna/Veigar (BC/SI)
33.0%
(32.3%)
44.8%
(47.7%)
55.1%
(53.4%)
47.1%
(52.0%)
58.0%
(56.8%)
NA
(NA)
42.5%
(43.3%)
54.0%
(48.6%)
48.3%
(48.1%)
39.5%
(37.9%)
69.9%
(67.3%)
66.1%
(64.6%)
59.5%
(69.4%)
30.4%
(30.9%)
52.8%
(53.1%)
Lissandra/Taliyah
28.4%
(27.8%)
59.4%
(59.0%)
31.9%
(39.2%)
42.2%
(40.2%)
60.4%
(62.2%)
57.5%
(56.7%)
NA
(NA)
50.0%
(43.1%)
42.0%
(48.2%)
44.8%
(44.9%)
49.4%
(51.4%)
55.0%
(50.7%)
67.6%
(69.0%)
47.5%
(57.1%)
62.3%
(68.2%)
Swain/Teemo (BC/NX)
56.6%
(56.4%)
35.2%
(32.6%)
36.8%
(33.3%)
46.0%
(46.9%)
55.0%
(53.0%)
46.0%
(51.4%)
50.0%
(56.9%)
NA
(NA)
43.5%
(38.7%)
51.2%
(47.3%)
69.0%
(64.4%)
38.8%
(41.2%)
43.4%
(45.0%)
55.8%
(60.0%)
36.5%
(40.0%)
Jayce/Lux
48.8%
(49.6%)
41.5%
(36.6%)
37.1%
(31.4%)
44.1%
(32.3%)
39.5%
(45.2%)
51.7%
(51.9%)
58.0%
(51.8%)
56.5%
(61.3%)
NA
(NA)
52.0%
(51.4%)
36.1%
(NA)
46.4%
(NA)
65.1%
(NA)
46.2%
(NA)
65.6%
(NA)
Akshan/Sivir (DE/SH)
47.5%
(49.7%)
41.3%
(37.6%)
51.2%
(48.6%)
56.5%
(57.3%)
34.8%
(38.2%)
60.5%
(62.1%)
55.2%
(55.1%)
48.8%
(52.7%)
48.0%
(48.6%)
NA
(NA)
55.6%
(44.4%)
48.7%
(47.8%)
49.5%
(60.0%)
60.9%
(59.1%)
63.7%
(60.0%)
Lee Sin/Zoe
33.5%
(33.1%)
56.5%
(54.6%)
66.1%
(70.9%)
48.0%
(46.8%)
69.5%
(68.6%)
30.1%
(32.7%)
50.6%
(48.6%)
31.0%
(35.6%)
63.9%
(NA)
44.4%
(55.6%)
NA
(NA)
57.9%
(60.7%)
40.2%
(35.9%)
37.2%
(31.1%)
53.2%
(54.8%)
Gangplank/Twisted Fate (BC/BW)
56.6%
(56.5%)
48.0%
(49.5%)
60.9%
(62.1%)
58.8%
(56.7%)
58.5%
(59.0%)
33.9%
(35.4%)
45.0%
(49.3%)
61.2%
(58.8%)
53.6%
(NA)
51.3%
(52.2%)
42.1%
(39.3%)
NA
(NA)
62.2%
(NA)
69.5%
(80.6%)
35.3%
(37.5%)
Heimerdinger/Jayce (BC/PZ)
44.7%
(46.6%)
39.8%
(36.7%)
37.4%
(42.2%)
53.5%
(45.3%)
56.0%
(58.6%)
40.5%
(30.6%)
32.4%
(31.0%)
56.6%
(55.0%)
34.9%
(NA)
50.5%
(40.0%)
59.8%
(64.1%)
37.8%
(NA)
NA
(NA)
48.8%
(NA)
48.5%
(NA)
Fizz/Poppy (BC/NX)
46.5%
(48.5%)
51.6%
(46.8%)
53.8%
(51.4%)
57.4%
(54.8%)
33.1%
(41.5%)
69.6%
(69.1%)
52.5%
(42.9%)
44.2%
(40.0%)
53.8%
(NA)
39.1%
(40.9%)
62.8%
(68.9%)
30.5%
(19.4%)
51.2%
(NA)
NA
(NA)
41.4%
(NA)
Sentinel Control
58.1%
(58.2%)
48.0%
(47.2%)
67.2%
(68.4%)
47.2%
(44.6%)
42.0%
(45.7%)
47.2%
(46.9%)
37.7%
(31.8%)
63.5%
(60.0%)
34.4%
(NA)
36.3%
(40.0%)
46.8%
(45.2%)
64.7%
(62.5%)
51.5%
(NA)
58.6%
(NA)
NA
(NA)
The upper value is from Last-Season Masters while the bottom value is from New Masters. MU with less than 30 games are not included. Order of the Archetypes based on the playrate over the last 7 days from the last-update from Plat+ (change to Master once the ladder is more populated). Source: Metadata of games collected with RiotGames API

Match-up Table

Deck of the week

At Swain this season is finally the “cool Daddy” who helps everyone; for this week I opted for a deck that is barely played at Master but still played enough to appear in my stats, also it seems interesting.

It’s a differentiation of “Seena/Ez-Regreats”, with Swain package instead of Ezreal.

Senna/Swain (Regrets)

Deckcodes

How to read the table:
- 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 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.

Static version

Interactive Version

Win Marathons Leaders

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
Fogacinha 15 Thresh/Viego (IO/SI)
Fufusnag 14 Taliyah/Ziggs (BC/SH)
Black Axis 13 Pyke/Rek'Sai
DasPerin11 13 Gangplank/Sejuani
Sir DiegoADM 13 Gangplank/Miss Fortune (BW/NX)
Asia
서폿쌤 15 Fizz/Poppy (BC/NX)
astro 13 Gangplank/Sejuani
북미 판다곰 12 Fizz/Lulu/Poppy (BC/NX)
이렐리아 12 Poppy/Zed (DE/IO)
Europe
NA 18 Poppy/Zed (DE/IO)
Stroppo83 16 Lulu/Poppy (DE/IO)
bubblefish 14 Lux/Poppy (BC/DE)
Cyrano86 14 Gangplank/Sejuani
Eclipse 14 Draven/Sion (NX/PZ)
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

Play Rate

It seems that not even Twin Disciple can beat Sharsight

Top 3 Play Rates by Region

Forgotten Cards

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

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.↩︎

  2. LMI - Early Theory↩︎

  3. LMI - Adding a Ban Index↩︎

© 2021 Vazzoler Valentino

LlorR Stats was created under Riot Games’ “Legal Jibber Jabber” policy using assets owned by Riot Games. Riot Games does not endorse or sponsor this project.