THE META REPORT NAME IS TOO LONG, TOO DAMN LONG (n°49)

Patch 3.3 - Week 2 - Long (Broken) turns have we waited, Tri-Beam Activated

Valentino (Legna) Vazzoler
03-16-2022

Data

Number of Master Players: 1041

Number of HighDiamond 1 Players: 2566

Number of (Ranked) Master matches analysed 36873 or 73746 games.

Number of (Ranked) ~HighDiamond matches analysed 106974 or 213948 games.

Last Update: 2022-03-16 19:19

Games

Patch 3.3 - Week 2 - by the Numbers1
Characteristic3 Master2 ~HighDiamond2
N = 59,6854 N = 36,8734 N = 150,6724 N = 106,9744
Status
Ranked 36,873 (62%) 106,974 (71%)
Other 15,750 (26%) 24,400 (16%)
PathOfChampion 5,288 (8.9%) 15,880 (11%)
Friendly 1,774 (3.0%) 3,418 (2.3%)
Server
americas 21,309 (36%) 13,120 (36%) 59,808 (40%) 40,343 (38%)
apac 19,897 (33%) 11,151 (30%) 45,319 (30%) 32,040 (30%)
europe 18,479 (31%) 12,602 (34%) 45,545 (30%) 34,591 (32%)
1 Max datetime recovered: 2022-03-16 17:41:24 UTC from 2022-03-09 18:00:00 to 2022-03-16 18:00:00 UTC
2 EU Master 316/316 NA Master 366/367 APAC Master 352/352
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

Account

Shard/Server Americas, N = 1,3481 Apac, N = 1,1471 Europe, N = 1,1121
Player Rank
Master 366 (27%) 353 (31%) 322 (29%)
Diamond 982 (73%) 794 (69%) 790 (71%)
1 n (%)

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 Apac Europe
BandleCity 17.97% 18.99% 15.45% 19.15%
Demacia 15.71% 15.91% 15.12% 16.03%
Piltover 13.12% 13.25% 14.04% 12.18%
Noxus 11.11% 10.81% 10.97% 11.53%
ShadowIsles 8.66% 9.05% 8.38% 8.51%
Shurima 8.48% 8.09% 8.59% 8.80%
MtTargon 8.41% 8.97% 8.64% 7.63%
Freljord 6.29% 5.66% 6.76% 6.54%
Bilgewater 5.92% 4.49% 8.52% 5.10%
Ionia 4.32% 4.78% 3.53% 4.54%
Patch 3.3 - Week 2 Ranked games from 2022-03-09 18:00:00 UTC to 2022-03-16 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-03-16 18:18:01.897511

Play Rate by number of Cards

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 Apac Europe
BandleCity 22.51% 24.13% 19.42% 23.57%
Demacia 13.69% 12.96% 14.13% 14.06%
Piltover 13.54% 13.72% 13.93% 13.02%
Shurima 9.74% 9.29% 10.09% 9.88%
MtTargon 9.19% 9.92% 9.26% 8.37%
Noxus 8.59% 8.13% 8.78% 8.90%
ShadowIsles 8.22% 8.36% 8.38% 7.94%
Freljord 5.76% 5.05% 6.18% 6.12%
Bilgewater 4.40% 3.64% 6.39% 3.42%
Ionia 4.36% 4.80% 3.44% 4.71%
Patch 3.3 - Week 2 Ranked games from 2022-03-09 18:00:00 UTC to 2022-03-16 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-03-16 18:18:01.897511

Champions Combinations

Play Rates

Plot

from Master

Data from Master Only. Source: Metadata of games collected with RiotGames API. Last Update: 2022-03-16 18:20:31.130008 FALSE

from ~HighDiamond

Data from ~HighDiamond Only. Source: Metadata of games collected with RiotGames API Last Update: 2022-03-16 18:20:32.048194. FALSE

Day by Day

Highlighting the play-rates of most played [^at the moment of the last game] decks over time.

Master

HighDiamond

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.

The upper value is from all the Masters players, the bottom one only from HighDiamond.

MU with less than 30 games are not included.

Senna/Veigar Pantheon/Yuumi (DE/MT) Tri-Beam (NX/PZ) Gnar/Teemo/Tristana (BC/DE) Pyke/Rek'Sai BandleTree Miss Fortune/Quinn Akshan/Sivir (DE/SH) Gnar/Trundle (FR/PZ) Fizz/Lulu (BC/PZ)
Senna/Veigar
NA
42.9%
45.3%
51.3%
49.8%
42.1%
45.3%
52.4%
47.4%
18.4%
28.5%
41.9%
42.0%
37.7%
39.6%
53.8%
50.3%
58.0%
56.2%
Pantheon/Yuumi (DE/MT)
57.1%
54.7%
NA
49.1%
48.3%
54.1%
48.7%
50.7%
50.5%
44.1%
45.3%
66.7%
63.7%
67.0%
62.2%
57.1%
55.0%
36.8%
33.2%
Tri-Beam (NX/PZ)
48.7%
50.2%
50.9%
51.7%
NA
43.5%
44.8%
54.3%
53.0%
58.2%
58.8%
48.7%
52.8%
43.1%
48.2%
37.2%
39.4%
47.3%
51.3%
Gnar/Teemo/Tristana (BC/DE)
57.9%
54.7%
45.9%
51.3%
56.5%
55.2%
NA
52.0%
52.8%
61.5%
62.0%
48.4%
51.0%
50.0%
51.1%
59.2%
49.7%
43.3%
52.1%
Pyke/Rek'Sai
47.6%
52.6%
49.3%
49.5%
45.7%
47.0%
48.0%
47.2%
NA
43.1%
46.4%
57.1%
49.4%
48.8%
42.0%
44.8%
39.8%
32.0%
30.6%
BandleTree
81.6%
71.5%
55.9%
54.7%
41.3%
41.2%
38.5%
38.0%
56.9%
53.6%
NA
36.6%
30.2%
47.4%
52.0%
48.4%
39.6%
33.0%
50.0%
Miss Fortune/Quinn
58.1%
58.0%
33.3%
36.3%
51.3%
47.2%
51.6%
49.0%
42.9%
50.6%
63.4%
69.8%
NA
44.6%
48.5%
44.1%
54.4%
39.7%
47.5%
Akshan/Sivir (DE/SH)
62.3%
60.4%
33.0%
37.8%
56.9%
51.8%
50.0%
48.9%
51.2%
58.0%
52.6%
48.0%
55.4%
51.5%
NA
50.6%
47.7%
44.1%
55.3%
Gnar/Trundle (FR/PZ)
46.2%
49.7%
42.9%
45.0%
62.8%
60.6%
40.8%
50.3%
55.2%
60.2%
51.6%
60.4%
55.9%
45.6%
49.4%
52.3%
NA
49.2%
51.7%
Fizz/Lulu (BC/PZ)
42.0%
43.4%
63.2%
66.8%
52.7%
48.7%
56.7%
47.9%
68.0%
69.4%
67.0%
50.0%
60.3%
52.5%
55.9%
44.7%
50.8%
48.3%
NA
MatchUp values from Ranked games with Master (upper) and ~HighDiamond (bottom) Ranked players. Decks and order of the Archetypes based on the playrate over the last 7 days. 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 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.

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
滿季包子 13 Pantheon/Yuumi (DE/MT)
AK Tomaszamo 13 Gnar/Tristana (BC/DE)
HDR Dudu de Nunu 13 Gnar/Tristana (BC/DE)
StolenConch 13 Jinx/Lulu
Apac
ゴーゼワロス 18 Miss Fortune/Quinn
PanglnwZa007 12 Championless (NX/PZ)
Sleep on bush 12 Elise/Kindred/Vi
Europe
Bülat 16 Darius/Gnar (FR/NX)
Frag1Le 15 Tri-Beam (NX/PZ)
Arren 12 Ahri/Akshan
Conansson 12 Miss Fortune/Quinn
Feanor Curufinwë 12 Fizz/Gnar (BC/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

Top 3 Play Rates by Region

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 Two to Three copies of Both Legion Marauder and Strength in Numbers
Mistwraith Allegiance Three copies of both Mistwraith and Wraithcaller
RubinBait - <Champ> Burn Deck using <Champ> to bait mulligan
Sentinel Control PnZ/SI deck with a combination of Elise/Jayce/Vi
SunDisc Mono Shurima with 1+ Sun Disc - without Rek'Sai
Viktor - Shellfolk Viktor + at least one of Curious Shellfolk/Mirror Mage + at least 2 Trinket Trade

Credits

Special thanks to Trinathan, Jump, bA1ance and for the recent support (ᐛ)ᕗ

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. HighDiamond are defined as “players who played against Master player in a Ranked games but are not Master themselves”↩︎

  2. LMI - Early Theory↩︎

  3. LMI - Adding a Ban Index↩︎