Data
Number of (Prev) Seasonal Players used: 2415
Number of (Ranked) matches analysed 175794 or 351588 games.
Last Update: 2022-06-02 08:46
| 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 (%) | ||
| 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
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) ∈[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.
| 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% |
| ShadowIsles | 9.51% | 9.84% | 9.60% | 8.95% |
| 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
| 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% |
| ShadowIsles | 8.79% | 9.18% | 8.80% | 8.23% |
| 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
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.
Each playrate is stacked upon the other with the decks with the highest overall play-rate (the written value) being at the bottom.
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.
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
Win rates of the most played combination of champions. Play Rate ≥1% in at least one of the servers.
Top Win rates of the top10 best performing least played combination of champions. Play rate ∈[0.11 [^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 ≥ 97.5 Tier1 with LMI ∈[85,97.5) Tier2 with LMI ∈[60,85) Tier3- with LMI < 60
The LMI
1 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. 2
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 | |||
| 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
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 |
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.