BEM Gamification: Skill vs Chance

In this article, I started working around how to understand a challenge in terms of game design, so it could be used to make better gamification experiences. I have now been playing with those ideas and have been trying to connect them with my previous challenge framework to create a more comprehensive and useful taxonomy, so I want to share my analysis. Again, this should be part of a more comprehensive research, but, I hope, as an analysis go, it can prove really useful to find how to keep players engaged with your designs. In this article I will focus on how you can create challenge understanding the differences of skill vs chance.

The dichotomy of Skill vs Chance

This is something that is well know in the gaming world, some games are built through testing the players' skills, and some are built under the scope of playing with chance. I have been understanding this through the lense of a tension within the autonomy driver, as for one part, it encompases the need for discovery, which is built under the idea of resolving uncertainty, which requires giving away control and playing with randomness and the unknown, while on the other hand it also encompases the need for empowerment, which is built under the idea of control.

Why some players prefer one or the other type, might also be related to the theory of locus of control, that shows that, when explaining bad outcomes, some people will blame external factors (I was too tired to take that exam) while others will blame themselves (I did not study enough). The first are more prone to feel that they are controlled by random events, which takes away some of the responsibility of failing ("I always lose at Risk because the dice are never on my favor"), while the second are more inclined to grab control and prefer games of skill ("I didn't see that knight being able to attack my king and rook at the same time. My fault."). Skill and chance are deeply rooted on the way we see life, and this is deeply built into game design.

Now, I always thought games of chance would be those with randomizers, like dice, cards or many Math.random() functions, while games of skill would have open and controllable information. And I think I was half right, in terms on how player's tend to make that division, but now I think it goes deeper than that, as games of pure skill don't really exist (it would kill the uncertainty principle needed to keep players engaged). So now I'm working on a different point of view.

Games of skill are born from the imperfection of human beings

A challenge can only be a challenge when some objective tests the limits of your skills, which means that your skills are not perfectly honed. And that's part of the beauty of it, our brains and bodies are, in a sense, random event generators that always have a probability of failing, or succeeding, a task. You can do a 100 times the same action perfectly just to botch it the 101 (Kasparov lost to deep blue out of exhaustion, which lead to human error). But we do have the ability to improve skills through repetition and learning, so we might only botch an action the first 20 times, just to see how the next 20 our chances of getting it right start improving. With practice, we can adjust those probabilities in a way they can favor us and give us an advantage.

And with games, the design is built in a way that we can see this improvement almost right away. The first time you played Mario Bros, I can assure you, you sucked at it. Probably lost the first time with the first goomba or koopa, or fell through the first hole in the ground. But with just a couple of repetitions you could see how you started advancing in the level until you finally reached the goal. This quick learning is really engaging, in opposition to other kinds of slow learning mechanisms, as it creates a sense of control over time. These are the games we perceive as games of skill!

Games of chance are born from external means of unpredictability

Games of chance, on the other hand, have built-in mechanisms that will not allow you to optimize gameplay just by skill. Skill can give you an edge, like when you are playing poker, but it will never ensure you the victory. You could never become 100% certain (not even a 60%) that you will always beat your opponents in a game like Risk. Your strategies are modulated by the roll of some dice, which you cannot control. In games of chance you try to find the things you can control to improve your odds, but still, those odds suck by nature (which is what creates that feeling of rush when you actually win!).

Games of chance bring the idea of "luck" into the table in a special way, as our brains tend to understand luck as an actual skill! Some people will tell you that they are just really lucky, or that they suck in games of luck, which is obviously (well, not really) false. Some brains have a tendency to better remember good outcomes and forget bad ones, while others tend to fixate only on bad outcomes. The first brains will enjoy way more those games of chance, while the other will only enjoy them if they are offered a way to control the odds. Control randomness is an important concept in this kind of games on modern game design: you might need to roll a die to hit your opponent, but you might buy some power tokens that, if spent, will add 2 to your die result. Now you have some choice back, which gives a sense of control and skill in an otherwise game of luck.

The complex spectrum of luck and chance

Modern games are really a mixture of both schemes, using some chance to create replayability, while using elements of control to give a sense of choice and improvement to players. In Zelda you might need to recognize patterns to fight bosses, but you also get loot boxes and randomly generated damage scores, with critical hits and all. Most board games have some kind of "event card" mechanics, which allows randomness to occur, but might give you powers to check the deck before hand or rearrange the cards if you spend some resources. I could almost argue that most modern games would be almost impossible to actually rate them as games of chance or games of skill.

This spectrum is hard to understand because games might play with skill in some areas of the design, while giving away to luck on different areas. But the probabilistic nature of our brains and bodies, as I said before, creates another layer of uncertainty, where, even in games that tend to revolve around skill, the actual outcome of each game round feels like it has some features of chance. Let's go back to Mario Bros. With each attempt you can see how you don't always lose in the same place, even if all the elements of the game are responding to the same algorithm and move predictably. You might learn how to react to the environment, but you might react half a second to late and fall though a cliff you usually are able to jump proficiently. In Mario you (almost) never hone your skills to the point where you can be 100% sure that you can pass the level, you just hone them enough so that reaching the goal becomes a probable event, and, when you finally reach the pole, you go to the next level and never look back (this is classic Mario, of course). So, even games of skill are built around elements of chance. And here comes how this can be incorporated into a challenge framework for gamification (and game design of course!).

Challenge through uncertainty, not chance

Chance is important for replayability, and may play a role in challenge design, but, maybe in a purist form, a challenge is a design paradigm built around skill testing. You might think that challenge design is about setting goals, but that is not actually true, as you can place a goal like "climb 20 steps", and it will not feel like a challenge. Why climbing 20 steps is not a "game" challenge, but climbing 20 steps in under five seconds can start feeling like one? Because of probabilities.

Many "challenges" in gamification are built like the 20 steps example. Go to the gym 3 times, watch 3 episodes of a series, read 20 pages. This feels more like work than like play, and you know that, if you attempt it, your probability of success only depends on your perseverance. A game challenge forces the player to make strategies, test hypothesis, make choices and be creative, but also takes you to a place where you can actually fail. If you have to climb 20 steps in under five seconds, you might start thinking how many steps you can skip through a single jump, if you can use the railing to give yourself a boost, and you may pressure yourself to the point you actually trip and lose precious time! And that last bit is what makes it a challenge: you have some natural odds built in the way your body acts that, when pressured under time, might make you err. Now let's take away the timer an put a competitor: the game is the same, but the stakes feel different, as now the timer is uncertain as well (if you opponent trips, you might just win some extra seconds!), and there is social pressure.

Understanding this probabilistic nature is a key aspect to create an engaging experience, as you might build features into your game that rely more on skill, or more in luck, without it even having any kind of elements of chance! Of course you can add elements of chance, but this article is about challenge design. Taking this into account, I have updated my challenge framework around aspects that might help me create better challenges, so, finally, I give you a list of things you can work with!

BEM's Updated Challenge Framework

I have 7 domains I work with when building challenges. This is old, but now I have divided each domain in two subdivisions: elements of uncertainty and elements of control. This connects BEM's driver of Mastery with the driver of Empowerment and Discovery. I will leave a quick list of the domains and those elements so you can feel how this framework might be used. This is still a WIP, but is a starting point to understand how game challenges are built.

Domain of Alea: the proper domain of creating challenge through chance, that is through random generators. Even in this realm, skill plays an important part, as you can have features that allow calculating and controlling the odds.

• Uncertainty: Beating the odds and surprise, deterministic randomness.
• Control: Playing the calculated odds, controlling the odds, tactical randomness.

Domain of Perceptio: plays with the natural perception errors of our brain, and our inability to process large amounts of information. This makes as prone to failing noticing important details.

• Uncertainty: Perception errors and filters, reflexes and reaction times, perceptual contradictions, information ultra-corrections.
• Control: Prediction of future states, pattern recognition, controlled sequences.

Domain of Memoriae: games play with our flawed memory system. Memory tournaments show still how trainable this skill can be, but most of us have a limited capacity of storage and recollection.

• Uncertainty: Recollection ambiguity, forgetfulness, random memories and associations.
• Control: Sequencing memory, mental palace, count keeping, information tracking.

Domain of Oikonomia: relates to our cognitive processes used when managing resources. It's a big element in games where managing points and resources is key. As behavioral economists can tell you, we are not particularly skilled on managing resources, which allows a chance of failure.

• Uncertainty: Betting, gambling, risking, random incomes, unpredictable outcomes.
• Control: Book keeping, controlled investments, productivity engines.

Domain of Logica: our rational cognitive processes, which can fail constantly due to biases, lack of knowledge or external pressures.

• Uncertainty: Brainstorming, quick choices, partial data, meaningful choices, non-causal relationships, poetic thought, bizarre logic, word play, black boxes, cognitive dissonances.
• Control: logical connections, puzzle solving, systemic analysis, data analysis, slow thinking, spatial analysis, narrative structures and clues.

Domain of Dexteritate: Related to our motor and coordinations imperfections that can be honed with time, practice and repetition. Playing with a controller is a way of designing through this domain in video games.

• Uncertainty: fast movements, motor contradictions, secondary hand effect, interconnected movements, uncoordination, lack of precision.
• Control: motor training, muscle memory.

Domain of Intelligentia: the realm of playing against other intelligences, which can be human, animal or artificial.

• Uncertainty: unpredictable behaviors, open choices, bluffs and lies, secret agendas, emotional targeting, unreliable help.
• Control: Behavior patterns and predictions, tells, restricted choices, common goals, open intentions.

This list is meant to show you how games convey, through mechanics, elements related to skill and elements related to luck. When you don't have the skill, you don't feel in control, but if you see that after losing a couple of times you start improving, that's part of the magic behind the path to mastery!

How can this be applied to Gamification? Boring tasks often revolve around repetition and certainty, or around difficulty with high stakes for losing. When you have to deal with the first kind of choices, your experience with them will be of boredom, routine and satiation. With the second kind, there is challenge, but the stakes prevent you from enjoying it, as Flow is dependent on this "perceived importance" (Engersen & Rheinberg) for experience optimization. And our challenge is to manage to incorporate this elements of uncertainty in an otherwise results-oriented world. And you can only sell this idea if you have clear game loops that will allow the players to improve fast while playing with this uncertainty, as the overall business results will improve over time as well.

So it comes back to learning from error, but beware, not every error is the same and not every mistake is forgivable! Innovation tries to sell this idea of learning from mistakes, but what happens when you invest a big budget on a new product just to see it fail in the market and receive a bad PR? Agile design bring the fail fast concept to the table to minimize this risk, but how can this be achieved when you have tight time tables and deliverables? Optimizing a system for challenge through trial and error is not just about saying out loud that you embrace failure, but about having a rules that allow mistakes without racing the stakes, and that is were games shine again. So, what I think is, how can I allow my players to fail in the workplace, without damaging their real world indicators? Let's talk more about this on another article on creating game loops and optional challenges.