Overview: Balancing games is never easy. This specific strategy aims to make quick iterations to accurately find balanced numerical values. Ensuring balanced numbers means a fair game and more fun for the player base as well. Examples are taken from Hearthstone and Jesse Schell's The Art of Game Design.
You’ve just released a bestselling game to the community, and within 24 hours popular game discussion forums are filled with posts ridiculing the game’s balance. Despite spending months, or even years, developing this game, you find out that the player base is largely dissatisfied with the overall balance of the game. So, what’s the best way to deal with this situation as it stands? Hire more QA? Wrong. Work overtime to redo what’s imbalanced? Wrong again. The most simple and honest answer is: to avoid the situation in the first place.
As someone who likes the design and analysis of games, I can’t stand crunching the numbers myself and thinking, “Why would a player choose to use [insert some item/stat/character] when it is clearly outclassed by [insert more powerful substitute]?” I believe that an easy way to enhance the player’s experience when making a critical choice in the game is to give the player several balanced options to choose from.
A quick example of this is building an arena deck in Hearthstone, one of Blizzard’s newest games (currently in closed beta). In the Arena game mode, the player must first choose a class amongst three randomly chosen classes. The most experienced players will instantaneously be able to pick the strongest of the three. Rarely will you see someone ponder the pros and cons of each class and spend even a few minutes comparing them. Then when building a deck, the player is presented with three randomly chosen cards. The player picks one of the three and the process is repeated until the number of chosen cards completes their deck. Not surprisingly, experienced players will immediately select the strongest card of the three and never give a second thought to the other possible options.
To me, this behavior is unacceptable (granted the game is still in beta) but also unavoidable to a certain extent. It is my job as a game designer to minimize the number of times a decision is thoughtlessly made. In order to do this, certain statistics or mechanics in the game must be tweaked. Ideally everything in the game is equally balanced yet fills a specific niche to make it a desirable choice. This number intensive balancing needs a solid strategy...
I am going to discuss a game design strategy brought up in Jesse Schell’s The Art of Game Design and explain how to adapt it to quickly hone in on the most balanced number.
The strategy is appropriately named “doubling and halving” (Schell 201). Beginning with the currently implemented number, a designer can quickly find a range of values bounded by two numbers by doubling or halving it, such that one of the numbers too low and is labeled “underpowered” and another which is double the first and is “overpowered.” This strategy helps the designer find a suitable range to begin testing. Schell then suggests using your intuition to guess a number in the range (202). Depending on whether you found the number you guessed was too low, high, or perhaps just right, you can make another guess until you eventually get a number that seems balanced.
I prefer a more mathematical approach. Once the above range is found, a designer can then begin to narrow his search for the most balanced number by testing the median value and getting feedback that will determine if that value is considered underpowered, overpowered, or balanced. The designer can then repeat the search with the old median equal as the new minimum or maximum accordingly. Does this type of search sound familiar? Think of this strategy as using a binary search to reach the most optimal number. Plus, intuition can still direct the designer’s decisions. The designer can perform each binary iteration mentally instead of going to QA for feedback. For those who are curious, this binary testing strategy means worst case O(log2(initial range)) iterations.
With an endless stream of balance-related issues to solve, making minor changes here or there based simply on your intuition is an unreliable strategy. Time is money, and the more iterations you make because you guessed wrong, the more time it will take to find the actual number and the more money it will cost the company. By using my more mathematical approach, one can still use their intuition to narrow down the range, but my strategy ensures that during each iteration, significant progress will be made towards the balanced solution.
Works Cited
Schell, Jesse. "Game Balancing Methodologies." The Art of Game Design: A Book of Lenses. Amsterdam: Elsevier/Morgan Kaufmann, 2008. 201-02. Print.
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