Data
Number of (Prev) Seasonal Players used: 2415
Number of (Ranked) matches analysed 127058 or 254116 games.
Last Update: 2022-06-08 21:27
Games
| Patch 3.8 - Week 2 - by the Numbers1 | ||
|---|---|---|
| Characteristic | All Games2 | Ranked2 |
| N = 211,1723 | N = 127,0583 | |
| Status | ||
| Ranked | 127,058 (60%) | |
| ThePathOfChampions | 57,966 (27%) | |
| Other | 23,353 (11%) | |
| Friendly Bo3 | 2,795 (1.3%) | |
| Server | ||
| Americas | 83,032 (39%) | 48,201 (38%) |
| Apac | 56,173 (27%) | 32,879 (26%) |
| Europe | 71,967 (34%) | 45,978 (36%) |
| 1 Max datetime recovered: 2022-06-08 17:59:57.999166 UTC from 2022-06-01 18:00:00 to 2022-06-08 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 (%) | ||
Account
| Shard/Server | Total | |||
|---|---|---|---|---|
| Americas | Apac | Europe | ||
| Player Rank | ||||
| Seasonal | 946 (39%) | 653 (27%) | 816 (34%) | 2,415 (100%) |
| Total | 946 (39%) | 653 (27%) | 816 (34%) | 2,415 (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 | ||||
| Noxus | 17.26% | 15.93% | 17.95% | 18.17% |
| ShadowIsles | 12.21% | 12.17% | 12.87% | 11.78% |
| Piltover | 10.86% | 10.62% | 10.87% | 11.11% |
| Shurima | 10.21% | 10.70% | 11.26% | 8.94% |
| Demacia | 8.60% | 8.69% | 8.48% | 8.60% |
| Freljord | 8.19% | 8.46% | 8.51% | 7.69% |
| Bilgewater | 8.14% | 8.75% | 8.37% | 7.34% |
| MtTargon | 6.38% | 6.89% | 6.25% | 5.93% |
| BandleCity | 4.21% | 4.45% | 4.24% | 3.94% |
| Ionia | 4.11% | 4.13% | 3.46% | 4.54% |
| Runeterra | ||||
| Bard | 6.29% | 6.07% | 4.87% | 7.54% |
| Jhin | 3.54% | 3.14% | 2.88% | 4.42% |
| total | 9.82% | 9.21% | 7.75% | 11.96% |
| Patch 3.8 - Week 2 Ranked games from 2022-06-01 18:00:00 UTC to 2022-06-08 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-06-08 19:25:36.19328 | ||||
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 | ||||
| Noxus | 14.86% | 14.01% | 15.29% | 15.45% |
| ShadowIsles | 12.32% | 12.01% | 13.47% | 11.84% |
| Piltover | 11.59% | 11.63% | 11.22% | 11.81% |
| Shurima | 11.48% | 11.85% | 12.75% | 10.18% |
| Demacia | 10.24% | 10.34% | 9.87% | 10.39% |
| Freljord | 8.46% | 8.66% | 8.45% | 8.26% |
| Bilgewater | 8.00% | 8.59% | 8.06% | 7.33% |
| Runeterra | 7.53% | 6.86% | 6.08% | 9.25% |
| MtTargon | 6.03% | 6.52% | 5.77% | 5.70% |
| Ionia | 5.04% | 4.90% | 4.20% | 5.78% |
| BandleCity | 4.46% | 4.63% | 4.85% | 4.00% |
| Patch 3.8 - Week 2 Ranked games from 2022-06-01 18:00:00 UTC to 2022-06-08 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-06-08 19:25:36.19328 | ||||
Champions Combinations
Play Rates
Plot
Table
Source: Metadata of games collected with RiotGames API. Last Update: 2022-06-08 19:28:34.660805 FALSE
Day by day
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 Playrates
Game by game
An “updated” version of the old format. I don’t really find it useful (a bit cool, but not useful) and still most likely leave it
It display both daily aggregated data and hourly (background) data
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.
| Camavoran Deserter | Lissandra/Taliyah (FR/SH) | Annie/Jhin (NX/RU) | Annie/Ezreal (NX/PZ) | Bard/Galio (DE/RU) | Bard/Zed (IO/RU) | Illaoi/Jarvan IV (BW/DE) | Aphelios/Zoe (MT/PZ) | Maokai/Nautilus (BW/SI) | Pyke/Rek'Sai (BW/SH) | |
|---|---|---|---|---|---|---|---|---|---|---|
| Camavoran Deserter | NA
NA |
52.2%
(50.1% - 54.3%) |
55.6%
(53.0% - 58.1%) |
42.2%
(39.0% - 45.3%) |
54.2%
(50.6% - 57.7%) |
55.0%
(51.5% - 58.4%) |
63.8%
(60.3% - 67.1%) |
45.8%
(41.8% - 49.9%) |
55.3%
(51.3% - 59.1%) |
56.4%
(52.1% - 60.6%) |
| Lissandra/Taliyah (FR/SH) | 47.8%
(45.7% - 49.9%) |
NA
NA |
37.0%
(34.3% - 39.7%) |
65.5%
(62.2% - 68.6%) |
57.4%
(54.0% - 60.7%) |
54.9%
(51.1% - 58.7%) |
37.9%
(34.4% - 41.6%) |
69.0%
(65.1% - 72.8%) |
57.0%
(52.6% - 61.3%) |
46.5%
(42.2% - 50.8%) |
| Annie/Jhin (NX/RU) | 44.4%
(41.9% - 47.0%) |
63.0%
(60.3% - 65.7%) |
NA
NA |
42.0%
(37.9% - 46.1%) |
39.5%
(35.4% - 43.7%) |
60.8%
(56.6% - 64.8%) |
42.1%
(37.7% - 46.7%) |
34.3%
(29.3% - 39.6%) |
51.2%
(46.0% - 56.3%) |
51.5%
(46.0% - 56.8%) |
| Annie/Ezreal (NX/PZ) | 57.8%
(54.7% - 61.0%) |
34.5%
(31.4% - 37.8%) |
58.0%
(53.9% - 62.1%) |
NA
NA |
37.9%
(32.4% - 43.6%) |
58.5%
(53.3% - 63.6%) |
48.3%
(42.7% - 53.9%) |
41.4%
(35.4% - 47.7%) |
43.0%
(36.6% - 49.7%) |
58.2%
(51.6% - 64.6%) |
| Bard/Galio (DE/RU) | 45.8%
(42.3% - 49.4%) |
42.6%
(39.3% - 46.0%) |
60.5%
(56.3% - 64.6%) |
62.1%
(56.4% - 67.6%) |
NA
NA |
51.5%
(45.6% - 57.4%) |
53.7%
(47.4% - 59.9%) |
57.4%
(51.5% - 63.2%) |
57.7%
(50.4% - 64.8%) |
54.3%
(47.3% - 61.2%) |
| Bard/Zed (IO/RU) | 45.0%
(41.6% - 48.5%) |
45.1%
(41.3% - 48.9%) |
39.2%
(35.2% - 43.4%) |
41.5%
(36.4% - 46.7%) |
48.5%
(42.6% - 54.4%) |
NA
NA |
51.2%
(45.4% - 56.9%) |
39.7%
(32.8% - 46.9%) |
47.4%
(40.9% - 54.0%) |
54.2%
(46.6% - 61.7%) |
| Illaoi/Jarvan IV (BW/DE) | 36.2%
(32.9% - 39.7%) |
62.1%
(58.4% - 65.6%) |
57.9%
(53.3% - 62.3%) |
51.7%
(46.1% - 57.3%) |
46.3%
(40.1% - 52.6%) |
48.8%
(43.1% - 54.6%) |
NA
NA |
47.9%
(40.2% - 55.7%) |
57.8%
(51.1% - 64.4%) |
46.7%
(39.6% - 53.9%) |
| Aphelios/Zoe (MT/PZ) | 54.2%
(50.1% - 58.2%) |
31.0%
(27.2% - 34.9%) |
65.7%
(60.4% - 70.7%) |
58.6%
(52.3% - 64.6%) |
42.6%
(36.8% - 48.5%) |
60.3%
(53.1% - 67.2%) |
52.1%
(44.3% - 59.8%) |
NA
NA |
54.0%
(45.3% - 62.4%) |
63.0%
(54.8% - 70.6%) |
| Maokai/Nautilus (BW/SI) | 44.7%
(40.9% - 48.7%) |
43.0%
(38.7% - 47.4%) |
48.8%
(43.7% - 54.0%) |
57.0%
(50.3% - 63.4%) |
42.3%
(35.2% - 49.6%) |
52.6%
(46.0% - 59.1%) |
42.2%
(35.6% - 48.9%) |
46.0%
(37.6% - 54.7%) |
NA
NA |
45.3%
(36.9% - 54.0%) |
| Pyke/Rek'Sai (BW/SH) | 43.6%
(39.4% - 47.9%) |
53.5%
(49.2% - 57.8%) |
48.5%
(43.2% - 54.0%) |
41.8%
(35.4% - 48.4%) |
45.7%
(38.8% - 52.7%) |
45.8%
(38.3% - 53.4%) |
53.3%
(46.1% - 60.4%) |
37.0%
(29.4% - 45.2%) |
54.7%
(46.0% - 63.1%) |
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 \(\geq\) 97.5 Tier1 with LMI \(\in [85, 97.5)\) Tier2 with LMI \(\in [60, 85)\) Tier3- with LMI \(<\) 60
The LMI 1 2 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 |