Disillusion Avalon: Board Game Data Analysis

How would social deduction games look like with data?

Introduction: Board Game!

Source: https://gamecows.com/
https://www.proavalon.com/

Data Description & Caveats

The original JSON data format for a game
If you are a newcomer, you can also watch this video to understand the basics of the game.

Basic Statistics: What does the data look like?

Number of Games Played

The absence of data between 7/2019 and 10/2019 was due to a shutdown of the service.

Game Time: Huge variation in times!

Mean: 15.57 mins; Standard Deviation: 9.99 mins

Major Features: Who won, and how

Spy/Evil team has different win conditions

Win Rate & Time: Longer games, more balanced results

A clear distinction between which team wins the game.

Win Rate & Failed Vote: Dispute results in more losses for the good team?

The number of games with each count of failed votes for 5-player games (left) and 6-player games (right).
The Good team’s win rates for 5-player games (left) and 6-player games (right), based on the number of failed votes in the game.

Advanced Analysis: Win condition vs Voting and starting position

First leader

A chi-squared analysis on “howTheGameWasWon”

The sequence of leadership

Wow, there are 5,791 unique sequences in this dataset!
Top 10 common sequences in leaderships with “How the game was won”

More Practical: Special Characters as the first leader

Player’s view: What would you do if you are a special character?

Morgana and Assassin: Does complicated play pay off?

If you are in the Evil team, what would you do?

Merlin: What should the player who knows everything do?

Percival: Can the player who knows half the story influence game results?

Sadly, we can’t reject the hypothesis that Percival's choice doesn’t matter on its own.

Conclusion: A fair and complicated game!

Photo by Vlad Sargu on Unsplash
Photo by Karthik Balakrishnan on Unsplash

What’s next?

If you are also interested, please feel free to contribute to the project as well!

MS in Columbia & Data Practitioner in New York! | Linkedin: https://www.linkedin.com/in/jeff-chia-ching-lu/

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