THE META REPORT NAME IS TOO LONG, TOO DAMN LONG (n°31)

Patch 2.18 - Week 3 - Path of Jayce

Valentino (Legna) Vazzoler
11-10-2021

Data

Number of (Ranked) matches analysed 21052 or 42104 games. / Master

Number of (Ranked) matches analysed 126156 or 252312 games. / ~Plat+

Last Update: 2021-11-10 22:12

Patch 2.18 - Week 3 - by the Numbers1
Characteristic3 Current Master2 Last-Season Master2
N = 31,5724 N = 21,0524 N = 183,7094 N = 126,1564
Status
Ranked 21,052 (67%) 126,091 (69%)
Other 9,919 (31%) 54,859 (30%)
Friendly 601 (1.9%) 2,759 (1.5%)
Server
americas 12,999 (41%) 8,219 (39%) 84,529 (46%) 55,115 (44%)
asia 6,642 (21%) 4,308 (20%) 27,429 (15%) 18,656 (15%)
europe 11,931 (38%) 8,525 (40%) 71,751 (39%) 52,385 (42%)

1 Max datetime recovered: 2021-11-10 16:59:57 UTC from 2021-11-03 17:00:00 to 2021-11-10 17:00:00 UTC

2 EU Master playerDecks in the ladder 211 while number of possible Master playerDecks recovered is 207, Number of Last-Season EU Master used 1509 NA Master playerDecks in the ladder 229 while number of possible Master playerDecks recovered is 225, Number of Last-Season NA Master used 1733 ASIA Master playerDecks in the ladder 105 while number of possible Master playerDecks recovered is 104, 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 19.35% 18.30% 23.48% 18.29%
Noxus 15.11% 14.51% 14.90% 15.80%
Bilgewater 11.46% 11.38% 10.36% 12.10%
Piltover 11.06% 10.94% 13.33% 10.04%
Demacia 9.20% 9.79% 6.69% 9.90%
Freljord 8.50% 7.97% 6.86% 9.83%
Shurima 8.24% 8.20% 9.55% 7.61%
Ionia 7.17% 8.01% 5.44% 7.24%
ShadowIsles 6.25% 5.82% 7.24% 6.18%
MtTargon 3.65% 5.08% 2.17% 3.01%
Patch 2.18 - Week 3 Ranked games from 2021-11-03 17:00:00 UTC to 2021-11-10 17:00:00 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
BandleCity 22.20% 20.98% 26.95% 20.98%
Bilgewater 15.33% 14.70% 13.84% 16.69%
Noxus 12.53% 11.93% 11.74% 13.52%
PnZ 10.94% 11.10% 11.84% 10.34%
Shurima 9.32% 9.05% 11.51% 8.48%
Demacia 8.79% 9.64% 6.20% 9.27%
Ionia 7.03% 8.13% 4.85% 7.07%
ShadowIsles 5.74% 5.31% 7.04% 5.50%
Freljord 4.68% 4.46% 3.79% 5.35%
MtTargon 3.43% 4.70% 2.23% 2.81%
Patch 2.18 - Week 3 Ranked games from 2021-11-03 17:00:00 UTC to 2021-11-10 17:00:00 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 Pyke/Rek'Sai Swain/Teemo (BC/NX) Senna/Veigar (BC/SI) Draven/Sion (NX/PZ) Poppy/Ziggs (BC/NX) Gangplank/Twisted Fate (BC/BW) Fizz/Poppy (BC/NX) Akshan/Sivir (DE/SH) Lux/Poppy (BC/DE) Dragons (DE/MT) Thresh/Viego (IO/SI) Draven/Viktor Lissandra/Taliyah
Poppy/Zed (DE/IO)
NA
(NA)
57.3%
(57.2%)
59.5%
(59.0%)
41.6%
(37.6%)
65.0%
(62.7%)
44.8%
(43.7%)
45.4%
(46.8%)
42.2%
(40.8%)
59.1%
(61.0%)
55.7%
(57.0%)
49.5%
(50.0%)
59.8%
(54.1%)
64.5%
(68.8%)
55.0%
(51.0%)
66.8%
(80.5%)
Gangplank/Sejuani
42.7%
(42.8%)
NA
(NA)
56.7%
(59.3%)
64.8%
(64.6%)
50.4%
(53.4%)
55.1%
(56.1%)
48.6%
(52.4%)
53.9%
(49.6%)
53.4%
(48.8%)
61.3%
(60.6%)
58.7%
(57.7%)
52.2%
(41.7%)
53.3%
(52.3%)
55.6%
(57.4%)
39.9%
(31.1%)
Pyke/Rek'Sai
40.5%
(41.0%)
43.3%
(40.7%)
NA
(NA)
51.0%
(43.5%)
51.7%
(59.5%)
34.7%
(39.6%)
44.0%
(38.0%)
42.2%
(47.0%)
45.4%
(31.1%)
48.8%
(50.9%)
56.4%
(46.7%)
66.1%
(NA)
51.0%
(NA)
42.3%
(NA)
59.1%
(60.0%)
Swain/Teemo (BC/NX)
58.4%
(62.4%)
35.2%
(35.4%)
49.0%
(56.5%)
NA
(NA)
52.9%
(51.2%)
48.3%
(47.7%)
39.5%
(44.4%)
40.1%
(39.8%)
57.4%
(64.9%)
53.7%
(55.4%)
46.2%
(51.2%)
45.0%
(NA)
65.5%
(74.3%)
47.9%
(50.0%)
61.2%
(65.8%)
Senna/Veigar (BC/SI)
35.0%
(37.3%)
49.6%
(46.6%)
48.3%
(40.5%)
47.1%
(48.8%)
NA
(NA)
60.1%
(64.2%)
53.5%
(56.7%)
60.4%
(56.4%)
30.6%
(30.4%)
39.9%
(41.3%)
60.7%
(NA)
49.8%
(NA)
73.2%
(NA)
52.1%
(62.9%)
46.9%
(44.4%)
Draven/Sion (NX/PZ)
55.2%
(56.3%)
44.9%
(43.9%)
65.3%
(60.4%)
51.7%
(52.3%)
39.9%
(35.8%)
NA
(NA)
58.8%
(60.2%)
44.3%
(47.5%)
58.4%
(57.9%)
60.5%
(64.7%)
49.2%
(43.5%)
68.8%
(NA)
38.4%
(NA)
51.0%
(48.4%)
51.6%
(41.3%)
Poppy/Ziggs (BC/NX)
54.6%
(53.2%)
51.4%
(47.6%)
56.0%
(62.0%)
60.5%
(55.6%)
46.5%
(43.3%)
41.2%
(39.8%)
NA
(NA)
45.2%
(42.2%)
54.5%
(60.0%)
48.7%
(38.5%)
59.3%
(NA)
62.5%
(NA)
46.3%
(NA)
45.0%
(NA)
61.2%
(NA)
Gangplank/Twisted Fate (BC/BW)
57.8%
(59.2%)
46.1%
(50.4%)
57.8%
(53.0%)
59.9%
(60.2%)
39.6%
(43.6%)
55.7%
(52.5%)
54.8%
(57.8%)
NA
(NA)
66.7%
(64.7%)
41.9%
(36.1%)
38.1%
(NA)
41.1%
(NA)
36.9%
(NA)
50.0%
(NA)
29.6%
(NA)
Fizz/Poppy (BC/NX)
40.9%
(39.0%)
46.6%
(51.2%)
54.6%
(68.9%)
42.6%
(35.1%)
69.4%
(69.6%)
41.6%
(42.1%)
45.5%
(40.0%)
33.3%
(35.3%)
NA
(NA)
38.7%
(NA)
70.3%
(NA)
61.8%
(NA)
73.3%
(NA)
36.7%
(NA)
46.7%
(NA)
Akshan/Sivir (DE/SH)
44.3%
(43.0%)
38.7%
(39.4%)
51.2%
(49.1%)
46.3%
(44.6%)
60.1%
(58.7%)
39.5%
(35.3%)
51.3%
(61.5%)
58.1%
(63.9%)
61.3%
(NA)
NA
(NA)
51.3%
(NA)
62.7%
(NA)
50.0%
(NA)
57.6%
(NA)
61.9%
(NA)
Lux/Poppy (BC/DE)
50.5%
(50.0%)
41.3%
(42.3%)
43.6%
(53.3%)
53.8%
(48.8%)
39.3%
(NA)
50.8%
(56.5%)
40.7%
(NA)
61.9%
(NA)
29.7%
(NA)
48.7%
(NA)
NA
(NA)
36.1%
(NA)
60.9%
(NA)
56.7%
(NA)
45.7%
(NA)
Dragons (DE/MT)
40.2%
(45.9%)
47.8%
(58.3%)
33.9%
(NA)
55.0%
(NA)
50.2%
(NA)
31.2%
(NA)
37.5%
(NA)
58.9%
(NA)
38.2%
(NA)
37.3%
(NA)
63.9%
(NA)
NA
(NA)
57.4%
(NA)
42.9%
(NA)
55.9%
(NA)
Thresh/Viego (IO/SI)
35.5%
(31.2%)
46.7%
(47.7%)
49.0%
(NA)
34.5%
(25.7%)
26.8%
(NA)
61.6%
(NA)
53.7%
(NA)
63.1%
(NA)
26.7%
(NA)
50.0%
(NA)
39.1%
(NA)
42.6%
(NA)
NA
(NA)
52.6%
(NA)
63.0%
(NA)
Draven/Viktor
45.0%
(49.0%)
44.4%
(42.6%)
57.7%
(NA)
52.1%
(50.0%)
47.9%
(37.1%)
49.0%
(51.6%)
55.0%
(NA)
50.0%
(NA)
63.3%
(NA)
42.4%
(NA)
43.3%
(NA)
57.1%
(NA)
47.4%
(NA)
NA
(NA)
59.1%
(NA)
Lissandra/Taliyah
33.2%
(19.5%)
60.1%
(68.9%)
40.9%
(40.0%)
38.8%
(34.2%)
53.1%
(55.6%)
48.4%
(58.7%)
38.8%
(NA)
70.4%
(NA)
53.3%
(NA)
38.1%
(NA)
54.3%
(NA)
44.1%
(NA)
37.0%
(NA)
40.9%
(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

I wanted to highlight this deck (or anything with Xerath, currently the champ I love the most) as it is the deck I’m OTP the moment. Sadly as I couldn’t find even a single instance to justify it, this week can be considered a whim of mine.

Note: I’m still a scrub player compared to the other analyst the worse one, last season I almost didn’t play and was only gold from the usual plat/diamond. Currently I’m almost back to Diamond playing just and only this deck I know the deck is just ok, if not a little bad but it’s not that bad, I’m sure there are a couple of other ways to play Xerath but the play pattern of this version if one I really love.

This deckcode is the version I’m mostly playing.

CQBQGBIKAZE2MAIDAUDQOCYOAUCAODJFEYTVSAICAUFBXUIBAIAQKBYEAICQUAI2

Xerath/Zilean

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
ChristmasTime 15 Gangplank/Sejuani
Dnr 15 Gangplank/Sejuani
Riot RubinZoo 15 Gangplank/Twisted Fate (BW/NX)
RusticlesLOR 15 Akshan/Sivir (DE/SH)
Asia
PlanetCloset 17 Gangplank/Sejuani
kazu 16 Draven/Sion (NX/PZ)
澁谷かのん 15 Poppy/Ziggs (BC/NX)
Europe
kaasmetfeesthoed 15 Gangplank/Sejuani
Masquerade 14 Gangplank/Sejuani
PCS Tealcos 14 Gangplank/Sejuani
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.