Riftline.

Support · patch 16.18

Renata Glasc

the Chem-Baroness  /  Support, Mage

Adjusted
34.8%
Win rate
45.1%
Pick
3.2%
+1.9 since 16.17
Ban
0.3%
Games
82
Tier
C

On patch 16.18, Renata Glasc won 45.1% of 82 ranked solo games as support in the games Riftline holds, a rate the sample supports down to 34.8%. Renata Glasc was picked in 3.2% of games and banned in 0.3%.

That places Renata Glasc in tier C among support champions on this patch, ranked by that lower figure rather than the raw win rate, so a champion with few games does not outrank one with many.

A typical game as support ends 1.3 / 5.3 / 16.0 with 1.0 CS a minute and 8,236 damage to champions.

Renata Glasc rose from the ashes of her childhood home with nothing but her name and her parents' alchemical research. In the decades since, she has become Zaun's wealthiest chem-baron, a business magnate who built her power by tying everyone's...

Role
2.5k matches on patch 16.18
KDA
3.25
K / D / A
1.3 / 5.3 / 16.0
CS per min
1.0
Gold
8.3k
Damage
8.2k
Vision
86

These are the builds players finished games with, not the order they bought things in. Riot's match data records the final inventory, and the slots carry no purchase order. Fetch match timelines and a real build order appears here.

Most built items

Counted individually, so this survives a small sample best.

46.2%

65 games, 79%

48.9%

45 games, 55%

42.3%

26 games, 32%

55.6%

18 games, 22%

40.0%

15 games, 18%

42.9%

7 games, 9%

Completed builds

The full set of finished items, most common first.

  • Knight's Vow, Locket of the Iron Solari

    44.4%

    18 games, 22%

  • Knight's Vow, Locket of the Iron Solari, Mikael's Blessing

    57.1%

    7 games, 9%

  • Locket of the Iron Solari

    28.6%

    7 games, 9%

  • Bandlepipes, Knight's Vow, Locket of the Iron Solari

    60.0%

    5 games, 6%

Boots

43.5%

62 games, 76%

72.7%

11 games, 13%

Summoner spells

FlashHeal

45.0%

80 games, 98%

Back to the tier list

How our numbers are made: the score's weights and how well they track wins, the win-chance model's accuracy, and the rules behind the death review.

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