If you’re here, reading a game designer blog discussing analysis paralysis, then I’m pretty sure you probably have some idea of what I mean by the words “Analysis Paralysis” (hereafter referred to as AP). If you don’t, don’t fret! Jump back to Part 1 and read the “What is AP?” section for a primer on the subject.

This is the fourth article in a series of 7, each article in this series will go into depth on one potential cause of AP, examples of situations where it can be problematic, and present some solutions that can improve the situation.

If you have any suggestions, examples, questions, or want to point out something I’ve missed, please do so in the comments. This is not a scientifically rigorous examination of AP, and I would be happy to include any contributions you have!

The Maze to Victory

The problem of plotting for the future.

Category: Quality

Player Symptoms:

Uncertainty or questions regarding relative value of options.
Difficulty selecting and maintaining a consistent strategy.
Confusion over strategic choices other players make.
Expression of choices or options not being useful.
Selection of options or choices that are contradictory or non-complementary.
Delay or indecision coupled with poor decision making.
New players to this game unable to play competitively regardless of general gaming and strategic experience.

Cause of Problem:

Planning for the future is always a primary source of AP, whether it is trying to guess your opponent’s actions, or trying to maximize your own score. In the Maze to Victory we are considering three different shades of one specific type of planning for the future: plotting for the future; or being able to distinguish and make strategic choices for the purpose of implementing a chosen strategy.

Problem 1: Short Term Benefit vs Long Term Potential

The tug-of-war between choosing a course of action that grants a short term benefit while possibly compromising your long term potential is a staple feature of many games is sometimes an essential part of the gaming experience.

The problem of AP can arise though when the benefits and potential of long term choices is ambiguous, poorly defined, or hidden due to a dependency on components that are not visible yet to the players. This typically produces a disparity in success between players who are new to the game and players who have played it many times – regardless of their relative skill or experience with other similar style games.

A classic counter-example to this problem is the party game. A party game is exemplified by simple, easy to understand rules, quick action, and general lack of strategic depth. A party game is one where the best choice is often obvious, and there is no benefit to be gained by not choosing it. These games work best when a greedy strategy is a good strategy. A greedy strategy or algorithm is one that attempts to solve a problem by taking the optimal choice at each opportunity in hopes of finding the best possible (global) result.

The reason I am taking time to point out party games and greedy strategies, is that players who are new to a game will often be inclined towards using some manner of greedy strategy when they are new to a game, until they better understand the nuances of how the game works. The time that it takes a player to progress beyond using a simple greedy strategy to more complicated indirect strategies is dependent on their skill and their experience with similar types of games. This is part of a game’s learning curve.

This applies to the original problem in two ways. The magnitude of the experience disparity, and the severity of strategic aspect of the learning curve.

Games where the difference between a greedy strategy and a nuanced strategy are relatively minor – usually because they can be negated by random chance – and that inexperienced players still have a reasonable chance at winning are less likely to cause AP problems for those players. Catan for instance, where the best strategies can easily be undermined by the roll of the dice, is one where AP doesn’t often play a significant role.

But games where a nuanced strategy cannot be overcome – Puerto Rico for example – produces a situation where new or relatively inexperienced players cannot win without developing a relatively sophisticated strategic approach to the game. When the magnitude of this experience gap is too large, it results in a situation where inexperienced players must carefully consider their options in detail before making a choice to have any possibility of winning… thus, a situation rife with AP potential.

The other aspect that applies, is the severity of the learning curve. A game where all available options are visible, clearly marked, and available for everyone to see is much easier for an inexperienced players to make connections between strategic choices and is easier for them to devise strategies that are competitive with more experienced players.

A game where the value of long term or nuanced choices is hidden from view, or relies upon memorization or extensive experience to know what options may become available later in the game is much more difficult for a new player to grasp or make reasonable choices about their approach. This too is a situation where choices become ambiguous and as a result difficult to make, another prime opportunity for AP to strike.

Problem 2: Seeing the Forest for the Trees

The problem of Forest for the Trees is being able to see and understand the existence of strategy and the ways in which victory can be achieved. A game in which a player can only infer how victory can be accomplished is one that is at increased risk for AP.

A limited example might be if we go back to Catan, but imagine the possibility that you were not allowed to know what kinds of cards existed in the development card deck. You didn’t know about Victory Points, the condition of Largest Army was only printed on soldier cards. Suddenly entire paths to victory are hidden from view and unknown to a novice player. The choice of buying a development card becomes a larger risk with unknown value and that uncertainty leads to paralysis when the opportunity to do so is available but the purpose of doing so is unknown.

Another more currently relevant example would be the category of Escape Room games. The victory condition of an escape room game is to solve puzzles and escape within a certain time frame, but famously they provide no guidance on what ‘escaping’ means, what might be required to do so, or how many solutions need to be discovered to do so. Granted, the game is intended as a puzzle and figuring out what victory means is the core purpose of playing the game in the first place.

Escape room games work amazingly well for players who are interested in having that experience, but there is also a not-insignificant proportion of players to whom this uncertainty is frustrating and places them in a position of not being able to make decisions because of that very reason.

Problem 3: A Maze of Twisty Little Passages, All Alike

The third problem in the Maze to Victory is the bridge between the first two. It is the problem of linking individual complementary choices with a strategic outcome.

If we consider the first problem as being able to understand and devise a strategy, and the second as being able to understand what victory means, this third problem is being able to execute that strategy toward achieving victory.

This problem I find to be well illustrated by Tigris and Euphrates. The game clearly delineates the rules between placing temples, farms, markets, and settlements and scoring points by the use of the four leaders and the building of monuments. It also defines well that the victor is the player with the most points in their weakest category. However, the bridge between applying the basic rules of the game and strategies used to gain points in order to achieve victory is vastly open and varied and there is no inherent structure to indicate or evaluate which approaches might be successful.

As a direct result, the process of understanding how to implement strategies, what works, and what doesn’t is one of practice and repeated failure – and which approaches are more or less valuable in various situations is also highly dependent on what the other players are doing. A novice player will almost never be able to overcome an experienced one. Overall it is a deep and complex game, but also one that can be highly frustrating and prone to AP for those very reasons.

The core of this problem is understanding and applying a strategy towards a goal. Strategic options and victory conditions may be well laid out and clear, but a player who is challenged to comprehend how a strategic path may be effective and earn progress towards their goal is likely to spend additional time analyzing their own choices and whether or not they should switch tactics rather than executing.

Solutions:

The challenge of this problem is that it is one of inexperience. A well-versed player who has played the game a hundred times isn’t going to be challenged by these problems. But a new player who is frustrated by them may never find the game compelling enough to invest their time in and achieve that level of proficiency.

As a result these solutions all revolve around lowering the barrier to entry, clearly marking options, and ways to reduce that learning curve to allow inexperienced players to understand the game and become competitive more quickly.

Linking / Theming:

Using graphic design to link complementary choices together in a way that makes it easier to classify and group them. If your players are regularly needing to read text, look up effects, or examine options in detail in order to make relatively simple choices – your design may need a visual update. Although this example is not perfect in its execution – I recommend looking at Star Realms for the way it themes ship factions to make it quick and easy to visually distinguish selections that work together and the additional bonuses they provide when played during the same turn.

This concept of graphic design enabling gameplay is also useful for transformations – exchanging resources or cubes or cards or whatever for something else, and for comparisons – checking to ensure a condition is satisfied or an obstacle overcome. One Deck Dungeon does this well by theming Strength, Agility, Magic, and Life and allowing a player to quickly compare the number of dice they have to defeat a monster or trap, but also their special ability dice transformation rules that allow them to modify or exchange dice for others.

Valuation:

Like theming, valuation is about quick and easy interpretation of relative value between similar objects or components. This is commonly done using numbers, but size, colour, saturation, and shape are useful as well to enable players to distinguish more valuable options from less valuable ones.

It may also be useful to provide players with additional information that link game state or components to victory conditions. Adding markers to represent victory points, diversifying scoring tokens to include multiple denominations or creating a scoring track to make relative scores more readily visible.

Use explicit representations of progress towards victory conditions rather than inferred ones. Examples: adding a 1 VP marker to each card rather than having a rule that states “score 1 VP for each card”, or adding VP tokens or a scoring track to a game that would otherwise only have VP designations on cards.

By providing concrete and clearly visible progress or scoring markers enables players to more quickly judge relative value and whether they are gaining or losing ground on their goal.

Instruction:

From a purely educational point of view, providing instructional materials in your game that teach players not only the rules and concepts of the game, but basic strategy as well is one way to cut down on beginner hesitancy. Providing a tutorial, a video, or a simpler ‘easy mode’ walkthrough configuration of the game that point out options, strategic decisions, and purpose behind those choices can go a long way towards overcoming early decision making challenges.

The potential solutions that have been presented so far are relatively minor in their scope. They discuss graphical and instructional changes that don’t necessarily impact the game itself. These next few solution options may be worth considering but implementing them would likely result in a dramatic mechanical shift in gameplay.

Unmasking:

Changing hidden information into visible information. Any piece of hidden information is a source of uncertainty, and if that information is important to a decision being made then uncertainty leads to calculation, which can lead to AP. This is especially true if that hidden information directly impacts the conditions or a player’s progress towards victory.

Unmasking information can happen at different scales, and each will impact a game differently. Let’s consider a drawing from a deck of cards:

Fully Hidden: You do not have any idea what the draw deck contains – players must react and use whatever they get but generally cannot plan for the future. The result is a very reactive, greedy strategy or Russian roulette style of gameplay. Players who have played the game before and are aware of the deck contents are at an enormous advantage over players who do not.

Hidden but Known: You know what cards are in the deck, but do not have any idea of what order they are in – players must react and use what they draw, but can evaluate whether what they draw is relatively good or bad compared to other cards are in the deck. This introduces an element of risk into the game, where players might choose to use what they draw or risk obtaining something better. This risk and choosing whether what has been drawn is ‘good enough’ is a prime source of AP. Players who are more familiar with the draw deck are more likely to be successful, and players with greater ability to memorize the cards that have been revealed are better able to evaluate the odds successfully.

Minimal Reveal: You can see the top card on the deck allowing you to more accurately evaluate whether or not the draw is beneficial to you or not. This greatly reduces the risk of drawing, and increases the strategic capability to evaluate your own play and your opponents play depending on what they draw and what they do not.

Multiple Reveal: Seeing more than one card on the top of the deck allows the ability to plan for the future and introduces elements of manoeuvring between opponents. This results in less guess-work and more head-to-head attempts to out-think the other players. This can result in bluffing, and punitive decision making when a player chooses to take actions for the purpose of denying an opponent the opportunity.

Fully Visible: Seeing the entire deck removes all randomness, turning a contest into one of pure skill. Players compete based on their ability to envision future states and moves, and the greater ability to predict and counter an opponent’s choices.

Choosing a level of information visibility can be challenging, too far one way and a game becomes flipping a coin – entirely random. Too far the other way and it becomes a game of chess – analyzable but mentally taxing. Both extremes can result in AP but for different reasons.

Consider the game Pandemic. How would the game change if the infection discard pile was also hidden and you had to remember which cities were revealed recently and which are still on the top of the deck at all times? How would the game change if the next city to be infected was always visible to you? How would it change if the entire infection deck was visible and it became an exercise analyzing the pattern of infections and solving the puzzle?

Randomize:

Wait, what? Adding randomization? I’m sure any serious, competitive, strategic players out there are cringing at this idea… I certainly know more than one who would. Players who laud games of pure skill and despise the variability of a randomizer, especially if the luck of the draw causes them to lose a game.

But that is entirely the point. A deep, strategic, complex game may be impractical or undesirable to implement the solutions I’ve given above. And that’s ok – these articles are all subjective depending on the experience you want your players to have. What a randomization element does is mitigate some of the advantage that a skilled player has over an unskilled one. It opens the door for a poor player to defeat a better one simply through chance. A good randomizer doesn’t make the odds 50/50 – you might as well simply play a game of heads or tails then – but it does open the door by maybe 5%, maybe 20%.

The reason this may be a good thing, is that it allows inexperienced players to feel like they have a chance to win. Even if intricate strategy is beyond them, a random element reduces the pressure of making perfect strategic choices and reduce the amount of time they spend thinking about them, it enables them to try new things and still have the possibility for that rush of victory. A random element may allow those players to have more fun while they are learning and thus keep them playing long enough to pick up those strategies.

Catch-up Mechanics:

Adding a catch-up mechanic to your game has a similar effect to including randomization, except that the effect is applied more evenly across the board and there is less of a feeling that the outcome was beyond the players control. A catch-up mechanic (think Mario Kart where the trailing karts go faster, can draft, and get better items) is used to balance the playing field by reducing the impact of sub-optimal decisions made early in the game by provided trailing players with a way to gain on those in the lead. Whether this might be gaining extra points, moving faster or further, or having first pick, it has the same benefit of reducing the importance of making perfect choices early in the game by letting players recover later in the game.

Next Week

If you have any comments, suggestions, or examples that you would like to share about this week’s topic, please tell us about them in the comments.

Next week we will be looking at the Relationship Status: It's Complicated.

Designer Blog

Breaking the Chains of Analysis Paralysis – The Maze to Victory (Part 4 of 7)