support
This will vary because unlike other stat sites we include 100% of a brackets champions played and never include champions that don't belong in the bracket.
Master Champions Analysed: 1,799,799
We include 100% of the champions played of every selected tier bracket in our analysis, we never include champions from outside the tier quoted tier.
Renata Glasc Counters
Renata Glasc support vs support Counters
Renata Glasc support on Patch 15.16 is the strongest counter to support champions of Thresh, Rakan & Milio. While Renata Glasc support is countered most by support champions of Bard, Karma & Nautilus. Below is a detailed breakdown of Renata Glasc support counters against support champions with a minimum of 100 games.
Bard
Gardien errant
Renata Glasc wins against Bard 44.44% of the time which is 3.52% lower against Bard than the average opponent.
After normalising both champions win rates Renata Glasc wins against Bard 7.99% less often than would be expected.
The average opponent winrate against Bard is 47.96%.
Karma
Sagesse incarnée
Renata Glasc wins against Karma 44.81% of the time which is 2.87% lower against Karma than the average opponent.
After normalising both champions win rates Renata Glasc wins against Karma 7.34% less often than would be expected.
The average opponent winrate against Karma is 47.68%.
Nautilus
Titan des profondeurs
Renata Glasc wins against Nautilus 49.03% of the time which is 0.18% higher against Nautilus than the average opponent.
After normalising both champions win rates Renata Glasc wins against Nautilus 4.29% less often than would be expected.
The average opponent winrate against Nautilus is 48.85%.
Alistar
Minotaure
Renata Glasc wins against Alistar 49.07% of the time which is 1.77% higher against Alistar than the average opponent.
After normalising both champions win rates Renata Glasc wins against Alistar 2.70% less often than would be expected.
The average opponent winrate against Alistar is 47.30%.
Nami
Aquamancienne
Renata Glasc wins against Nami 50.00% of the time which is 3.50% higher against Nami than the average opponent.
After normalising both champions win rates Renata Glasc wins against Nami 0.97% less often than would be expected.
The average opponent winrate against Nami is 46.50%.
Rell
Vierge de fer
Renata Glasc wins against Rell 52.85% of the time which is 4.70% higher against Rell than the average opponent.
After normalising both champions win rates Renata Glasc wins against Rell 0.23% more often than would be expected.
The average opponent winrate against Rell is 48.15%.
Lulu
Sorcière féérique
Renata Glasc wins against Lulu 53.36% of the time which is 5.21% higher against Lulu than the average opponent.
After normalising both champions win rates Renata Glasc wins against Lulu 0.74% more often than would be expected.
The average opponent winrate against Lulu is 48.15%.
Leona
Aube radieuse
Renata Glasc wins against Leona 53.70% of the time which is 6.81% higher against Leona than the average opponent.
After normalising both champions win rates Renata Glasc wins against Leona 2.34% more often than would be expected.
The average opponent winrate against Leona is 46.89%.
Milio
Douce flamme
Renata Glasc wins against Milio 56.38% of the time which is 10.65% higher against Milio than the average opponent.
After normalising both champions win rates Renata Glasc wins against Milio 6.19% more often than would be expected.
The average opponent winrate against Milio is 45.73%.
Rakan
Charmeur
Renata Glasc wins against Rakan 57.69% of the time which is 9.54% higher against Rakan than the average opponent.
After normalising both champions win rates Renata Glasc wins against Rakan 5.07% more often than would be expected.
The average opponent winrate against Rakan is 48.15%.
Thresh
Garde aux chaînes
Renata Glasc wins against Thresh 58.52% of the time which is 11.94% higher against Thresh than the average opponent.
After normalising both champions win rates Renata Glasc wins against Thresh 7.47% more often than would be expected.
The average opponent winrate against Thresh is 46.58%.
