10. Decision-Making

A man without decision can never be said to belong to himself.

—JOHN WATSON FOSTER

It’s not enough to ask players to make decisions—the designer must frame decision points in a way that is conducive to generating or maintaining flow for the player. This critical component is where many games fail. To understand how to craft the most effective decisions, designers must first understand the basics of decision-making in games and then understand the basic features that make those decisions interesting or less interesting.

Interesting decision-making does not necessarily mean “decision-making that I, the designer, like.” Instead, it is decision-making that keeps the player in a space between frustrating challenge and tepid boredom.

Player Agency

For players to have a meaningful decision-making experience during play, they must have agency. Agency means being able to act on your own behalf. You do not have agency when watching movies, because you cannot affect the state of the events. A player who can make only decisions that do not affect the game state does not have agency.

The goal of designers is to give players agency in areas where they require it and to remove it in areas where they do not need it. Take SimCity for example. Running all the operations of a city is a lot of hard work. One responsibility of city planners in some jurisdictions is to determine how and when trash is collected. SimCity, however, does not make you do that. Why? SimCity is mostly about placing resources in proximity to each other and balancing the budget of a city despite the seemingly random wants and needs of the population. For SimCity, Will Wright (the designer of the original game) and the designers of subsequent revisions decided that the player did not need the agency of setting the trash schedules. Perhaps it was not a fun decision to make, or perhaps it did not effectively meet the theme of what the designers wanted players to do. And SimCity is stronger for it.

Look at two games in contrast: NBA Street and NBA Live. These are two games made by the same company (and at one point, the same studio) that tackle the same thematic elements (in part) but offer wildly different levels of player agency. In NBA Live, computer-controlled players (CPU players) get injured, and teams have to manage their bench, negotiate CPU player contracts, and set up offensive and defensive schemes for the CPU players to execute. NBA Street forgoes all this and takes that kind of agency out of players’ hands, greatly simplifying the play. The reason is that the two games target different experiences. These are colloquially known as simulation and arcade, but in reality, the distinction is less binary and more of a spectrum. It is really a question of player agency. In simulation games, players are given much more agency, whereas in arcade-style games, the focus is squarely on smaller sets of game mechanics and many elements are either abstracted away or handled by the computer.

More agency is not necessarily better. Some players find NBA Live frustratingly complex, and others find NBA Street boring because it is too simplified. The key is to give players agency only for decisions they care about and those that effectively serve the experience that the designers wish to create.

Anatomy of a Choice

Salen and Zimmerman’s book Rules of Play (2003) includes a great questionnaire for examining a choice.¹ The following five aspects help you understand the context of a choice:

¹ Zimmerman, E., & Salen, K. (2003). Rules of Play: Game Design Fundamentals. Cambridge, MA: MIT Press.

• BEFORE: What happened before the player was given the choice? What is the context of the choice? What is the game state?

• COMMUNICATION: How is the possibility of choice conveyed to the player? How does the player know there is a choice or what the options are?

• ACTION: How did the player make the choice? What mechanism did the player use to make the choice? Did the player say something aloud, play a card, press a trigger?

• CONSEQUENCES: What is the result of the choice? How will it affect future choices? This aspect combines two questions into one—cheating, I know, but they are tightly coupled. For a choice to have meaning, it must affect the game state in some meaningful way.

• FEEDBACK: How is the result of the choice conveyed to the player? How does the player know what happens after the fact?

Chess, one of the most studied games in the world, features discrete decisions that make it a comparatively easy game to analyze in this way.

In Figure 10.1, it’s white’s move, and the player is faced with the choice of what to move. Let’s analyze this chess game with respect to Salen and Zimmerman’s five aspects:

Figure 10.1 A possible set of chess positions.

• BEFORE: What happened before the player was given the choice? Obviously some of the game has been completed. A few pieces are missing from each side, but the game is still fairly even. By looking at the board, you can get some context. Most of the pawns are locked up by being face to face with each other, and thus they can no longer move unless they can capture another piece.

• COMMUNICATION: How is the possibility of choice conveyed to the player? Board games like chess make this easy. Since this is a game of perfect information, both players are aware of the whole board state at any time. The white player can see all the available moves. In computer chess, the client will often show all available moves by highlighting squares.

• ACTION: How did the player make the choice? The player had to first analyze which white pieces could move and where they could move. White would also have to analyze where black’s pieces could move and where they were likely to move. With all this congestion on the board, white feels that knights are more powerful than bishops, so the white bishop is moved to B5 to put black’s remaining knight in danger. If black moves the knight out of danger, black puts his queen directly in danger.

• CONSEQUENCES: What is the result of the choice? How will it affect future choices? Now black is faced with a problem: give up the knight or the queen? It is a great move for white and will affect future choices by giving her a piece advantage.

• FEEDBACK: How is the result of the choice conveyed to the player? Games of perfect information like this are understood by both players and don’t have issues communicating the options or results of those options.

White has plenty of options here, and each has its pros and cons. White did not have to move the bishop. The rook at B1 could have been moved in to threaten the knight. Or white could start maneuvering her remaining knight to jump the blockade of pawns and start picking off the cluster of high-value pieces in the back. This is an interesting decision because many of the options available to white have real consequences for the game state that shift from turn to turn.

By using these questions, you can diagnose where your game is running into problems. For instance, if decisions feel meaningless or arbitrary, it’s likely that your answer to the Consequences question is the culprit. If your players are confused, then your answers to the Communication and Feedback questions are likely where you need to look. If players understand what the game is trying to do but still cite frustration at the actual functioning of the game, your answer to the Action question may be the reason.

I’ve discussed the importance of meaningful decisions in games. A related point is that the act of choosing is highly motivating. Choice itself means control, even when the choice doesn’t result in increased control.²

² Cordova, D. I., & Lepper, M. R. (1996). “Intrinsic Motivation and the Process of Learning: Beneficial Effects of Contextualization, Personalization, and Choice.” Journal of Educational Psychology, 88(4), 715.

Less-Interesting Decision-Making

It is easy for a game designer to add decision-making to the design of her game, but how does she know what is an interesting decision versus a less-interesting decision? Some forms of decision-making are more likely to fall flat than others. They are not always completely inappropriate for use in games, but when bad decision-making needles players in a game, it’s often reducible to one of the following categories.

Blind Decisions

This is a type of decision-making seen often in RPGs. As the game begins, you are given a choice: Would you like to be a Human, a Mole-person, or a Lizard-man? What information does the player use to determine which is the best choice? Since he has just started the game, he doesn’t have a basis for making the decision, except possibly from previous experience with the game or genre. If he has no reason to pick any of the proposed options, then the decision is blind; he might as well throw darts at a dartboard to choose (Figure 10.2).

IMAGE OF THE COMPUTER GAME LEGEND OF GRIMROCK (2012) BY ALMOST HUMAN LTD. USED WITH PERMISSION

Figure 10.2 Many interesting choices the player is not yet equipped to make.

Blind decision-making can be difficult for designers to root out. Since the designer knows all the under-the-hood mechanics, she has an inside edge and the decision may not be blind for her. But the players are the ones interacting with the system. Even giving them hints, such as “Mole-people can see in the dark,” may not help, because the player doesn’t know how useful a trait that may be.

If a player is allowed to play all three races in a tutorial world that show the pros and cons of each choice, his decision of which to play for the rest of the game is informed. The converse of blind decision-making is informed decision-making. When a coach of American football chooses to call a run play, the decision is an informed decision with information about the opponent’s defenses. He believes that, given the personnel on the field and information from previous plays, calling a run play will yield better results than a pass play. He does not pick arbitrarily.

Blind decisions can be acceptable if they lead to information that makes later similar decisions informed. Say you are fighting a boss in Mega Man 3 and have nine different weapons from which to choose. Your initial decision of what weapon to use is blind. Any weapon is likely as good as any other. But as you cycle through your weapons and see which does the most damage, you can incrementally solve the dilemma of what the optimal play is. The same goes for the role of football coach. If the coach has never seen the opposing team before, the first few play calls may be blind. But as the coach accesses the effectiveness of the different types of play versus the opponent’s changing defenses, the decision-making becomes more and more informed. In both of these examples, the decision-making is iterative and the player is not locked into a blind decision made earlier. If the designer must force the player to make a blind decision, she should make the choice reversible or its effect minimal. For example, the effect of choosing an incorrect weapon for the first few seconds of a battle in Mega Man 3 is minimal as long as you quickly switch to another weapon.

Obvious Decisions

Another form of ineffective decision-making is the obvious decision. An obvious decision is one where every rational player would only ever choose one option. Consider tic-tac-toe. If your opponent is one square away from making three in a row, then the choice of where to move is obvious. If you do not block your opponent, the opponent will win. If you are one move away from three in a row, your move is also obvious and a guaranteed win. Since so many of the scenarios involved in tic-tac-toe are obvious choices, it gets lumped in with the games that offer no choices at all!

In Monopoly, when you land on the Income Tax space, you can pay 10 percent of your assets or you can pay $200. This is a decision, certainly, but if you know what your assets are worth, the decision is obvious. If you have $2000 in assets or more, you pay the $200. Otherwise, you pay the 10 percent.

Consider the folk game nim, a form of which is shown in Figure 10.3. In this version, the game has three bowls of marbles. Each player takes a turn, taking as many marbles from a single bowl as she wishes, but she must take at least one. The winner is the player who takes the last marble in the game.

Figure 10.3 A set of bowls containing marbles for a game of nim.

Adults can play this game with interest, but it is just as solved as tic-tac-toe. The difference is that solving the game is less intuitive and requires a bit more math. Nonetheless, the first player can never lose if she plays optimally, much like in tic-tac-toe, meaning the decisions are meaningless for players who understand the strategy. Much like a child can play tic-tac-toe with interest before he understands the strategy, adults can play nim and make meaningful decisions until they know the optimal strategy.

Another form of obvious decision-making is the Hobson’s choice. A Hobson’s choice is a “take it or leave it” choice. Certainly you faced one of these as a child. If you complained about dinner, your mother might say, “You can eat the broccoli or have no dinner at all.” Hobson’s choice is so named because of a 17th-century livery stable owner. Although Hobson had 40 horses in his stables, giving you the illusion of choice about which to borrow, he allowed only the one closest to the door to be rented, leaving his best horses farther back to best preserve their value. Hobson offered the choice “Take the horse by the door or no horse at all.” This is an obvious choice for someone who needs a horse that day. The broken-down horse near the front, although not as good as the young steeds in the back, was certainly better than no horse at all. A choice of the form “Do X or lose the game” is a Hobson’s choice. Although a player could always choose to lose the game, why would he?

Generally speaking, if the action can be automated and the game state is no different for it, then the choice is obvious. Take the evolution of reloading in shooter games, for example. When a player has no bullets loaded in her gun and tries to fire, what happens? What would happen in reality is that the gun would click but not fire. However, almost universally now in games, the gun starts reloading automatically when the player attempts to shoot without bullets loaded. Why? This is an obvious choice. The player wants to shoot but cannot because she has no ammo in the clip. Therefore, she must choose to reload. The answer is obvious and so the digital action is automated.

Meaningless/Misleading Decisions

A decision that is meaningless results in no difference to the game state.

Narrative-based games are often forced into meaningless decisions because of the cost of making content to fulfill every possible option. At the beginning of many RPGs, the king asks the protagonist if he will go find the magic MacGuffin in order to save the kingdom/princess/world/universe. The player is then given a “Will you accept the quest?” prompt. If the player chooses No, he does not engage in a simulation of what the rest of the protagonist’s life would be like. Usually, at this point, the king just acts flummoxed and asks the question again and again until the player says yes. Then everyone can continue with their assigned roles.

Telltale’s Walking Dead series of adventure games puts an interesting spin on this principle. Many of the dialogue choices the player makes in the game are meaningless in that they offer no difference or extremely negligible differences in the game’s reaction to those choices. But mixed in with those are similar-looking choices that are extremely meaningful and lead to major changes in cast and plot. By mixing the two, Telltale makes it so the player never really knows what decisions will come back to haunt her, and thus she has to treat every dialogue choice as meaningful. It’s a difficult scheme to reinforce, but Telltale does it by making some of the players’ early dialogue decisions extremely poignant; this approach functions as a tutorial for players so that they can see that the dialogue choices they make have serious effects.

Sometimes, meaningless decision-making is apparent only after the fact. Consider the offensive play caller for a football team. He will make dozens of decisions about what plays to call over the course of the game. Even if the calls are perfect and the team scores four touchdowns, perhaps the defense is poor and allows five touchdowns. The offensive play caller’s decision-making was after-the-fact meaningless. Nothing the caller could have done would have changed the result of the game. The offensive play caller’s decision-making was meaningless in retrospect, and this incentivizes him to care less about his decision-making in the future.

Blackjack is a game with after-the-fact meaningless decisions. If I am dealt a 16, I can stay or hit (take another card). The next card in the deck is a 10. The dealer has a 20. If I hit, I lose because I go over 21. If I stay, I lose because I have less than 20. Since I do not know what the next card is or what the dealer has, I “play the odds” that my choice will be correct. It has meaning at the time I make the choice, but afterward, it is revealed that the choice had no importance at all. I would have lost either way.

A misleading decision is a special case of the meaningless decision. It is when the player chooses to do one thing, but the game or system does another. In the previous “Do you want to save the kingdom?” example, imagine if you had said “No, thanks” to saving the kingdom and the game let you. You then go home to find that the same monster that you would have had to fight to save the kingdom has just broken into your home and stolen your family. Now you must go on the same quest as you would have if you had chosen to save the kingdom. Why have this decision at all if you are just going to mislead the player into making the decision contrary to her desires? This type of decision is often used to force the player into particular narrative situations. If you must force a player into a narrative situation, it is best to do so without the dishonest illusion of player choice.

Handcuffing Decisions

Designer Daniel Solis pointed out on his blog an interesting excerpt from an interview with Paul Peterson, the designer of the Guillotine card game.³ Peterson says his biggest mistake as a game designer is the Guillotine card labeled “Callous Guards.” The game Guillotine is about manipulating a line of nobles on their way to the guillotine during the French Revolution. When a player plays the Callous Guards card, it renders other players unable to alter the order of the line of nobles. This eliminates, in one fell swoop, a large portion of the options that players have. Their universe of interesting options shrinks to possibly nothing.

³ Solis, D. (2015, July 15). “One Thing to Avoid in Game Design.” Retrieved June 30, 2019, from http://danielsolisblog.blogspot.com/2015/07/one-thing-to-avoid-in-game-design.html.

A handcuffing decision is one that takes away the ability of players to make further meaningful decisions. The most common way to handcuff players in poor games is to make them freeze or skip a turn. Much like some of the other decision types, handcuffing decisions are not always bad. The value of the handcuffing needs to be weighed against its impact. In Monopoly, players are handcuffed (thematically and mechanically) by going to Jail. Jail serves a purpose in that it limits the possibility of someone taking infinite turns by rolling consecutive doubles forever. It also serves the purpose of providing a safe harbor to temporarily prevent the player from landing on high-rent spaces late in the game. Those benefits have to be weighed against the fact that some players will sit in Jail attempting to roll doubles, and make no meaningful decisions for a long stretch of the game.

Handcuffing decisions need to be weighed against the dynamics of the game. Some games are inherently combative, and reducing the decision space is part of the normal dynamics of the game. In chess, you would not say that putting someone into check is handcuffing them because it reduces their possible moves to any that get them out of check. Instead, this is a normal dynamic for the game, especially considering that an implicit objective of the game is to avoid endangering your king. However, if playtesters are consistently saying, “I don’t have anything to do,” “There’s nothing I can do,” “I don’t have many options here,” or “When am I going to get to take a turn?” then they may be encountering decisions that are serving as handcuffs.

More-Interesting Decision-Making

Whether the actual decision-making in a game is interesting or not is up to the players themselves, but certain types of design patterns help make for interesting decision-making.

Trade-offs

The single most useful technique for making a decision interesting, hands down, is introducing a trade-off. In a trade-off, the player is given two or more options, each of which has its own unique benefits and drawbacks. For instance, in Team Fortress 2, the Pyro can choose as their weapon the flamethrower or the backburner (among others). The flamethrower is the standard weapon. If the player chooses the backburner, she can deal more critical hits than she can with the standard flamethrower, but her secondary attack costs 150 percent more, meaning it can be used less often. The player gets to deal a little bit more damage with her primary attack, but trades that advantage for reducing the effectiveness of her secondary attack.

In the board game Ticket to Ride, the players are able to do one of three things on their turns: acquire trains for building, build using those trains, or acquire tickets for additional objectives. Since players cannot acquire the resources and build on the same turn, the trade-off requires them to choose between acquiring resources and locking in those resources to score points.

For a trade-off to be effective, each option must provide some benefit and some drawback when compared to the other options available. In a trade-off, the players are always giving up something for something else. Otherwise, the choice is dominated (see Chapter 19) or obvious (see the section “Obvious Decisions,” earlier in this chapter). Trade-offs incorporate the concept of opportunity cost from economics. An opportunity cost is the cost of using the next-best alternative. If you choose to go to the movies with your partner instead of going to work, the cost is not only the ticket price, but also the cost of a few hours of lost productivity since you cannot work on developing your game during that time.

In the card game Dominion, the players are faced with the choice of purchasing Action cards, which help them during the game but are worth nothing at the end of the game, or buying Victory cards, which are worth points at the end of the game but are useless in the player’s deck. When the player chooses to buy a Victory card, his opportunity cost is the benefit he could have received from a similarly valued Action card. Since the game has an endpoint, buying Action cards early in the game is best, because the Victory Action card may come up many times. But as the game nears its end, the opportunity cost lessens, since any bought Action card may never come up at all. Note that this change in value is all implicit. The cost in coins written on the card never changes. The cost of each card is 5 (see the lower-left corner of the card in Figure 10.4), yet on the first turn of the game, almost all players choose Laboratory over Duchy, whereas on the last turn, almost all players choose Duchy over Laboratory (Figure 10.5).

THE DUCHY CARD IS © 2009–2016 RIO GRANDE GAMES AND ALANA LEMMER. USED WITH PERMISSION.

Figure 10.4 The Duchy card is useless in the beginning of the game but very useful at the end of the game.

THE LABORATORY CARD IS © 2009–2016 RIO GRANDE GAMES AND JULIEN DELVAR. USED WITH PERMISSION.

Figure 10.5 The Laboratory card is useful during the game but worth nothing at the end of the game.

Trade-offs are not always a wise thing to offer players. In narrative-based games, often the designer would need to make a lot of unique content so the player can have truly meaningful trade-offs. For instance, in another medieval game example, the player can choose to support the king, or kill the king and take the throne for herself. If the game allows that option, it must tailor all the remaining events in the game to the results of that decision. The expectation is that characters will treat the player differently—as someone who committed regicide and stole the throne for herself. Quests that would have made sense for a normal adventurer would no longer make sense for the new queen. Now that is certainly a meaningful trade-off: The player gets the rights and privileges of the ruler of the land, but she has to deal with the responsibilities of being what her subjects see as an unrightfully crowned monarch. The downside for game makers is that the game has a huge swath of content that the player will never see. If the player chooses the “support the king” role, all the interesting post-regicide quests are inaccessible. A game that offers a trade-off like this would seem shorter to a player who only plays through the game once, because she unknowingly misses a large amount of content down the narrative paths she did not choose.

Trade-offs can backfire in some situations. Have you ever been paralyzed with your choices when a waiter comes by to take your order at a restaurant? The issue of an overabundance of choice was the subject of a popularly cited study.⁴ The research group set up a booth at a local supermarket; the booth displayed a number of jams with free samples. Periodically, they would switch from having six jams on display to having 24 jams on display. The researchers found that more customers were drawn to the display when it had 24 on display (we love choice!), but when the display had only six jams, the display was ten times as effective at converting those tasters to sales. The conclusion of the study is that although we may like having options, it doesn’t always result in optimal behavior.

⁴ Iyengar, S., & Lepper, M. (2000). “When Choice Is Demotivating: Can One Desire Too Much of a Good Thing?” Journal of Personality and Social Psychology, 995–1006.

Risk–Reward

One of the other surefire ways to make a decision more interesting is to offer options with less certainty and higher payoffs pitted against options of high certainty and low payoff. This is more commonly called a risk–reward choice.

One of the most salient examples of this is the classic game show Let’s Make a Deal. In it, contestants win prizes and then are asked if they want to keep that prize or trade it for what is behind a curtain, sight unseen. Say the player had just won a $500 television. He could keep that television or trade it for the mystery prize. He does not know whether that mystery prize is worth more than $500 or less than $500. He knows that on these trades the show often gives away great prizes like vacations and cars, but that the show also often has joke prizes that are worthless, such as boxes of bubble wrap. If he knew what was behind the curtain, the choice would be obvious. He would just go with the prize that he valued more. But the fact that the prize is hidden creates risk and makes the decision interesting.

These kinds of risk decisions can be much more subtle. Look at the following diagram of the Elevator level from Donkey Kong (Figure 10.6).

Figure 10.6 The Elevator level of Donkey Kong.

Mario (or Jumpman) starts in the lower left and has to reach Pauline at the top. Meanwhile, Donkey Kong is throwing these nasty spring things and sentient fires are running around trying to roast our plucky hero. The left elevator cycles platforms up. The right elevator cycles platforms down.

You can tackle this level in at least two ways. Assume that you are at the position marked A in Figure 10.6. The elevator platforms to the right of the A position are moving downward. One route is to quickly jump onto the elevator platform and then onto the high platform with the jump labeled B. The other route is to ride the elevator down to the bottom and take the jump labeled C.

Taking route B is incredibly risky. It involves a pair of split-second jumps that need to be executed perfectly. Route C, however, does not require those precision jumps, but you have to deal with the spring things that are constantly raining down. In addition to that, you must make six more jumps than if you had taken route B. Although those jumps are considerably easier than the ones in route B, each is a chance to make a mistake. And in addition, taking route C involves dealing with a flame monster in the upper-right corner (not pictured).

This is a real risk–reward scenario. A player taking route B is taking a huge risk by taking on the difficult jumps, but the reward is being able to bypass a large section of the level. Many risk–reward scenarios take the form of time-shifting: turning short-term risk into the potential for long-term gain versus short-term certainty for short-term gain.

Expected Value

One helpful concept that you can use when analyzing choices is the economic concept of expected value. One explanation of expected value is that it is the average value you would receive out of a game if you played it numerous times.

For instance, say I offer you a chance to play a simple coin-toss game. In it, you flip a coin and call it in the air. If you get it right, I give you $3. If you get it wrong, you give me $2. Sounds like a pretty compelling game for you, right? Why?

The expected value is the sum of the rewards for each event multiplied by the probability of each event. In this coin example, you would have the following:

Expected Value = Probability of Correctly Calling the Flip * $3 + Probability of Incorrectly Calling the Flip * –$2.

Expected Value = 0.5 * $3 + 0.5 * –$2

Expected Value = $0.50

Since the expected value for you is to gain $0.50 per game, it makes sense for you to play it because each game, on average, should net you $0.50. If this expected value were negative, it wouldn’t make sense for you to play.

Now say that you are trying to balance a monster’s treasure drop in an RPG. You want the player to have to beat 100 monsters on average to be able to amass 10,000 gold’s worth of treasure because the key to the next dungeon costs 10,000 gold. The monster can drop one of three items: a rusty sword worth 10 gold, a necklace worth 200 gold, or a statue worth 1000 gold. What should the drop rates be?

If 50 percent of the time defeating a monster gives you a shield, then you would say that the shield has a 50-percent drop rate from that monster. Another way to note this is by using nomenclature from probability. Here, I use P(Event) to note the probability of an event. I’ll discuss probability in greater detail in Chapter 29.

E(X) = P(Sword)*10 + P(Necklace)*200 + P(Statue)*1000

First, you know that you want the expected value to be 100 gold because 10,000 gold/100 monsters = 100 gold/monster. You have two simultaneous equations for three variables, so you know from algebra that you can have many solutions. To make this easier, give P(Statue) an arbitrary value of 1 percent. It’s a valuable drop. It makes sense that it should be pretty rare. Now the equation simplifies to one solution:

100 = 10* P(Sword) + 200 * (0.99 – P(Sword)) + (0.01 * 1000)

190 * P(Sword) = 108

P(Sword) = 0.568

P(Necklace) = 0.421

P(Statue) = 0.01

In crafting interesting decisions, the expected value per time or action of your choices must be similar or the choice will be obvious. There is a caveat here that will be better covered when human decision-making is covered in Chapter 26. We do not always choose what is mathematically “better” for us. Luckily, game designers can use certain observed biases to craft desired behaviors, which will also be covered in Chapter 26. When you craft options for your player with similar expected values over different risk profiles, the choices require the player to make some interesting decisions.

Summary

• Decision-making is crucial to games because good decisions for a player will keep him within his flow channels.

• You can analyze a choice by noting what happens before the choice, how the information about the choice is communicated to the player, what the player chooses, what consequences that choice causes, and how those consequences are communicated to the player.

• Not all decision-making is created equal. There are categories of decision-making offered to players that do nothing for or work against players’ need for balanced challenge.

• Two ways to offer more interesting decisions are to frame the consequences of a decision as a trade-off between two resources or as a decision between a high-value reward with low probability and a low-value reward with high probability.

• The concept of expected value allows you to boil down a menu of possibilities to a weighted average result in order to compare complex events.