Work detail

Player Skill Rating for Games with Random Matchmaking

Author: Mgr. Jan Hubík
Year: 2016 - summer
Leaders: RNDr. Michal Červinka Ph.D.
Consultants:
Work type: Economic Theory
Masters
Language: English
Pages: 117
Awards and prizes:
Link: https://is.cuni.cz/webapps/zzp/detail/165714/
Abstract: Traditional skill ratings are not suitable for new types of games. We developed
a general skill rating framework for games which do not discriminate players
based on their skill. This class of games is widely present in the world. We use
Bayesian statistics to convert aggregate data about the player’s performance to a
percentile rank describing his skill. The system is applicable to both single-player
and multiplayer games with binary and non-binary endings. The rating formulas
do not contain any arbitrary constants. We have tested the system in simulations
and on real game data, and we outline its possible applications.

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