Does Reducing Random Events Make a Game Feel More Predictable?
Reducing random events can make a game easier to plan around, but fewer rolls alone do not guarantee a more predictable experience. A single event with a large, unexplained impact can outweigh many small variations. To decide what to change, examine the event’s visible odds, how much variation it creates, whether players can influence their exposure to it, and whether its consequences can be recovered from. The aim is to make uncertainty understandable and playable, while keeping the surprises that serve the game.
Start with the event’s impact, not its frequency
For each random event, ask how different the best and worst outcomes are. A small range of outcomes may add texture without changing a player’s broader plan. A wide range can decide a fight, remove a scarce resource, or overturn several turns of preparation. Game designer Sina Shahbazi describes this difference as the event’s “delta of randomness” and argues that outcome range should be considered alongside other properties of the mechanic. “Dissection of Randomness in Games”
This suggests a practical first pass: list the game’s recurring random events, note their possible outcomes, and estimate what each outcome changes in the player’s next decisions. Then prioritize high-impact events. If an event can abruptly close off a route, eliminate a key unit, or determine a match, reducing how often it occurs may help—but so may narrowing its outcome range, adding warning, or giving players a response window.
The frequency still matters when events repeatedly interrupt a single task or create noisy results. Former *Civilization IV* lead designer Soren Johnson notes that adding random variation to every attack can make a system harder to grasp and slow play, even when the overall effect on results is small. Randomness can also add variety or give less experienced players a chance against stronger opponents, so removing it has a cost. “Analysis: Soren Johnson On Playing The Odds”
Make probabilities and triggers understandable
Visible odds help players interpret a risk before committing. That does not mean every game needs precise percentages: a clear range, a named risk tier, or odds shown only when relevant may fit better. The important design question is whether the information provided lets the player make the decision the game expects them to make.
Johnson describes examples in which showing dice or displaying exact combat probabilities made the calculations easier for players to understand. He also warns that people often misjudge small and large probabilities, treating a low chance as if it should happen regularly or a high chance as if it were a guarantee. “Analysis: Soren Johnson On Playing The Odds”
For a designer, transparency includes more than a number. Explain what triggers the event, what outcomes are possible, and whether previous results affect the next chance. If a “bad luck protection” system changes the odds after repeated failures, disclose that rule when it matters to a player’s strategy. Shahbazi notes that a system that adjusts results based on history can itself become part of play if players know how it works. “Dissection of Randomness in Games”
A useful test is to ask players to describe the risk in their own words before they act. If their understanding differs from the rule, improve the explanation or interface before reducing the underlying randomness. This is a design diagnostic, not proof that every player will calculate probabilities accurately; the goal is to make the game’s terms readable enough to support informed choices.
Give players time and options to respond
A random result delivered at the instant an action resolves leaves little room to adapt. A randomized map, starting hand, or forecast, by contrast, can become information the player uses to plan. Shahbazi distinguishes these as output randomness, with little time to influence what happens, and input randomness, which arrives early enough to inform later decisions. These are ends of a spectrum rather than rigid categories. “Dissection of Randomness in Games”
This makes timing a useful alternative to simply cutting events. A storm might be announced one turn before it arrives; an enemy attack might have a readable target; a random reward might offer a choice among several results. Each design preserves variation but gives the player time to change position, spend a resource, or accept a known risk.
Choice should change something consequential. Allowing players to alter a target pool, select a risk level, or spend a limited resource to improve odds can connect their decisions to the result. Shahbazi’s framework calls attention to whether a random effect can be influenced by the player’s actions or by the game’s state. “Dissection of Randomness in Games”
There is no need to make every result controllable. If the player can always cancel the downside at no cost, the event may stop functioning as a risk. Instead, make the available response meaningful: reduce the possible harm, redirect it, trade one resource for another, or choose to take the gamble. These are design options derived from the source framework, not universal rules; their fit depends on the game’s central decisions.
Preserve variety while controlling extreme outcomes
Procedural variation can produce distinct situations, but unrestricted generation may create combinations that are difficult to anticipate or balance. Travis Fort’s University of Central Florida honors thesis examines how procedural generation can be used to shape the uncertainty embedded in a game, including by adding or reducing it. “Controlling Randomness: Using Procedural Generation to Influence Player Uncertainty in Video Games”
One example of constrained variation is to keep the arrangement unpredictable while guaranteeing minimum conditions that protect viable play. Johnson describes *Civilization IV* spacing important strategic resources so that random placement could not cluster them too tightly, while leaving less critical resources freer to cluster. This preserved variety while reducing the chance that an unlucky map arrangement would deny a player access to an important resource. “Analysis: Soren Johnson On Playing The Odds”
For another system, define guardrails before tuning event frequency: a maximum damage range, minimum resource availability, limits on consecutive high-impact events, or a recovery route after a setback. Treat each guardrail as a hypothesis to test in play, since changing one part of a system can alter the value of other choices. Keep outcomes varied enough to create new situations, but avoid combinations that leave no viable response unless that outcome is an intended part of the game.
Make setbacks recoverable when they are meant to be risks
The timing of a setback affects how many decisions remain afterward. Johnson argues that unlucky results are easier to respond to when players have more game left to adapt, and describes card games where random card distribution sets the initial conditions before later decisions determine the result. “Analysis: Soren Johnson On Playing The Odds”
Apply that principle by checking what happens after a bad outcome. Can the player choose a different tactic, rebuild a resource, or protect another objective? Is the event placed so early that its effects shape a longer stretch of play, or so late that it effectively decides the result? Consequences do not have to be harmless to be reversible: recovery may cost time, a scarce item, or a less favorable position. What matters is that the game offers a next decision when the event is meant to create a challenge rather than end the player’s options.
When an event is intentionally decisive, signal that clearly through its stakes and rules. When it is not meant to decide the game, provide room to respond and avoid stacking several severe outcomes before the player has another meaningful turn. That approach retains risk while making the game’s cause-and-effect easier to follow.
A practical design checklist
Before reducing an event, answer these questions:
Impact: How far apart are the best and worst outcomes, and which player decisions do they affect?
Legibility: Can players see the trigger, odds or range, and any rule that changes those odds?
Timing: Does the result arrive early enough for players to act on it, or only after their choices are locked in?
Influence: Can players change the target, exposure, timing, or probability—and is that influence clear?
Recovery: After a poor result, does a meaningful next choice remain?
Purpose: Does the event add variety, create a tactical problem, or keep a contest open? If not, reducing or removing it may simplify the game without sacrificing a useful function.
Use the answers to choose the smallest change that addresses the problem. An event that is too frequent may need a lower rate; an event with opaque odds may need better explanation; an event with an extreme swing may need a narrower range or a recovery path. Reducing random events can make play more predictable when interruptions or noise are the problem, but thoughtful control over visibility, variation, choice, and consequences gives designers a more precise way to preserve surprise while keeping player decisions relevant.