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MSIRanking — Overall
Play VSTick two checkboxes to compare them
| # | Name | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | 86 | 86 | 89 | 85 | 74 | 86 | 97 | ||
| 2 | 84 | 81 | 74 | 87 | 81 | 89 | 90 | ||
| 3 | 81 | 76 | 91 | 72 | 69 | 94 | 84 | ||
| 4 | 76 | 75 | 73 | 70 | 67 | 93 | 78 | ||
| 5 | 74 | 73 | 82 | 79 | 77 | 67 | 68 | ||
| 6 | 74 | 68 | 61 | 77 | 97 | 68 | 70 | ||
| 7 | 74 | 73 | 70 | 74 | 70 | 73 | 82 | ||
| 8 | 71 | 65 | 79 | 64 | 89 | 70 | 61 | ||
| 9 | 65 | 86 | 69 | 68 | 74 | 48 | 45 | ||
| 10 | 62 | 66 | 59 | 71 | 53 | 62 | · |
- Mechanics86Laning89Teamfighting85Macro74Consistency86Versatility97
- Mechanics81Laning74Teamfighting87Macro81Consistency89Versatility90
- Mechanics76Laning91Teamfighting72Macro69Consistency94Versatility84
- Mechanics75Laning73Teamfighting70Macro67Consistency93Versatility78
- Mechanics73Laning82Teamfighting79Macro77Consistency67Versatility68
- Mechanics68Laning61Teamfighting77Macro97Consistency68Versatility70
- Mechanics73Laning70Teamfighting74Macro70Consistency73Versatility82
- Mechanics65Laning79Teamfighting64Macro89Consistency70Versatility61
- Mechanics86Laning69Teamfighting68Macro74Consistency48Versatility45
- Mechanics66Laning59Teamfighting71Macro53Consistency62Versatility·
Axis leaders · records
Champion per stat
Overall distribution (10 members)mean 75·median 74
6286
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LCK Support 2023 ranking at a glance
LCK Support 2023 compares 10 members across 6 stats including Mechanics, Laning, Teamfighting. The overall top is Keria, with an average of 86. In Mechanics, BeryL ranks highest. The overall average here is 75, ranging from 86 down to 62.
Frequently asked questions
- Who is ranked #1 in LCK Support 2023?
- The overall #1 in LCK Support 2023 is Keria, averaging 86.
- How many are compared in LCK Support 2023?
- 10 entries compared across 6 stats including Mechanics, Laning, Teamfighting.
- Who leads in Mechanics?
- BeryL 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.