THE META REPORT NAME IS TOO LONG, TOO DAMN LONG (n°62)

Patch 3.8 - Week 3 - LoR Twitter: bla bla game dead, bla bla deck tracker, bla bla Rito nerf this deck

Valentino (Legna) Vazzoler
2022-06-15

Data

Number of Master Players: 1185

Number of HighDiamond 1 Players: 2897

Number of (Ranked) Master matches analysed 39607 or 79214 games.

Number of (Ranked) ~HighDiamond matches analysed 124485 or 248970 games.

Last Update: 2022-06-19 07:30

Games

Patch 3.8 - Week 3 - by the Numbers1
Characteristic3 Master2 ~HighDiamond2
N = 59,2864 N = 39,6074 N = 169,9864 N = 124,4854
Status
Ranked 39,607 (67%) 124,485 (73%)
Other 9,456 (16%) 15,905 (9.4%)
ThePathOfChampions 8,576 (14%) 28,217 (17%)
Friendly Bo3 1,647 (2.8%) 1,379 (0.8%)
Server
Americas 19,263 (32%) 12,809 (32%) 60,633 (36%) 43,625 (35%)
Apac 19,475 (33%) 11,864 (30%) 57,375 (34%) 40,327 (32%)
Europe 20,548 (35%) 14,934 (38%) 51,978 (31%) 40,533 (33%)
1 Max datetime recovered: 2022-06-19 04:08:07.772338 UTC from 2022-06-08 18:00:00 to 2022-06-15 18:00:00 UTC
2 EU Master 403/403 NA Master 420/421 APAC Master 362/366
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 420 (10%) 362 (8.9%) 403 (9.9%) 1,185 (29%)
Diamond 1,063 (26%) 873 (21%) 961 (24%) 2,897 (71%)
Total 1,483 (36%) 1,235 (30%) 1,364 (33%) 4,082 (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 16.24% 15.74% 14.92% 17.71%
Piltover 14.05% 12.48% 15.36% 14.37%
Shurima 13.11% 13.61% 14.31% 11.75%
ShadowIsles 12.25% 12.35% 11.94% 12.40%
Freljord 7.70% 8.28% 7.57% 7.31%
MtTargon 7.21% 7.44% 8.13% 6.28%
Demacia 7.09% 7.99% 7.31% 6.15%
Bilgewater 5.76% 5.89% 7.04% 4.64%
BandleCity 5.13% 4.49% 4.45% 6.21%
Ionia 3.10% 3.86% 2.50% 2.94%
Runeterra
Bard 5.98% 5.72% 4.83% 7.10%
Jhin 2.36% 2.14% 1.62% 3.14%
total 8.34% 7.86% 6.45% 10.24%
Patch 3.8 - Week 3 Ranked games from 2022-06-08 18:00:00 UTC to 2022-06-15 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-06-19 05:30:01.234702

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
Piltover 15.64% 13.89% 16.45% 16.50%
Shurima 15.31% 15.60% 16.86% 13.83%
Noxus 14.24% 14.04% 12.97% 15.41%
ShadowIsles 11.24% 11.52% 11.28% 10.96%
Demacia 8.78% 9.78% 8.93% 7.81%
Freljord 7.67% 7.94% 7.24% 7.79%
MtTargon 6.81% 7.24% 7.39% 5.99%
Bilgewater 5.75% 5.96% 6.99% 4.58%
Runeterra 5.71% 5.20% 4.34% 7.23%
BandleCity 5.21% 4.43% 4.67% 6.31%
Ionia 3.64% 4.40% 2.87% 3.59%
Patch 3.8 - Week 3 Ranked games from 2022-06-08 18:00:00 UTC to 2022-06-15 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-06-19 05:30:01.234702

Champions Combinations

Play Rates

Plot

from Master

Source: Metadata of games collected with RiotGames API. Last Update: 2022-06-19 05:31:15.52542 FALSE

from Diamond

Source: Metadata of games collected with RiotGames API. Last Update: 2022-06-19 05:31:15.788045 FALSE

Day by day

Hourly/Dialy lines

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

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.

Lissandra/Taliyah (FR/SH) Camavoran Deserter Annie/Elise (NX/SI) Annie/Jhin (NX/RU) Fizz/Riven (BC/NX) Heimerdinger/Jayce (PZ/SI) Aphelios/Zoe (MT/PZ) Bard/Galio (DE/RU) SunDisc Aphelios/Viktor (MT/PZ)
Lissandra/Taliyah (FR/SH)
NA
NA
42.7%
(38.4% - 47.2%)
62.8%
(56.2% - 69.1%)
38.6%
(33.1% - 44.5%)
48.9%
(42.8% - 55.0%)
60.8%
(54.5% - 66.7%)
65.8%
(58.7% - 72.4%)
58.8%
(52.4% - 65.1%)
46.3%
(39.3% - 53.4%)
44.3%
(35.9% - 52.9%)
Camavoran Deserter
57.3%
(52.8% - 61.6%)
NA
NA
48.7%
(40.7% - 56.8%)
58.0%
(51.5% - 64.3%)
40.6%
(34.5% - 46.9%)
39.8%
(33.1% - 46.8%)
34.8%
(28.6% - 41.5%)
56.2%
(49.3% - 62.9%)
57.1%
(49.6% - 64.4%)
50.7%
(42.0% - 59.5%)
Annie/Elise (NX/SI)
37.2%
(30.9% - 43.8%)
51.3%
(43.2% - 59.3%)
NA
NA
73.6%
(65.2% - 81.0%)
46.5%
(37.1% - 56.1%)
42.0%
(32.2% - 52.3%)
58.8%
(48.3% - 68.7%)
21.0%
(12.7% - 31.5%)
35.6%
(25.6% - 46.6%)
43.1%
(30.8% - 56.0%)
Annie/Jhin (NX/RU)
61.4%
(55.5% - 66.9%)
42.0%
(35.7% - 48.5%)
26.4%
(19.0% - 34.8%)
NA
NA
53.4%
(45.0% - 61.6%)
34.6%
(26.4% - 43.6%)
37.0%
(27.9% - 46.9%)
37.1%
(27.9% - 47.1%)
76.3%
(66.4% - 84.5%)
39.7%
(28.5% - 51.9%)
Fizz/Riven (BC/NX)
51.1%
(45.0% - 57.2%)
59.4%
(53.1% - 65.5%)
53.5%
(43.9% - 62.9%)
46.6%
(38.4% - 55.0%)
NA
NA
66.7%
(57.7% - 74.8%)
48.3%
(39.0% - 57.7%)
48.7%
(39.5% - 58.1%)
60.6%
(51.6% - 69.2%)
40.3%
(28.5% - 53.0%)
Heimerdinger/Jayce (PZ/SI)
39.2%
(33.3% - 45.5%)
60.2%
(53.2% - 66.9%)
58.0%
(47.7% - 67.8%)
65.4%
(56.4% - 73.6%)
33.3%
(25.2% - 42.3%)
NA
NA
53.2%
(43.4% - 62.7%)
45.2%
(35.9% - 54.8%)
41.5%
(30.7% - 52.9%)
57.1%
(43.2% - 70.3%)
Aphelios/Zoe (MT/PZ)
34.2%
(27.6% - 41.3%)
65.2%
(58.5% - 71.4%)
41.2%
(31.3% - 51.7%)
63.0%
(53.1% - 72.1%)
51.7%
(42.3% - 61.0%)
46.8%
(37.3% - 56.6%)
NA
NA
41.7%
(32.7% - 51.0%)
62.1%
(51.6% - 71.9%)
45.8%
(31.4% - 60.8%)
Bard/Galio (DE/RU)
41.2%
(34.9% - 47.6%)
43.8%
(37.1% - 50.7%)
79.0%
(68.5% - 87.3%)
62.9%
(52.9% - 72.1%)
51.3%
(41.9% - 60.5%)
54.8%
(45.2% - 64.1%)
58.3%
(49.0% - 67.3%)
NA
NA
37.7%
(26.3% - 50.2%)
56.6%
(42.3% - 70.2%)
SunDisc
53.7%
(46.6% - 60.7%)
42.9%
(35.6% - 50.4%)
64.4%
(53.4% - 74.4%)
23.7%
(15.5% - 33.6%)
39.4%
(30.8% - 48.4%)
58.5%
(47.1% - 69.3%)
37.9%
(28.1% - 48.4%)
62.3%
(49.8% - 73.7%)
NA
NA
41.5%
(28.1% - 55.9%)
Aphelios/Viktor (MT/PZ)
55.7%
(47.1% - 64.1%)
49.3%
(40.5% - 58.0%)
56.9%
(44.0% - 69.2%)
60.3%
(48.1% - 71.5%)
59.7%
(47.0% - 71.5%)
42.9%
(29.7% - 56.8%)
54.2%
(39.2% - 68.6%)
43.4%
(29.8% - 57.7%)
58.5%
(44.1% - 71.9%)
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