Isolation Protocol

BCU Year 2 Undergraduate Project

Main learning points

Don't work on too many areas at once!
We didn't apply our design philosophy as much as we should have.

A Roguelike developed over 8 months with 2 programmers and myself as designer / producer.

I wanted to apply all I learnt from Temple Imperium to this game's production.

We choose Unity and C# since we had prior experience with it, and wanted to utilise the simplicity of C# to iterated quickly using an Agile workflow.

Before we even began pre-production, I did a lot of research into Agile practices, all of which is concentrated here.

Or play the game here!

Pre-production

We created our own design brief and given complete creative freedom over this project.

We decided to create a Roguelike Dungeon Crawler for these reasons:

Less team members = Less manpower -> We cannot overscope at all.
Simple game but well refined would stand out amongst all the other projects.
Simple game is easier to playtest and get feedback for ; we can quickly iterate.

________________________________________________

With a general idea of our game, we began to code.

Having a refined game is our ultimate goal, so user feedback was absolutely essential.

For this reason, I developed a player feedback system with the help of the programmers. This system collects data directly from the game itself, and uploads this to a Google Sheet.

We identified trends in data. We understood what was working, what was not working. We could easily pilot our game's production towards something more refined.

________________________________________________

With feedback, we began to iterate the design.

With this feedback, we designed and iterated as a team. We made our idea from general to specific!

Finally, we came to an MVP and Plan of Action!

________________________________________________

Pre-production is going steadily

As pre-production moved along, we made the MVP and the design more detailed.

To organise all of this information into an accessible document, we created a refinement graph.

At the beginning, this graph was empty. In production, we finished each sprint by adding an collectively agreed progress to this graph.

When we had created every feature for our game we began our production.

Production

We used a Google Sheets backlog and a Trello page for Sprints.

We picked tasks from the backlog, using the refinement graph to inform what needed the most attention, and assigned work into a Sprint.

We used Trello to organise our Sprints.

________________________________________________

The end is near...

16 Sprints later, we finished creating all features for our game and debugging most of the problems.

At this point, we had no time left before our submission date.

We were mostly happy with our game; it is certainly finished and requires no more features.

To make it great, all we need to do is refine and iron out any problems in the design or code.

To finalise this game is something I want to do, but I've had a busy personal life (see here). One day we will finish this game!

Below is documentation used to guide the production of our game.

Documentation

Refinement tracker document

I focused on clear project management using graphs to track scope

Simple but robust documentation was a guiding philosophy

Copy of Refinement Tracker

Presentations

This is an example of the quality of PowerPoint Presentations I can give in a team environment

Copy of 3rd iteration

Game Proposal

Design documentation

Here is an example of iteration-led design. I clearly recorded characteristics of each room layout, and tracked positive and negative changes, demonstrated by the iterations.

Another example of user-in-mind design; here I've documented how the game will dripfeed new elements to the player. With this document we can easily re-arrange when elements are introduced.

Copy of List of levels

Copy of Progression Sheet

Playtest statistic analytics

Here is the backend of our playtest analytics tracker. We recorded multiple gameplay stats to see how strong enemies were, how effective guns were. With this data, we can balance the meta of our game and ensure it is as fair of a challenge as possible

With the raw data, I've synthesied it using statistical formulae. This gives us mathematical proof of trends about our game, such as "The less bullets a player shoots, the less time they spend in the game". Armed with certainity, we can further refine our game to create a fun challenge for everyone.

Copy of Playtest data

Screenshots from our game and development