Campfire Queue

Winner of ConUHacks VIII - Behaviour Interactive's Challenge

Campfire Queue - Visualizing and Estimating DBD Queue Duration in a Fun and Interactive Way

Inspiration

We were inspired to work on this project because of the interesting challenge provided this year involving data analysis and data visualization. All team members have a passion for coding and learning new skills in the programming and gaming fields. This challenge presented us with an amazing opportunity to expand our knowledge of data analysis, and gain valuable insight into the back end workings of highly successful games. Additionally, were inspired by Behaviour Interactive's accomplishments in the gaming sector and wanted to partake in a challenge specifically crafted by them.

What it does

This project visualizes wait times in Dead By Daylight in a 3D lobby environment by showing how different factors are influencing the players' wait time. We delved into multiple scenarios and considered numerous factors which may influence queue times. Namely, we considered how different regions may experience different killer:survivor ratios, how the demographic of players will influence peak hours played, how the time played at influences the diversity of players (in terms of rank) and how this may influence queue times. Additionally, we also considered how different regions may have different ratios of party vs solo players, and how this would affect queue times. Our project also includes a presentation displaying the formulas used and additional graphs for a more comprehensive understanding of our project.

Additionally, data is dynamically visualized in the lobby scene, and players can walk around and view the data from different angles (x-axis shows wait time, y-axis shows queue score, and z-axis shows score) and view how different variables affect queue times.

How we built it

This project is built using C# and Unity. A random row of data is chosen from the database, and is used to estimate that queue sessions queue duration using the functions and assumptions we made.

Challenges we ran into

During the brainstorming process, we initially wanted to use a Poisson or Standard distribution to approximate the estimated queue duration. However, after discussing all the variables and scenarios we wanted to account for, we decided to use a point system in which we could grade and weight every variable's importance. Additionally, the scope of our project was too large for the time constraints and we considered too many possible variables. We adjusted this to consider a more reasonable number of variables. We also encountered challenges when using Git/GitHub as a team when merging our work.

Accomplishments that we're proud of

We are incredibly proud of understanding/figuring out how different variables effect each other, namely how different regions may have different ratios of solos vs party teams and how this influences the queue time of different queue sizes. We also considered each factor thoroughly and did research on each one to have the most accurate point system possible for our estimation process. We are also proud for submitting this project and having a fun time together!

What we learned

We learned how to visualize data in Unity, and how there can be dozens or even hundreds of factors effecting one element of gameplay. We learned about the social roles that different countries may play in console/PC preference for certain gameplay, queue party sizes, and how this may effect queue duration.

What's next for Tomster Project

This project definitely inspired us to learn more about gaming trends and the underlying influence of socials/populations demographics in the gaming sector. We experienced how important it is to take an innovative approach to data analysis and consider factors not previously considered. In the future, this team will always be looking for different ways to analyze and understand data, we will think outside the box and never stop trying to learn. We definitely plan on participating in more exciting hackathons!