Reblog: Game Internals – Straightening Out Final Fantasy X’s Sphere Grid


Chad Birch breaks down the Sphere Grid, a foundational aspect of character customization and growth in Final Fantasy X. He found is that what appears to be a sprawling, diverse web of options is actually several linear paths with very limited opportunities to branch. The UI makes the simple system look complex influencing the player to feel like they are making more decisions than they actually are.

Mike Says: It’s a great exercise to separate the mechanics and systems of a game from its UI so we can get a real glimpse of what’s happening under the covers. Graphics and good interface design can obscure certain potentially negative properties of systems and lead the player into enjoying a game more than the bare mechanics would indicate they should. It’s great that Chad did the legwork to show just how much obfuscation was going on with the Sphere Grid. He shows how important UI design can be to affecting players regardless of the reality of the systems beneath that UI.

Richard Says: In my experience RPG tech trees and leveling systems like the Sphere Grid are not designed to be deep in themselves. They work best as a way of foreshadowing progress in clearly defined, ability based steps. I wish Chad presented an actual critique or argument about these systems. As it is, he doesn’t say much about game design or UI design. On a final note, I love the graph work Chad did. Nice and clean.

Reblog: Game Maker’s Toolkit – Secrets of Game Feel and Juice


Mark Brown presents a pared down version of Jan Willen Nijman’s talk on game feel (see Vlambeer Scale here). Like in Vlambeer’s talk, Mark’s definition of game feel is remarkably close to a “I know art when I see it” level of scrutiny. But like Vlambeer’s talk, examples provide a much needed base to take game feel from an overly abstract buzz word to a methodology we can apply when making games.

Marcus Says: The two games Mark contrasts at the beginning of the video to show the difference between games with bad and good game feel, scored a 12 and 17 respectively on our Vlambeer Scale. The details listed in the video (screen shake, hit pause, ect.) are all visual details that can be assessed fairly well from a video or an animated gif. The “eye test” seems like a good way to get an initial feel for a game. Without visuals, writing about how a game feels (reviews, previews, ect.) often fails to communicate what a simple picture can. Assuming watching a video is the next best thing to playing when analyzing game feel, I wonder how effective the Vlambeer Scale is?

Richard Says: Great quote: “I’m not sure that ‘be Shigeru Miyamoto’ is particularly useful advice.” In general, I don’t think game design or the sub-category game feel is “elusive,” “ mostly abstract,” or a “largely invisible” art. Hearing Mark Brown say this (47s) reminds me of a forum comment stating that you can’t “see mind games.” If you can’t see mind games, then how do players fall for them when staring at a game screen? Games are complicated and appeal to a lot of different disciplines. Breaking games down, paying careful attention, and taking good notes demystifies a lot of aspects of game design. Also, game feel is rooted in a lot of long standing techniques on animation and sound, so there’s a wealth of knowledge there. Even when a games get game feel right, as Mark claims Super Meat Boy does, players can still have very different play experiences. It took me a bit to get used to the super loose, floaty, crazy acceleration of Meat Boy’s movement. Game feel is an art, not a science.

Reblog: Tron Bonne, an Echo of Better Days

POV: Journalist.  DIFFICULTY 3. LEVEL 1-1
POV: Journalist.  DIFFICULTY 3. LEVEL 1-1

A retro “review” of The Misadventures of Tron Bonne by Jeremy Parish from USgamer.

Marcus Says: I really enjoy how Parish detailed the The Misadventures of Tron Bonne’s genre conventions. Parish did it in a way that didn’t rely on technical jargon. Instead of focusing on rules, systems and mechanics, he explained how the story and feel of the game is a spin off of a spin off, which reflects its oddball gameplay. Parish’s approach reframes expectations. Instead of describing how some mechanics fall short of genre standards, he focuses on how the mechanics enrich the aforementioned story and theme of this misadventure.

Richard Says: I need to take writing lessons from Parish. The writing flowed so nicely. I feel like I have a really good idea what kind of game and experience Tron Bonne is, and I don’t think watching a let’s play would give me a clearer picture. The article overall is more of a summary and review than a critique, but the few statements made clear: “The mission, puzzle, and adventure stages may have been fairly small, but they rewarded experimentation with all sorts of funny and surprising Easter eggs” Also, +1 point for Sokobon puzzles.

Reblog: Sonic and All Stars Racing Transformed – Critique Hit

POV: Designer.  Difficulty 3. Level 1-1
POV: Designer.  Difficulty 3. Level 1-1

GameMage shares his analysis of the design goals behind the item design in Mario Kart and Sonic and All-Stars Racing Transformed. He discusses how the available game modes in each game reflect their overall design goals.

His thesis is that Sonic Racing is a more skill- and skill-building-oriented game, while Mario Kart 8 is more about casual multiplayer play. 

Mike says: It’s an ambitious effort with some pacing and over-scoping problems caused by bringing in too many games later in the video. A promising first episode of a new series of game design analysis videos, though!

Richard says: I like the zoomed in focus on just the power-ups found in Mario Kart 8 and Sonic and All Stars Racing Transformed. The details on when certain power-ups are acquired and the interplay (counters) for them is great. I wish GameMage covered all the power-ups. GameMage essentially argues that the power-up design is the crux of the skill based play in both games. There are many other aspects of these games that determine their capacity for skillful play and depth like controls, frame rate, modes, and options.

Chris says: It’s great that GameMage is able to compare two different games in a genre without succumbing to the temptation to praise one game as better in all aspects over the other. This is why focusing on the details is valuable!

Pac-Man Design: Arcade. Doodle. Map. Mechanics


On May 21st 2010 Google cost the world $120 million. I remember it as the day I visited and found a playable version of Pac-Man in place of Google’s logo. The doodle wasn’t any larger than the normal logo, but the faithful recreation of the sights, sounds, and gameplay of Pac-Man took me from yet another Google search to a glimpse into my past. Now, about five years later, Google has outdone itself with another Pac-Man project.

On April 1st, 2015, I got to play Pac-Man through the streets around my apartment, the DFW airport, and exotic locations around the world via Google’s April Fools’ Day promotion that created Pac-Man levels out of map data.

Between the original Arcade version of Pac-Man and the two Google Pac-Man projects, we have the perfect case study to examine the design of this classic. Because Pac-Man is a relatively simple game, we can dig deep into its entire design and highlight how the small differences between Google’s recreations and the original game make a big difference in the player experience. In this article, I’ll cover the basic mechanic of Pac-Man and build from there in future posts.

There is only one mechanic in Pac-Man; MOVE. No jumping, punching, or shooting. Just moving up, down, left, and right with no momentum or acceleration to worry about. In fact, You don’t even have to hold a particular direction since Pac-Man continues to move in the direction he’s going until stopped by a wall or a Ghost. What’s great about Pac-Man, and what creates gameplay of interesting choices, isn’t deciding how to move, but deciding where to move and when. Still, with controls so simple, there are a few subtle details in the tuning of Pac-Man’s MOVE mechanic we should cover.

In the original Pac-Man arcade, the entire game is designed to fit onto a grid. Pac-Man and the Ghosts are one square large. The walls and lanes are also mapped to this grid so that all movement through the maze is both clear in how it communicates travelable spaces, and clean in that there are no sprite edges to get hung up on as Pac-Man rounds corners.

To make movement even smoother, players can input the direction they want Pac-Man to move before Pac-Man reaches a turn. Doing so allows Pac-Man to turn the corner as quickly and efficiently as possible. This leaning into turns due to the buffered input helps reduce the skill needed to make efficient turns thus freeing up the player’s attention to focus on the strategy of surviving the maze.

The Google doodle nails the controls of Pac-Man. It’s free and you should play it right now to remind yourself how smooth controls lay the foundation for smooth gameplay. Treasure the finely tuned controls while you have them because the controls in the Google map Pac-Man are frustratingly bad.

The core creative conceit of Google Maps Pac-Man (GMPM) is obvious: play Pac-Man out on the roads of the world. The organic geometry of roads, with curves and many-way intersections at odd angles, significantly complicates the control design of Pac-Man.

There are two facets of controller design to focus on here: directness and intuitiveness. Controls are direct when mechanics (player actions) are designed in a way that matches the input method. For Pac-Man arcade version Pac-man can only ever move in a cardinal direction, and an arcade stick allows only cardinal directions, thus forming a perfect mapping. In other words, the player cannot manipulate the input in a way that can’t be reflected in the game. Pressing up moves Pac-Man up always. This design also makes the controls intuitive.

In GMPM, even the controls are not as direct or intuitive as the Pac-Man arcade version, and I blame the curves. When you press up on the Google Maps version, Pac-Man’s path can eventually curve so that Pac-Man moves left, right, down, or any angle in between. Pac-Man will keep traveling down even a curved path automatically. But it’s when I attempt to buy time by moving back and forth along a single curved road that the lack of directness becomes troublesome. On a curved road do I press left-right-left, up-right-up, or some combination of diagonals?

Diagonal road intersections are especially frustrating in GMPM. It’s hard to tell if you should press one or two directions to make a diagonal turn. Because the turns can branch off at any angle, even adding diagonals through 8-way movement controls won’t eliminate ambiguous turns. Since you often can’t tell where Pac-Man will go at an intersection if you hit a certain direction, playing Google Map Pac-Man becomes more about how to move instead of just when and where.  

D-pads are the best input device for instantaneous movement at constant speeds and quick, repeatable discrete movements along 4 axes. Curved movement in games necessitates the use of more complex rules to govern movement that tend to benefit from more complex control input devices like analog sticks. Fortunately, the Google map Pac-Man offers mouse control. With a small yellow arrow indicating the direction Pac-Man will move if possible, the mouse helps players navigate curved paths and angled turns with greater accuracy than the digital arrow controls. Unfortunately, because the mouse is a relative pointing device, Pac-Man will attempt to move toward the mouse cursor at all times. This means you can’t simply move down roads by tapping a direction and taking your hand off the controls. If you aren’t constantly adjusting where the mouse points, Pac-Man may take turns or even reverse direction when unintended. The worst case of this is happens when Pac-Man moves off the edge of the screen–where he ends up is often asymmetrical to where he came from and unpredictable. Keeping control over Pac-Man via mouse position tends to require quick and precise mouse movements. During these brief moments, I feel like I’m playing a first person shooter, not a maze runner.

For the Google Map Pac-Man I like the arrow keys for their simplicity, but I end up using the mouse controls for their accuracy.


Controls and mechanics are the first step to understanding a game. In part 2, we’ll look at what makes Pac-Man gameplay so interesting

Exeggutor Space


This video showcases a unique strategy that revolves around the Pokemon Exeggutor and a rare ability called Harvest. This ability is only found on 5 grass type Pokemon and it lets them consume and regrow Berry items. In the video the Berry chosen is the Petaya Berry which boosts a Pokemon’s special attack when consumed. After seeing the strategy in action, I laughed. I gasped. I pondered why I haven’t thought of it before, and then I laughed again. But if you’re not familiar with Pokemon, you probably don’t really understand what’s going on. There might be this gap preventing you from relating to my excitement or the creativity here.

To illuminate the mystery of creativity and conveyance, I’ll explain why this Harvest + Exeggutor strategy is creative and why it’s so difficult to convey to those unfamiliar with Pokemon and its metagame. To do so I’ll touch on the game design topics of complexity, design space, and nuance.

Whether you’re familiar with Pokemon or not, you should know that the Pokemon handheld RPG video games are very complicated. When I say complicated, I mean there are a lot of rules. Even if we just focus on competitive battling (ignoring all single player challenges, secrets, etc.) we’re talking about hundreds of Pokemon, hundreds of attack moves, half a hundred held items, a handful of variable stats, and a few abilities per Pokemon. There’s a lot of individual rules to learn that come together to make billions of combinations.  

To help organize all this data, it’s helpful to think in terms of the design space, which is a way of organizing all the stuff in a game. In this case, we’re specifically looking at the design space of competitive Pokemon battling. By looking at the big picture and how all the battle rules combine, we see new patterns and groups. For example, fighting type Pokemon generally have high physical attack. Makes sense, right? Also, special (non-physical) fighting type attacks are rare and tend to be inaccurate or weak. That’s good to know. Knowing this pattern, if you see a new fighting type Pokemon you can make a few safe assumptions. Recognizing what is rare, uncommon, and common across the entire game helps players make more informed decisions against the staggering (billions) unknown possible combinations.

Even after seeing the big picture of the design space, there are still dozens of complexities to learn per category. Competitive battlers first learn the moves that seem most powerful or that are most frequently used in competition. As part of a communal learning environment, it’s hard to go against the trends of what’s popular/powerful as the strategies the community prioritizes will be the ones that are refined over time. After all, it’s these strategies that have the most thinkers and testers working on them. And whatever rises to the top of this priority list generally does so because it’s effective in an obvious way that most people can understand and use.

from bulbapedia Bulbagarden  from bulbapedia Bulbagarden

There are many reasons why I haven’t seen the Petaya Berry Exeggutor Harvest strategy before:

  • Exeggutor has some pretty big weaknesses to popular Pokemon and popular moves. Being a Grass-Psychic type, Exeggutor is 4x weak to bug attacks not to mention 2x weakness to Dark, Ghost, Fire, Ice, Poison, and Flying type attacks. U-turn is a popular Bug type move that’s on many non-bug type Pokemon. And most teams have some kind of Fire or Ice attack to deal with other annoyingly strong Pokemon like Ferrothorn and Landorus.
  • The more popular Grass type Pokemon are Venusaur, Breloom, and Ferrothorn.
  • The few Grass Pokemon with the Harvest ability often use a berry that recovers from a status effect or heals back HP instead of the Petaya Berry which raises special attack. Gaining HP is much more directly and obviously related to winning battles than raising special attack. Even with raised special attack, if Exeggutor switches out for another Pokemon, the boost will be nullified. Gained HP is never reset. Healed statuses are never reset.
  • One of the most popular user created formats for competitive battling features a “sleep clause” which limits the number of Pokemon a player can put to sleep on their opponent’s team. This clause works against Grass type Pokemon the most as they cannot use the move Sleep Powder as often as they would want. Sleep-inducing moves are rare within the entire design space of Pokemon.
  • The strategy requires the teamwork of two Pokemon: Emolga and Exeggutor. Exeggutor is too slow on its own unless it gets the speed boost from Emolga. The more Pokemon and steps to a strategy, the more potential weak links in the chain.


Each of the reasons detailed above is the result of thousands of players who chased power and thus defined the overused, popular options. As the community seeks and refines the powerful and popular strategies, all other strategic possibilities are implicitly categorized as less powerful, less obvious, and less effective. In other words, it’s the complexities that get ignored or overlooked that become nuanced.

Keep in mind this sorting is based on what seems powerful. All the overlooked, nuanced Pokemon, moves, and combinations may still be effective, but they’re simply off most players’ radar. The nuanced possibilities therefore surprise us so much more when they turn out to be effective. And for games like Pokemon, surprise and unpredictability are powerful. It takes someone with a vision, or inspiration, or enough luck when throwing random things together to show everyone just how powerful the overlooked and the unexpected can really be; and how much room for novelty and diversity there is within the design space of Pokemon battling.

When I see the Exeggutor strategy begin to fall into place, my entire understanding and history of Pokemon is brought into a sharp focus, reminding me that though I’ve competed at events, explored the worlds of each game, and even dreamed up my own Pokemon games, that there is still a grand possibility space to explore between all of the known areas I’ve charted. Seeing Exeggutor dominate takes me back to 1999 when I retooled my team in Pokemon Red by replacing the Venusaur I had since the start of the game  with an Exeggutor because I noticed Exeggutor’s superior special attack strength. I changed my whole team and strategy because I noticed one detail in a sea of options. Despite all the trends, I decided to go in a different direction, while I huddled over a Prima strategy guide searching for my own unique way to be the very best.


On “Perfect Imbalance”: Memorization and Balance


In their video “Perfect Imbalance” Extra Credits mentions that a problem with balanced games is that there’s often a lot of memorization involved in learning to play them well. They suggest that because Chess is perfectly balanced, players can memorize openings and gain significant advantage from knowing early-game optimal play. By briefly examining why and how players memorize strategies, we can see that balance has nothing to do with memorization being so effective.

“ [Chess is a great game] but it does suffer from the standard problems that perfectly balanced games build up, namely that a collection of fixed strategies end up getting established over time. If you’ve only played casual games of chess at home it’s great. There’s thousands of interesting strategies to discover and try out, and your tactics will evolve over the course of a match. But if you’ve gone a step further and really look at taking your game to the next level you’ll find that there’s a lot of a rote work to do. There are a great number of established strategies and play sequences that you have to memorize before you get to a high enough level of play that you’re really experimenting with anything new again or are once again able to start crafting your own strategies. The set of canonical strategies has built up to such a point that one can spend years if not decades of one’s life studying chess without really getting to create new plays or develop your own stratagems.”

What properties of Chess allow memorizing strategies to be so effective?

In order to use plans that you memorize, you need to recognize that you are in a familiar position. No position is more familiar to a Chess player than the starting board position, since it’s the same every game. It’s an easy and useful starting place for elaborate acts of memorization and recall.

Since you know what the board’s going to look like, you can start thinking about what you’re going to do and what your opponent is going to do in reaction based on this stable foundation. As the game progresses, you’ll be able to know the positions of all the pieces at all times, since Chess is a game of perfect information. All moves in Chess are perfectly reliable, so the only obstacle in the way of predicting a whole game’s moves is your ability to analyse the position and predict play accurately. What makes Chess an interesting game is that its broad possibility space means that it takes practice and a high level of mental skill to hold all of the possible viable moves in your head and think through the different possible outcomes for even the next 5 to 10 moves.

Because of all this reliability and the repetition involved in the opening position, you’ll start memorizing brief runs of play in the early-game that you’ve noticed lead to better positions more often than not. Over hundreds of games you’ll pick out more of these patterns at different common board positions throughout the game and commit them to memory. Broadly, this is not atypical of the learning process required to gain skill in all turn-based strategy games. No matter what game you’re playing, you need to at least memorize enough game rules to be able to imagine what the next few turns might look like in order to determine what you should do this turn. This process of picturing the next few turns and developing short-term strategies gets more efficient and effective with practice, in part because you’re memorizing snippets of strategy and patterns of play that lead to certain outcomes, then reusing them.

The rules of Chess don’t place any obstacles between calculation and memorization. Any time you calculate the right move for a board position, you might as well memorize it and reuse it next time, since there’s no way it could turn out differently–unless your opinion on the right move is actually incorrect! Considering how many people play Chess around the world, and the extensive database of past games logged and commented on by experts, it’s more likely than ever that you’ll find out you’re incorrect without even having to play your way into that realization.

That huge community, and the metagame it creates, makes a sizable contribution to biasing players towards memorization as a way of improving their skill. There are thousands upon thousands of publicly available recorded chess games to review. There are thousands of books about Chess strategy, many of which contain lists of common openings and the patterns of play that seem most effective against them. The depth of available material gives you an almost unlimited number of master-endorsed strategies to memorize if you’d like. This weight of accumulated knowledge can feel oppressive to a new player who wants to get good at game–this is exactly what Extra Credits is talking about when they say that Chess is stale due to memorization.

Notice that I’ve said nothing of balance so far, I’ve only talked about the properties of the system. Balance does nothing to increase the effectiveness of players memorizing strategies as a way to improve their performance. Even if Chess were a battle between armies with asymmetric capabilities, if those sides were used in every Chess match and perfect information were still available, the game would be just as prone to memorization, since asymmetry alone does nothing to change the conditions required to make and re-use extensive plans. If Chess were incredibly unbalanced (say white had all pieces replaced by queens and black had a normal set-up), memorization would be just as prevalent. Memorization would likely be *more effective* in unbalanced chess, because the imbalance would lead to the overpowered player often winning in fewer moves, thus requiring less memorization on average to produce winning results.

In summary, memorization is prevalent in Chess because

  • perfect information is available about the game state, so the players know enough to plan perfectly if they are mentally capable;
  • all moves are perfectly reliable, so that perfect plan will not have to be altered during the course of play;
  • and the game starts from the same state every time, so the perfect plan has a perfectly-reliable starting point.

Badaladaladala: Characterization Through Mechanics


Below is a clip of the funniest scene and one of the most interesting moments of characterization in Big Hero 6.

In this early scene, we see Hiro interacting with Baymax. Baymax is a caretaker robot, so he is out of his element when it comes to learning kung fu and understanding the celebratory actions of modern youths. The scene plays out in a classic way: the robot can’t understand a well-understood human action and must be taught something basic despite having advanced AI.

Watch the first example in the video and then read below.

“Hiro: Yeaha fist bump.
Baymax: “fist bump” is not in my fighting database
Hiro: no, this isn’t a fighting thing. It’s what people do sometimes when they’re excited or pumped up.
[goes through step by step fist pump sequence ending in an “explosion” move]
Bamax: Badaladaladala”

The master animator and storyteller Hayao Miyazaki once described an effective method he uses to convey subtle differences between characters. He does this not with dialog, but with body language. By animating characters going through the same sequence of actions minor differences between each character are highlighted.

So here’s why Badaladaladala made me laugh out loud and sing its loopy refrain for weeks after watching Big Hero 6. This scene uses the Miyazaki mirror characterization and dialog together to give us a unique peek into the mind of Baymax. We can’t know for sure what’s going through Baymax’s robot mind, but here is my interpretation of his thought process:

  1. Mimic Hiro
  2. Hear sound
  3. Break down waveform to match syllables
  4. Recognize word(s)? If yes, repeat word(s). If no..
  5. Resequence response according to closest matching syllables.
  6. Imitate inflection.

Baymax assumes the explosion sound effect is actually a word. And after processing it, he attempts to respond in kind. The result isn’t exactly the “explosion” that Hiro does, but it’s comically close. Now the question is, does Baymax really understand what it means to do a fist bump? Without knowing what Baymax is actually thinking (thoughts, code, or otherwise) we’re left to interpret his actions and watch as he continues to interact with Hiro and his friends.

In two scenes late into the film (on top of the balloons, and back in Hiro’s workshop), Baymax’s inability to empathize and understand common human emotional states makes him oddly oblivious and uniquely insightful. Instead of understanding that Hiro might be motivated by revenge, he relies on his sci-fi bio-medical scanners to check Hiro’s well being. Since the beginning of the film, Hiro is a brilliant, independent inventor who mostly keeps to himself. When his talents are focused on seeking revenge and justice no one can keep up with Hiro’s pace except Baymax. In other words, Baymax is his only caretaker. And at the peak of Hiro’s emotional distress, Baymax’s even tempered care and  innocent obliviousness is what brings Hiro and the film back to their emotional core. The key is Baymax never does anything out of his narrowly defined, oblivious caretaking nature.

Characters defined by clear rules that are meticulously detailed and consistently applied is the essence of what I call characterization through mechanics. Sure, you could say this is basically keeping the narrative details straight, which applies to all kinds of stories and types of characterization. But characterization through mechanics is a bit more specific than that. In the same way we gain insight into the nature and character of real life players as we watch them struggle and puzzle through challenging gameplay scenarios, we gain a unique kind of insight when we watch characters work through consistent limitations in stories. The best part of engaging with “mechanical” or rule-based details in stories is we can extrapolate these rules and accurately theorize alternate possibilities, then be delighted all the more when the unexpected happens while still fitting into our mental framework for the character.

Vlambeer Scale of Quality


At the 2013 INDIGO Classes, Jan Willen Nijman detailed Vlambeer’s tricks for creating better game feel, which is essentially how the play experience and game information hits the player, which is the result of precise details and minor tweaks. In the Talk, Jan took a game with bad game feel and applied each of his 31 tricks step-by-step until the game had what he considered to be good game feel. Some of the tricks are simply visual changes while others address actual gameplay mechanics. The 31 tips are general, genre specific, and the result of a refined personal style from this odd and idiosyncratic indie developer.

Below I have organized the tricks to create The Vlambeer Scale of Game Feel.  Jan’s category names are on the left, and I’ve added my notes on the right. Simply add these simple tricks and you’re game will have great game feel too… maybe. In the meantime, keep a look about for The Vlambeer Scale of Game Feel seal. When the seal is applied to a game, the score is calculated based on the number of tricks it implements. The higher the rating the more Vlambeer-ian (Vlambiric, Vlambeeo?) the games feel.


  1. Basic Sound and Animation – Is it entertaining?
  2. Lower Enemy HP – Is 3 shots the magic number?
  3. Higher Rate of Fire – Increase frequency of core player actions.
  4. More Enemies – Parade (large groups) of enemies
  5. Bigger Bullets – Make bullets Mega Man “lemon” big.
  6. Muzzle Flash – Make the first frame of bullet sprites a white circle.
  7. Faster Bullets – Make Bullets 5 times faster than the player. Or make bullets move half the length of the screen in half a second.
  8. Less Accuracy – Random bullet spread
  9. Impact Effects – Animated “pop” when a bullet hits a wall or an enemy.
  10. Hit Animation – Enemy flashes white when hit
  11. Enemy Knockback – Enemy gets pushed back when shot
  12. Permanence – Leave dead bodies on the ground. Have destructible environment.
  13. Camera Lerp – Camera slightly lags behind the player movement
  14. Camera Position – Position camera to highlight the focus of the game.
  15. Screen Shake – Small shake of the screen when the gun fires
  16. Player Knockback – Player is pushed backwards when firing forwards.
  17. Sleep – A slight pause to the game state when hits connect with targets. (hit pause)
  18. Gun Delay – Gun animates independently from player sprite/model.
  19. Gun Kickback – Animation flourish.
  20. Strafing – Rules that tie moving and shooting together (like stop-and-pop gameplay)
  21. More Permanence – Leave bullet casings on the floor (find at least 3 examples)
  22. More Bass – Gives the gun more kick. (audio design)
  23. Super Machinegun – Have a machinegun (or a supercharged version of core mechanic)
  24. Random Explosions – 33% chance that enemies explode on death hurting other enemies.
  25. Faster Enemies – Compensate for random explosions to increase difficulty.
  26. More Enemies – Compensate for increased fire power.
  27. Higher Rate of Fire – Compensate for increased enemies.
  28. Camera Kick – In addition to the shake, jerk the camera moves in the opposite direction of the fire.
  29. Bigger Explosions – Because bigger is better
  30. Even More Permanence – Smoke from the explosion lingers
  31. Meaning – Have a purpose for the action

The Problem With Theoretical Player Perspective Critique

POV: Academic.  DIFFICULTY 1.   LEVEL 1 - 1 POV: Academic.  DIFFICULTY 1.   LEVEL 1 – 1

Have you seen those infomercials where they show some inferior product used by a poor soul who lives in a black and white world? The person who struggles to do a simple task due to the incompetent design of an inferior product? Perhaps water leaks on the sofa, food accidentally falls on the floor, or the cat just smells too bad to sit next to.

This black and white disaster infomercial scene is part of a formula that is effective at conveying an idea by creating an emotional through line from the frustrating experience of using the inferior product to the newfound joy of using whatever product that’s for sale. The music, the coloration, and the histrionic performance are designed to get you to feel great about the for-sale product. Whether this miracle product works or not, the point is these scenes are not designed to inform viewers of the pros and cons of each option. The sale is the bottom line and the less customers think and the more they feel, the better.

The same approach is being used commonly within games criticism videos, and it comes mainly in the form of youtube level design analysis. The analyst walks through a level of a game explaining what a first-time player thinks, feels, and how they play. This approach often notes how gameplay concepts are taught and supposes how a player with no prior knowledge of the game, the genre, or even video games might progress.  I call this approach to critique theoretical player perspective (TPP) analysis.  

Though there are many types of players out there with various levels of skill and experience, the one thing we have in common is that we all have a similar first time experience with a game. We all start without knowing exactly what we’re doing or exactly how everything works, and we take things one step at a time. Focusing on this first time experience is a great way to establish the starting point of the players skill acquisition trajectory. With this knowledge we can better understand why certain players give up or why some levels “click” for players.

The problem with the theoretical player perspective when applied to first time players is it tends to paint a picture of a player who is astute, quick to pick up even the most minute of details, thoughtful, reflective, and patient. This depiction is just as extreme as the black-and-white frustrated infomercial people but in the opposite way. I’m not assuming this theoretical player can’t exist; I’m saying it is hard to find all these these qualities within a single person. It’s even harder to find someone who exhibits these qualities when playing video games, which are largely consumed for entertainment, as doing so requires a high level of attention and self-discipline.

Most players’ actual first experience with a game is far more stressful, frustrating, and unfocused than analysts would have you believe. The explanations TPP analysts provide tend to be oversimplifications of how any player would learn. Sure, a player is likely to pick up on some of the correct details and connect some of the dots, but they’re not going to latch on to all the details, and certainly not so cleanly on their first time playing a game.

image and example from Sequelitis image and example from Sequelitis

The final problem with the theoretical player perspective analyses is that they tend to only focus on tutorials and how the player learns the basic rules of play including new enemy and level elements. I have yet to find a TPP analysis that comments on the hints, scaffolding, or tutorial design of higher levels of play. Initially, this may not seem like a big deal. After all, a critic doesn’t need to be the best player or a highly-skilled player to examine the design details of a game and write a thoughtful analysis. However, I’m worried that the lack of coverage for the higher design of these games is a symptom of a bigger issue.

It’s one thing for a critic to not have time or energy to take their game to that “next level” whether that be attempting to speedrun, achieve 100% completion, reach a high score, or top the leaderboards. It’s another thing if a critic is completely blind to high-level play. My stance is that, like in school, learning piano or any other discipline, the goal isn’t to learn the basics and barely pass. Learning the basics and passing is just step one. There are many steps on the path to mastery, and once mastery is achieved  you gain access to a whole new world of expression and understanding. As my former piano teacher explained, when you learn all the notes and all the rhythms and all the fingering for a song, you haven’t passed yet. In fact, you get a 0. Only after you’ve put in the work to smooth everything out and really practice the song until it’s so comfortable in you that you have control over every phrase and note and dynamic, then you get to a level where you deeply understand the song and you can truly make the music your own. Even in school, the grade on the paper wasn’t the point. Hopefully, the grade reflected your genuine dedication to learning and how much you made the material a part of who you are.

In my experience, most of what is interesting about games comes from what happens after one learns the basics. Though there may be no cap to how “high” high-level play gets, a critic’s journey upwards will show in the kind of insight they bring to their analysis. Digging deeper changes the player and critic in a profound way. There’s a whole world of interesting concepts and experiences in each game. Our goal here at Design Oriented is to dig deeper than others and bring you more than the typical beginner-level coverage of game design you can readily get elsewhere.