Developing an Elo Based, Data-Driven Rating System for 2v2 Multiplayer Games
How to Create a Data-Driven Elo Rating System for 2v2 Games
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My name is Lazare and I just finished my second bachelor degree in Business Data Analysis. This article is based on the work I did for my bachelor thesis.
From friendly matches to intense competition, foosball has found its niche in corporate culture, providing a unique way for teams to connect and compete.
This article explores the math behind a 2v2 Elo-based scoring system that can be applied to foosball or any other 2v2 game. It also examines the architecture that supports data processing, and presents the creation of a web application that provides real-time ranking and data analysis using Python.
The Elo Ranking
The Elo rating system is a method used to determine the relative skill level of a player in a zero-sum games. It was first developed for chess but is now being applied as a rating system in a variety of other sports such as baseball, basketball, various board games and e-sports.
One well-known example of this system is in chess, where the Elo rating system is employed to rank players worldwide. Magnus Carlsen, also known as the "Mozart of Chess", holds the highest Elo rating in the world with a rating of 2,853 in 2023, demonstrating his extraordinary skills in the game.
The Elo rating formula is a two-part formula: first, it calculates the expected outcome for a given group of players, and then it determines the rating adjustment based on the outcome of the match and the expected outcome.
Expected Outcome Calculation
Consider the following example in chess with Player A and Player B with ratings R
