Unveiling the Economic Model of Blockchain Gaming

(I) Foreword: Why write such a theoretical piece?

“Blockchain gaming,” as the name suggests, refers to games that run on the blockchain. For us, whether we’re players or investors, there’s often little need to deeply grasp the operational mechanics or technical intricacies behind these games. As long as we’re entertained and make profits, that’s what counts. However, since the latter half of 2021, several blockchain gaming projects infamously collapsed, resulting in significant losses for many GameFi enthusiasts.

As an emerging industry, discerning which blockchain gaming projects are worth investing in, determining the appropriate amount to invest, and gauging a project’s lifespan are subjects deserving of thorough research. Indeed, the economic model of a blockchain game is its most challenging aspect, and it can be viewed as the shining gem in its crown.

Our content team at Gua Tian Guild consists of a quirky bunch who can spend hours on end discussing various gaming economic models without tiring. We relish sharing our findings and are adept at synthesizing them. Over the next few weeks, we’ll gradually compile our discussions into vibrant texts, hoping to reach more GameFi players. Our goal is not only to minimize potential losses but also to guide gamers towards the blockchain games most suited to their tastes.

Alright, let’s get started! First and foremost: the economic model of blockchain gaming refers to the theoretical structure describing the interdependence of all in-game economic variables. Sounds complex, doesn’t it? Well, hang in there—this might be the only seemingly profound statement in this lengthy article. We’ll ensure the rest is easily digestible.

In simpler terms, the blockchain gaming economic model concerns the changes in quantities and prices of all in-game NFTs and tokens. By understanding this, you can discern what drives the entire system, who benefits from sell-offs, under what circumstances there’s a positive feedback loop, and when risk factors emerge.

This comprehensive piece will adopt a systematic approach, broken down into three levels of analysis:
1、 Basic primary models (single-token, dual-token, or multi-token);

2、 Model variations (such as integration with DeFi, stacking NFT attributes, etc.);

3、 Supplementary mechanisms (time-based taxes, lock-in periods, token burning, etc.).

With that said, let’s dive in!

(II) The Four Modes of Single-Token Models

Let’s start with the simpler single-token model:A single-token project refers to one unified token, with the in-game economic cycle sustained entirely by this sole token. Classic examples adopting this token model include Crypto Zoon, Playvalkyr, Hashland, and Radio Caca (note that ZOON introduced a sub-token later in its lifecycle).

From the above, it’s evident that in a single-token model, both the output and intake revolve around token A. To profit from a Play-to-Earn (P2E) mechanism, there needs to be a consistent influx of new players or reinvestment from existing players, meaning an absolute external cycle is required. Depending on whether the single-token model utilizes the game’s native token A (referred to as “Token-Standard”) or widely recognized market value tokens such as USDT, BTC, ETH, BNB (known as “Gold-Standard”, even if a process requires converting cash into tokens to purchase NFTs, as long as the amount of cash is fixed, it’s considered Gold-Standard), we can categorize the single-token model into four modes:

The Four Modes of Single-Token Models

Mode A: Fixed Peg Entry + Token-Standard Out

During the Gamefi boom of 2021, this was a common model. Players used USDT or BNB to purchase NFTs, but the rewards earned through the game were in the form of Token A. Notably, this model resembles the approach adopted by most mining-based DeFi platforms. Its characteristics include a fixed entry barrier and profits that fluctuate with token price. If the token’s value is on an upward trend, the payback period will decrease with the rising token price. Under this setup, a positive momentum can create strong FOMO sentiments. However, it can also amplify the gap between token production and consumption, possibly leading to a detrimental spiral that’s irreversible. In this scenario, once a downturn emerges, less reputable projects tend to disappear, while reliable ones resort to investing substantial funds to stabilize the market, simultaneously releasing favorable news to attract new players, leveling the price chart and delaying any decline.

Interestingly, many less reputable projects favor Mode A: what goes into their pockets are solid assets like USDT, while players receive tokens they’ve minted themselves.

Our assessment of blockchain games using Mode A: They experience high growth initially but have a short lifespan. For players considering this model, the advice is to mine, withdraw, and sell primarily. Once a declining price trend is observed, the best move is to sell without hesitation.

B-Mode: Fixed Peg Entry + Fixed Peg Exit

With the A-Mode being widely used, some project teams have developed the B-Mode with a “Fixed Peg Exit”: Are you worried about the swift depreciation of the tokens you cash out? I’ll solve the problem by giving you tokens based on a fixed peg quantity! For instance, if the set output is 100U daily and the token price was 1U yesterday, you would receive 100 TokenA. But if the price drops to 0.5U today, then you’d get 200 TokenA.

B-Mode presents a commendable innovation. It provides a stable entry point and consistent daily returns. In an upward price trend, the corresponding decrease in token output ensures a relatively constant payback period. Meanwhile, during a price decline, players’ pegged returns remain consistent on a day-to-day basis.

However, is it as good as it sounds? Not necessarily. In B-Mode, withdrawals often come with a lock-in period. For instance, you might have to wait seven days to access the 200 TokenA mentioned earlier, and by then, the price may not be 0.5U anymore.

Take, for example, a fairly renowned project on BSC: PlayValkyrio, or Valkyrie. It epitomizes the B-Mode. Despite lacking standout features in mechanics, aesthetics, or narrative, it flourished, mainly because there were few games at the time with a fixed peg exit. Paired with the thriving nature of blockchain gaming, Valkyrie soared for the first two weeks. However, it began a descent shortly after, spiraling downwards over the following fortnight.

Some might recall Binance Hero, BNBH, as an even more notable example of the “Fixed Peg Exit.” Their situation is intricate, and we’ll dive into their specifics in subsequent discussions. It’s essential to remember that such models are just tools to help analyze a project’s profit points and risk areas more effectively. Full project evaluations demand insights from multiple angles, like the team’s credibility and the soundness of contract codes. Take Hashland, a game played by some members of the Guatian Guild. It uses the A-Mode, and while its model might not be perfect, underlying strong stakeholders and a low likelihood of the team exiting ensures its relevance. Even with a prolonged price decline, it has seen continuous updates over its three months since public testing, presenting players with three Our perspective on B-Mode blockchain games? They offer stable income, with lesser chances of sharp price fluctuations, leading to an extended lifecycle. For potential players, it might be wise to mine and stockpile tokens early on, selling once prices surge for more substantial gains. As the influx of newcomers dwindles, the strategy should pivot to mining, holding, then selling.

C-Mode: Token Peg Entry + Token Peg Exit

The distinctive feature of the C-Mode is that both the entry barrier and returns fluctuate with the token’s price. During a rising price trend, the C-Mode significantly amplifies the returns for older players—it’s like an accelerated model on steroids! For instance, if on the first day the exchange rate for TokenA is 1:1, with an entry threshold of 100 TokenA, players can join the game by spending just 100U and earn 10 TokenA in a day. On the second day, if the price rises to 2U, the older players still earn 10 TokenA, now valued at 20U. However, the entry threshold for new players has doubled to 200U!

Does this sound familiar? That’s right, Raca is a prime example of this model. The project team initially collaborated with Elon Musk’s mother and CZ for an AMA, attracting a continuous influx of players. As new players consistently needed more U to purchase the original beast NFTs, and once they became older players, they continued to draw in newer players. The entry fee kept soaring, making it common to see the value of a single original beast multiply several hundred times.

The C-Mode most readily induces a FOMO (Fear Of Missing Out) sentiment, with countless “rags-to-riches” tales. As long as there’s a substantial foundational player base, it’s easy to initiate an upward spiral. Essentially, older players not only benefit from the appreciation of the token’s price but also “feed” off the high entry fees from the newer players. The C-Mode most transparently manifests the essence of external loops (older players profiting from the capital of new players) and is frequently the preferred single-token model for many projects aiming to make a quick fortune.

Our assessment of C-Mode in blockchain games: They are prone to dramatic price surges and plunges, with a short life cycle, unless they have a robust foundational base. For those considering participation, we recommend mining during the initial stages. At the same time, assess the project’s ability to continuously attract new players—if this capability diminishes, it’s best to exit immediately.

D-Mode: Token Peg Entry + Fixed Value Exit

Currently, it seems that no projects are adopting this model, as it’s unfavorable for both the developers and players. From the developer’s perspective, they receive their own tokens while doling out actual currency—there doesn’t appear to be a need for this. For players, they initially need to exchange real money for tokens and then use those tokens to purchase NFTs, adding an element of uncertainty. Therefore, hardly any games are utilizing this approach.

Our assessment of the D-Mode in blockchain games: This seems like a model devised by teams who aren’t well-versed in the industry. Unless the project offers some uniquely compelling features or utilities in subsequent iterations that require the use of D-Mode initially.

To summarize the four single-token modes, let’s consider a table. Please note that the evaluations provided are based on an assumption that all four models share the same project team, market environment, and number of players entering the game.

In the table, judgments about the longevity and initial price increases are solely based on the intrinsic logic of the four models. Beyond the base model, factors such as variations and auxiliary elements need to be considered. We will share more about these in our next article with our friends. Additionally, it’s important to note that as long as there is a continuous influx of new players, even projects adopting the D-Mode can flourish.

(II) Foundations of the Dual-Token Model

After discussing the single-token model, the enthusiasm from our readers surpassed that of our previous series “The Evolutionary History of Blockchain Games.” The primary reason being, players can deduce the broader developmental strategy of a game by understanding the intricacies of its design model. Many readers, after going through the article, discussed in the community why the single-token games they played faced challenges. Only after categorizing them into four modes did they have the “Aha!” moment. So, let’s delve deeper into the currently popular dual-token model.

The dual-token model originated in the first half of 2020, with the pioneering blockchain game, Axie, introducing its sub-token, SLP (Smooth Love Potion, a name that always has some mischievous connotations; one wonders if MASA coined it). This new token absorbed the selling pressure originally on the primary token, AXS, marking the advent of the dual-token model.

Those familiar with Axie know that before the introduction of SLP, the Axie model was based on a single token. It followed the “A model” we discussed in the first article of this series: entering with a gold standard and exiting with a token. The trustworthy Axie team didn’t vanish overnight. With a consistent influx of new users and continuous investments from various private equity bigwigs, Axie thrived under the A model for over a year. However, the project team must’ve realized that structural changes determine destiny. Without new players, the A model would eventually spiral into decline.

In Axie’s dual-token model, the selling pressure was shifted onto the sub-token SLP, a tactical move to protect the primary asset. To illustrate: AXS’s price started skyrocketing from July 2020 onwards, as the selling pressure was alleviated. In contrast, SLP initially played the role of the undervalued underdog. While its value did surge with the influx of new players during the bull market, it soon entered a downward spiral. Its revival now depends on centralized adjustments by the project team. A recent adjustment eliminated the SLP rewards from PVE outputs, leading to another surge in SLP’s price.

*The above information is from CoinMarketCap.

In summary, the dual-token model consists of a parent token and a child token. The parent token is mainly a game governance token, while the child token functions as an in-game economic token. Most in-game outputs are primarily in the form of child tokens, with the parent token being secondary. Apart from the aforementioned Axie, there were also popular projects in 2021 like BinaryX and StarSharks that adopted the dual-token model. Moreover, both of these projects introduced some innovative modifications to the model. Below is a structure diagram of the dual-token model:

(IV) Classification of Dual-Token Models in Practice

During discussions about the classification of dual-token models, our guild’s content team debated for a long time. The reason was that if we continued to categorize using the single-token’s ABCD modes of “X standard in, Y standard out,” there would be numerous categories. With four main tokens and four sub-tokens, the combinations amount to 16 - this isn’t practical. More importantly, there aren’t that many varieties in actual projects. We further observed a trend: most of the newer dual-token models have adopted a token-standard for both input and output. For instance, BinaryX uses the main token for input and the sub-token for output, whereas Starsharks uses the sub-token for both input and output.

Why is this the case? Our team’s conclusion is that dual-token models offer greater flexibility in adjustments without the need for the centralizing adjustments present in the gold standard model. Under the gold standard, an oracle mechanism is required to specify the corresponding token quantity. Using the gold standard becomes complicated in a dual-token model. (This is just our opinion, and we hope others will further explore this topic.)

So, how should we classify them? K-shen came up with an approach to solve this dilemma, focusing on speculating about the project team’s intentions: After the Genesis NFT sale, what methods do project teams adopt to increase the number of NFTs in the market to meet the demands of new players?

Initially, most blockchain games, during their Genesis phase, would sell Genesis NFTs on official platforms or on partner platforms such as Binance NFT/Opensea to accumulate their first batch of players, a stage that every blockchain game goes through. As for subsequent NFT minting, we observed that most blockchain games in the market have essentially adopted one of the following two different modes:

Model One: Breeding Consumption Model

In this model, the second-generation NFTs and subsequent ones originate from the Genesis NFT’s breeding process. The official side will no longer sell mystery boxes.

Parent NFTs produce child NFTs. These child NFTs can have varying attributes, welcoming new players. The breeding process requires consuming a specific amount of tokens to mint new NFTs. This consumption is the primary method of token usage in this model. Compared to a single-token model, the dual-token model simply redistributes consumption and production at different ratios between the main and sub-tokens, determining which token faces the main selling pressure.

Take AXIE, for example, as mentioned earlier. In the game, a significant number of SLPs are produced, with only a minimal amount of AXS. However, during the breeding process, only a certain number of AXS and SLP are consumed. As the number of NFTs increases, the selling pressure on the sub-token SLP will also intensify, leading to a gradual decrease in its price.

Games built on the Breeding Consumption Model inherently have a gambling element. Everyone hopes to breed a high-attribute offspring, and one can breed at any time. There’s a weaker centralized control approach, and there’s fun in strategizing with various NFT combinations, which further tests the team’s model design capability.

Summary of the Breeding Consumption Model: Observe which token faces the selling pressure. Ruthlessly consume it in the early stages of the game or mine, withdraw, and sell in the later stages. For the tokens with lesser selling pressure post-production, consider hoarding some based on the number of new players and trading volume, and sell at high positions.

Second Model: Mystery Box Sales

Compared to the breeding consumption model, the mystery box sales model is straightforward: The quantity of NFTs in the game is determined by the project team. When the market is booming, they release more; when many are consumed, they release again, making the centralized control evident. In this model, based on different pricing methods for the mystery boxes, they can generally be categorized into three types: U-box, primary token box, and secondary token box. The pricing strategy of these three boxes reveals the project team’s overall game plan:

U-Box: As the name suggests, NFTs are purchased using tokens like U or ETH. A surge of players leads to a significant accumulation of capital. With the funds raised from selling NFTs, the project team can support the token price, promote the game, organize PVP tournaments, or, in some cases, abscond with the money. The U-box method provides relatively flexible funding to the project team, offering the chance to create a blockbuster. However, this also means greater risks for players, making it a common choice for many new blockchain games.

Player Strategy Suggestion: High risk, high reward. Bet small, win big.

Primary Token Box: Players need to exchange their U tokens for primary tokens to purchase NFTs, causing significant consumption of the primary token. Whether the tokens are burned or flow back to the project’s account, it drives the price of the primary token upwards. Furthermore, the project team can easily control the market: if the primary token’s price is too high, discouraging newcomers, they can sell off some primary tokens to stabilize the price. For secondary tokens, the team either believes in their game mechanics, expecting a substantial consumption of these tokens or might even give up on them, leading to endless selling pressure.

Player Strategy Suggestion: Short-term speculation on the primary token might be more profitable than playing to earn in the game.

Case Study: BinaryX adopts the primary token box model. Looking at BinaryX’s primary token BNX and its secondary token Gold price trend: BNX surged from a low of 4U to a high of around 200U, a 50-fold increase, while the in-game earned Gold token only rose fourfold. Thus, in this model, token trading is likely more lucrative than playing to earn. However, if the primary token price cannot be sustained in the long run, the game is likely to decline.

Data sourced from DexGuru

Token Blind Boxes: A significant number of players enter the game and exchange U tokens for sub-tokens, leading to a substantial consumption of the sub-tokens. This model is somewhat similar to breeding-consumption based systems. Project developers aim to balance the price of sub-tokens internally within the game, extending the game’s lifespan as much as possible. Their goal is to continually introduce new gaming mechanics to encourage internal circulation.

Strategy for players: Focus on earning steadily and playing it safe until the number of new entrants noticeably decreases.

Case Study: StarSharks adopts the sub-token blind box model, which explains its longevity. Over several months, it maintains a consistent ROI of 40-50 days until it gets listed on Binance. Observing the trend of their primary token, SSS, and the sub-token, SEA: SSS remains stable between 7U-10U, while SEA shows more fluctuations, ranging from 0.6U to 2U.

Data sourced from DexGuru

Nowadays, some major projects explicitly announce that a significant portion of the funds raised from blind box sales (whether in U tokens or primary/sub-tokens) will be directly burnt or added to the treasury. What’s taken from the players is used for the players. The popularity of StarSharks can be attributed to their announcement that 90% of sub-tokens obtained from blind box sales would be destroyed. When encountering such projects, players should pay special attention. A transparent team suggests a promising future.

From our categorized analysis, you should now have a general understanding of which types of games under a dual-token system yield more profits from token trading than from in-game earnings, and whether it’s more beneficial to mine the primary or sub-token.

(V) Summary of Single vs. Dual Token Main Models

The basic main model serves merely as the underlying structure for blockchain games. Thus, for any such game, it’s not feasible to solely judge a project’s value based on this model alone. Whether it’s a single or dual token model, their essence lies in the infusion of new funds to allow veteran players to play to earn. If the rate at which new players join can’t match the rate of outputs by older players, given the spiraling increase of coin value and entry thresholds, a tipping point or even a death spiral might occur. Therefore, for any blockchain game, it’s crucial to always monitor three parameters: the number of new players, the number of active players, and the comparison between outputs and consumption.

As the entire GameFi sector evolves, each project is on the hunt for the key that fits its lock. Some aim to establish a cycle system of positive growth, FOMO inflation, bubble burst, and stabilization by backing up prices with funds and gameplay mechanisms during bubble elimination phases. Others delay the bubble and death spiral through high consumption, token-locking, and market control mechanisms, seeking a longer lifecycle, gradually transitioning from external to internal cycles. Many newly launched blockchain games showcase innovative mechanisms.

Therefore, once the basic game model is set, the real thrill of a blockchain game lies in the innovative and adaptive game mechanisms. Think of it as a tree, where the economic model is the trunk - plain but supportive; while the modifications are like flowers blooming on its branches, captivating and radiant. Next, let’s delve into the familiar categorization of these modification patterns.

(VI) Variation of Economic Models: GameFi + DeFi

Most GameFi projects in 2021 merely took the simplistic DeFi 1.0 product codes, reskinned them, and launched. This approach is somewhat outdated and doesn’t fit our definition of the “GameFi + DeFi” variation. Our definition of “GameFi + DeFi” starts with the establishment of a core GameFi economic model, which is then augmented with certain DeFi mechanisms. This empowers select tokens, positioning GameFi as the primary focus and DeFi as the secondary. The purpose of this integration is to create layers of nested structures, retaining more funds within the game environment and reducing token sell pressure.

DeFi Mechanism I: Staking Mining

The crux of DeFi lies in staking mining, where single token staking or combinations of a single token with a stablecoin for LP (Liquidity Pool) staking linearly releases rewards. This mode often appears in dual-token models. Because the governance token (the primary token) has limited utility within the game, the combined LP staking of the primary token and a stablecoin is used to stabilize its circulation and price.

Based on different staking outputs, we can further categorize:

1.Staking rewards as secondary tokens:

This is straightforward and was a favorite among many projects in previous cycles. The secondary token becomes the catch-all: not only the payout medium in-game but also bears the sell-off pressure from NFT yields, and ultimately, the sell-off from primary token staking. During a FOMO period, secondary tokens might elevate the primary token’s value, but if the consumption of in-game secondary tokens lags, the oversupply of secondary tokens can lead to both gaming and primary token staking profits plummeting, resulting in rapid capital flight and an accelerated death spiral.

2.Staking rewards as primary tokens:

This method often uses an LP staking combination of the primary token and a stablecoin, offering users high annual returns initially to attract investments. However, just like the secondary pools in DeFi, such high yields cannot be sustained indefinitely. They must be replaced by in-game utility of the primary token within a controllable timeframe.

Take the DNAxCAT game as an example: in its early days, it lured significant investments on the Yooshi platform with stable annual returns of 400-500%. Coupled with a degree of market enthusiasm, its primary token, DXCT, managed to surge 3-4 times even against market trends. But in-game breeding issues led to a price drop. When high annual returns couldn’t be sustained and LP yields decreased to around 100%, players exited, leading to a mass capital exodus, intensifying the game’s decline.

Take the DNAxCAT game as an example: in its early days, it lured significant investments on the Yooshi platform with stable annual returns of 400-500%. Coupled with a degree of market enthusiasm, its primary token, DXCT, managed to surge 3-4 times even against market trends. But in-game breeding issues led to a price drop. When high annual returns couldn’t be sustained and LP yields decreased to around 100%, players exited, leading to a mass capital exodus, intensifying the game’s decline.

3.Special Staking Rewards

Instead of directly rewarding Tokens, this method uses special points, rights, medals, and other in-game “soft tokens”. These “soft tokens” are designed to be closely integrated with the game’s mechanics and content, with players recognizing their inherent value. This is a staking method that is highly appreciated in the current gaming community as it doesn’t put direct selling pressure on the main or subsidiary tokens but instead naturally integrates into the game’s operations.

Games that implement the staking mining mechanism include familiar names like BNX and Starsharks. BNX locks a portion of the player’s earnings from completing in-game dungeons, and only those who stake the main token can linearly obtain them. Starsharks originally had a mechanism for locking the main token. In their latest AMA, they mentioned that players will be able to stake a certain amount of the main token and, upon staking a Shark NFT, can directly receive the highest subsidiary token mining rewards. Let’s wait and see how this unfolds.

The Utility of the Ve Model in DeFi Mechanisms II

The Ve model first appeared in the DeFi yield aggregator, Curve. Put simply, Curve’s token asset CRV is staked to produce a secondary token, veCRV (which can be thought of as a securitized asset certificate in the real world). The amount of veCRV received by stakers varies depending on the duration they commit their CRV. The primary function of veTokens is voting, giving ardent supporters more influence. For instance, a supporter locking 10 tokens for four years may receive more Ve tokens—and thus more voting power—than an average user locking 1,000 tokens for just one month.

Recently, some GameFi economic models have adopted the VeToken approach, using it for in-game module voting. For example, Frog Hoppers on Avalanche allows players to stake the FLY token to produce veFLY. veFLY then allows voting on four different instances, with the system allocating additional FLY rewards based on these votes. Could it also be possible to vote on which instance offers higher token rewards? This would incentivize players to vote on instances they’re familiar with or ones better suited to their NFT card squads. Furthermore, what if voting could determine how to distribute the game’s treasury (if any)? Indeed, VeToken naturally integrates the popular DAO mechanism into GameFi. The soon-to-be-discussed “DAO Treasury” can efficiently utilize VeToken.

On a fun note, a gaming team I met last month is considering incorporating OHM’s Ve (3,3) model into GameFi. The principle is “if you don’t sell, and I don’t sell, we all benefit more”. However, this begs the question: is this moving further away from the essence of gaming? Just a thought!

DeFi Mechanism III: Gamification of DeFi

This mechanism is rather unique. It presents DeFi functionalities such as DEXes and AMMs in a gaming format while also incorporating some genuine game content. The idea is to attract funds through the fusion of DeFi and GameFi and then retain those funds through engaging game content and DeFi returns. This model is somewhat akin to children’s English learning software: the essence is English learning, but with leveling-up elements to provide the pleasure of learning while playing.

Existing examples include Defiland and DeFi Kingdoms, which recently became the first to launch a subnet on AVAX. The reality is that it’s challenging to offer rich gaming content. As a result, we often see vast amounts of DeFi capital entering these platforms, but there’s a lack of actual gamers, making a sustainable loop challenging. It’s worth keeping an eye on this mechanism.

(VII) Variation in the Economic Model II: GameFi + NFT

Across the horizon, NFTs seem to have become an essential component for all blockchain-based games. There isn’t a single game out there that would say they don’t need NFTs. For project developers, besides raising funds through tokens, selling NFTs is another revenue stream. Why not capitalize on it, as long as there are players willing to pay? For players, since the NFT boom in Q3 of the previous year, getting a favorable spot on a premium NFT whitelist can yield multiple returns. If there’s money to be made, why not seize the opportunity? Under this shared consensus, NFTs have become indispensable in GameFi.

Let’s delve deeper into the role of NFTs within GameFi. Functionally, NFTs in GameFi can be categorized into three types:

1. Entry Ticket NFTs

Simply put, these NFTs serve as an entry barrier to the game. Essentially, they are the ERC721 or ERC1155 codes. If the game is well-developed, the value of such NFTs rises; if not, their value diminishes. For instance, lands in certain games like the Land NFTs recently sold by Mavia may seem ordinary at a glance. However, because the game requires players to own land to participate, everyone vies for a spot on the whitelist. When Mavia became popular, its NFTs peaked at a value five times higher than their minting price.

Another classic example of an entry-ticket NFT is the “Wolf-Sheep Game”. The initial gameplay isn’t overly complex: There are 10,000 genesis NFTs for players to mint. Players have a 90% chance to mint a sheep and a 10% chance for a wolf. Sheep can mine tokens at a rate of 10,000 per day in a barn, but to claim the rewards, players have to give up 20% of the rewards to the wolf they’ve staked. To retrieve the sheep, players must forgo two days of earnings and only have a 50% chance of success. Later entrants need certain tokens to mint NFTs. Wolves, besides getting rewards, also have a chance to snatch the NFT every time a player mints one.

The Wolf-Sheep game introduced factional opposition and the theft mechanism involving both ERC-20 and ERC-721 tokens. At its peak, wolves could break even in one day, and sheep in three. The high yields resulted in rising NFT prices during that period. Subsequent games improved upon this, incorporating more game theory mechanics, enriching and balancing the ecosystem. Examples like Wizards And Dragons and Pizza Game maintained their popularity for a time.

Our Assessment: Entry-ticket NFTs ride on the popularity of the game. When the game is in demand, such NFTs retain high value.

2.NFTs with Intrinsic Value

Take the simplest example: Bored Apes by Yuga Labs, a top-tier project in the NFT community. Whether they issue their Apecoin or collaborate with the game Nwayplay, neither affects the inherent value of the NFT. It’s the community and consensus that truly influence these types of NFTs.

Bored Apes is an example of an entity moving from the NFT space to the GameFi realm. Is there an example of the reverse – from the GameFi realm to the NFT space, establishing NFTs with intrinsic value? Currently, there aren’t any. However, signs are emerging. Consider Chikn on the AVAX platform. Their model is straightforward: players who own a Chikn NFT can stake it to produce “eggs” (a token). Staking these eggs can yield “feed,” which can nurture the NFT, increasing its “weight” and producing more eggs in a continuous loop.

It’s evident that, compared to the standard dual-token model, Chikn’s system merely adds an additional layer. However, the meme characteristic inherent to the NFT and the layering provide a sense of community dependence among players. A consensus is forming, which means the NFT’s price isn’t decreasing with the token’s price. Chikn continues to thrive on the Avalanche blockchain. Of course, its initial model was too simple, so subsequent projects introduced more unique gameplay mechanics, like Avalant and Hoppers.

Our assessment: Compared to NFTs that serve as mere “entry tickets,” NFTs with intrinsic value will be the focal point of blockchain gaming’s future. The entire setting and economic model should revolve around NFTs, attributing them with various appearances and traits, and developing game mechanics around them. For metaverse-based games, it’s strongly advised to prioritize this direction from the outset.

3. In-game NFTs

Certain “soft tokens” within games can be established using NFTs. The premise is that players perceive these “soft tokens” as valuable or are socially recognized and admired.

A few days ago, during a discussion with a game CEO about token types in blockchain gaming models, an idea sparked a breakthrough on a previously challenging topic: how can the guild war system integrate with the current dual-token model? The earlier approach debated whether the reward for guild wars should be the primary token, a secondary token, or even a third type. The recent idea was to use a unique NFT as the reward. Every member of the victorious guild could view this NFT as a medal. Moreover, this NFT could empower accelerated or multiplied in-game earnings.

Our judgment: Integrating NFTs into game operations can enhance and smooth transitions between different game modules. Subsequently, this can augment players’ social attributes. After all, these social attributes are the most crucial factor for the longevity of a game.

(VIII) Summary of Economic Model Variations

The two major categories of innovative variation models introduced above are among the most frequently used and popular in the current wave of blockchain gaming development. However, they don’t represent the entirety of such models. These models can also intertwine; for instance, the Avalanche Frogs (Hoppers) mentioned in the article combine NFTs with meme attributes, collaborate with Trade Joe to incorporate an FLY LP pool, and integrate Vetoken’s lock-up mechanism in-game.

The content within the Gamefi sector continues to expand, with more gameplay options and increasingly intricate mechanisms. It’s unpredictable who or what will be the next big hit. However, when players are exposed to these innovative ideas, it sparks more thought and creativity, potentially leading them to come up with brilliant concepts themselves.

The industry is still nascent, with no established experts. We hope more creative minds will join teams capable of deep reflection, to learn and grow together, and seize the opportunities to profit.

(IX) Auxiliary Means of Economic Models

Compared to the main models and their variations discussed previously, auxiliary means for blockchain games are akin to adding a hint of mango and strawberry to an already delicious mousse cake. It doesn’t change the overall flavor but makes it more colorful and tantalizing.

In the context of blockchain gaming, auxiliary means refer to small methods and tricks. The more of these you have, the more intricate the game appears. The core purpose of these auxiliary methods is to extend the game’s life cycle. There’s no one-size-fits-all tool; what’s crucial is assessing the project’s stage, market fluctuations, player emotions, on-chain data trends, and then determining which auxiliary tool to employ.

There are various auxiliary tools available. We’ll briefly introduce a few based on their applicability:

1.Time Tax and Lock-in Threshold

Time Tax: Project developers establish a tax rate on profit withdrawals based on the player’s PlaytoEarn expectations. This tax rate gradually decreases over time. For instance, if you earn a profit today and decide to cash out, you might be subjected to a 20% tax on your profits. If you wait until tomorrow, the tax drops to 15%. By the fifth day, the time tax decreases to 0%.

Lock-in Threshold: Developers will lock in the earnings from PlaytoEarn and set a fixed threshold for withdrawals. This could be based on a set number of days or a specific token quantity.

The purpose of the time tax and the lock-in threshold is to alleviate the pressure caused by players selling off their tokens en masse. These measures are among the most fundamental and common strategies in the current Gamefi arena. The time tax ensures that the selling pressure of tokens is distributed evenly over a specific period, while the lock-in threshold simply delays this selling pressure to a later period.

Most developers will implement both the time tax and the lock-in threshold when launching a game. Players can gauge the potential circulation volume of tokens in various projects based on these values, determining if there’s room for arbitrage. A few projects may use these tools as a backup plan, introducing them when they notice excessive token selling that could hamper game operations. For example, Starsharks recently updated their policy to a 14-day lock-in period for withdrawals. Players must stay informed and adapt their strategies promptly to benefit from any potential arbitrage.

2.Limited Centralized Control

Whenever the term “centralization” is brought up, many seasoned players in the crypto space scoff at it, believing it deviates from the essence of blockchain. However, I personally believe that there’s no absolute right or wrong between “centralization” and “decentralization”. Given the industry’s current inability to solve the “impossible trinity” dilemma, blockchain games should consider how to appropriately employ both at different stages to ensure the smooth progress of the project.

For blockchain gaming projects, our team firmly believes that introducing a limited degree of centralized control in the early stages, assuming the project operators have good intentions (benevolent operators), is beneficial for the long-term development of the project. In the early stages, most blockchain gaming projects are like newborn foals, shaky and vulnerable. Various factors, such as gameplay and promotion, can attract a significant inflow of capital in a short time, causing a rapid surge in the value of NFTs or Tokens, leading to a bubble. Once the speculative money withdraws, the bubble bursts quickly, resulting in asset depreciation and a downward spiral, which significantly shortens the project’s lifecycle. Therefore, we believe it’s necessary to introduce a limited centralized control in the early stages to guide the project smoothly.

So, how would a project with limited centralized control operate?
In one scenario, the project can set up in-game mechanisms and adjust certain parameters to slow down the inflation rate of NFTs or Tokens. For instance, adjusting the yield parameters for BNX mining and dungeon raids, or regulating the quantity and price of NFTs released through the PAAS mechanism in DaoFarmer.

In another scenario, the project might use early token controls to provide liquidity for LP, stabilizing the Token price and trying to maintain a consistent ROI period for players. A good example of this is PokeMoney, which has done well in peer-to-peer promotions. Our team’s analysis of on-chain data revealed that the project has a high degree of control over its tokens, fixing the ROI period for players at 30-40 days to maintain project enthusiasm and stability during peak sales periods.

Projects that employ benevolent centralized control tend to have smaller profit margins but longer lifespans. Players should first assess the capability and background of the project operators, as well as their core intentions behind the project, before deciding whether to participate in such blockchain games.

3.The Establishment of the Treasury

The treasury is a mechanism where the project team allocates a portion of blind box revenues, market transaction fees, or protocol income to a specific address. This treasury serves as a reserve for the future development of the game. The primary intention is to assure players: the team operates transparently, taking from the players and giving back to them.

Recently, treasuries have evolved from being freely allocated by the team to becoming DAO (Decentralized Autonomous Organization) treasuries, constituted via contracts, LPs, and other mechanisms. In this setup, players decide how to use the assets in the DAO treasury based on predefined governance rules.

Regardless of the approach adopted for the treasury, its purpose remains consistent: to send a positive signal from the project team to the players. This reduces the perceived risk of a “rug pull” and strengthens the consensus among players. For instance, the 20 million WU treasury of DNAxCAT or the recent 8 million WU treasury of DAOfarmer have managed to retain a portion of their loyal players even during the project’s downtrends.

Let’s revisit a pitfall observed in a single token model, exemplified by BNBH – Binance Hero. In BNBH, the treasury forms a part of the in-game Play-to-Earn (P2E) system. Players purchase blind boxes using tokens to obtain NFTs. Periodically, the project team would convert the tokens from blind box sales on secondary markets into BNB and add them to the treasury (prize pool). All in-game profits for players come directly from this treasury. However, between December 6th and 7th of 2021, a significant withdrawal of BNB by large holders (“whales”) triggered panic-selling among players, plummeting the value of BNBH tokens. This event marked the end of that year’s GameFi craze. In essence, as long as there’s sufficient BNB in the treasury, players can mine with confidence. Hence, astute players of BNBH, by closely monitoring on-chain data for the treasury address, could have withdrawn in time to prevent substantial losses.

In conclusion, while discussing economic models’ supplementary measures, their function is to help the project team realign with the preset development trajectory during specific periods. Most of these measures aim to delay a potential decline. Whether or not to deploy these measures, and when to do so, depends on the project team’s assessment of the current stage. However, our team suggests always having these supplementary measures in reserve, especially when establishing the economic model, to incorporate them from the outset.

(X) Unveiling the Economic Model of Blockchain Games: The Conclusion

Tech enthusiasts do have impressive planning skills. Aptly, this final chapter is Chapter 10, a little point of pride. A few words on the series: this was the first collaborative writing effort of the content team of the “Gua Tian” Guild. The primary framework and initial draft were spearheaded by Kluxury (Twitter handle: @LuxuryWzj), with each piece roughly 1500 words. Gua Tian then added their own insights and refined the text, adding another 1500-2000 words, aiming to keep each piece between 3000-3500 words.

Before penning the series, the core ideas and tone had already been discussed extensively within the content team of the guild. A special thanks to the team member, Lao Wu, for contributing many case studies and viewpoints. Only after achieving a consensus did the creative process begin.

The intent behind this series was to enable players to understand how project teams design their models and subsequently determine their approach to playing blockchain games. Moreover, we were committed to ensuring that even readers with just a hint of blockchain knowledge could grasp the content, so we opted to remove a lot of jargon, explaining concepts using plain language and practical examples. This approach also addresses feedback from some enthusiastic readers who suggested that our writing could be more technical. Our hope is to welcome as many interested players into the blockchain gaming world without overwhelming them initially. The goal is to get them playing and collectively grow the industry.

I will now share the conclusion of this series written by K, as it is, for all the readers. Through it, you can grasp K’s pragmatic thought process:

Up to now, I’ve dissected the current economic model of blockchain gaming from my personal perspective, touching upon many formerly mainstream projects. While we often joke that today’s blockchain games are just a scheme, akin to Ponzi scams, at their core, Gamefi is still a game. Both the gameplay and the economic model are essential. It’s just that the current environment, technology, user groups, and various other factors have made the economic model more emphasized than it perhaps should be.

Lastly, I’d like to share my personal strategy for engaging in blockchain gaming:

1. Look at the popularity. Popularity is the fundamental metric to determine whether to get involved.
   Monitor platforms like Twitter, Discord, Telegram, the virality of stories, mentions in various groups, rankings on Dappra, on-chain user numbers, etc. Based on experience, establish your own assessment criteria.

2. Review information to judge the economic model and risks, and then decide on an entry strategy.
   Options like trading or mining, reinvesting or withdrawing to sell…

3. Analyze data to determine turning points, and then decide on the right time to exit.
   Summary of Personal Style by Gua Tian:
   The entire “Unveiling the Blockchain Game Economic Model” can be likened to a bikini-clad lady on the beach. The main economic model discussed in the first and second parts is like the lady’s figure, which is the fundamental attraction. The third part, discussing various modifications, represents the style and color of the bikini. When paired well with the figure, it dazzles like a radiant lotus rising from the water. The fourth part, talking about supplementary methods, can be seen as the adornments on the bikini – it might be a butterfly or a flower, something that catches the eye instantly.

However, after discussing the entire series and analyzing it, Gua Tian felt a sense of loss. This is because a personal judgment became evident, one that had been previously sensed but reluctantly accepted: blockchain game economic models primarily based on token-economics will inevitably face a downward spiral. The four articles in this series only discuss ways to delay this outcome.

I’ve been pondering: Does the “Play-to-Earn” GameFi model represented by Axie truly embody all facets of blockchain gaming? Probably not. It’s not that Axie misled players; Axie’s dual-token model introduction in 2020 was undoubtedly innovative. However, by 2022, a more refined model is needed to better encapsulate the essence of blockchain gaming.

How can blockchain games evolve to avoid this downward spiral and return to a regular gaming lifecycle? Gua Tian offers three perspectives:

• Make blockchain games more enjoyable, so compelling that players in the crypto world are motivated to spend on them.
• Transition the current model from being primarily token-economics-driven to one that emphasizes assets with stronger anchoring but less liquidity, mainly an NFT-based economy.
• Broaden the horizon, such as by incorporating metaverse scenarios. In this case, blockchain games are just a part of the larger metaverse, and their lifecycle would be influenced by other interconnected parts of the metaverse.

Let’s look forward to and work towards a smoother and more efficient blockchain gaming economic model.

Special thanks to the data team at Footprint Analytics for their support; we enjoy daily discussions with data enthusiasts. Also, a big shout-out to Nathan from the CryptoPlus+ community for his strong recommendation! We look forward to engaging with more friends for further discussions.

End of article.

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