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MSIRanking — Overall
Play VSTick two checkboxes to compare them
| # | Name | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | 70 | 58 | 84 | 64 | 48 | 84 | 84 | ||
| 2 | 61 | 54 | 69 | 57 | 55 | 70 | 58 | ||
| 3 | 60 | 53 | 69 | 50 | 51 | 60 | 77 | ||
| 4 | 56 | 52 | 44 | 50 | 77 | 52 | 62 | ||
| 5 | 55 | 46 | 54 | 60 | 55 | 61 | 54 | ||
| 6 | 53 | 59 | 52 | 52 | 53 | 52 | 50 | ||
| 7 | 53 | 48 | 50 | 45 | 59 | 48 | 68 | ||
| 8 | 52 | 64 | 43 | 62 | 64 | 40 | 40 | ||
| 9 | 51 | 67 | 49 | 61 | 45 | 48 | 37 | ||
| 10 | 42 | 46 | 42 | 46 | 43 | 40 | 34 |
- Mechanics58Laning84Teamfighting64Macro48Consistency84Versatility84
- Mechanics54Laning69Teamfighting57Macro55Consistency70Versatility58
- Mechanics53Laning69Teamfighting50Macro51Consistency60Versatility77
- Mechanics52Laning44Teamfighting50Macro77Consistency52Versatility62
- Mechanics46Laning54Teamfighting60Macro55Consistency61Versatility54
- Mechanics59Laning52Teamfighting52Macro53Consistency52Versatility50
- Mechanics48Laning50Teamfighting45Macro59Consistency48Versatility68
- Mechanics64Laning43Teamfighting62Macro64Consistency40Versatility40
- Mechanics67Laning49Teamfighting61Macro45Consistency48Versatility37
- Mechanics46Laning42Teamfighting46Macro43Consistency40Versatility34
Axis leaders · records
Champion per stat
Overall distribution (10 members)mean 55·median 55
4270
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LCS Mid 2022 ranking at a glance
LCS Mid 2022 compares 10 members across 6 stats including Mechanics, Laning, Teamfighting. The overall top is Bjergsen, with an average of 70. In Mechanics, PowerOfEvil ranks highest. The overall average here is 55, ranging from 70 down to 42.
Frequently asked questions
- Who is ranked #1 in LCS Mid 2022?
- The overall #1 in LCS Mid 2022 is Bjergsen, averaging 70.
- How many are compared in LCS Mid 2022?
- 10 entries compared across 6 stats including Mechanics, Laning, Teamfighting.
- Who leads in Mechanics?
- PowerOfEvil leads in Mechanics.
- How are these scores calculated?
- Each axis is a percentile within this ranking, averaged from measured match metrics, with sample shrinkage and — for international events — anchoring to the major-league distribution and a strength-of-schedule adjustment. A rank is not a raw metric; the full method is at everystat.ai/clusters/method.