Clarity and trust
Randomness in games: probability and player trust
The attack had a 90% hit chance, yet it missed twice. The calculation may be correct while the player suspects the game is cheating. The question is what information they need to understand and trust the result.
Key idea
You can hide a complex formula, but players need clues about the causes that change its result.
Digital games can automate complex probabilities and calculations. This expands the possibilities of design, but also creates a responsibility: the player needs to understand the logic of what happens, even if they cannot see the entire formula.
Why a die feels more trustworthy than a percentage
When a die lands on the table, the process is visible. A bad result may be frustrating, but the player has seen how it happened. In a video game, a 90% indicator followed by two misses can raise suspicions even though it is mathematically possible: two independent events with a 10% failure chance will both fail approximately once in every hundred pairs of attempts.
Perception matters because players do not always interpret a percentage as a probability. They often read it as a promise of success. That is why some digital systems adjust streaks or protect against extreme results: they aim to make randomness feel fair as well as remain consistent with the game's goals.
Hide operations without hiding causes
A computer can combine attributes, equipment, distance, terrain and status effects in a fraction of a second. On the tabletop, the same amount of calculation could interrupt the pace. This difference allows deep digital systems, provided their consequences remain readable.
If an attack deals twelve points of damage and the player does not know whether the cause was the opponent's armour, distance, their weapon or an active status effect, complexity can feel arbitrary. There is no need to show every component of a formula, but the relevant factors should be communicated through predictions, icons, colours, animations, status indicators or clear messages.
Trust as a design requirement
A system does not work simply because its numbers are correct. The player needs to connect a decision to its result to learn, adapt their strategy and trust the rules. Information design determines which calculations the machine can perform in the background and which clues the person playing needs to receive.
Apply it to your game
- Choose a result that raises suspicions, such as a miss or unexpected damage. Check the calculation and the information the player received before deciding.
- Identify the factors players can actually use: distance, armour, status or probability. Make them visible when they help players choose.
- After the action, ask players to explain why they got that result and what they would change on the next attempt. Compare their explanation with the actual system.
Understanding a defeat helps turn failure into learning. When someone describes the system as unfair, interpreting playtests helps you investigate whether the calculation, information or expectation is at fault.
Shadow Strike tackles another readability problem: how to make the camera clearly communicate which target the player is selecting. Read the Shadow Strike target-selection case.