Randomness in games and systems is a double-edged sword. When designed well, it creates variety, surprise, and replayability. When done poorly, it leads to frustration, a loss of agency, and the feeling that outcomes are arbitrary rather than earned. This blog post dives into examples of bad randomness that rob players and users of control, focusing on key themes such as predictability versus variety, procedural generation with boundaries, chance-based outcomes versus skill-based responses, and the misconceptions around pattern-seeking and streaks.
Why Does Randomness Matter?
Randomness isn’t inherently bad. MrQ, a company known for its online gaming platform, leverages randomness to keep players engaged. Yet, the key difference lies in how the randomness is applied and perceived. Scientific American has explored the psychology behind randomness perception, highlighting how humans naturally seek patterns—even when none exist—which can exacerbate frustration when games or systems lean too heavily on arbitrary chance.
The ACM (Association for Computing Machinery) has published research about procedural generation algorithms, advocating for controlled randomness with strict boundaries. This strikes a balance between predictability and variety, preventing chaos while still delivering novel experiences.
Predictability vs Variety: Finding the Sweet Spot
Good randomness introduces enough variety to keep users engaged without stripping away their sense of control. Unfortunately, when randomness feels arbitrary, it breaks immersion and engagement.
- Predictability: Too predictable, and games become boring. A player can easily memorize patterns and exploit them.
- Variety: Too random, and the system feels volatile and uncontrollable, which leads to frustration and a loss of player agency.
One example noted in MrQ’s playtests involves slot-like games where the outcome feels purely random. Players shared quotes like “I have no idea if I won because of skill or just dumb luck,” highlighting the frustration caused by poorly balanced randomness. This loss of agency is a core issue with arbitrary randomness.
Procedural Generation With Boundaries
Procedural generation is a popular tool that, if left unchecked, can produce unsatisfying results. The ACM emphasizes that procedural generation must rely on well-defined boundaries to prevent chaos that feels out of control.
Consider rogue-like games that generate levels procedurally. When done right, each run feels fresh but fair. Levels have rules for enemy placement and item distribution, which creates a predictable yet variable experience. If procedural generation is too random, randomly placed impossible obstacles can block player progress without warning—leading to what players describe as “death by bad luck.”
Chance-Based Outcomes vs Skill-Based Responses
One of the most criticized forms of bad randomness occurs when chance completely overrides player skill. Players naturally expect a mix of skill and luck where their decisions influence outcomes, but the game doesn’t hand over the reins.
For example, in many modern “loot box” mechanics, like those found on some MrQ titles, the randomness governs rewards regardless of skill or random encounters effort. Players often express frustration, sharing quotes gathered from playtests: “I can play perfectly but still lose because the game decided so.” This disconnect between player input and outcome causes a profound loss of agency.
By contrast, games that incorporate chance explicitly but still allow skillful play to mitigate or take advantage of randomness foster more satisfying experiences. For instance, card games where draw order is random, but strategic deck building and play decisions allow a skilled player to outmaneuver the odds.
Pattern-Seeking and Streak Misconceptions
Humans are hardwired to detect patterns—even in pure randomness. This natural tendency leads to misconceptions about streaks and “hot” or “cold” runs. Scientific American points out that these are cognitive biases, not meaningful patterns.
Unfortunately, many games and systems exploit this, either deliberately or inadvertently. Players may believe a bad streak is some conspiracy or that a skillful behavior is paying off due to superstition, which piles on frustration when these streaks inevitably end.
In smaller indie games, I’ve counted how many times players blame “RNG” when the real issue is unclear or incomplete rules. It’s common for a player to hear “the game was just ‘unlucky’” when the real root cause lies in opaque mechanics.
Examples of Bad Randomness Impacting Player Experience:
How to Fix Bad Randomness
Based on years of playtesting and narrative design experience, here are practical ways to improve randomness in games and systems:
- Set clear boundaries: Use procedural generation with constraints that ensure fairness.
- Communicate rules clearly: Help players understand what randomness affects and what is skill-based.
- Design randomness to support agency: Allow players to react or manipulate chance elements.
- Avoid unbounded streaks: Randomness needs guardrails to prevent catastrophic chains of bad luck.
- Educate players: Help them recognize cognitive biases around patterns and streaks.
Conclusion
Bad randomness—arbitrary randomness without clear boundaries or player agency—is a major source of frustration. It makes everything feel out of control, robbing players of meaningful engagement. Balancing predictability with variety, controlling procedural generation, blending chance and skill, and addressing misconceptions around streaks are all essential steps to designing randomness well.
For developers and designers, it’s vital to remember: random doesn’t mean uncontrollable. Tools like those used by MrQ and insights from Scientific American and ACM research offer solid foundations for creating randomness that enhances rather than destroys player experience.
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