Have you ever wondered how various game rating systems work? Many websites assign standard scores from 0 to 10, or 0 to 100%. Where do these numbers come from? Clearly, no one examines a game with a ruler and calculator, calculating pixel size and overall graphics quality. No one counts by ear how many different notes and octaves are used in the musical score. No one counts the number of characters and the length of their dialogue. All of this would be silly, and the results would be useless to the player (although this does happen; some games simply have nothing to boast about other than the number of different cars and tracks, the number of new characters, and the size of textures).
From this reasoning, we logically come to the solution to the gaming industry’s dark secret: all computer games are rated “by eye.” How does this happen? It goes something like this, as the average reviewer on a gaming website would say:
“What do we have here? A shooter from unknown developers. So many new features in the game, it’s a shame I’m short on time, I won’t have time to figure everything out. Fine, I’ll give it a 7.5 for their efforts. It’s just average, though; it’s unlikely anything epic will happen after the first mission.
What’s this? It’s another sequel to a world-famous shooter. Well, it’s all the same, only the setting has changed. Why so short? They’ve gotten completely lazy. But you can’t argue with that, I’m giving it a 9.0. Everyone will buy the game anyway, everyone will praise it. You can’t buck the trend.
So, what’s next? Oh no, another shooter, another new installment in the series? Enough already, I’m sick of playing the same old thing. Yes, it’s high-quality, yes, it looks great, but why the same old thing? They’re no longer such an unquestionable authority; I can argue with them. I’ll demonstratively give them a 6.0, so they’ll finally shut down their production line! And the buzz on our forum will liven things up, which is a good reason for that.
And finally, the last game is a three-color pixel indie platformer. Wow! After three shooters, at least this has some variety (+1). I’ve loved these games since I was a kid (+3). I think a new generation of players should love them, too. To that end, I’ll give it a higher rating—a 9.5. No one really plays them anymore, but maybe they’ll see my rating and at least get a little interested.
In short, a game’s rating depends far more on the reviewer’s personality, habits, and taste than on the quality of the game itself. Of course, more professional reviewers don’t take such liberties, but to some extent, they too do make subjective assessments.
Why does this happen? Because no one has any specific criteria for evaluating a game. What, exactly, should be evaluated? Every game consists of many different and distinct components. Which should be prioritized? Which should be ignored as insignificant? There’s no single answer that would suit everyone.
Existing solutions
for the Game Rating System
How to get out of this situation?
- Some well-known sites don’t just give a rating; they break down the game into several components (graphics, sound, plot, gameplay), rate them separately, and then add the resulting numbers to form an overall rating.
It sounds convincing, but it doesn’t work in practice. In practice, the opposite happens: the overall assessment is routinely determined “by eye,” and then it’s divided into its components to make everything fit together. And so it turns out that the assessment of the components serves not as the cause of the overall assessment, but rather as its consequence and justification.
Look at these ratings on top gaming sites. While the overall ratings somehow correspond to the overall quality of the game, the ratings for individual components are random, simply because the editor-in-chief ordered it. Players don’t even pay attention to this fiction. When was the last time you looked at these numbers?
This tool doesn’t work as implemented. It’s clear that this system was imposed on the authors from above, or even inherited from previous colleagues. The authors themselves don’t fully understand why they need it. Unaware authors are trying to give advice to even more unaware players.
- There’s a practice where websites display two ratings: one from a professional editorial team, and the other from the players themselves. This creates the false impression that the ratings of thousands of players should be more objective. Who better than the players themselves to evaluate games based on their own experience? However, such a system is completely vulnerable to false information. While reviewers can occasionally distort ratings, even though they need to protect their reputations, players have no restraints or accountability whatsoever. If you didn’t like a game, you give it a “0.” If you really disliked a high-quality game because you lost in multiplayer, you give it a “0” from every computer you could reach. If you wanted to prove to someone that the game was “cool,” you did the same, but gave it a “10.” No matter what sane players give, one insane player can easily rig the score and skew it to their advantage.
- Some gaming websites have abandoned the use of objective numerical ratings, opting instead for text-only game reviews. This allows authors to be more honest with readers, as ratings are based solely on their judgment and specific information, not encoded in numbers. However, reading long articles wastes precious time. It’s impossible to immediately determine whether you’ll play the game. This method allows you to win in accuracy, but lose in time.
- In the wake of distrust in specific assessments, global assessment aggregators have emerged, collecting figures from all websites and calculating the “average temperature in the hospital.”
Global sites like GameRankings.com, GameStats.com, and Metacritic.com handle this. In our country, only two sites do this: MetaGames.ru and Kritikanstvo.ru.
The service is enjoying some popularity. Aggregators clearly show which games are well-made and which are less so. These tools partially address the problem, mitigating it, but they don’t eliminate it completely.
The global problem
of ludology – the science of games
So what’s the actual problem? No, I’m not talking about why grades are distorted. I’m talking about why we need these grades at all? The grading tool is broken, but what is the purpose of this tool? I didn’t specifically address this in the text, only alluded to it in passing. Now, I’ll clearly formulate the main problem:
The huge flow of computer games is our joy and our main problem .
Currently, around 2,700 games are released annually (as of 2014) on PC alone, not counting consoles and mobile devices. (Of these, only 700 more or less popular games have been reviewed.) Playing them all would take several years, so most games will have to be put on hold. And next year, even more will be released, and so on, steadily increasing.
Remember the young Skywalker’s line in Star Wars: “How many stars are there in the sky? I want to visit every one!” As a child, I had similar ambitions for computer games—to play everything there was. A naive dream. The volume of games released has long since exceeded the human capacity to absorb information. The situation is exactly the same as with the stars—it’s impossible to embrace the immensity. We have to choose only the best, the most suitable, the unusual, and the interesting. We are faced with the problem of choice.
Problem analogs
Let’s see how this problem was solved with previous forms of information.
For example, books. A great many are still being published, but they all have their place in libraries. Books are shelved, sorted by genre and author’s name. You arrive at the library, and before you is no longer a shapeless pile of paper, but a structured data warehouse. Any book can be quickly found by entering the genre, author’s name, and title. At least that’s no longer a problem. But what if you want to read something but don’t know what exactly? The only option is to personally explore all the shelves with your chosen genre. If you have enough time, you can choose a book yourself. If you’re in a hurry, ask a trusted source, like a librarian, for advice. Your choice is theirs.
Something similar happens with games. There are online stores where thousands of games are categorized by genre, developer, and year of publication. This doesn’t help you much; you have your own game needs, but you can’t ask anything. You’re left with the option of browsing through all the shelves, looking at covers, screenshots, and videos, which again takes a lot of time; or you can take the advice of one of the hundreds of game “librarians” and find out the numbers they’ve assigned to games.
As we can see, the problem is far from new. It’s been around for quite some time, wasn’t addressed in time, and now crops up in every new form of information, and indeed in any overcrowded market.
The other side of the problem
Do you think I’m exaggerating? The problem exists, but it’s not important enough to address? Not at all. On the contrary, we’ve only just scratched the surface of an iceberg whose hidden underwater dimensions are simply astounding in their scale.
Think the problem of choice is unimportant? You go to buy a game, see several of the biggest brands, and easily choose between them? In fact, this hasn’t eliminated the problem of choice; it’s simply been solved for you from a different perspective—from the manufacturer’s.
Advertising is the engine of commerce. Sound familiar? Aggressive and intrusive advertising helps you discover new products. When you go to a store, you don’t always want to spend time browsing the entire selection; it’s easier to choose from what you already know. Advertising easily and effortlessly sorts products into two categories: well-known brands and everything else. The selection is significantly reduced, and you’re in the black, but in reality, the choice was made for you. It’s quite possible that among the unfamiliar products was the perfect one for you, but due to the lack of advertising, you didn’t even know about it.
While advertising isn’t so scary for consumers, it’s a real nightmare for manufacturers. Not only do they have to manufacture their product and deliver it to stores, but they also have to inform consumers—as many as possible—of its existence. Failure to do so will result in minimal sales. This forces manufacturers to compete less on product quality and more on the scope of their advertising campaigns.
A huge amount of human and material resources are spent on advertising. This industry accounts for approximately a third of all global financial flows. All this is done not to create something useful, lasting, or kind, but to solve the problem of consumer choice, without the participation of the consumers themselves.
It’s quite expensive for us to solve this problem, don’t you think? I’m sure I’ve convinced you of the relevance of this topic.
Game Studies Problem Statement
What do we see as the ideal solution to this problem? What should the end result be? Most likely, we should offer people only what they really need, and nothing extra. IT specialists involved in marketing will have understood what I’m talking about and where I’m headed from the very beginning. For the rest of our readers, I’ll give a clear example from real life.
Let’s go back to the happy days of my youth. I had a friend who worked as a sales assistant in a cell phone store. Back then, phone designs were incredibly diverse, with plenty to choose from, unlike today’s phones, which are all flat and buttonless.
The girl wasn’t just a saleswoman; she’d earned a degree in psychology by correspondence. She wasn’t just passing exams to earn a diploma; she was actually studying and already beginning to apply her knowledge in practice.
Here’s how she worked: a new customer would enter the store, she’d quickly look them over from head to toe, studying their demeanor and gestures. Based on this data, she’d select the phone that best suited their style and taste. She’d approach the potential buyer with the phone and clearly explain why they needed that particular product. Surprisingly, many were actually looking for what she was offering.
Perhaps the choice wasn’t based on logical reasoning, perhaps it was simply intuition, psychic abilities, or feminine charm, but the main thing was that it worked flawlessly. No one who bought anything returned complaining that they’d been sold something they didn’t need. On the contrary, they became regular customers, often returning for new items and consulting with this particular girl about purchases. You’d agree, any store owner dreams of having salespeople like her.
Now imagine yourself in that shopper’s shoes: you walk into the store, expecting to spend at least an hour searching, but a saleswoman is already walking toward you, carrying exactly what you wanted. There it is—the perfect solution.
It’s unlikely you’ve encountered such insightful salespeople in real life, but it certainly sounds familiar, doesn’t it? Of course! Such a system already exists all around us—contextual advertising in internet search engines.
The Ideal Sales System
Search algorithms automatically do exactly what my friend did manually 10 years ago—they actively collect information about us and, based on that information, suggest exactly what’s most relevant to us, or what we’ve previously shown interest in. Thanks to this technology, search engines have suddenly become the most effective marketers in the world. Google has become the richest company in the world, and Yandex the richest company in Russia.
The new trendy IT trend—”Big Data”—is nothing more than part of a larger system of perfect sales, aimed at collecting information about potential buyers. Having realized the effectiveness and high profitability of these new tools, other companies are also trying to use Big Data in other areas of human activity. However, this system is only useful to those with access to truly large amounts of information.
What is the benefit?
Where did this sector’s high profitability come from? How did search engines suddenly become so rich? To understand this, let’s look at how the price of any product is formed:
Price = Cost + Profitability + Transport + Advertising
The cost price includes the cost of creating a product: raw materials, workers’ wages, electricity, rent, and other minor expenses. Historically, these expenses have been minimized through factories, assembly lines, and automation. Reducing production costs further is quite challenging.
Profitability is the profit for the manufacturer, built into the price of the product. No one will operate at a loss, so no one will give up profitability.
Transportation costs sometimes account for half the price of a finished product, because delivering it requires purchasing vehicles, hiring carriers, and organizing all of this with logistics. This is unavoidable. If scientists were to invent teleportation devices and bring their cost down to an acceptable level, it would replace the entire existing transportation infrastructure and revolutionize trade. All goods would be halved in value, and in particularly hard-to-reach places, prices would drop several times. But for now, this is just a science fiction dream.
Advertising often accounts for one-third of a product’s cost. When you buy particularly expensive, well-known brands, you’re not buying quality; you’re mostly buying a name that’s been heavily promoted. An oversaturated and poorly structured market simply forces manufacturers to resort to advertising. If you release a high-quality product but don’t advertise it, no one will even know it exists and won’t be able to find it in the vast marketplace.
That’s the benefit. Search engines have taken over the largest chunk of the advertising industry, which in turn accounts for one-third of the global economy.
And if we can build a sales system completely without advertising, the cost of goods will decrease by a third. There will be no need for large billboards on city streets, leaflets on fences, and advertising on radio, television, and the internet. Advertising agencies, PR specialists, SEO specialists, creators of videos, banners, presentations, and leaflet distributors will all lose their jobs overnight and start doing something more useful.
Note that the creation of an advertising-free sales system is on par with the invention of teleportation in terms of relevance and relevance. But while teleportation currently exists only as a few basic principles in people’s minds, this new type of sales system is already being actively implemented in real life and is steadily approaching perfection.
Has the problem already been solved?
Gameology. The tasks of science
Online advertising is much cheaper than offline advertising. Contextual advertising and its targeting significantly increase standard effectiveness. Servers powered by Big Data technology collect more and more information about users, daily increasing the already high sales efficiency.
We’d only just faced the problem of choice when we discovered that large IT corporations had been solving it for a long time, for the past decade. This is a global, very serious change. But all global processes occur slowly and unnoticed by the average person. Advertising platforms of all stripes still have no idea that the ground is slowly slipping away from under their feet.
Traditional advertising methods are being replaced by more convenient and transparent tools. For example, Yandex Market and Puls Tsen (Price Pulse) display all available product types, categorizing them and highlighting all their numerous characteristics. A knowledgeable buyer will choose a product based on its characteristics, not flashy advertising claims, without wasting much time. Contextual advertising will help less informed buyers.
This is the current situation. But it can still be improved.
There is no limit to perfection
The imperfection of the modern online sales system is that the majority of buyers are uninformed, and a structured database won’t help them. And contextual advertising still operates not in the buyer’s interests, but in the old-fashioned way—in the interests of the wealthiest and most advertising-generous manufacturer. This is understandable, as Big Data systems are very data-hungry. Storing digital data requires servers, network equipment, and maintenance personnel. And when you multiply all this by the enormous amount of data used in the system, it becomes clear that this is an expensive endeavor, certainly beyond the means of ordinary citizens.
There are only two options here:
- Or train everyone in the new sales system from the school level. Although, in any case, no one will be able to understand all types of products at once.
- Or eliminate the commercial component. As long as large companies pay search engine advertising, the situation will remain the same. To create an ideal sales system for consumers, contextual advertising would need to include every product in the database and select suitable ones using pre-defined algorithms. But this would mean shifting the costs of running thousands of servers to the state, and therefore to all citizens.
Either option is unacceptable for existing large corporations, which enjoy a significant advantage in today’s markets. Losing their hard-won position and finding themselves back on a level playing field with everyone else—whoever would willingly agree to such a thing. For this reason, Big Data technology is not yet widely publicized; only the programmers who work with it know about it. It’s not exactly a global conspiracy, but you certainly won’t hear about it in detail on television. Even Wikipedia, which is supposed to explain everything, merely acknowledges the existence of Big Data technology, but doesn’t explain its origins or its intended destination. And even less so, you’ll never know the content of the final information collected through such expensive means.
These are global economic processes, and there is little we can influence here; we can only monitor how events develop.
(You could say you’ve just completed the full lecture course “Theory of Internet Marketing.” Perhaps such courses aren’t even taught anywhere else, but you were lucky enough to hear them. Now you know the theoretical foundation on which modern internet commerce was built.)
The Perfect Gaming Site:
Computer Game Theory
Let’s return from our in-depth exploration of the global economy to our familiar topic of computer games. Let’s further discuss what the ideal ad-free game sales model would look like.
There’s no point in fantasizing; we already have ready-made working examples of such stores: Steam, GOG, UPlay, Origin, Google Play, and the App Store. These are huge structured databases armed with Big Data technologies. Divided into genres, tags, and price categories, any game can appear on the website’s main page without paying for advertising. Search algorithms display similar games and other games in the same genre.
It seems like all the ingredients for success are in place, but users still remain dissatisfied. Recommended games include games you only happened to visit once, and completely different games with little in common are lumped into a single category. Ultimately, users only play a few of the most popular games, while the rest of the undiscriminate stream of games passes them by. Few pay attention to store recommendations; everyone still reads reviews on information sites, watches Let’s Player videos, and listens to friends’ advice.
Old mistakes
Does Big Data technology really not work for computer games? Yes, it does, but the problem lies elsewhere. Let’s return to where we started this article—game ratings. Household goods are easily broken down into a multitude of digital characteristics: dimensions, power, power consumption, supported features. Now try breaking down games into at least some of their components. Okay, so they have some non-digital characteristics: graphics, sound, gameplay, storyline. But can you use this to sort them in a way that’s useful and convenient for users? Imagine how difficult this would be for an automated system, to which you haven’t even fully explained what it’s supposed to do.
Major publishers have actively embraced the migration of the entire existing distribution system of the gaming industry to the new online store format. But in doing so, they have also carried over all the old, unresolved mistakes.
– The very foundation of the division of games (the genre system) is unstructured.
– There are no specific criteria for making a general assessment of the games; this is done purely intuitively.
– No one is finding out what the players themselves need, no one is looking for connections between their characters and genre preferences.
Big Data technologies are used so clumsily because there is no concrete application for them, and the topic of computer games lacks a sound theoretical basis.
Possible future
The Steam store is convenient and familiar, but it’s not perfect. Other online stores emerged later, copying all the ideas, and now can’t catch up in popularity. Weak, uninspired competitors create a certain illusion of Steam’s inviolability and unquestionable authority. But if the truth in “computer game theory” can be uncovered, the first store based on this new knowledge could easily surpass all other gaming services and become the rightful leader, leveraging the full power of Big Data technologies.
Still think we’re doing something irrelevant, delving into the obscure essence of games? Why approach games philosophically when you can just play them? Why write pseudo-scientific texts that most players will never read, unlike standard reviews and walkthroughs?
I am confident that I have just given clear answers to all these questions, and you will join our important work.
