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--- Auto-Generated Description --- This diagram models a simplified Glicko matchmaking system, an algorithm commonly used in competitive gaming for evaluating player skill levels, as seen in popular games like Pokémon Go, CS:GO, and Team Fortress 2. The core of the diagram revolves around the dynamics of player interactions through matches, affecting their rating (R) and rating deviations (RD). It allows for the modeling and simulation of wins and losses based on match participation, with a specific focus on how these results impact a player's overall rating. Wins increase the rating, while losses decrease it, adhering to the principle that a player's skill level is reflected by their win-loss record. Furthermore, the model incorporates the concept of Ratings Deviation (RD), which quantitatively represents the uncertainty in a player's rating. The RD adjusts based on activity. If a player participates in at least two matches per day, their RD decreases, implying increased confidence in the player's rating accuracy. Conversely, inactivity leads to an increase in RD, indicating a loss of confidence in the rating's precision. The system also considers the probability of logging in and playing matches, affecting the accumulation of wins and losses and consequently, the player’s rating and RD. This setup offers insights into how different rates of participation and performance outcomes can influence a player's standing within a competitive environment.