How is MegaETH's public sale allocation distributed?

Source: MegaETH

Handling a 28x oversubscribed sale with over 53,000 participants is not as easy as it sounds. In my previous article, I mentioned that our sale focused primarily on two groups:

· Those who were early active members of the MegaETH community

· Those whom we believe will be long-term supporters of MegaETH

A few days before the sale ended, @artemis_onchain (our data lead) and I met in Istanbul to start extensive simulations. We tried many different methods to "perfectly" measure each person's contribution, but quickly realized that in such a short period, this was not feasible as "contribution" is a multidimensional concept.

So we decided to break down the issue into two parts:

· Fairly distributing to existing community members

· Establishing a data-driven scoring and allocation system for long-term investors

The following part of this article will detail how we achieved these two goals and the outcomes we eventually reached.

Allocation to Existing Community Members

For the first allocation pool — our existing community, we took the most traditional approach: manual allocation.

Relying on our existing community infrastructure, including @Heisenbruh and our mod network, we compiled a list covering members who have continuously been deeply involved since MegaETH emerged from stealth mode.

This list includes those:

· Who early joined and remained active

· Who helped shape the project's culture and values

· Who supported us during bear markets and quiet periods

· Who provided feedback, signals, and energy before there was a token for speculation

It should be noted that most of these individuals did not opt for vesting. We believe this is perfectly fine. Their contribution has already been rewarded through time, attention, and trust. In our view, they have already "put in the work".

In the spirit of transparency, we hereby disclose the list of sales participants that we believe represent the core community from the past few years.

We acknowledge that this list is not perfect, and some people are definitely missing. If you are one of them, I am truly sorry.

Apart from these community members and selected application developers with a one-year lockup, the rest were not personally selected by the team.

Even among this group selected by the team, not everyone received a full allocation, and the disparity is quite significant.

Due to the scale of the sale and market demand constraints, we had to make some trade-offs. However, we believe that this approach, while respecting those who have supported us all along, also avoids turning the entire sale into a mere popularity contest.

Compared to the results of algorithmic automatic allocation, these users generally have higher allocations. Except for the aforementioned application developers, most participants' shares are non-lockup.

Measuring Long-Term Investors

The second allocation pool is aimed at users who participated in the sale through a public process and those who may become long-term holders of MegaETH.

In this part, we hope to adopt a more systematic approach. We have designed a scoring mechanism that takes into account the following dimensions:

· On-chain activity

· Social signals and organic exposure

· Specific interactions with MegaETH

· Whether the participation is seen as a long-term commitment (e.g., willing to lock up for a year)

Our goal is not to reward "score-grinding players" but to identify true believers as much as possible.

Evaluation Metrics

We use four different metrics in our overall scoring system:

1. Moni Score

The Moni Score is used as both:

· A foundational screening criterion

· A component of the social score

For example:

· My Moni Score is approximately 7,000

· @artemis_onchain's Moni Score is approximately 300

Based on this distribution, we consider setting the Moni Score at 50 to be a reasonable lower threshold in most cases. It is not a perfect measure of user quality, but it remains a useful reference point in distinguishing between completely dormant accounts and those with some level of activity.

For alternative approaches to social validation, we also discuss and implement them later in the text.

2. On-chain Activity Score

The On-chain Activity Score consists of multiple dimensions, each with different weights. The overall design is as follows:

· Early Participation (15%): Represents early adopters and willingness to take risks

· OG Status (15%): Long-term participation in the entire crypto ecosystem

· Asset Holding (15%): Serves as a reference for financial investment and "skin in the game" participation

· NFT Activity (7.5%): Manifestation of current on-chain activity, especially through NFT participation

· Recent Activity (15%): Focuses not only on past participation but also on recent on-chain behavior

· MegaETH-related Behavior (32.5%): Includes CAP Score, MEGA NFT holdings, and participation records directly related to MegaETH, such as specific testnet behavior

3. Social Score

The Social Score combines multiple dimensions:

· Moni Score

· Kaito Data

· Other reference information (such as [ ] and Ethos) used for manual review

We did not rely on a single metric but instead used a combination of multiple tools. This approach helped us effectively filter out obvious bots and low-quality spam accounts, while also better identifying participants who genuinely engage with the community.

4. Mega Score

The Mega Score is specifically tailored to MegaETH's participation signals, including:

· CAP Score

· Holding of MEGA NFTs

· Specific testnet behaviors

We used the Mega Score in two main ways:

1. As part of the on-chain activity score

2. As a basis for certain filtering thresholds to ensure that genuine MegaETH participants are not crowded out of the allocation range by generic on-chain "Farmers"

Why Vesting Is Important

We placed significant emphasis on whether to choose to vest $MEGA for one year.

In our view, being willing to vest for a year in a highly volatile market is a testament to strong conviction. No one can predict what will happen tomorrow, and choosing to vest for a year is an expression of: "I am not here for short-term trading; I am here for long-term participation."

Participant Screening and Allocation Process

After completing the scoring, we still need to decide on two things:

1. Who can enter the allocation list

2. How to convert the score into actual allocation quotas

We have divided the process into two categories:

· Vesting Participants

· Non-vesting Participants

Lockdrop Participant Selection Method

For users opting for lockdrop, they must meet any of the following conditions to be considered:

· Moni Score above 50

· On-chain score above 200

· Mega Score indicating ownership of more than one Fluffle NFT

In other words, you need to have at least one of the following:

· Basic social activity

· Clear on-chain behavioral signals

· Strong MegaETH participation history

After applying these filtering criteria, approximately 29.4% of the lockdrop addresses entered the allocation list, totaling around 1,000 addresses.

Once a wallet passes the filtering, its allocation amount will be determined based on the final score, which combines on-chain and social signals. We have adopted a segmented continuous curve approach, ensuring the minimum allocation while rewarding high-score users more.

The specific allocation logic is as follows:

· Top 5%: Linear decrease, allocation ratio from 100% to 95%

· Next 3% (5%-8%): Rapid decrease, from 95% to 55%

· Following 7% (8%-15%): Continued decrease, from 55% to 35%

· Remaining 85%: Exponential decay, with a minimum allocation of 25%

Non-Lockdrop Participant Selection Method

Non-lockdrop addresses must meet any of the following conditions to enter the allocation list:

· Moni Score > 200

· Social Score > 200

· On-chain Score > 300

· Mega Score > 68 (meaning holding at least one Fluffle)

If you are active on-chain, have a strong social signal, or have a significant participation record on MegaETH, you are eligible to participate, and you do not need to meet all conditions simultaneously.

The actual screening results are as follows: out of 49,976 non-staking participants, a total of 5,031 wallets passed the screening, with an admission rate of approximately 10.1%. Even with the lowest allocation threshold, the competition is very fierce. We trust the judgment of our algorithm and are well aware that even if some users have significant activity and holdings on MegaETH, if other metrics are weak, they may not be selected. However, this is a fair mechanism, and we respect the results.

In the screened list, we rank wallets based on a comprehensive score and determine their allocation ratio accordingly.

The higher the ranking, the higher the allocation ratio. As the ranking decreases, the allocation ratio gradually decreases. Once a certain ranking is reached, the curve flattens out, and the remaining users receive a uniform minimum allocation.

Micro Bid Protection and High Score Mechanism

We have noticed that some micro bidders are on par with large bidders in the rankings. To ensure fairness, we have implemented a mechanism: no participant's actual allocation amount shall be lower than the allocation of the 5 adjacent addresses in the ranking.

For example, @thedefinvestor is ranked in the top 15 among non-staking participants, but their bid is not high. Based on the percentage allocation, they should have received a smaller amount. However, their neighbor is a full bid participant who received a higher allocation.

To confirm @thedefinvestor's high ranking performance, we have increased their allocation to a level close to that of their neighbor. This is also the source of some 100% allocation ratios.

Case Study 1: Low Social Score, High On-Chain Score

@cp0xdotcom has almost no presence on Twitter, has never posted any tweets about MegaETH, hence having a low social score. However, they are still ranked in the top 20 of all participants and have received 92% of their staking bid.

Their advantages include:

· Over 8 years of on-chain history

· Gas consumption of 194 ETH

· Early participant in multiple contracts that later gained widespread adoption

· Interacted with 3,490 unique contracts

· Been active on the mainnet for 164 out of the past 180 days

· No NFTs and no MegaETH-related activity

His case illustrates that even without social activity or MegaETH endorsement, as long as one performs well on-chain, they can still achieve a high ranking.

Case Two: Low on-chain score, high social score

@nics_off is almost the opposite of the above case. His wallet's on-chain history is less than two years, with only 1.5 ETH gas spent and interactions with about 150 contracts, resulting in a low on-chain score. However, his social score is remarkably high:

· High Twitter engagement

· Ranked 13th on the Kaito MegaETH leaderboard

· Shared a large amount of high-quality MegaETH content

These factors have placed him at 17th position among non-staking participants, receiving the highest allocation ratio (20%) in that category.

His case also demonstrates that having a large following alone is not sufficient; a good social score is a weighted combination of Moni and Kaito, where the quality of MegaETH-related content is far more important than the number of followers.

We see many similar cases at the top of the leaderboard, with some notable examples being:

· @barthazian: Ranking first among all users, excelling in all metrics

· @0xMaxBT: Revered as a MegaETH testnet legend, being the only one to complete all testnet contract interactions (out of 53,000 participants)

Sybil Attack Prevention Mechanism

We have implemented multiple layers of Sybil protection:

1. Sybil cluster reports from the community and external teams (such as Bubble Maps and Echo) serve as direct filtering criteria

2. Our scoring system itself is unfriendly to Sybil attacks. To earn a high score, a wallet must have genuine and trustworthy on-chain activity, as low-quality associated addresses usually do not pass through

3. We have found that some wallets or social media accounts are linked to multiple KYC submissions. Once such a pattern is identified, all related requests will be invalidated.

4. For wallets that have already been allocated, we will continue to conduct Sybil checks. If any malicious behavior is discovered, we reserve the right to issue refunds.

This article is contributed content and does not represent the views of BlockBeats.