Glicko-2 Rating System
Why Not ELO?
Traditional ELO systems have a fundamental flaw: they treat all ratings as equally certain. A new item with 5 votes and rating 1500 is treated the same as an established item with 500 votes at rating 1500.
Glicko-2 solves this by tracking rating deviation. New items start with high RD (uncertainty), which decreases as more votes are collected. This allows the system to make more conservative updates for established items while allowing rapid discovery for new items.
Rating Scale
Pairwise Comparison
Voting uses a pairwise comparison model. Voters are presented with exactly two items and must choose which is better. This simplifies the voting task and produces more reliable data than asking voters to rate items on an absolute scale.
The matchup selection algorithm prioritizes:
- Items with high rating deviation (to reduce uncertainty)
- Avoiding repeated pairings
- Similar-rated items for competitive matchups
Bot Protection
To maintain ranking integrity, RankHub employs multiple anti-gaming measures:
Reference
Glickman, M. E. (2013). Example of the Glicko-2 Rating System.
http://www.glicko.net/glicko/glicko2.pdf →