Oliver Kiley(Mezmorki)United States
I’ve been on BGG for a little over a year, and I must say that I’ve learned a ton. The discussions, conversation, and support has been an immeasurable help for creating better games and getting a thorough understanding of the gaming community, exposure to new mechanics, industry environment ... and the list goes on (I guess this my personal thanks to BGG and the wonderful users!).
During this time, I’ve found myself intrigued by a few lines of conversation and discussion that pop up from time to time. I wanted to summarize a few of these threads and provide links back to the original discussions where appropriate. In many ways, these conversations, to me, aim towards the makings of a "science" of boardgames, complete with its own (possible) analytical tools, classification schemes, and technical vocabulary. The size of the BGG database, coupled with a very willing survey audience, opens up a lot of doors for scientific exploration.
Warning: Long thread!
A Boardgame Taxonomy
A taxonomy or classification system for describing the subject matter of a scientific investigation is essential for building a body of scientific work. Without a means of uniformly and consistently describing X in a way that makes it uniquely different from Y, the community as a whole will be plagued by a lack of clarity and accuracy in describing the subject matter it holds so dear and near.
As wonderful as the BGG game data is, with the myriad of options for aligning games with mechanics, categories, and families, those data fields are not complete, consistent, or well-described and understood. There are mechanics listed as categories, families that should be categories, etc. It works, but just barely, and there is ample room for improvement.
The Alternative Classification of Boardgames, developed by Selwyth, is from what I have come across, the most comprehensive effort to develop a boardgame taxonomy and classification system. He begins by describing the many possible elements of a game that can be measures/categorized, including:
Ordinal Dimensions (rated in some way, i.e. 1-10 scale)
- Length (the replayability of each modular map/setup)
- Breadth (the complexity from rules)
- Depth (the complexity from decisions)
- Luck (randomness driven by mechanisms)
- Chaos (randomness driven by other players for each # of supported players)
- Degree of perfect information
- Inter-Player Relationship
The ordinal dimensions are difficult to assess objectively (at this point in time), but I will continue the discussion of those aspects later in this post and others. Ultimately however, Selwyth focused on two elements for greater exploration: Genres and Mechanisms.
On Genre! On Mechanism!
Genres describe "the main point or flavor/feel of the game, how you'd summarize the game with just 1-3 sets of words, when you fill in the blank as you tell somebody, [for example] "Chess is a _______ game" (Selwyth, 2010). The genre fills a critical role in stating the primary activity and/or scoring mechanisms, and would be immensely helpful for quickly describing a game. Frankly, replacing the BGG categories with Genres would be wonderful. The existing categories are a mixed bag of broad level mechanics, game types, and themes, which are different kinds of descriptors than the genre.
Mechanisms describe the finer details of a how a game is played and operates. Selwyth notes the need to take a "medium level zoom" on the field of possible mechanics. If a mechanic is so specific and narrow in scope that it only applies to a very few games, it should be weeded out or aggregated into a higher level mechanic. Likewise, mechanics that are too broad (i.e. "Random Events") apply to so many games that it really isn’t useful to the classification system.
The level of thought that has gone into the developing the Genres and Mechanisms field is astounding (peruse the Taxonomy GeekLists to see the evolution of the conversation). While the rational and basis of the work is sound, I do have some critiques that pertain to the implementation of such a classification system. The primary one is that the classification system doesn’t always respond to or work with commonly used terms across the broader BGG community, making it counter-intuitive until you wrap your head around the taxonomy (which may be an issue for less deeply entrenched BGG users).
For example, "Deck Building" appears nowhere as a Genre or as a Mechanism. Taking Dominion for example, the Genre is "Economic Engine" as your deck of cards is increasingly used to generate VP’s. The actual deck building concept is deconstructed into a series of mechanics, including tile drafting (granted the game uses cards not tiles), deck stacking, and development actions. Most self-described "deck-building" games would be similarly described in other terms. It makes one wonder what the usefulness or validity of the "deck-building" term is, and it certainly creates a high amount of confusion (i.e. deck building pre-game ala Magic versus deck building during the game ala Dominion).
Following the critique, there are some mechanisms that are splitting hairs in my opinion. For example, Action Choice Drafting vs. Worker Placement, where the only difference is when the action is resolve (either immediately or later). It causes Agricola to be classified as Action Choice Drafting, despite being commonly understood as a Worker Placement game. Given these critiques, I’m fine with having more specific mechanisms (as in the example above), but perhaps they can be listed as sub-mechanisms or as a variation on a principle mechanic.
Overall, I feel that Selwyth’s classification scheme is great step forward. I would love to see a way to retool the BGG database around this classification scheme, recognizing that it probably needs another round of review and input from more BGG users.
Scott Nicholson gave an interesting talk at MIT talking about game design and mechanics. He took a (very) brief stab at organizing the existing BGG mechanics according to the function or purpose of the mechanics. For example
(1) Action Selection Mechanics: roll + move; action point allowance; worker placement; deck building; variable player powers.
(2) Resource Collection: set collection; hand management; auctions; stock holding; press your luck; drafting
(3) Conflict Resolution: Rock-Paper-Scissor; die rolling; voting; battle cards
The idea wasn’t wholly fleshed out, but I thought it might be an interesting way to provide some more structure to Selwyth’s mechanisms, ordering them based on what the mechanics typically try to achieve.
Selwyth considers the type of player interaction in a game to be the highest level of categorization. I’m inclined to believe this in some ways, for the type of interaction drives whether the game is a game, a competition, a puzzle, etc. For reference, his breakdown includes the following categories:
- Competitive (beat your opponents, one player is the winner
- Cooperative (all players against the board)
- Coordinative (all players against the board, separation of player responsibilities, i.e. one player can’t play for all players)
- Semi-Cooperative (all players against one player, i.e. against a dungeon master)
- Teams/Partnerships (competitive teams with coordinative action)
- 2v2 (competitive games with an option for 2v2 team/partnership)
At the broadest level, this makes sense for organizing games (except the 2v2 category, I don’t see why that’s needed). After all, wanting to play a cooperative game (Pandemic) is very different from a competitive game (Chess), and the experience is fundamentally different. The list above captures the gamut of player interaction from mechanics standpoint, but in my mind misses a crucial piece of information (particularly for competitive games), which is how intense/direct the competition is. Granted, Selwyth’s intention was to purely gauge interaction from an objective standpoint, but the intensity and nature of the competition is perhaps more important.
This GeekList Nasty Moves and Expectations: Types of Player Interaction in Board Games aims to describe the range of player interaction as it manifests itself through the gameplay experience, getting at the "how" intense from above. In otherwords, what is the feeling of the interaction? Is it harsh and confrontational, underhanded, or non-confrontational but still competitive? The categories according to the list (with my notation) are as follows:
Players interact directly via force; i.e. chess, wargames, etc. You must actively destroy your opponents’ assets to win / aggression is required for victory
- Direct Competition
Players can affect each other directly for/with/by their assets, but the aim is to further your own relative position. i.e. You can destroy/block your opponents assets, but it isn’t required for victory. Potentially about diminishing your opponent’s capacities, reducing their score/resource/etc
- Indirect Competition
Players compete for the same resources but cannot directly affect another player. I.e. You can prevent access to neutral territory/resources/choices (blocking, taking something first, etc.), but cannot directly affect your opponent’s acquired assets. Often riddled with "negative" interactions.
- Solitaire Competition
Aka pure "Race" style games) where players strive to be the first to reach a finish line. I don’t like the "solitaire" (or multi-player solitaire) tag line personally. Yahtzee is a good example of a pure race game, as there is zero interaction between players. In my experience, most games labeled as multiplayer solitaire nonetheless have some interaction and aren’t pure race games (i.e. Race for the Galaxy).
Included as an additional modifier to the above, referencing games with the ability to severely hinder/hamper/undermine an opponent). I’m not too intrigued with this descriptor, as it appears more of a latent quality of most competitive (except solitaire) multiplayer games.
I can imagine a refinement and intersection of these two approaches, with the former system (Selwyth’s) identifying the "structure" of the interaction and the latter describing the "how interactive".
Evaluating the "Experience"
While the objective classification of games (above) is interesting, it doesn’t tell us a lot how a game "feels" to play or what the "net experience" is. I’ve become increasingly interested with the more subjective qualities of a game. From the standpoint of making recommendations, people are often less interested in what the specific mechanics are employed by a particular game than what type of strategy or level of randomness might be in the game.
An interesting discussion of the experiential aspects of games was raised in the thread Level of Introductions. While the thread was pitching an approach to rope non-gamers in from gateways to more complex games (discussed in a subsequent topic), the conversation grew a bit to cover a broader experiential-based classification of games. A post I made and elaborated on subsequent pages included the following as major elements:
- Player Interaction (relates to Player interaction categories discussed above)
- Mechanical Complexity / Rules Complexity (How easy is it to learn the game?)
- Gameplay Depth (How deep or layered is the strategy?)
- Theme Integration
I would also add to the list, based on Selwyth’s and other posts the need to assess
- Luck (randomness driven by mechanisms)
- Chaos (randomness driven by other players)
- Skills (what the player needs to do/think about)
- Degree of Perfect Information
Each one of these topics can (and often does) spiral off into its own intriguing line of discussion. Let’s do some spiraling here!
Weight and the Complexity/Depth Milieu
Weight is used on BGG to score games based on a continuum from "light" to "heavy." It isn’t really clear what the assessment of weight should really be based on. While the weight ratings themselves don’t appear to be debated too much for specific games, what is debated pretty heavily is what the heck weight is actually measuring.
One quote which I’ve been re-quoting a lot, from BGG User Clearclaw, is that weight is a measure of the level of effort required to play well. I rather like that measurement as a "holistic" measure, but it still doesn’t really answer the question. What are requirements for playing well? The post Meaning of Light and Medium Games contained an interesting discussion about the various aspects of weight (including the prior quote).
To me, weight is best understood as an aggregate measurement of both "Rules Complexity" and "Decision Depth." Let's consider each.
I’ve begun thinking that Rules Complexity may be able to be assessed in an objective fashion. Certainly we can look at the rules for Tic-Tac-Toe and say that the rules are easier to teach/learn/understand than the rules to Through the Ages. But what accounts for this difference?
My hypothesis is that we can assess the complexity of a game’s rules by determining the number of primary mechanics/rules and how many hierarchical nested sub-levels exist in each. I’ve yet to test this approach with any games mind you. But imagine the rules presented as an outline to essay, and you assess how many main paragraphs/topic sentences are there, and then how much detail is included in each main paragraph. The more main paragraphs and the more detail in each, the more complex the rules are. Maybe we can try this...
Let’s take a relatively simple game like Citadels and attempt to map the rules. We will ignore all the setup rules/requirements for the time being, and focus primarily on the actual gameplay. For the primary mechanics and sub-levels, I see the following:Quote:PRIMARY: Role Selection (i.e. the card drafting mechanic)That’s relatively straightforward, and I believe a similar approach can be taken for all games. What I’m not sure on is how you translate the above structure into some type of 1-10 or 1-5 rating scheme that measures relative rules complexity between games. You could take the most complex game you can find, and map the rules. You might be able to do something like make each primary rule worth "10" points, each SUB-LEVEL worth "5" and each level below that "1" ... then add up the total. Assign a "10" in rules complexity to this game, and then repeat the procedure for any other games of your choice. You can then use a normalization formula to derive the 1-10 scores of any less complex games. Tricky right?
---- SUB-LEVEL: Face down role cards depending on # of players
---- SUB-LEVEL: Selection order based on who has the Crown
PRIMARY: Turn Resolution Order (depending on role number)
PRIMARY: Player Actions
---- SUB-LEVEL: Collect Coins
---- ---- Bonus coins depending on role
---- SUB-LEVEL: Draw District Cards
---- SUB-LEVEL: Play District Cards
PRIMARY: Role Powers
---- SUB-LEVEL: Assassin
---- SUB-LEVEL: Thief
---- SUB-LEVEL: Wizard
---- SUB-LEVEL: King
---- SUB-LEVEL: Bishop
---- SUB-LEVEL: Merchant
---- SUB-LEVEL: Architect
---- SUB-LEVEL: Warlord
PRIMARY: District Card Special Powers
---- SUB-LEVEL: Card Text Interpretation (not detailed in rulebook)
PRIMARY: Endgame Scoring
---- SUB-LEVEL: End Game Trigger (# of districts)
---- SUB-LEVEL: Points for districts
---- SUB-LEVEL: Bonus points
---- ---- Meeting the end trigger # of districts (1st and subsequent players)
---- ---- One of each color district
Some people call it depth, or strategic depth, or decision complexity, etc. To me, "Decision Depth" is really about how much effort, thought, intuition, instinct, etc. is needed to play well and win. It might be thought of, as considered in the thread Depth in Games, What is it?, how many levels of strategic learning or mastery is present in the game. Tic-Tac-Toe (to pick on it again) doesn’t have many strategic levels, and a handful of games are sufficient to explore the entire decision space and frame all possible strategies. Go on the other hand, while a pretty simple game from a rules complexity standpoint, has an incredibly huge "mastery curve" and very deep/complex decisions to make.
As with Rules Complexity, I’m intrigued with means of a more objective evaluation of decision depth. A few articles are of interest in this matter. Nate Straight’s blog post An Idea for an Action Space / Impact Metric was one possible approach that looked at modeling the volume of potential player actions and the size of the decision space. The size of the decision space, in my mind, has a big bearing on the depth of strategy. Tic-Tac-Toe has a decision space of 9 on the first turn, then 8, then 7, etc... Go? I don’t want to even think about it.
The Objective Driven Gameplay thread presents a cool idea for how to map a Decision Tree for a game, in a progression working from actionable player choices to victory conditions. Such a tree highlights the possible number of decision points/nodes and their interconnections. Different strategies are possible following different pathways towards the victory conditions.
Here's the original example, using Settlers of Catan.
I also attempted to make a goal tree for Race for the Galaxy to map the possible actions/decisions that a player would take to achieve victory.
But perhaps more so than the objective size of the decision space, the number of decision points, and the tree complexity, are the factors influencing the decision space and framing valid/logical/reasonable drives the depth of the game. The current board state, the intentions (known or unknown of the opponents), future uncertainty, timing, etc. all shape and influence the decision space, and that’s where the depth emerges. Go isn’t deep just because there are so many possible places to place a stone. It is deep because there are so many long-term and short-term factors and uncertainties that go into your decision of where you ultimately end up placing a stone.
Using the Race for the Galaxy example (and goal tree above), there is a higher unwritten level of decision making going on. When choosing which action to perform for the round, you need to balance what you ideally want to do against what roles your opponent’s are likely to take in order to effectively leech off them while minimizing the leeching they do on you. When choosing a card to play, you constantly assess the opportunity costs of using a card as money versus the desire to keep it for potential future use. These factors ultimately weigh heavily into the decision depth.
Luck (randomness from the game mechanics), chaos (uncertainty from other players), and degree of perfect information, are big factors influencing decision depth as well. Chaos ties heavily into the type of player interaction in the game. Luck and information flows from the game mechanics and components. We might also consider the philosophical approach for how the game is balanced as it bears on strategy (See Game Balance: Five Schools of Thought)
Another proposed measurement (or indicator) for depth is based on how many apparent "skill levels" there are from rookie to master, the assumption being that the more skill levels are present, the more layers of strategy (and hence depth) exist. On one hand I think that’s reasonable, and clearly demonstrated in many games that are played in competitive tournament formats (from Magic to Chess). We can relate such an assessment, perhaps tangentially, by the number of books that are written on such games. Chess and Go for example have countless books written on the strategy of those games. But I’m not convinced that this really means there is more strategy de factor than another game that doesn’t have books written about it. If we put big tournament money on the line for playing Carcassonne, I bet you would see a lot more fervor and activity around its strategy, and additional layers of strategy would likely become apparent as competition intensifies.
Strategy vs. Tactics
Last, there is a seemingly never-ending discussion of strategy versus tactics, from what they mean in a general, dictionary standpoint to what they mean in games. The Strategy/Tactics Continuum post has some interesting poll data positioning games based on a continuum of strategic focus to tactical focus. I agree with many of the comments in that post that games aren’t strategic OR tactical, but that usually both are at work in varying amount and they each should be plotted on their own continuums. Also see the thread Difference between Strategic and Tactical Games
I also tend to think that while tactical decisions are generally understood to be shorter term than strategic decisions, there can be "depth" in each. That is, a game that is more strategically focused, isn’t de facto a deeper game than one that is more tactically focused. I believe this is because depth, as discussed above, is largely driven by the factors (and their evaluation) that influence a decision more so than the number or type of decision itself. Short-term vs. long-term is just one of many possible factors influencing the depth of a decision.
I’ve also been tracking conversations that discuss player skills used in games. Selwyth has pointed out that many of the mechanics in the current BGG database are really player skills, and not mechanics at all. Hand Management? That’s a skill. The mechanical equivalent is having a hand and drawing and playing cards in various ways. The management implies a skill.
On one hand (no pun intended), I can see why these types of things show up as mechanics, but from an experiential standpoint, calling these things skills outright might be more insightful to a potential game player. If (for example), I’m terrible at memorization, or pattern recognition, or dexterity, I want to know if a game requires that and maybe avoid those games.
In considering the potential range of skills, I see the following list, although I’m sure there are others:
- Pattern Recognition (matching properties, seeing connections)
- Spatial Planning (visualizing future states)
- Memory (locational memory, card memory)
- Asset/Resource Management (hand management, resource balancing)
- Risk Management (press your luck, prediction, short/long term tradeoffs)
- Economic Cost / Benefit Valuation (stock valuation, auction valuations, opportunity costs)
- Timing (sequencing, manipulating turn order)
- Deduction (inductive/deductive reasoning)
- Negotiation / Psychology
Meepletown has an interesting discussion of skills in games that elaborates on some of the above list. But wouldn’t it be interesting to see what skills are used in a game and how intensely they might be used? I think it could be interesting indeed.
The final experiential element I wanted to touch on is the idea of theme integration, that is, how aligned or deeply connected the game’s mechanics are with it its theme. Opinions vary quite a bit on this subject depending on the individual and the type of games being discussed, but nonetheless it is an important experiential dimension. We can have games "dripping with theme" in terms of artwork and components, but the mechanics might not have any real relationship to theme. A criticism of many games is that the theme is "pasted on." Yet other games seek to accurately model real world (or fictionalized) phenomenon by taking a simulation approach, often incorporating an abundance of detail and subsystems into the mechanics. Others might model such phenomenon through abstraction in ways that convey the feeling of a real world activity but in a streamlined or simplified fashion.
One sub-thread in the Level of Introductions thread examined the range of theme integration options, which I’ve clarified below:
1 - Abstract (essentially no theme)
2 - Superficial (theme exists but has little relationship to game play mechanics)
3 - Stylized (moderately strong theme that is simplified or abstracted into game mechanics, may be more fictional in nature; applies to many euros)
4 - Immersive (heavy theme that is well tied to mechanics; minimal abstractions, applies to many eurotrash or hybrid games)
5 - Simulation (strong theme with highly detailed and/or representative mechanics that drive gameplay, applies to many more complex wargames)
The thread Literal vs. Abstracted Game Interactions contains some additional detail that bears onto these classifications. One of the noteworthy points is how "intuitive" the game is. Mechanics that are well aligned with the theme can support a more intuitive gameplay, where the players are enabled to act and think in accordance with the theme in ways that are supported mechanically.
What about the Cardboard?
Certainly the physical components play a role in the assessment of games. Selwyth made an interesting comment at one point that the BGG mechanic "modular board" mat not be so much as a game mechanic as meta-game mechanics. Its something that contributes to replay ability and variation from one game to the next, but often isn’t a part of the in-game mechanics itself. An interesting consideration for sure, and there may be other elements or properties of games that follow suite.
Good Game Design + Interesting Decisions
From a game design standpoint, there are some great articles and posts talking about what make decisions interesting and deep as a basis for good game design. The thread, What makes a “well-designed” game? was one I started that generated some interesting discussion. Here’s a quote that summarizes everyone’s responses.Mezmorki wrote:(14) Tension and UncertaintyI think this is an interesting list that really touches on many of things discussed throughout this blog post. It highlights the range of perspectives and viewpoints that are important to consider when evaluating AND by consequence designing games. One thing I find interesting is the distinction made between a well "designed" game and a "fun" game. Many people separate the two as discrete elements, and (for example) might not enjoy a certain game even though they recognize that is well designed. Others tend to lump these two factors together, and playing a well-designed game is a pre-requisite for having an enjoyable time. The thread What Makes a Game Fun? contains additional perspectives.
Tension, a lot hangs in balance, no pain no gain (8)
Right amount of luck, players can adapt/respond to randomness (6)
(11) Choices and Execution
Choices that matter, wide range of choice, interesting AND meaningful choices, depth of strategy (6)
Ambiguity, uncertainty in decisions, risk vs. reward, no one "correct" move (3)
Understandable "game state" (2)
(10) Balance and Interaction
Keep players engaged - all players should be able to work towards winning throughout (2)
Player interaction, game as a social tool, appropriate level of interaction, avoidance of "mutual inaction" (4)
Balance, avoidance of runaway leaders/looses (2)
Either elimination or no elimination (1)
Appropriate challenge (1)
*** Counterpoints (2)
(9) Clarity and Simplicity
Clear, unambiguous rules, streamlined rules/play, "consistency and simplicity", elegance, avoid "special cases", rules should cover all possible outcomes (7)
Easy to learn / lifetime to master. (2)
(8) Depth and Scope
Pacing matches depth / Play time commensurate with level of competition, integration of design, synergy... appropriate amount of actions, choices (4)
Appropriate scope, right amount of detail to fit the concept (1)
Multiple pathways / multiple layers to victory (1)
Appropriate use of strategy-tactics to match game intent, Contains both strategy and tactics - have an overall approach that requires particular executions (2)
(8)Mechanics and Theme
Mechanics fit theme, believability of mechanics, minimize thematic absurdities, immersion (7)
"Invisible" game mechanics / all components work in synergy (1)
*** Counterpoints (3) Feeling that theme is not critical to the "design"
(8) Ergonomics and Aesthetics
"Ergonomics" (avoid repetitive tasks), efficiency in use , functional components (4)
Good Component quality/artwork design, aesthetics, easy to comprehend board state (4)
(7) Design Intent and Outcomes
Intent / execution (2)
Clear goal or objective (1)
Decisive results, avoid draws or inconclusive outcomes, need tie-breakers (2)
Clear endpoint / endgame condition, controlled game length, don't go on forever (2)
Scales well across players (2)
*** Counterpoints (2) Player scaling not a critical quality, but nice
Variability, Replay value, variety, each game could be different, each turn could be different (5)
Incidentally, you might also refer to this article by Wolfgang Kramer, which covers a very similar listing of "good game" qualities.
There is a lot of fascinating discussion about good game design and making interesting decisions. A few are referenced below, but it is really a much larger topic than I can cover in this already insanely long post.
Putting It Together
Phew, we’re almost done!
So as I’ve been collecting these thoughts a larger idea has started forming in my brain. Essentially, is there a way to look comprehensively across all the factors, criteria, and elements above, and organize them into a standard framework or model that can be used to describe a given game? Before answering that question, let’s summarize what we have so far in terms of evaluating a game:Quote:GAME TYPE / PLAYER INTERACTIONSo here is my final hypothesis and kick-off point for this assessment framework.
- Mechanical relationship between players (i.e. competitive free for all, co-op, teams, etc.), (objectively determined)
- Experiential relationship between players (i.e. directness of competition(generally objectively determined)
- What is the game holistically about / how do you win or score points? (objectively determined)
- What specific mechanics are employed over the course of the game? (objectively determined)
- How complex are the rules? How long does it take to learn/teach the rules?
- How long does the game take to play?
- How complex or large is the goal tree?
- How many factors influence your choices?
- What is the balance of strategic choices and tactical choices?
- What is the influence of luck + chaos?
- What skills are used and to what degree?
THEME + INTEGRATION
- What is the theme?
- How well is the theme connected to the mechanics?
- What are the physical components?
- Number of players?
(1) What if we take the "Goal Tree" idea as the central component of this framework? The Goal Tree represents the decision/logic sequence as manifested by the mechanics, in order words, what player actions fundamentally lead to victory and/or score points. Inherent in the goal tree is an understanding of the game’s genre and types of player interaction.
(2) The second component of the framework is layered above the Goal Tree and reflects decision depth by relating each of the decision ‘points’ of the goal tree to all of the factors that contribute to depth of that decision (i.e. role of luck/chaos, board state, the intention of other players). This is an assessment of decision depth (subjective measure).
(3) The third component is a skill assessment, which relates the kinds of player skills that are needed to sort out and make decisions based on the many factors that need assessment and consideration.
(4) The fourth component is a raw mechanical connection back to the goal tree, tying the games specific mechanisms to the Goal Tree’s decision points. With the above four components, we have a strong picture of the complexity of the game, the depth of the game, and the type of mechanisms that are employed. It is an assessment of rules or mechanical complexity.
(5) The final component acts a wrapping around the above four components, articulating the theme and its integration into the decision space and the mechanics, the type of physical components that are used, the intra-game variability/customization, and other relevant information.
Okay, so now what?
The difficult part is standardizing a way to evaluate and express all of the components above, assuming we can agree on the framework. Certainly many of the components can be designated in a fairly objective fashion, but many of them are quite subjective in nature. The key is not to get hung up on a subjective vs. objective debate. Instead, if we can develop a consistent approach for measuring each particular element, even if relying on user polls, comparative benchmarks, or other subjective measures, then we can still populate the information and get a comparable database of information assembled.
What I’ll talk about in a subsequent blog post is how all of this information and ways of assessing games can be applied to and translated to understanding the hobby as a whole, including gaming trends. We can start to ask intriguing questions like whether games have become more or less complex over the years. Is there a correlation between mechanisms and BGG rank? What is the genealogy of a particular game? Being able to pair a detailed game assessment with the BGG data for plays, ranks, votes, and other things opens up a lot of opportunity for more inquiry and investigation.
So that’s all for now. I welcome any and all feedback. Cheers!
Musings on games, design, and the theory of everything. www.big-game-theory.com
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