THE META REPORT NAME IS TOO LONG, TOO DAMN LONG (n°72)

Patch 3.13 - Week 1 - When in doubt, Pirate-Aggro them!

Valentino (Legna) Vazzoler
2022-08-24

Data

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

Games

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

Account

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%)

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 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

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 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

Champions Combinations

Play Rates

Plot

from Master

Source: Metadata of games collected with RiotGames API. Last Update: 2022-08-24 16:23:50.25593 FALSE

from Diamond

Source: Metadata of games collected with RiotGames API. Last Update: 2022-08-24 16:23:50.575804 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) 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