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Worlds Bot 2024

13 members·6 stats

Ranking — Overall

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  • Mechanics77Laning95Teamfighting77Macro84Consistency95Versatility92
  • 2
    85
    Mechanics95Laning74Teamfighting80Macro82Consistency80Versatility98
  • Mechanics93Laning90Teamfighting85Macro81Consistency70Versatility90
  • Mechanics88Laning82Teamfighting89Macro77Consistency74Versatility85
  • 5
    81
    Mechanics85Laning55Teamfighting84Macro78Consistency91Versatility93
  • Mechanics83Laning64Teamfighting71Macro86Consistency74Versatility85
  • Mechanics70Laning91Teamfighting71Macro68Consistency80Versatility79
  • 8
    73
    Mechanics71Laning80Teamfighting67Macro74Consistency71Versatility76
  • Mechanics67Laning71Teamfighting67Macro76Consistency58Versatility88
  • 10
    71
    Mechanics80Laning50Teamfighting71Macro65Consistency79Versatility80
  • 11
    63
    Mechanics66Laning68Teamfighting66Macro56Consistency57Versatility63
  • 12
    56
    Mechanics54Laning51Teamfighting51Macro54Consistency63Versatility60
  • Mechanics47Laning26Teamfighting41Macro41Consistency38Versatility49
Axis leaders · records

Champion per stat

Overall distribution (13 members)mean 73·median 77
4087

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Worlds Bot 2024 ranking at a glance

Worlds Bot 2024 compares 13 members across 6 stats including Mechanics, Laning, Teamfighting. The overall top is Gumayusi, with an average of 87. In Mechanics, Elk ranks highest. The overall average here is 73, ranging from 87 down to 40.

Frequently asked questions

Who is ranked #1 in Worlds Bot 2024?
The overall #1 in Worlds Bot 2024 is Gumayusi, averaging 87.
How many are compared in Worlds Bot 2024?
13 entries compared across 6 stats including Mechanics, Laning, Teamfighting.
Who leads in Mechanics?
Elk 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 →