The original post: /r/pcgaming by /u/falsedrum on 2024-04-28 00:36:05.
When presenting the idea of rating between video games, a common response that comes across is tier listing. A well known format that is easily created by and presented to anyone. I find the method useful as it provides quick insight on a certain discussion or topic. Looking a little further, one can quickly notice how this system oversimplifies certain aspects or rating making it sometimes unfair.
To elaborate: A tier list between Bloodborne Bosses can create discussions around the games variety while a different tier list between Terraria and Apex Legends can create confusion and conflict of which of the two is better.
Provided this information, you come across a common issue with rating different products that serve different purposes. To avoid this problematic way of rating one can look no further than to rate a product within itself and how well did it perform for ones standards and preferences. But how does one make a system that provides this information in detail to the player?
The best approach I found in forming said system was to first put together six fundamental categories that apply across (almost) all gaming titles.
The categories go as follows:
- Game Direction
The creative vision/innovation, how well put together is the product
- Art Direction
The style of the environment / graphics, the visual experience
- Narrative
The story (if applicable to the games genre)
- Score and Music
Self explanatory
- Audio Design
The quality combined with the selection of sound for the product
- Gameplay
The hands on experience the player has with the product
Now lets create a scenario where you have to vote for each of these categories for a gaming title on a “out of ten” scale. That would make a total of 60 values across all six categories (with the maximum vote for a category being 10 and the lowest being 0).
Now what would happen if I proceeded to select a variety of titles I completed, rating them across all six categories and wanted a percentage (%) for each individual title? The method of rating and conversion is simple and can most likely be automated but for the sake of this example we will calculate it manually.
The resulting percentages will be measured by summing up the values of all six categories, multiplied by one-hundred (%), then divided by the total maximum value that can be numbered (60 in our case)
Additionally if a title doesn’t qualify within a certain category, the values will adjust accordingly to the remaining categories excluding the one that is considered unfit (example: if one category is ruled out the sum of the remaining 5 categories will be divided by 50 as the new maximum value).
In text, listing should look something like this:
BioShock Infinite
Game Direction: 9
Art Direction: 10
Narrative: 10
Score and Music: 9
Audio Design: 9
Gameplay: 8
↓
Total from categories: 55
↓
55 x 100 = 5,500
5,500 ÷ 60 = 91.66666666666667
Percentage: 91.6%
This method allows us to rate key aspects without involving other gaming titles. Giving us in the form of percentage, how close to our preference is the product.
Taking it a step further, one can now form a list from a large selection of games, applying the method individually and ending up with a selection of percentages that can now be sorted through any software like Excel or LibreOffice Calc etc. The result of this sorting isn’t to compare the titles, but to create a list that displays which products came closer to what the player (you) wanted to experience. One can gather other data like the genres and themes that are more commonly preferred.
This system while attempting to be as fair as possible for variety, doesn’t present perfect results, as it may be more friendly to games that apply to all six mentioned categories, leaving titles like shooters or survivals with lower percentages (even with the alternative calculating method that is performed). I personally found the method helpful in providing a clearer insight on personal preference and thought someone with enough time to read through and recreate could benefit in finding more new products that are close to what one is after.
I encourage any improvements as it can be very time consuming for the common user to be formed as it stands, with it lacking complete automation.