Patch 3.13 - Week 1 - When in doubt, Pirate-Aggro them!
Number of Master Players: 2134
Number of HighDiamond 1 Players: 3959
Number of (Ranked) Master matches analysed 80401 or 160802 games.
Number of (Ranked) ~HighDiamond matches analysed 192864 or 385728 games.
Last Update: 2022-08-24 18:22
Patch 3.13 - Week 1 - by the Numbers1 | ||||
---|---|---|---|---|
Characteristic3 | Master2 | ~HighDiamond2 | ||
N = 132,7794 | N = 80,4014 | N = 262,0344 | N = 192,8644 | |
Status | ||||
Ranked | 80,401 (61%) | 192,864 (74%) | ||
Other | 29,449 (22%) | 29,654 (11%) | ||
ThePathOfChampions | 18,461 (14%) | 35,826 (14%) | ||
Friendly Bo3 | 2,871 (2.2%) | 1,324 (0.5%) | ||
Labs | 1,597 (1.2%) | 2,366 (0.9%) | ||
Server | ||||
Americas | 49,419 (37%) | 29,446 (37%) | 92,442 (35%) | 68,254 (35%) |
Apac | 39,568 (30%) | 22,599 (28%) | 83,837 (32%) | 59,073 (31%) |
Europe | 43,792 (33%) | 28,356 (35%) | 85,755 (33%) | 65,537 (34%) |
1 Max datetime recovered: 2022-08-24 14:42:07.124926 UTC from 2022-08-17 18:40:00 to 2022-08-24 18:00:00 UTC | ||||
2 EU Master 734/741 NA Master 790/795 APAC Master 610/615 | ||||
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 |
Shard/Server | Total | |||
---|---|---|---|---|
Americas | Apac | Europe | ||
Player Rank | ||||
Master | 790 (13%) | 610 (10%) | 734 (12%) | 2,134 (35%) |
Diamond | 1,393 (23%) | 1,236 (20%) | 1,330 (22%) | 3,959 (65%) |
Total | 2,183 (36%) | 1,846 (30%) | 2,064 (34%) | 6,093 (100%) |
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.
Region Play Rate | ||||
---|---|---|---|---|
Relative Frequencies by Inclusion Rate of a Region | ||||
Freq | Shard | |||
America | Apac | Europe | ||
Regions | ||||
ShadowIsles | 17.80% | 17.30% | 16.79% | 19.11% |
Shurima | 13.29% | 14.16% | 13.11% | 12.53% |
Bilgewater | 11.24% | 10.27% | 11.37% | 12.13% |
Noxus | 10.67% | 10.54% | 10.66% | 10.80% |
Piltover | 9.82% | 11.04% | 9.80% | 8.59% |
Demacia | 9.13% | 9.80% | 8.47% | 8.96% |
BandleCity | 7.31% | 7.04% | 7.22% | 7.65% |
Freljord | 6.81% | 5.91% | 8.27% | 6.57% |
Ionia | 5.31% | 5.30% | 5.04% | 5.54% |
MtTargon | 4.92% | 5.31% | 5.18% | 4.32% |
Runeterra | ||||
Evelynn | 2.10% | 2.05% | 2.01% | 2.23% |
Jhin | 1.04% | 0.85% | 1.25% | 1.06% |
Bard | 0.57% | 0.42% | 0.82% | 0.52% |
total | 3.71% | 3.32% | 4.08% | 3.81% |
Patch 3.13 - Week 1 Ranked games from 2022-08-17 18:40:00 UTC to 2022-08-24 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-08-24 16:07:31.303097 |
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 | 17.29% | 16.82% | 16.32% | 18.56% |
Shurima | 14.69% | 15.96% | 14.46% | 13.57% |
Bilgewater | 12.25% | 11.23% | 12.36% | 13.23% |
Noxus | 9.52% | 9.47% | 9.50% | 9.58% |
Piltover | 9.02% | 10.13% | 8.97% | 7.90% |
Demacia | 8.47% | 8.95% | 7.76% | 8.55% |
Freljord | 7.30% | 6.06% | 9.11% | 7.16% |
Ionia | 6.85% | 6.96% | 6.74% | 6.82% |
BandleCity | 6.63% | 6.31% | 6.58% | 7.00% |
MtTargon | 4.94% | 5.44% | 4.86% | 4.49% |
Runeterra | 3.03% | 2.68% | 3.33% | 3.15% |
Patch 3.13 - Week 1 Ranked games from 2022-08-17 18:40:00 UTC to 2022-08-24 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-08-24 16:07:31.303097 |
Source: Metadata of games collected with RiotGames API. Last Update: 2022-08-24 16:23:50.25593 FALSE
Source: Metadata of games collected with RiotGames API. Last Update: 2022-08-24 16:23:50.575804 FALSE
Each playrate is stacked upon the other with the decks with the highest overall play-rate (the written value) being at the bottom.
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
Top Win rates of the top10 best performing least played combination of champions. Play rate \(\in [0.1%, 1%)\)
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”.
The win rates on the grid are among the 10 most played champion combination.
WR (WRmeta) | Pirates (BW/NX) | Senna/Veigar (BC/SI) | Akshan/Kai'Sa (DE/SH) | Ezreal/Kennen (IO/PZ) | Trundle Timelines (FR/PZ) | Evelynn/Viego (RU/SI) | Heimerdinger/Jayce (PZ/SI) | Trundle/Tryndamere (FR/SI) | Ekko/Zilean (PZ/SH) | Nami/Twisted Fate (BW/SI) | |
---|---|---|---|---|---|---|---|---|---|---|---|
Pirates (BW/NX) | 56.0%
53.6% |
NA
NA |
46.1%
(42.9% - 49.3%) |
57.5%
(54.4% - 60.5%) |
62.0%
(57.9% - 65.9%) |
56.9%
(52.0% - 61.7%) |
49.3%
(44.6% - 54.0%) |
55.1%
(50.2% - 60.0%) |
40.6%
(35.6% - 45.7%) |
35.6%
(30.3% - 41.1%) |
47.3%
(41.7% - 52.8%) |
Senna/Veigar (BC/SI) | 48.9%
44.8% |
53.9%
(50.7% - 57.1%) |
NA
NA |
37.2%
(33.7% - 40.8%) |
48.9%
(44.0% - 53.8%) |
35.8%
(30.4% - 41.5%) |
52.6%
(46.9% - 58.3%) |
50.4%
(44.2% - 56.6%) |
36.7%
(30.9% - 42.7%) |
57.9%
(51.6% - 63.9%) |
49.4%
(42.9% - 55.9%) |
Akshan/Kai'Sa (DE/SH) | 55.8%
53.6% |
42.5%
(39.5% - 45.6%) |
62.8%
(59.2% - 66.3%) |
NA
NA |
52.4%
(47.1% - 57.7%) |
59.4%
(53.4% - 65.3%) |
50.7%
(45.3% - 56.2%) |
54.6%
(48.5% - 60.6%) |
75.0%
(68.8% - 80.5%) |
51.3%
(44.6% - 58.0%) |
58.4%
(51.8% - 64.9%) |
Ezreal/Kennen (IO/PZ) | 51.6%
48.0% |
38.0%
(34.1% - 42.1%) |
51.1%
(46.2% - 56.0%) |
47.6%
(42.3% - 52.9%) |
NA
NA |
63.5%
(55.5% - 71.0%) |
49.4%
(41.9% - 57.0%) |
48.8%
(40.8% - 56.8%) |
45.7%
(36.8% - 54.7%) |
60.5%
(52.2% - 68.5%) |
50.8%
(41.9% - 59.6%) |
Trundle Timelines (FR/PZ) | 52.8%
50.1% |
43.1%
(38.3% - 48.0%) |
64.2%
(58.5% - 69.6%) |
40.6%
(34.7% - 46.6%) |
36.5%
(29.0% - 44.5%) |
NA
NA |
52.8%
(43.6% - 61.9%) |
50.5%
(40.6% - 60.3%) |
53.7%
(43.8% - 63.3%) |
58.5%
(47.9% - 68.6%) |
52.2%
(41.4% - 62.9%) |
Evelynn/Viego (RU/SI) | 51.0%
48.1% |
50.7%
(46.0% - 55.4%) |
47.4%
(41.7% - 53.1%) |
49.3%
(43.8% - 54.7%) |
50.6%
(43.0% - 58.1%) |
47.2%
(38.1% - 56.4%) |
NA
NA |
44.0%
(34.8% - 53.5%) |
38.6%
(29.6% - 48.2%) |
70.9%
(59.6% - 80.6%) |
33.3%
(23.7% - 44.1%) |
Heimerdinger/Jayce (PZ/SI) | 53.3%
49.0% |
44.9%
(40.0% - 49.8%) |
49.6%
(43.4% - 55.8%) |
45.4%
(39.4% - 51.5%) |
51.2%
(43.2% - 59.2%) |
49.5%
(39.7% - 59.4%) |
56.0%
(46.5% - 65.2%) |
NA
NA |
56.5%
(47.3% - 65.3%) |
54.3%
(43.7% - 64.6%) |
47.2%
(37.5% - 57.1%) |
Trundle/Tryndamere (FR/SI) | 52.7%
50.1% |
59.4%
(54.3% - 64.4%) |
63.3%
(57.3% - 69.1%) |
25.0%
(19.5% - 31.2%) |
54.3%
(45.3% - 63.2%) |
46.3%
(36.7% - 56.2%) |
61.4%
(51.8% - 70.4%) |
43.5%
(34.7% - 52.7%) |
NA
NA |
59.7%
(47.5% - 71.1%) |
56.8%
(45.3% - 67.8%) |
Ekko/Zilean (PZ/SH) | 49.3%
48.9% |
64.4%
(58.9% - 69.7%) |
42.1%
(36.1% - 48.4%) |
48.7%
(42.0% - 55.4%) |
39.5%
(31.5% - 47.8%) |
41.5%
(31.4% - 52.1%) |
29.1%
(19.4% - 40.4%) |
45.7%
(35.4% - 56.3%) |
40.3%
(28.9% - 52.5%) |
NA
NA |
55.7%
(43.3% - 67.6%) |
Nami/Twisted Fate (BW/SI) | 51.8%
48.6% |
52.7%
(47.2% - 58.3%) |
50.6%
(44.1% - 57.1%) |
41.6%
(35.1% - 48.2%) |
49.2%
(40.4% - 58.1%) |
47.8%
(37.1% - 58.6%) |
66.7%
(55.9% - 76.3%) |
52.8%
(42.9% - 62.5%) |
43.2%
(32.2% - 54.7%) |
44.3%
(32.4% - 56.7%) |
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 |