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LCK Mid 2019

13 members·6 stats

Ranking — Overall

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  • Mechanics87Laning95Teamfighting59Macro77Consistency93Versatility95
  • Mechanics93Laning84Teamfighting66Macro76Consistency82Versatility88
  • Mechanics82Laning78Teamfighting76Macro73Consistency85Versatility93
  • 4
    80
    Mechanics76Laning83Teamfighting83Macro74Consistency77Versatility86
  • Mechanics85Laning85Teamfighting80Macro77Consistency79Versatility70
  • 6
    78
    Mechanics77Laning71Teamfighting69Macro90Consistency83Versatility80
  • 7
    74
    Mechanics80Laning77Teamfighting90Macro65Consistency65Versatility69
  • Mechanics62Laning74Teamfighting67Macro80Consistency80Versatility80
  • Mechanics75Laning69Teamfighting78Macro75Consistency78Versatility68
  • 10
    71
    Mechanics71Laning64Teamfighting86Macro80Consistency64Versatility62
  • 11
    70
    Mechanics65Laning86Teamfighting71Macro74Consistency64Versatility62
  • 12
    69
    Mechanics58Laning63Teamfighting72Macro72Consistency72Versatility78
  • 13
    G
    65
    Mechanics72Laning63Teamfighting78Macro60Consistency60Versatility57
Axis leaders · records

Champion per stat

Overall distribution (13 members)mean 75·median 74
6584

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LCK Mid 2019 ranking at a glance

LCK Mid 2019 compares 13 members across 6 stats including Mechanics, Laning, Teamfighting. The overall top is Chovy, with an average of 84. In Mechanics, Faker ranks highest. The overall average here is 75, ranging from 84 down to 65.

Frequently asked questions

Who is ranked #1 in LCK Mid 2019?
The overall #1 in LCK Mid 2019 is Chovy, averaging 84.
How many are compared in LCK Mid 2019?
13 entries compared across 6 stats including Mechanics, Laning, Teamfighting.
Who leads in Mechanics?
Faker 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.

How the six-axis ratings work →