THE META REPORT NAME IS TOO LONG, TOO DAMN LONG (n°64)

Patch 3.9 - Week 2 - Featuring the new meta as special guest

Valentino (Legna) Vazzoler
2022-06-29

Data

Number of Master Players: 2094

Number of HighDiamond 1 Players: 4329

Number of (Ranked) Master matches analysed 53073 or 106146 games.

Number of (Ranked) ~HighDiamond matches analysed 138348 or 276696 games.

Last Update: 2022-06-29 19:09

Games

Patch 3.9 - Week 2 - by the Numbers1
Characteristic3 Master2 ~HighDiamond2
N = 112,5384 N = 64,9884 N = 248,0354 N = 165,7474
Status
Ranked 64,988 (58%) 165,747 (67%)
Other 23,900 (21%) 29,939 (12%)
ThePathOfChampions 22,006 (20%) 50,972 (21%)
Friendly Bo3 1,644 (1.5%) 1,377 (0.6%)
Server
Americas 36,652 (33%) 21,494 (33%) 87,660 (35%) 59,814 (36%)
Apac 37,486 (33%) 19,187 (30%) 77,556 (31%) 49,012 (30%)
Europe 38,400 (34%) 24,307 (37%) 82,819 (33%) 56,921 (34%)
1 Max datetime recovered: 2022-06-29 16:14:01.69833 UTC from 2022-06-22 18:00:00 to 2022-06-29 18:00:00 UTC
2 EU Master 731/734 NA Master 741/745 APAC Master 622/622
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 Unknown
Player Rank
Master 741 (12%) 622 (9.7%) 731 (11%) 0 (0%) 2,094 (33%)
Diamond 1,589 (25%) 1,289 (20%) 1,450 (23%) 1 (<0.1%) 4,329 (67%)
Total 2,330 (36%) 1,911 (30%) 2,181 (34%) 1 (<0.1%) 6,423 (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
Piltover 15.16% 16.04% 15.11% 14.45%
Noxus 12.28% 11.46% 10.98% 14.03%
Shurima 11.53% 12.26% 11.70% 10.77%
ShadowIsles 10.35% 9.99% 11.05% 10.10%
Demacia 8.76% 8.52% 8.53% 9.16%
Bilgewater 6.96% 6.87% 7.04% 6.96%
Freljord 6.78% 6.45% 7.01% 6.88%
MtTargon 6.62% 7.61% 7.12% 5.36%
Ionia 5.82% 5.57% 6.00% 5.89%
BandleCity 4.26% 4.14% 4.29% 4.34%
Runeterra
Bard 9.82% 9.74% 9.75% 9.94%
Jhin 1.66% 1.35% 1.40% 2.13%
total 11.48% 11.09% 11.15% 12.07%
Patch 3.9 - Week 2 Ranked games from 2022-06-22 18:00:00 UTC to 2022-06-29 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-06-29 17:08:41.163717

Plot (New Patch)

Table (New Patch)

Region Play Rate
Relative Frequencies by Inclusion Rate of a Region
Freq Shard
America Apac Europe
Regions
ShadowIsles 14.09% 14.03% 14.39% 13.95%
Piltover 12.99% 13.77% 13.12% 12.16%
Noxus 12.67% 13.71% 10.45% 13.22%
Ionia 11.06% 10.01% 10.14% 12.68%
Shurima 10.54% 9.15% 11.33% 11.30%
Bilgewater 8.74% 8.91% 8.16% 8.97%
Freljord 6.12% 6.34% 5.78% 6.13%
Demacia 5.92% 5.55% 7.09% 5.46%
MtTargon 4.92% 5.29% 5.13% 4.43%
BandleCity 4.56% 5.11% 5.10% 3.66%
Runeterra
Bard 6.36% 6.40% 7.05% 5.84%
Jhin 2.04% 1.72% 2.25% 2.20%
total 8.40% 8.13% 9.30% 8.04%
Patch 3.9 - Week 2 Ranked games from 2022-06-22 18:00:00 UTC to 2022-06-29 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-06-29 17:08:41.163717

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 16.17% 16.46% 16.15% 15.93%
Shurima 13.80% 14.90% 14.55% 12.22%
Demacia 11.80% 11.67% 11.70% 12.01%
Noxus 11.25% 10.73% 9.88% 12.80%
ShadowIsles 8.81% 8.53% 9.61% 8.41%
Ionia 7.88% 7.25% 8.11% 8.23%
Bilgewater 7.46% 7.44% 7.49% 7.46%
Freljord 6.60% 6.36% 6.68% 6.73%
MtTargon 6.06% 6.94% 6.22% 5.17%
Runeterra 5.96% 5.40% 5.50% 6.82%
BandleCity 4.21% 4.32% 4.10% 4.22%
Patch 3.9 - Week 2 Ranked games from 2022-06-22 18:00:00 UTC to 2022-06-29 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-06-29 17:08:41.163717

Plot (New Patch)

Table (New Patch)

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 14.72% 15.13% 15.04% 14.11%
ShadowIsles 13.83% 14.00% 13.61% 13.82%
Ionia 12.79% 11.59% 11.52% 14.82%
Noxus 11.79% 13.19% 9.23% 12.24%
Shurima 10.74% 9.64% 11.91% 10.96%
Bilgewater 8.97% 9.05% 8.66% 9.11%
Demacia 6.68% 5.98% 8.60% 6.01%
Freljord 6.11% 6.36% 6.02% 5.94%
Runeterra 5.24% 4.77% 5.78% 5.30%
BandleCity 4.59% 5.19% 5.01% 3.72%
MtTargon 4.54% 5.08% 4.64% 3.96%
Patch 3.9 - Week 2 Ranked games from 2022-06-22 18:00:00 UTC to 2022-06-29 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-06-29 17:08:41.163717

Champions Combinations (~Old Patch)

Play Rates

Plot

from Master

Source: Metadata of games collected with RiotGames API. Last Update: 2022-06-29 17:10:33.65925 FALSE

from Diamond

Source: Metadata of games collected with RiotGames API. Last Update: 2022-06-29 17:10:33.897011 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

The stacked plots are “more interesting” this week as they easily show the shift from the “old meta to the new one” but in term of absolute number of games being played and regarding with which decks.

Win Rates

For the rest of the report only the data pre-patch will be used

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.

Bard/Poppy (DE/RU) Lissandra/Taliyah (FR/SH) Ahri/Bard (IO/RU) Nami/Twisted Fate (BW/SI) Annie/Ezreal (NX/PZ) Akshan (PZ/SH) Camavoran Deserter SunDisc Annie/Jhin (NX/RU) Heimerdinger/Jayce (PZ/SI)
Bard/Poppy (DE/RU)
NA
NA
52.4%
(48.3% - 56.5%)
53.6%
(49.5% - 57.7%)
51.5%
(46.2% - 56.8%)
53.2%
(47.6% - 58.7%)
68.0%
(62.4% - 73.2%)
45.3%
(39.2% - 51.5%)
53.7%
(47.6% - 59.7%)
71.4%
(65.3% - 76.9%)
39.3%
(33.4% - 45.5%)
Lissandra/Taliyah (FR/SH)
47.6%
(43.5% - 51.7%)
NA
NA
42.1%
(37.6% - 46.6%)
56.0%
(50.2% - 61.8%)
71.3%
(65.5% - 76.5%)
47.9%
(41.4% - 54.4%)
43.9%
(37.5% - 50.5%)
45.9%
(38.9% - 52.9%)
39.8%
(32.9% - 47.0%)
65.7%
(58.7% - 72.2%)
Ahri/Bard (IO/RU)
46.4%
(42.3% - 50.5%)
57.9%
(53.4% - 62.4%)
NA
NA
55.6%
(49.3% - 61.8%)
51.4%
(45.5% - 57.3%)
61.2%
(54.4% - 67.7%)
75.5%
(69.5% - 80.9%)
64.9%
(57.8% - 71.4%)
33.2%
(26.9% - 39.9%)
61.5%
(54.6% - 68.2%)
Nami/Twisted Fate (BW/SI)
48.5%
(43.2% - 53.8%)
44.0%
(38.2% - 49.8%)
44.4%
(38.2% - 50.7%)
NA
NA
71.4%
(63.6% - 78.4%)
42.5%
(34.5% - 50.7%)
59.3%
(50.7% - 67.5%)
38.9%
(30.3% - 48.0%)
56.8%
(47.3% - 65.9%)
54.1%
(45.3% - 62.8%)
Annie/Ezreal (NX/PZ)
46.8%
(41.3% - 52.4%)
28.7%
(23.5% - 34.5%)
48.6%
(42.7% - 54.5%)
28.6%
(21.6% - 36.4%)
NA
NA
63.0%
(55.2% - 70.4%)
63.0%
(54.4% - 71.1%)
32.3%
(24.3% - 41.2%)
57.9%
(48.3% - 67.1%)
34.7%
(25.5% - 44.8%)
Akshan (PZ/SH)
32.0%
(26.8% - 37.6%)
52.1%
(45.6% - 58.6%)
38.8%
(32.3% - 45.6%)
57.5%
(49.3% - 65.5%)
37.0%
(29.6% - 44.8%)
NA
NA
59.8%
(49.6% - 69.4%)
52.7%
(43.0% - 62.2%)
15.5%
(9.3% - 23.6%)
39.1%
(29.1% - 49.9%)
Camavoran Deserter
54.7%
(48.5% - 60.8%)
56.1%
(49.5% - 62.5%)
24.5%
(19.1% - 30.5%)
40.7%
(32.5% - 49.3%)
37.0%
(28.9% - 45.6%)
40.2%
(30.6% - 50.4%)
NA
NA
58.4%
(48.8% - 67.6%)
53.8%
(43.1% - 64.2%)
40.6%
(30.9% - 50.8%)
SunDisc
46.3%
(40.3% - 52.4%)
54.1%
(47.1% - 61.1%)
35.1%
(28.6% - 42.2%)
61.1%
(52.0% - 69.7%)
67.7%
(58.8% - 75.7%)
47.3%
(37.8% - 57.0%)
41.6%
(32.4% - 51.2%)
NA
NA
20.0%
(11.9% - 30.4%)
57.7%
(46.0% - 68.8%)
Annie/Jhin (NX/RU)
28.6%
(23.1% - 34.7%)
60.2%
(53.0% - 67.1%)
66.8%
(60.1% - 73.1%)
43.2%
(34.1% - 52.7%)
42.1%
(32.9% - 51.7%)
84.5%
(76.4% - 90.7%)
46.2%
(35.8% - 56.9%)
80.0%
(69.6% - 88.1%)
NA
NA
31.8%
(22.3% - 42.6%)
Heimerdinger/Jayce (PZ/SI)
60.7%
(54.5% - 66.6%)
34.3%
(27.8% - 41.3%)
38.5%
(31.8% - 45.4%)
45.9%
(37.2% - 54.7%)
65.3%
(55.2% - 74.5%)
60.9%
(50.1% - 70.9%)
59.4%
(49.2% - 69.1%)
42.3%
(31.2% - 54.0%)
68.2%
(57.4% - 77.7%)
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