THE META REPORT NAME IS TOO LONG, TOO DAMN LONG (n°91)

Patch 3.21 - Week 4 - Riot Hybernation is over this week! Patch Notes Waiting Room!

Valentino (Legna) Vazzoler
2023-01-04

Data

Number of Master Players: 9024

Number of HighDiamond 1 Players: 10247

Number of (Ranked) Master matches analysed 201392 or 402784 games.

Number of (Ranked) ~HighDiamond matches analysed 339049 or 678098 games.

Last Update: 2023-01-07 09:29

Games

Patch 3.21 - Week 4 - by the Numbers1
Characteristic Master2 ~HighDiamond2
N = 391,4513 N = 201,3923 N = 504,8543 N = 339,0493
Status
    Ranked 201,392 (51%) 339,049 (67%)
    ThePathOfChampions 106,156 (27%) 100,737 (20%)
    Other 77,510 (20%) 59,648 (12%)
    Labs 3,306 (0.8%) 3,732 (0.7%)
    Friendly Bo3 3,087 (0.8%) 1,688 (0.3%)
Server
    Americas 154,702 (40%) 79,111 (39%) 187,228 (37%) 127,701 (38%)
    Apac 114,649 (29%) 52,165 (26%) 152,548 (30%) 92,282 (27%)
    Europe 122,100 (31%) 70,116 (35%) 165,078 (33%) 119,066 (35%)
1 Max datetime recovered: 2023-01-04 17:59:58.93294 UTC from 2022-12-28 18:00:00 to 2023-01-04 18:00:00 UTC
2 EU Master 3018/3020 NA Master 3625/3644 APAC Master 2381/2385
3 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 Total
Americas Apac Europe
Player Rank
    Master 3,625 (19%) 2,381 (12%) 3,018 (16%) 9,024 (47%)
    Diamond 3,807 (20%) 2,896 (15%) 3,544 (18%) 10,247 (53%)
Total 7,432 (39%) 5,277 (27%) 6,562 (34%) 19,271 (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
ShadowIsles 13.59% 13.78% 13.84% 13.18%
Noxus 12.21% 12.34% 12.18% 12.10%
Demacia 11.10% 10.92% 10.79% 11.55%
Piltover 10.63% 10.39% 11.18% 10.50%
BandleCity 7.75% 7.56% 7.86% 7.89%
Freljord 7.43% 7.76% 7.45% 7.04%
Bilgewater 6.47% 6.41% 5.68% 7.12%
Ionia 6.05% 5.76% 7.59% 5.21%
Shurima 5.91% 5.57% 5.84% 6.36%
MtTargon 3.84% 4.04% 4.12% 3.41%
Runeterra
Aatrox 9.18% 9.59% 7.85% 9.72%
Kayn 1.85% 2.32% 1.48% 1.58%
Ryze 1.76% 1.38% 1.94% 2.07%
Jhin 0.81% 0.74% 0.80% 0.90%
Varus 0.55% 0.62% 0.54% 0.50%
Bard 0.49% 0.44% 0.52% 0.53%
Evelynn 0.19% 0.22% 0.20% 0.16%
Jax 0.17% 0.18% 0.14% 0.20%
total 15.01% 15.47% 13.47% 15.65%
Patch 3.21 - Week 4 Ranked games from 2022-12-28 18:00:00 UTC to 2023-01-04 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2023-01-07 08:27:01.652056

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
Freq Shard
America Apac Europe
Regions
ShadowIsles 14.08% 13.90% 14.81% 13.74%
Demacia 12.78% 12.59% 12.23% 13.41%
Runeterra 12.10% 12.55% 10.77% 12.59%
Piltover 11.94% 11.84% 12.60% 11.57%
Noxus 11.64% 11.89% 11.65% 11.35%
Freljord 7.77% 8.61% 7.53% 7.00%
Shurima 7.36% 6.66% 7.36% 8.13%
BandleCity 7.05% 6.99% 6.96% 7.19%
Bilgewater 6.31% 6.21% 5.53% 7.00%
Ionia 5.45% 5.22% 6.72% 4.76%
MtTargon 3.52% 3.54% 3.85% 3.25%
Patch 3.21 - Week 4 Ranked games from 2022-12-28 18:00:00 UTC to 2023-01-04 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2023-01-07 08:27:01.652056

Champions Combinations

Play Rates

Plot

from Master

Source: Metadata of games collected with RiotGames API. Last Update: 2023-01-07 08:30:41.149701 FALSE

from Diamond

Source: Metadata of games collected with RiotGames API. Last Update: 2023-01-07 08:30:41.510485 FALSE

Day by day

Hourly/Dialy lines

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 Games

Win Rates

Meta Decks

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

Format changed to replicate the one used in the Meta - page

Underdog

Top Win rates of the top10 best performing least played combination of champions. Play rate \(\in [0.1%, 1%)\)

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.

WR (WRmeta) Aatrox/Vayne (RU/DE) Ezreal/Seraphine (BC/PZ) Gwen/Katarina (NX/SI) Pyke/Rek'Sai (BW/SH) Rumble/Vayne (DE/NX) Aatrox/Kayn (RU/RU) Trundle/Tryndamere (FR/SI) Hecarim/Zed (IO/SI) SunDisc Darius (FR/NX)
Aatrox/Vayne (RU/DE)
57.2%
53.7%
NA
NA
61.5%
(59.9% - 63.0%)
51.7%
(50.1% - 53.4%)
53.9%
(51.6% - 56.3%)
41.7%
(39.3% - 44.2%)
53.3%
(50.9% - 55.7%)
45.1%
(42.4% - 47.8%)
59.5%
(56.6% - 62.4%)
64.8%
(61.9% - 67.7%)
45.8%
(42.0% - 49.7%)
Ezreal/Seraphine (BC/PZ)
52.5%
47.8%
38.5%
(37.0% - 40.1%)
NA
NA
53.8%
(51.5% - 56.1%)
53.0%
(49.9% - 56.2%)
52.4%
(49.1% - 55.6%)
43.2%
(40.1% - 46.4%)
38.9%
(35.4% - 42.5%)
53.5%
(49.7% - 57.3%)
47.1%
(43.3% - 51.1%)
41.9%
(36.7% - 47.1%)
Gwen/Katarina (NX/SI)
55.6%
52.1%
48.3%
(46.6% - 49.9%)
46.2%
(43.9% - 48.5%)
NA
NA
59.4%
(56.2% - 62.5%)
49.0%
(45.6% - 52.3%)
48.7%
(45.5% - 52.0%)
57.8%
(53.8% - 61.8%)
58.0%
(54.0% - 61.9%)
61.8%
(57.7% - 65.7%)
59.9%
(54.6% - 65.1%)
Pyke/Rek'Sai (BW/SH)
50.5%
46.4%
46.1%
(43.7% - 48.4%)
47.0%
(43.8% - 50.1%)
40.6%
(37.5% - 43.8%)
NA
NA
46.0%
(41.3% - 50.7%)
54.2%
(49.8% - 58.6%)
56.6%
(51.1% - 62.0%)
48.5%
(43.4% - 53.7%)
55.3%
(49.7% - 60.9%)
50.0%
(42.9% - 57.1%)
Rumble/Vayne (DE/NX)
55.0%
52.5%
58.3%
(55.8% - 60.7%)
47.6%
(44.4% - 50.9%)
51.0%
(47.7% - 54.4%)
54.0%
(49.3% - 58.7%)
NA
NA
59.2%
(54.4% - 63.8%)
54.3%
(48.6% - 59.9%)
45.4%
(39.5% - 51.4%)
71.5%
(65.9% - 76.7%)
40.6%
(33.0% - 48.5%)
Aatrox/Kayn (RU/RU)
53.3%
49.6%
46.7%
(44.3% - 49.1%)
56.8%
(53.6% - 59.9%)
51.3%
(48.0% - 54.5%)
45.8%
(41.4% - 50.2%)
40.8%
(36.2% - 45.6%)
NA
NA
35.9%
(30.9% - 41.2%)
49.3%
(43.8% - 54.7%)
53.3%
(47.2% - 59.3%)
47.7%
(40.1% - 55.4%)
Trundle/Tryndamere (FR/SI)
54.0%
50.0%
54.9%
(52.2% - 57.6%)
61.1%
(57.5% - 64.6%)
42.2%
(38.2% - 46.2%)
43.4%
(38.0% - 48.9%)
45.7%
(40.1% - 51.4%)
64.1%
(58.8% - 69.1%)
NA
NA
38.3%
(31.6% - 45.4%)
58.3%
(51.2% - 65.2%)
47.2%
(39.3% - 55.2%)
Hecarim/Zed (IO/SI)
51.6%
48.4%
40.5%
(37.6% - 43.4%)
46.5%
(42.7% - 50.3%)
42.0%
(38.1% - 46.0%)
51.5%
(46.3% - 56.6%)
54.6%
(48.6% - 60.5%)
50.7%
(45.3% - 56.2%)
61.7%
(54.6% - 68.4%)
NA
NA
67.1%
(60.5% - 73.3%)
51.3%
(41.9% - 60.5%)
SunDisc
44.6%
40.5%
35.2%
(32.3% - 38.1%)
52.9%
(48.9% - 56.7%)
38.2%
(34.3% - 42.3%)
44.7%
(39.1% - 50.3%)
28.5%
(23.3% - 34.1%)
46.7%
(40.7% - 52.8%)
41.7%
(34.8% - 48.8%)
32.9%
(26.7% - 39.5%)
NA
NA
30.8%
(22.7% - 39.9%)
Darius (FR/NX)
54.2%
50.9%
54.2%
(50.3% - 58.0%)
58.1%
(52.9% - 63.3%)
40.1%
(34.9% - 45.4%)
50.0%
(42.9% - 57.1%)
59.4%
(51.5% - 67.0%)
52.3%
(44.6% - 59.9%)
52.8%
(44.8% - 60.7%)
48.7%
(39.5% - 58.1%)
69.2%
(60.1% - 77.3%)
NA
NA
MatchUp values from Ranked games of Master rank players. Order of the Archetypess 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 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.