deepak kumar

So why isnt $RLB falling with the rest of the market? Has it somehow managed to find buyers when the rest of the market has crashed? The answer to that is no, it has not. You can see if the last 3 week that a total of 300 holders have sold and across all holder categories from 100k + to 10M + the amount of holders is going down. So normally, when there are more sellers than buyers we would assume that price would naturually go down. But unlike the rest of the market, revenues from @rollbit are being used to buy the token, each and every hour. This equates to in the region of 800k of buy pressure each week, no matter how the market is. So as opposed to just about every other token, RLB can weather storms as it backed by a highly revenue positive business. And when finally narrative comes back into cash generative tokens, the marginal seller has been weeded out over the last year. This will lead to explosive growth. $RLB 2.30

In 1 hour, @rollbit bought and burnt 750k $RLB.. Gone forever. In 1 day 2.4 million was burnt - over 0.1 percent of supply. $RLB has a constant, hourly bid from real revenues. High deflation + constant bid = a rapid repricing at some point. $RLB - $2.30

Game theory in Crypto is super interesting as different tokenomic models look to provide new ways of price discovery. I have been a champion of $RLB tokenomics as I think they represent the best in the space - constant deflation derived from real revenues that @rollbit earns. What RLB needs is a narrative more than anything else. I think the OHM 3,3 narrative works well here. Have a look at the chart at the end. If we simply equalise buyers and sellers - as the token is primarily prices using constant product - we can have an exponential increase in price just with the buy and burn. As the article states - its the mathematics of inevitability. Over a long enough time period with the buy and burn the price has to rise. If RLB holders can simply (3,3) then 2.30 will come earlier than anyone thinks! Introduction When analyzing RLB's market structure, we find ourselves at an interesting intersection of two powerful concepts: the game theory mechanics popularized by OHM's "3,3" system and the mathematical certainty of revenue-driven buybacks. This analysis explores how these elements combine to create a unique and potentially powerful market dynamic. The Foundation: Learning from OHM The cryptocurrency space first encountered structured game theory mechanics at scale with OHM's "3,3" system. This mechanism attempted to create a cooperative game where all participants would benefit by holding and staking. However, it relied entirely on participant faith and coordination, with no external force driving value. RLB's Evolution: Adding Real Revenue RLB takes this game theory concept but fundamentally changes the dynamic by adding consistent, revenue-driven buybacks. Instead of relying solely on participant cooperation, the system introduces a steady buyer removing $4 million worth of tokens monthly, distributed hourly for maximum efficiency. This creates a fascinating hybrid: a game theory system backed by real market activity. The Mathematics of Inevitability Looking at the raw numbers, we can see how this system creates a compelling value proposition. The current liquidity pools contain 71 million RLB tokens paired with approximately $8.8 million in stablecoins. With daily buybacks of $133,333, we can map out a clear trajectory of price movement: In just one month, assuming neutral market conditions, the price could appreciate by 111% purely through mechanical buying pressure. This effect compounds dramatically over time - by six months, the model suggests a price increase of over 1,200%, and by one year, over 4,000%. Please see chart at end. Why These Numbers Matter These aren't just theoretical projections - they represent the minimum price impact if buying and selling pressure were exactly equal outside of protocol buybacks. The system's design creates an interesting predicament for market participants: Buyers who understand this mechanism have a mathematical basis for their investment thesis Holders benefit from both the price appreciation and the psychological comfort of knowing there's a constant buyer Sellers face an ever-present headwind, as they're not just selling to the market but competing against consistent protocol buying The Game Theory Evolution This creates a more sophisticated version of the original "3,3" concept. Instead of relying on pure coordination, participants can see the mathematical inevitability of supply reduction. The game theory now looks more like this: Buy (3): You're aligned with a force that's mathematically guaranteed to reduce supply Hold (2): Simply maintaining position captures the value of consistent buying pressure Sell (-2): You're fighting against both market participants and protocol mechanics Real-World Implications Understanding these mechanics helps explain why this system might be more sustainable than previous attempts at similar tokenomics. The hourly buybacks of $5,555 create steady, predictable pressure rather than large, manipulatable events. This constant presence changes market psychology in important ways: Traders can't easily front-run large buybacks Holders have clear mathematical support for their patience Short-sellers face consistent, quantifiable headwinds Looking Forward The model suggests increasingly dramatic price effects over time, but reality will likely be more nuanced. Additional liquidity will probably enter the system, moderating some of the more extreme projections. However, the core mechanism - consistent removal of supply through revenue-driven buybacks - remains a powerful force. Risks and Considerations While the mechanics are compelling, several risk factors deserve attention: The system depends on consistent revenue generation Liquidity dynamics become more challenging over time Market manipulation remains possible, just more expensive Regulatory environment could impact execution Conclusion RLB's system represents a fascinating evolution in tokenomics design. By combining game theory with revenue-driven mechanics, it creates a more robust and predictable system than pure coordination games like OHM's "3,3". The mathematical inevitability of supply reduction provides a strong foundation for the game theory aspects, while the hourly distribution of buybacks helps prevent manipulation and promotes more stable price discovery. This hybrid approach - merging predictable mechanics with game theory incentives - could represent an important step forward in cryptocurrency market design. While no system is perfect, the combination of mathematical certainty and psychological incentives creates a compelling framework for sustainable value accrual. @KaminoCrypto @cryptocevo @crypto_condom - sorry to be a shill, but do you mind retweeting please :)