Using Analytics For Balance

When designing an open-ended game such as DataJack, balance can become an issue. You want to allow the player to make meaningful choices without overly favoring one play style or weapon. This means fine-tuning not only the level designs but their rewards, as well as the host of statistics that define the weapons, items and upgrades.

I’ve been playing around with a spreadsheet to track the stats of each weapon before and after their full upgrades. Hopefully this will prevent any one weapon from being the obvious best choice. Using and visualizing this data effectively can be a challenge, but it’s a lot more objective than my previous method of “rough counting in my head.”

In particular, it seems a good idea to look out for major outliers in any particular stat. Some weapons, such as the railgun, are themselves outliers: the railgun holds only two shots, has the longest delay between shots, but can shoot through most of the basic walls in the game and still deal incredible damage.

Of course, some weapons or mods can make a particular weapon configuration far better in one category than its peers, which isn’t a problem as long as this benefit is offset by a steep cost. This needs to be considered in light of the player’s progression, and how plentiful cash will be in the early versus the late game. The cash flow in turn is controlled by mission progression, which is nonlinear and branching.

Altogether this makes balance a challenge to say the least, even without considering level difficulty, and it’s probably impossible to get it just right. Nevertheless, even an imperfectly balanced game can still be fun.

Work is continuing on making the missions, and I have a full plan written up for the remaining set. I will fall short of my planned 30 missions, but this will allow me to release the game sooner.