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MSIRanking — Overall
Play VSTick two checkboxes to compare them
| # | Name | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | SaintLYON | 74 | 77 | 71 | 59 | 71 | 83 | 83 | |
| 2 | QuidTeam Liquid Alienware | 71 | 80 | 79 | 74 | 47 | 82 | 61 | |
| 3 | LokiCloud9 Kia | 59 | 65 | 59 | 65 | 63 | 62 | 42 | |
| 4 | QuadFlyQuest | 59 | 57 | 57 | 60 | 48 | 60 | 71 | |
| 5 | APACloud9 Kia | 55 | 52 | 46 | 56 | 53 | 64 | 61 | |
| 6 | DarkWingsSentinels | 52 | 41 | 56 | 56 | 55 | 44 | 59 | |
| 7 | ZinieShopify Rebellion | 46 | 38 | 46 | 52 | 68 | 41 | 31 | |
| 8 | CallmeDisguised | 43 | 50 | 52 | 40 | 43 | 32 | 41 | |
| 9 | PalafoxDignitas | 36 | 36 | 32 | 36 | 45 | 32 | · |
- Mechanics77Laning71Teamfighting59Macro71Consistency83Versatility83
- Mechanics80Laning79Teamfighting74Macro47Consistency82Versatility61
- Mechanics65Laning59Teamfighting65Macro63Consistency62Versatility42
- Mechanics57Laning57Teamfighting60Macro48Consistency60Versatility71
- Mechanics52Laning46Teamfighting56Macro53Consistency64Versatility61
- Mechanics41Laning56Teamfighting56Macro55Consistency44Versatility59
- Mechanics38Laning46Teamfighting52Macro68Consistency41Versatility31
- Mechanics50Laning52Teamfighting40Macro43Consistency32Versatility41
- Mechanics36Laning32Teamfighting36Macro45Consistency32Versatility·
Axis leaders · records
Champion per stat
Overall distribution (9 members)mean 55·median 55
3674
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LCS Mid 2026 ranking at a glance
LCS Mid 2026 compares 9 members across 6 stats including Mechanics, Laning, Teamfighting. The overall top is Saint, with an average of 74. In Mechanics, Quid ranks highest. The overall average here is 55, ranging from 74 down to 36.
Frequently asked questions
- Who is ranked #1 in LCS Mid 2026?
- The overall #1 in LCS Mid 2026 is Saint, averaging 74.
- How many are compared in LCS Mid 2026?
- 9 entries compared across 6 stats including Mechanics, Laning, Teamfighting.
- Who leads in Mechanics?
- Quid 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.