Data
Number of Master Players: 3534
Number of HighDiamond 1 Players: 6155
Number of (Ranked) Master matches analysed 94462 or 188924 games.
Number of (Ranked) ~HighDiamond matches analysed 199477 or 398954 games.
Last Update: 2022-04-14 05:37
Games
| Patch 3.4 - Week 2 - by the Numbers1 | ||||
|---|---|---|---|---|
| Characteristic3 | Master2 | ~HighDiamond2 | ||
| N = 175,9494 | N = 94,4624 | N = 299,4374 | N = 199,4774 | |
| Status | ||||
| Ranked | 94,462 (54%) | 199,477 (67%) | ||
| Other | 52,946 (30%) | 57,907 (19%) | ||
| PathOfChampion | 20,843 (12%) | 30,699 (10%) | ||
| Friendly | 7,698 (4.4%) | 11,354 (3.8%) | ||
| Server | ||||
| americas | 67,346 (38%) | 35,449 (38%) | 114,856 (38%) | 76,520 (38%) |
| apac | 53,775 (31%) | 27,931 (30%) | 89,987 (30%) | 57,709 (29%) |
| europe | 54,828 (31%) | 31,082 (33%) | 94,594 (32%) | 65,248 (33%) |
| 1 Max datetime recovered: 2022-04-13 17:59:57 UTC from 2022-04-06 18:00:00 to 2022-04-13 18:00:00 UTC | ||||
| 2 EU Master 1120/1121 NA Master 1290/1291 APAC Master 1081/1082 | ||||
| 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
| Characteristic | Shard/Server | Total | ||
|---|---|---|---|---|
| Americas | Apac | Europe | ||
| Player Rank | ||||
| Master | 1,308 (13%) | 1,091 (11%) | 1,135 (12%) | 3,534 (36%) |
| Diamond | 2,341 (24%) | 1,814 (19%) | 2,000 (21%) | 6,155 (64%) |
| Total | 3,649 (38%) | 2,905 (30%) | 3,135 (32%) | 9,689 (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 | ||||
| Region | Freq | Shard | ||
| America | Apac | Europe | ||
| Piltover | 20.76% | 20.34% | 21.57% | 20.51% |
| Shurima | 16.28% | 17.26% | 17.71% | 13.93% |
| Noxus | 12.96% | 11.85% | 13.59% | 13.65% |
| MtTargon | 9.78% | 9.54% | 9.84% | 9.99% |
| BandleCity | 8.99% | 10.28% | 7.97% | 8.43% |
| ShadowIsles | 7.70% | 6.35% | 8.48% | 8.54% |
| Freljord | 7.01% | 5.93% | 6.64% | 8.55% |
| Demacia | 6.24% | 6.14% | 5.54% | 6.96% |
| Ionia | 5.21% | 6.22% | 4.52% | 4.70% |
| Bilgewater | 5.08% | 6.10% | 4.14% | 4.74% |
| Patch 3.4 - Week 2 Ranked games from 2022-04-06 18:00:00 UTC to 2022-04-13 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-04-14 03:34:58.988477 | ||||
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 | ||||
| Region | Freq | Shard | ||
| America | Apac | Europe | ||
| Shurima | 22.70% | 24.25% | 24.65% | 19.18% |
| Piltover | 21.52% | 20.29% | 22.61% | 21.94% |
| Noxus | 10.16% | 9.44% | 10.59% | 10.59% |
| MtTargon | 9.48% | 9.51% | 9.07% | 9.83% |
| BandleCity | 8.36% | 9.30% | 7.55% | 8.00% |
| Freljord | 7.19% | 5.90% | 6.76% | 9.05% |
| Demacia | 6.01% | 5.81% | 5.20% | 6.97% |
| ShadowIsles | 5.52% | 4.85% | 5.79% | 6.04% |
| Ionia | 5.04% | 5.97% | 4.46% | 4.49% |
| Bilgewater | 4.03% | 4.69% | 3.32% | 3.91% |
| Patch 3.4 - Week 2 Ranked games from 2022-04-06 18:00:00 UTC to 2022-04-13 18:00:00 UTC Source: Metadata of games collected with RiotGames API Last Update: 2022-04-14 03:34:58.988477 | ||||
Champions Combinations
Play Rates
Plot
from Master
Data from Master Only. Source: Metadata of games collected with RiotGames API. Last Update: 2022-04-14 03:38:16.867516 FALSE
from ~HighDiamond
Data from ~HighDiamond Only. Source: Metadata of games collected with RiotGames API Last Update: 2022-04-14 03:38:17.134265. FALSE
Day by Day
Highlighting the play-rates of most played [^at the moment of the last game] decks over time.
Master
HighDiamond
Win Rates
Meta Decks
Win rates of the most played combination of champions. Play Rate \(\geq 1\%\) in at least one of the servers.
Underdog
Top Win rates of the top10 best performing least played combination of champions. Play rate \(\in [0.1%,1%)\) [^Min number of games 50, during the times a meta/ladder just changed]
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.
The upper value is from all the Masters players, the bottom one only from HighDiamond.
MU with less than 30 games are not included.
| SunDisc | Tri-Beam (NX/PZ) | Riven/Viktor | Fizz/Lulu (BC/PZ) | Taliyah/Ziggs | Aphelios/Viktor | Lee Sin/Viktor | Pantheon/Yuumi (DE/MT) | Miss Fortune/Quinn | Trundle/Tryndamere (FR/SI) | |
|---|---|---|---|---|---|---|---|---|---|---|
| SunDisc | NA
|
65.3%
63.4% |
37.1%
36.2% |
40.7%
42.3% |
45.2%
43.7% |
48.9%
51.1% |
47.9%
45.6% |
43.4%
42.1% |
47.3%
45.8% |
59.5%
58.7% |
| Tri-Beam (NX/PZ) | 34.7%
36.6% |
NA
|
53.0%
57.9% |
50.2%
54.5% |
35.2%
37.1% |
51.4%
53.7% |
49.5%
54.0% |
51.1%
59.4% |
57.6%
61.0% |
22.8%
20.4% |
| Riven/Viktor | 62.9%
63.8% |
47.0%
42.1% |
NA
|
42.9%
47.7% |
61.3%
59.4% |
38.5%
41.7% |
51.3%
47.8% |
41.7%
45.1% |
47.8%
42.5% |
55.7%
54.3% |
| Fizz/Lulu (BC/PZ) | 59.3%
57.7% |
49.8%
45.5% |
57.1%
52.3% |
NA
|
56.7%
54.3% |
51.4%
41.8% |
36.5%
43.7% |
62.1%
63.0% |
52.7%
47.6% |
45.2%
38.6% |
| Taliyah/Ziggs | 54.8%
56.3% |
64.8%
62.9% |
38.7%
40.6% |
43.3%
45.7% |
NA
|
55.7%
56.6% |
43.6%
47.9% |
43.1%
46.5% |
45.5%
46.8% |
54.5%
53.1% |
| Aphelios/Viktor | 51.1%
48.9% |
48.6%
46.3% |
61.5%
58.3% |
48.6%
58.2% |
44.3%
43.4% |
NA
|
49.7%
46.7% |
56.4%
47.2% |
49.6%
48.7% |
52.7%
52.2% |
| Lee Sin/Viktor | 52.1%
54.4% |
50.5%
46.0% |
48.7%
52.2% |
63.5%
56.3% |
56.4%
52.1% |
50.3%
53.3% |
NA
|
39.9%
46.5% |
36.0%
35.4% |
80.2%
71.7% |
| Pantheon/Yuumi (DE/MT) | 56.6%
57.9% |
48.9%
40.6% |
58.3%
54.9% |
37.9%
37.0% |
56.9%
53.5% |
43.6%
52.8% |
60.1%
53.5% |
NA
|
67.7%
66.8% |
53.5%
54.3% |
| Miss Fortune/Quinn | 52.7%
54.2% |
42.4%
39.0% |
52.2%
57.5% |
47.3%
52.4% |
54.5%
53.2% |
50.4%
51.3% |
64.0%
64.6% |
32.3%
33.2% |
NA
|
56.5%
53.9% |
| Trundle/Tryndamere (FR/SI) | 40.5%
41.3% |
77.2%
79.6% |
44.3%
45.7% |
54.8%
61.4% |
45.5%
46.9% |
47.3%
47.8% |
19.8%
28.3% |
46.5%
45.7% |
43.5%
46.1% |
NA
|
| MatchUp values from Ranked games with Master (upper) and ~HighDiamond (bottom) Ranked players. Decks and order of the Archetypes based on the playrate over the last 7 days. Source: Metadata of games collected with RiotGames API | ||||||||||