1. Introduction

2. tl;dr

3. The Financial Impact: Quantifying the Drain & Costs

   3.1 Overall Scale of Value Extraction

   3.2 Attacker Economics: Costs vs. Profitability

   3.3 User Costs: Direct Losses and Transaction Fees

   3.4 Temporal Impact Trends

   3.5 Summary of Financial Implications

4. Who & How: The Attacker Landscape & Strategies

   4.1 The Dual Challenge: Attribution & Ecosystem Complexity

   4.2 Attacker Economics as a Behavioral Proxy

   4.3 Diverse Execution Methods & Infrastructure Insights

   4.4 Inferred Competition & Ecosystem Dynamics

   4.5 Implications for Understanding & Mitigation

5. Where & When: Attack Patterns & Hotspots

   5.1 Temporal Patterns: When Do Attacks Occur?

   5.2 DEX Hotspots: Which Platforms Are Targeted Most?

   5.3 Token Pair Hotspots: Which Assets Are Targeted Most?

   5.4 Connecting Targets and Timing

   5.5 Summary of Patterns and Implications

6. The Role of Network Infrastructure: Validator Incentives

   6.1 Overall Validator Revenue from Measured Sandwich Activity

   6.2 Per-Validator Revenue Distribution & Concentration

   6.3 Financial Incentives from Measured Sources

   6.4 Implications: Validator Role & Ecosystem Health

7. Methodology, Data Interpretation & Limitations

   7.1 Data Source and Scope

   7.2 Key Definitions and Metrics Used

   7.3 Analysis Methodology

   7.4 Limitations and Caveats

8. Conclusion & Implications

   8.1 Summary of Key Findings

   8.2 Implications for Stakeholders

   8.3 Relevance to Ecosystem Goals

   8.4 Areas for Further Research & Mitigation Context

   8.5 Final Concluding Statement

1. Introduction

Maximal Extractable Value (MEV) presents a complex challenge within blockchain ecosystems. On the Solana network, certain MEV practices, particularly malicious sandwich attacks, pose a significant threat to user confidence and network fairness. These attacks exploit transaction ordering by placing bids before (front-running) and after (back-running) a user's trade, manipulating prices to the attacker's advantage. This typically results in unfavorable execution prices and a diminished experience for the targeted user, effectively siphoning value from ordinary participants to sophisticated exploiters. While the existence of such activities is known, their precise scale, the actors involved, and the specific ecosystem vulnerabilities they exploit often remain obscured.

In response to the Helius "[REDACTED]" Hackathon's call for greater transparency regarding malicious MEV, the "MEV Monitor: Solana Sandwich Attacks" dashboard was developed. It serves as a public, open-source tool designed to surface and quantify this specific type of MEV activity on Solana.

This report leverages data captured by the MEV Monitor over a recent 7-day period to provide an overview of current sandwich attack dynamics. The primary objective is to analyze this recent activity and discuss its tangible implications for users, decentralized protocols (particularly DEXs), and the overall health and integrity of the Solana network. The analysis examines the financial impact of these attacks, the observable behaviors and methods of attackers, the specific platforms and assets most frequently targeted, and the role of validator incentives in this ecosystem. By exploring these facets, the report aims to foster a deeper understanding of the current state of sandwich MEV on Solana and inform ongoing discussions about network fairness and potential mitigation strategies.

2. tl;dr

This report analyzes recent sandwich attack activity on the Solana network using data from the MEV Monitor dashboard over a 7-day period. The analysis reveals that sandwich attacks remain a notable factor in the Solana DeFi ecosystem, imposing tangible costs on users and highlighting specific areas of vulnerability, with activity peaking during hours corresponding to US and European market overlap.

Over the observed week, 87,061 identified sandwich attacks resulted in over $620k USD in directly measurable extracted value from users. Critically, this figure significantly underestimates the true financial impact, as reliable price data is often unavailable for the newly launched and illiquid tokens frequently targeted. While attackers incurred estimated costs of ~$52,656 USD (primarily via Jito tips), the activity appears highly profitable based on the measured data (estimated net profit ~$570k USD), providing clear financial incentives. Users affected face direct value loss and potentially higher transaction fees.

The actors conducting these attacks operate largely anonymously, employing diverse and often complex execution methods that go beyond simple theoretical models. Reliable attribution to specific entities remains challenging due to the use of temporary addresses and varied techniques. Evidence suggests attackers may utilize infrastructure beyond the standard public Jito MEV pathways, exploiting potential alternative mechanisms for transaction ordering and inclusion.

Sandwich activity during this period was highly concentrated. The vast majority of attacks targeted newly launched, low-liquidity tokens, particularly those facilitated by specific launch platforms like Pump.fun and associated DEXs (e.g., pumpswap).

Validators play a crucial role in this ecosystem, earning measurable revenue from the transaction fees and Jito tips associated with including sandwich transactions in blocks they produce. While this analysis only captures revenue from these specific sources, the data indicates that this income stream can be significant for certain validators. This dynamic contributes to broader ecosystem concerns about the potential for MEV-driven stake centralization over time, where validators most active in MEV could disproportionately increase their network influence.

In summary, sandwich attacks, primarily focused on the volatile early moments of new token launches, represent a persistent challenge driven by clear financial incentives. They directly impact user experience and network fairness, highlighting ongoing tensions between MEV capture and ecosystem health on Solana.

3. The Financial Impact: Quantifying the Drain & Costs

Sandwich attacks inflict direct financial costs on users and generate revenue for attackers. This section quantifies these impacts based on data observed over the 7-day period from April 22nd to April 28th, 2025.

3.1 Overall Scale of Value Extraction

During the observed week, a total of 87,061 sandwich attacks were identified. These attacks resulted in approximately $623,647 USD in total reported extracted value (based on summing hourly data). This figure represents the direct financial loss incurred by users due to artificially induced slippage caused by sandwich attacks, based on the available data.

It is crucial to emphasize that this $623k figure significantly underestimates the true scale of value extraction. This underestimation stems from two key factors:

1. Data Filtering: Filters applied to identify sandwiches accurately (detailed in Section 7.3) inevitably exclude some true sandwich attacks, particularly complex variations.

2. Pricing Data: The lack of reliable, real-time price feeds for many newly launched/illiquid tokens means profits realized by attackers in these assets are frequently valued at $0 USD in the dataset. The reported USD value primarily reflects profits captured in the paired token (often SOL) and represents only a lower bound of the actual financial drain.

3.2 Attacker Economics: Costs vs. Profitability

Attackers incur costs primarily through transaction fees (FR Tx. Fees, BR Tx. Fees) and Jito tips (Jito Tips) paid for transaction inclusion and ordering. Over the 7-day period, the total measured costs for attackers amounted to approximately 353.73 SOL (~$52,656 USD based on an average SOL price of ~$148.86 for the period), calculated from the dedicated hourly cost data. Jito tips constituted the vast majority of these costs (~352 SOL), with transaction fees being relatively minor (~1.2 SOL).

Comparing costs to the reported extracted value (~$623k USD) yields an estimated Attacker Net Profit of ~$570,991 USD. The direct costs represented only ~8.4% of the reported extracted value, suggesting high profitability on successful, measured attacks. However, this calculation relies on the underestimated extracted value and only accounts for successful, measured attacks; it does not factor in costs from failed attempts or potential losses if attackers themselves become targets of MEV.

3.3 User Costs: Direct Losses and Transaction Fees

The primary cost for users is the direct loss of value through unfavorable execution prices, estimated at ~$623k USD (the underestimated Extracted Value). Additionally, users whose transactions were sandwiched incurred their own transaction fees and potentially Jito tips.

Over the period, victims paid approximately 103 SOL in total fees and tips associated with the sandwiched transactions (~62.69 SOL fees, ~40 SOL tips). Based on the 87,061 identified sandwiches, the average cost per sandwich event paid by victims (~0.00117 SOL) was considerably lower than the average cost paid by attackers (~0.00406 SOL). This is likely because attackers often bundle multiple transactions incurring costs for each, while the victim cost relates to a single swap transaction. Still, these fees represent an additional layer of cost for users caught in these attacks. Furthermore, qualitative impacts like subsequent transaction failures due to squeezed slippage remain an unquantified cost to user experience.

3.4 Temporal Impact Trends

The financial impact of sandwich attacks is not uniform throughout the day. Analysis of hourly data reveals that the Total Reported Extracted Value (USD) shows a distinct peak between 14:00 and 20:00 UTC, with a particularly notable spike around 19:00 UTC. This pattern closely mirrors the peak hours observed for both the frequency of sandwich attacks (Section 5.1) and the total attacker costs paid (fees and tips). This indicates that the period corresponding to US and European market overlap experiences not only the highest volume of attacks but also the most significant financial drain from users.

3.5 Summary of Financial Implications

In summary, sandwich attacks represent a significant drain of value on the Solana ecosystem over the observed week, even based on significantly underestimated figures (~$623k USD reported). While attackers incur measurable costs (~$53k USD), the activity appears highly profitable based on reported data. Users bear the brunt of this through direct value extraction and associated transaction costs. The concentration of this financial impact during specific peak hours further highlights periods of heightened risk for DeFi participants.

4. Who & How: The Attacker Landscape & Strategies

Understanding the actors behind sandwich attacks and the methods they employ is crucial, yet challenging due to the nature of on-chain activity and the complexity of MEV strategies. This section explores the observable characteristics of attackers and their execution techniques, acknowledging the inherent difficulties in attribution and the potentially diverse infrastructure involved.

4.1 The Dual Challenge: Attribution & Ecosystem Complexity

Reliably attributing sandwich attacks to specific, persistent actors remains a significant hurdle. While the signing addresses for frontrun and backrun transactions are visible, analysis indicates these are often ephemeral 'burner' wallets, changed frequently to obscure the larger picture of an individual attacker's operations. While identifying custom on-chain programs consistently used by an attacker could offer a more reliable attribution method, many sandwich attacks are executed without unique program IDs, using varied techniques that further complicate tracking. This inherent anonymity makes it difficult to definitively assess market structure (i.e., dominance by a few large players versus many smaller ones) or track the evolution of sophisticated actors. Furthermore, the complexity and variability of execution methods add another layer to the analytical challenge.

4.2 Attacker Economics as a Behavioral Proxy

While direct identification is difficult, analyzing the costs attackers incur provides insights into their behavior. Attackers primarily spend SOL on transaction fees and Jito tips. While attackers would likely pay necessary base fees regardless, the significant expenditure on Jito tips (~352 SOL vs ~1.2 SOL in base fees over the 7 days) highlights a preference driven by mechanism, not just cost. Tips enable attackers to use Jito bundles, which guarantee atomic execution and sequential ordering for their frontrun, victim interaction (implicitly), and backrun transactions. This greatly increases the probability of successfully landing the full sandwich strategy, a guarantee that priority fees alone do not offer. The high total value of tips paid reflects the value attackers place on this execution certainty, especially during peak activity hours (14:00-20:00 UTC). However, precise cost-per-sandwich analysis remains complicated by factors like split backruns where full costs may not be captured, and the third-party tipping issue discussed below.

4.3 Diverse Execution Methods & Infrastructure Insights

Real-world sandwich attacks often deviate from simple theoretical models, employing a variety of techniques:

• 4.3.1 Beyond the Basic Sandwich: Some attacks involve initial setup transactions to prepare conditions, adding steps beyond the core frontrun-victim-backrun sequence.

• 4.3.2 The Split Backrun Case: A notable technique involves the attacker splitting their backrun swap into two (or more) separate, successive transactions within the same block. The current dashboard methodology struggles to capture the full profit/loss and associated costs (especially tips paid after the second part) of these multi-part backruns. To mitigate resulting data noise, sandwiches appearing significantly unprofitable (< -0.05 SOL extracted value, based on the median) were filtered from certain value analyses, meaning a subset of these complex attacks are excluded from those specific results.

• 4.3.3 Jito Tip Placement Strategies & Risks: Attackers exhibit strategic choices in how they pay Jito tips – including them with the frontrun, with the backrun, or as a separate transaction within the bundle. The risk associated with placing the tip later (e.g., on the backrun) relates primarily to the possibility of the original block becoming uncled. If this happens, the atomicity guarantee of the bundle relative to the canonical chain state can be compromised. Transactions from the original bundle (excluding the one with the tip) might be executed individually or re-bundled by other searchers in the new context, potentially exposing the initial attacker to losses. Analysis of known bot strategies (e.g., the previously studied vpeN...and E6Yo... bots) has illustrated this specific risk trade-off.

• 4.3.4 Third-Party Tips & Data Gaps: The observation of Jito tips for sandwich bundles sometimes being paid by an address different from the frontrun/backrun signer adds another layer of complexity. Associating these tips correctly is difficult; simply matching based on transaction proximity (e.g., +/- 1 index) can lead to numerous false positives. Accurate attribution would require access to Jito's private bundle data, which is currently unavailable for this analysis, hindering precise cost accounting.

• 4.3.5 Questioning Jito's Exclusivity: Evidence of Alternative MEV Pathways: While Jito provides the most well-known infrastructure for MEV on Solana, observations suggest it may not be the sole pathway for sandwich attacks.

  • Successful Priority-Fee-Only Sandwiches: The consistent success of some attackers landing sandwiches using only priority fees is noteworthy, as standard priority fees do not guarantee the deterministic atomic ordering typically required, unlike Jito bundles. This strongly suggests these attackers leverage non-standard mechanisms, potentially including private order flow agreements with validators, modified validator clients, or other non-Jito block-building infrastructure.

  • Sandwiching of Jito-Tipped/"Protected" Swaps: Instances where user transactions paying Jito tips (which should receive ordering protection within Jito's system) are still sandwiched, sometimes by attackers paying only priority fees, directly contradict expected Jito behavior. This provides compelling evidence for MEV pathways operating outside or bypassing the standard Jito block engine/relay system.

4.4 Inferred Competition & Ecosystem Dynamics

The significant costs attackers are willing to pay (especially high Jito tips during peak hours for bundle guarantees) and the inherent risks (like exposure during uncled slots) point towards a highly competitive environment where actors vie for profitable opportunities.

4.5 Implications for Understanding & Mitigation

The attacker landscape appears to be characterized by anonymity, strategic diversity, technical sophistication, and the use of infrastructure potentially spanning both public (Jito) and private/alternative pathways. This makes comprehensive monitoring and targeted mitigation difficult. It suggests that effective defenses may need to focus more on protocol-level changes, DEX-specific designs that resist manipulation (discussed further in Section 5), and validator conduct rather than solely attempting to block constantly changing attacker addresses. The analysis presented, while insightful, captures a close approximation based on available data and known limitations, particularly regarding the full extent of non-Jito MEV facilitation.

5. Where & When: Attack Patterns & Hotspots

Analyzing where sandwich attacks concentrate and the timing of their occurrence helps illustrate the dynamics of this MEV activity within the Solana ecosystem. While temporal patterns primarily reflect periods of higher user activity (creating more sandwich opportunities), understanding these patterns alongside the specific platform and asset targets provides valuable context for protocols and observers. This section analyzes these patterns based on the 7-day data snapshot.

5.1 Temporal Patterns: When Do Attacks Occur?

Sandwich attack activity is not evenly distributed throughout the day. Analysis of hourly data (sandwich counts, attacker costs, and extracted value) reveals distinct cyclical patterns, likely influenced by global market activity:

• Peak Activity Window: A pronounced peak in activity occurs consistently between 14:00 and 20:00 UTC. This period, corresponding to the overlap of US and European market hours, sees the highest frequency of attacks, the largest amount of value extracted, and the highest expenditure by attackers (fees and tips). Variability exists within this window, with particularly notable spikes observed around 19:00 and 22:00 UTC in the dataset.

• Trough Period: Conversely, activity significantly dips during the early UTC morning hours, roughly between 04:00 and 08:00 UTC.

While knowing these peak times doesn't necessarily allow individual users to perfectly avoid risk (as vulnerable transactions can be targeted anytime), it highlights periods where the overall volume of sandwich activity is highest, potentially informing protocol-level monitoring or adaptive defense mechanisms.

5.2 DEX Hotspots: Which Platforms Are Targeted Most?

Analysis of sandwich activity across different Decentralized Exchange (DEX) programs reveals a strong concentration on platforms associated with new token launches and established high-volume venues:

• Dominant Platforms: Based on the latest 7-day data, platforms associated with Pump.fun dominate. This includes both the initial launchpad (pump.fun, ID: 6EF8...) and its associated swap platform (pumpswap, ID: pAMM...), which handles tokens after they graduate from the initial bonding curve. Together, they rank highest in both the sheer number of sandwich attacks: pumpswap saw the highest count (~56k sandwiches) while pump.fun saw the highest reported extracted value (~$241k USD). This highlights the intense focus of sandwich bots on the volatile environment surrounding memecoin launches facilitated by this ecosystem.

• Established DEX Activity: Raydium Liquidity Pool V4 (ID: 675k...) also features prominently, ranking high in sandwich count (~13.5k) and reported extracted value (~$175k USD). This reflects its position as a major DEX on Solana, likely seeing attacks targeted at pairs with established volume and liquidity. Raydium's other programs, like the constant product market maker (ID: CPMM...) and concentrated liquidity (ID: CAMM...), also experience sandwich activity, albeit at lower levels.

• The Underestimation Caveat: It is crucial to remember that the reported USD values significantly underestimate the true value extracted, especially on platforms like pumpswap and pump.fun where many targeted tokens lack reliable pricing data.

• Why Aren't All DEXs Targeted Equally? The lower prevalence of sandwich attacks on certain other DEXs or specific pool types might stem from several factors. These can include different AMM designs (e.g., Request-for-Quote systems, more complex order book logic, or liquidity management strategies in CLMMs), lower trading volumes in susceptible pairs, or the implementation of specific MEV mitigation techniques by the DEX protocol itself.

5.3 Token Pair Hotspots: Which Assets Are Targeted Most?

The concentration of attacks becomes even starker when examining individual token pairs:

• Dominance of New Launches: The top pairs by both sandwich count and reported extracted value overwhelmingly involve newly launched tokens paired against SOL. These are often identifiable by platform-specific suffixes in their addresses, such as ...pump for tokens originating from the Pump.fun platform or ...bonk for those associated with the Letsbonk.Fun platform (which utilizes Raydium's Launch Lab). Illustrating this, pairs like 6RLih...Npump-SOL (~2.3k count), CoXB4...mpump-SOL (~1.5k count), and Dfwxy...Ypump-SOL (~1.3k count) were among the most frequently sandwiched based on the latest data. In terms of reported extracted value, the top ranks featured pairs involving the newly launched LETSBONK token (LETSBONK-SOL, ~$13k reported extracted value) and other tokens with the .bonk suffix like 93a1t...Sbonk-SOL (~$9k). The consistent targeting of tokens launched via different platforms indicates that new platforms replicating similar launch mechanics inherit these MEV vulnerabilities.

• Target Characteristics: This data strongly confirms that attackers focus intensely on the initial moments of a token's lifecycle, exploiting the characteristic low liquidity and high speculative volume/volatility common to memecoin launches.

• Value Underestimation (Critical): For these newly launched pairs, the reported EXTRACTED_VALUE_USD is particularly unreliable and represents a bare minimum. The value attackers gain in the new token itself is often unpriced (reported as $0 USD), meaning the true profit and corresponding user loss could be substantially higher depending on the token's subsequent price movement.

5.4 Connecting Targets and Timing

The concentration of attacks on new token launches suggests that peaks in activity likely correlate not just with general market hours but potentially also with periods of intense community focus or specific launch windows for highly anticipated memecoins, occurring predominantly within the broader 14:00-20:00 UTC peak window.

5.5 Summary of Patterns and Implications

Sandwich attack activity in the observed period was heavily concentrated, targeting specific asset types (newly launched, low-liquidity tokens) on particular platforms (launchpads like Pump.fun/pumpswap, high-volume DEXs like Raydium V4) during distinct peak hours (14:00-20:00 UTC). This concentration creates periods and locations of significantly heightened risk. While providing opportunities for attackers, it simultaneously degrades the user experience on these platforms and underscores the challenge for DEXs in balancing open access with manipulation resistance, especially for highly volatile assets. The reported financial figures, while substantial, likely only scratch the surface of the true value extracted due to data limitations.

6. The Role of Network Infrastructure: Validator Incentives

Validators, as the producers of blocks on the Solana network, play an essential role in the transaction supply chain, including the processing of MEV-related transactions like sandwiches. Their actions are significantly influenced by economic incentives, which this section explores based on the measured revenue streams associated with sandwich attack facilitation.

6.1 Overall Validator Revenue from Measured Sandwich Activity

Including sandwich transactions in blocks generates direct revenue for validators through native transaction fees and Jito tips paid by attackers. For Jito tips, it's understood that validators receive the amount net of a fee retained by the Jito infrastructure (reportedly 6%). Applying this standard 6% fee to the total Jito tips paid by attackers (calculated at ~352.5 SOL from dedicated cost data) and adding the associated transaction fees (~1.2 SOL) yields an estimated ~333 SOL in total revenue received collectively by validators from facilitating sandwich attacks over the 7-day period.

Crucially, this revenue figure solely reflects native transaction fees and net Jito tips. It does not account for potential earnings validators might derive from facilitating MEV through alternative or private pathways (as discussed in Section 4.3.5), representing only a lower bound of the total financial incentive potentially available to validators from measured MEV sources. Analysis of hourly data indicates validator earnings peak concurrently with overall sandwich activity (14:00-20:00 UTC).

6.2 Per-Validator Revenue Distribution & Concentration

While the overall revenue attributed to sandwich facilitation is significant, its distribution among validators is uneven. The analysis below is based on the reported net revenue (fees + net tips received) directly attributed to individual validators in the leaderboard data (summing to ~333 SOL across all validators).

• Activity Concentration: A notable portion of the ~87,061 sandwich attacks occurred in blocks produced by a relatively small subset of validators. The top validator (6dwKX2BK..., listed as 'private') included nearly 2,500 blocks containing sandwiches, substantially more than other highly active validators in the top 5 by this metric, which included large operations like Binance Staking (DRpbCBMx...), Helius (HEL1USMZ...), Galaxy (DtdSSG8Z...), and Ledger by Figment (q9XWcZ7T...).

• Revenue Concentration: The measured revenue received is similarly concentrated. The same top validator (6dwKX2BK...) also received the highest reported net revenue (~21.3 SOL), more than double the next highest (7bLCyBuF..., ~9.9 SOL).

• Reliance on Sandwich Revenue: The proportion of a validator's total measured fee/tip revenue derived from sandwiches (Sw. Fees & Tips Pct.) varies dramatically. While for many large validators this percentage is very low (< 0.5%), several smaller or potentially MEV-focused validators show a much higher reliance based on the reported data. The top 5 by this metric derived between ~7.5% and ~11.9% (led by 4BevYSu... / 'MV 0feeMEV' at ~11.86%) of their measured income from sandwich fees and tips during this period, indicating a significant reliance for some operators.

6.3 Financial Incentives from Measured Sources

The estimated ~333 SOL earned collectively, and the high reliance demonstrated by certain validators based on reported figures, highlights a clear financial incentive derived from including sandwich transactions via standard fees and Jito tips. This incentive structure influences validator behavior regarding transaction inclusion.

6.4 Implications: Validator Role & Ecosystem Health

The financial incentives associated with MEV create a complex dynamic for the Solana network. The mechanism by which validators earning disproportionately high rewards (including MEV revenue) can potentially compound their stake faster than others is a recognized concern regarding long-term network decentralization. While the revenue measured here is limited in scope, it represents a tangible factor contributing to these incentive structures and potential centralization pressures. The observed variation in validator reliance on this income underscores diverse operational strategies. Addressing the potential negative externalities of user-harming MEV while maintaining robust validator economics remains an ongoing challenge, reflected in ecosystem discussions around validator conduct, application-layer defenses, and potential protocol-level changes.

7. Methodology, Data Interpretation & Limitations

This section outlines the methodology employed in this report, including data sources, key definitions, analysis techniques, and known limitations, to provide context for the findings presented.

7.1 Data Source and Scope

The primary data source for this analysis is the "🥪 MEV Monitor: Solana Sandwich Attacks" dashboard, a public tool developed for the Helius "[REDACTED]" Hackathon to monitor sandwich MEV activity. The analysis covers a 7-day period from 2025-04-22 to 2025-04-28, reflecting a recent snapshot of activity based on the data available at the time of report generation. Data regarding victim transaction costs (fees and tips) was sourced separately but corresponds to the same period and sandwich events identified by the dashboard. All data processing and analysis beyond the dashboard's visualizations were conducted using standard data analysis libraries.

7.2 Key Definitions and Metrics Used

• Sandwich Attack: Defined based on the dashboard's identification methodology, typically involving the detection of an attacker's front-run and back-run transactions executed immediately before and after a victim's swap transaction within the same block slot, targeting the same token pair.

• Extracted Value (USD): This core metric, as reported by the dashboard (e.g., in hourly sums or per-pair aggregations), is interpreted throughout this report as representing the attacker's gross profit before their own costs. It is assumed to be equivalent to the additional loss (slippage) incurred by the victim due to the price manipulation caused by the attack. (Caveat: See Section 7.4 regarding significant underestimation).

• Attacker Costs (SOL/USD): Calculated as the sum of native transaction fees and Jito tips paid by the attacker for the front-run and back-run transactions associated with successful sandwiches. USD estimates use an average SOL price for the period.

• Attacker Net Profit (USD, est.): Calculated as Total Reported Extracted Value (USD) minus Total Attacker Costs (USD, est.).

• Validator Sandwich Revenue (SOL): Measured as the sum of native transaction fees and net Jito tips received by validators for including sandwich-related transactions in blocks they produced (based primarily on leaderboard data where available, or calculated assuming a standard Jito fee where specified). (Caveat: See Section 7.4 regarding scope limitation).

• Victim Costs (SOL): Measured as the sum of native transaction fees and Jito tips paid by the victim for their specific swap transaction that was sandwiched.

7.3 Analysis Methodology

• Data Aggregation: Analysis relies on aggregated data provided by the dashboard (e.g., hourly summaries, per-DEX/pair totals) and supplementary calculations performed on this data (e.g., summing totals, calculating averages, identifying trends).

• Sandwich Identification Filters: To improve accuracy and reduce potential false positives, specific filters are applied after initial identification:

  • Backrun Amount Filter: Sandwiches where the amount of the primary token sold by the attacker in the back-run exceeds the amount purchased in the front-run are excluded. This targets potential false positives involving attackers selling unrelated tokens but may also exclude some true sandwiches incorporating overflows or external funding.

  • Split Backrun Filtering: To handle data inconsistencies arising from complex split-backrun attacks (where the dashboard might not capture the full sequence accurately), sandwich records showing an apparent extracted value loss greater than 0.05 SOL (i.e., less than -0.05 SOL, a threshold based on the median extracted value observed during development) were filtered out from certain value-based analyses to reduce noise.

• Attacker Analysis: Due to attribution challenges, attacker analysis focused on behavioral proxies like cost patterns and execution methods rather than tracking specific bot identities.

• Temporal/Target Analysis: Standard time-series analysis (identifying peaks/troughs in hourly data) and comparative analysis (ranking DEXs/pairs by activity/value) were used.

7.4 Limitations and Caveats

It is essential to consider the following limitations when interpreting the report's findings:

• Attacker Attribution: Attributing attacks to persistent actors is inherently challenging. While front-run/back-run transaction signers are visible, these addresses are often temporary ('burner wallets'). Identifying custom on-chain programs used consistently by an attacker is potentially more reliable but not always applicable and may not be fully utilized for attribution within this dashboard's scope.

• Execution Complexity & Incompleteness: Real-world sandwich methods are diverse (split backruns, setup txs, varied tip strategies, third-party tips). The dashboard provides a "close approximation" based on identifiable patterns but cannot capture every nuance, potentially underreporting activity involving highly complex or novel methods.

• Pricing & USD Valuation Underestimation: This is a major caveat. The lack of reliable, real-time pricing data for many newly launched/illiquid tokens (especially memecoins) means that all reported USD values (Extracted Value, Profits) significantly underestimate the true financial scale. Profits realized in these tokens are often valued at $0, making reported USD figures a conservative lower bound.

• Validator Revenue Scope: The reported validator revenue only includes native fees and net Jito tips captured by the dashboard/leaderboard data. It omits potential earnings from alternative/private MEV pathways, meaning the true financial incentive might be higher.

• Split Backrun Filtering Impact: Filtering out complex split-backrun cases based on the profitability threshold might slightly skew aggregated statistics derived from the remaining dataset.

• Tip Attribution Issues: Precisely attributing all Jito tips can be difficult, particularly with third-party payers, without access to richer off-chain bundle data.

• Analysis Focus: The report concentrates specifically on sandwich attacks as defined and captured by the dashboard, not the entirety of MEV activity on Solana.

• Time Window: The 7-day scope provides a valuable snapshot of recent activity, but observed trends, volumes, and dominant actors may differ significantly over longer time horizons or during different market conditions.

8. Conclusion & Implications

8.1 Summary of Key Findings

This analysis of the "MEV Monitor: Solana Sandwich Attacks" dashboard over a 7-day period (approx. April 22-28, 2025) provides a snapshot of the significant role sandwich attacks currently play within the Solana DeFi ecosystem. Key findings include:

• Substantial Financial Impact: Over 87,000 sandwich attacks resulted in approximately $623k USD in reported extracted value. This figure represents a tangible cost to users but is confirmed to be a significant underestimation due to the inability to accurately price profits gained in newly launched, illiquid tokens.

• Profitable Attack Vector: Despite attackers incurring measurable costs (~$53k USD, primarily via ~352 SOL in fees and Jito tips), the activity appears highly profitable based on the reported data (estimated net profit ~$570,991 USD), driving attacker behavior.

• Target Concentration: Attacks are overwhelmingly concentrated on newly launched, low-liquidity tokens (often memecoins) primarily accessed via specific platforms like Pump.fun/pumpswap and associated DEXs. Established DEXs like Raydium also face activity, but the financial scale appears highest around token launches.

• Complex & Opaque Actors: Attackers employ diverse, sometimes complex execution methods, operate largely anonymously using ephemeral wallets, and potentially leverage infrastructure beyond the public Jito MEV system, making attribution difficult.

• Clear Validator Incentives: Validators collectively received significant revenue (estimated at ~333 SOL, net of an assumed 6% Jito fee on tips plus transaction fees) for including these sandwich transactions. While distributed unevenly, this provides a clear economic incentive, with some validators deriving a notable percentage (~8-12%) of their measured income from this source.

• Temporal Patterns: Activity demonstrates clear hourly peaks, predominantly between 14:00 and 20:00 UTC, correlating with US and European market hours.

8.2 Implications for Stakeholders

The prevalence and nature of these sandwich attacks carry broad implications:

• For Users: The direct financial cost via extracted value and transaction fees, combined with a degraded trading experience (worse pricing, potential failures), erodes user trust, especially when interacting with new tokens or specific DEX platforms during peak times.

• For Protocols & DEXs: Platforms facilitating new token launches are clear hotspots, facing reputational risk and usability challenges. DEXs, in general, must contend with MEV undermining fair market principles, driving innovation in AMM design and integrated mitigation features.

• For Network Health & Fairness: Sandwich attacks represent a form of "MEV tax" on specific types of DeFi activity. Furthermore, the mechanism by which MEV revenue can compound validator stake contributes to recognized concerns about potential long-term stake centralization, impacting network governance and decentralization ideals. The evidence of potentially non-public MEV pathways also raises questions about transparency and equitable access.

8.3 Relevance to Ecosystem Goals

This analysis, facilitated by the MEV Monitor dashboard developed for the Helius “[REDACTED]” Hackathon, contributes to the goal of increasing transparency around malicious MEV. By quantifying the scale (albeit underestimated), identifying hotspots, and analyzing methods, it provides data-driven context for ecosystem participants grappling with these challenges.

8.4 Areas for Further Research & Mitigation Context

While this report provides a valuable snapshot, further research could deepen understanding. Key areas include developing robust methods to value profit in illiquid tokens, investigating the prevalence and impact of non-Jito MEV infrastructure, and conducting longer-term studies to track trends beyond the 7-day window. The findings underscore the importance of ongoing efforts within the Solana ecosystem to mitigate harmful MEV, ranging from application-layer solutions (e.g., improved swap interfaces, RFQ systems) and validator conduct initiatives (e.g., whitelists) to potential longer-term protocol adjustments (e.g., changes to block production mechanisms).

8.5 Final Conclusion

Sandwich attacks remain a significant and dynamic feature of the Solana DeFi landscape, particularly concentrated around the high-risk, high-reward environment of new token launches. Driven by substantial financial incentives for both attackers and, indirectly, the validators who include their transactions, these attacks impose real costs on users and present ongoing challenges to market fairness and network health. Addressing this requires a multi-faceted approach involving continued transparency efforts, user awareness, protocol innovation, and careful consideration of core network incentives.

It is a diverse mix of art, utility, and finance—some of which are familiar to all of us. Each use case has not only spurred innovation but also led to the development of tools, protocols, and the nurturing of communities and culture.

Not long ago, NFTs were proclaimed to be “Actually — Finally — Totally Worthless” in the ramblings of old men not able to see the forest for the trees. With a market cap of non-fungible collections valued at close to $2 billion, rivaling the entirety of DeFi on the blockchain and second only to Ethereum, the birthplace of NFTs, NFTs on Solana might actually — finally — be worth more than the blocks they were minted on. An increasingly sophisticated user base actively participates by collecting, bidding, listing and trading these assets each day, generating volumes of millions of dollars that trickle down the ecosystem in the form of network fees, protocol fees, and royalties.

Metaplex stands as the cornerstone of this rapidly advancing NFT ecosystem, driving innovation and growth. Over the years, Metaplex has set the standards for the industry, fostered the development of diverse digital assets, and has been synonymous with NFTs. Its most recent efforts to exponentially reduce the cost of new mints to a degree only possible on Solana, have been so compelling that the entire Helium network has migrated over in 2023, together with over 600 thousand device tokens.

The blockchain retains forever an immutable and flawless record of all the transactions and events that got us here. Yet the ecosystem it shelters is fleeting, and its gods vulnerable.

Solana is a relatively young blockchain, celebrating its fourth anniversary in March 2024, and having survived through hardship and misfortune. The breakneck speed of the blockchain permeates the culture of the ecosystem, which has so far been through multiple transformations. One such transformation has been brought by what’s been called Defi 2.0 — a new generation of builders with a new generation of products, taking on the old lineup of platforms and closer to the values, goals and aspirations of the community.

But perhaps a more relevant example is in the NFT market itself. Behind the overall volumes presented earlier, there is the story of competing marketplaces, their share of it over time, the battles won and lost.

Over the nearly three years of its existence, this market has witnessed two major shifts in dominance: first, the rapid ascent of MagicEden over Solanart, and secondly, the gradual and steady rise of Tensor over MagicEden. The reasons behind these shifts are numerous, and perhaps not all are fully understood yet or completely played out. However, what is certain is that even in this highly digital realm, natural forces are at play, creating opportunities and driving change.

At the time these wars were being fought, and on the blockchain that started it all, a small group of heretics sought to expand the capabilities of the Bitcoin network (again), in what’s been called an exploit, abuse, and an insult to the purity of the blockchain and its Satoshi-given purpose by the laser-eyed maxis. Nevertheless, they persevered, introducing inscriptions and ordinals—a development that effectively brought the equivalent of NFTs to the old blockchain.

At a technical layer, blockchains still find it difficult to communicate to one another. But the speed at which information travels at the social layer has allowed the concept of inscriptions to quickly permeate virtually every blockchain, sparking a revival of the crypto punk ethos across the industry. While the impact on most networks may have been short-lived, it proved profoundly consequential on Solana.

Not only Metaplex did not have the tools to help with the creation of these new digital assets, it’s centralised control and closed-source nature was the ideological opposite of inscriptions — an inefficient use of space, costly, and fundamentally rejecting what had become blockchain tradition. But the current was too strong, the people could not and would not wait, so Libreplex was created as an open-license, community-led protocol that swiftly gained traction and support from all major NFT marketplaces.

In the first month, close to 1 million inscriptions were created, a threshold it would soon after surpass. Additionally, thousands of creators were using Libreplex, thereby affirming the community's demand for these tools and fuelling an unstoppable momentum of community-led progress.

By the end of 2023, the hype around inscriptions had subsided, only to resurface tentatively in mid-January 2024. During this time, Libreplex quickly matured and expanded its toolset. Drawing further inspiration from the Bitcoin camp, Libreplex introduced SPL20 tokens, a merger of inscriptions and fungible tokens, bridging the gap between NFT marketplaces and DeFi.

But while Libreplex made significant strides, it remained partly dependent on Metaplex's metadata program for the creation of inscriptions and the fungible tokens they were paired with. However, this dependency was soon challenged by the imminent release of Token Extensions, offering expanded functionalities for native tokens.

Token Extensions, formerly known as Token 2022 or T22, introduced the possibility of expanding the functionalities of native tokens by using extensions to add an array of functionalities, but crucially, metadata. During Jupiter’s Jupuary, leading up to the release of the JUP token, the creation of the WEN NFT with the use of Token Extensions was showcased. This simultaneously introduced the Wen New Standard 0.0, another example of a new community-led protocol, free to use, built on top of a native standard and offered as a public good.

Inscriptions ignited a movement, SPL20s bridged NFTs and DeFi, Token Extensions liberated metadata, and ultimately it all converged to create the SPL22 standard, where both the fungible and the non-fungible tokens were now built on T22 tokens using a community-developed, open license standard and tooling.

This opens the door to envisioning a future where tokens transcend traditional categories of fungibility. Instead, a unified standard could seamlessly traverse between both realms, blending the strengths of each. One should be allowed to dream.

While the possibilities are indeed endless, what's truly remarkable is that the responsibility of turning our dreams into reality no longer rests solely on the shoulders of a single entity. The Solana ecosystem has evolved to challenge the revered status of its oldest gods and usher in a new era, empowering anyone prepared to pursue their imagination with the powers once reserved for the almighty.

One of such cases is Marinade Finance which saw its instant unstake pool drained during the week of November 08-14, with any new liquidity being immediately sucked back out over the course of a few days. While this didn’t put the protocol itself at risk, it did offer an extreme case study of how their own liquidity pool behaves in periods of stress and high demand.

In this report we will look at how the instant unstake pool of Marinade Finance got drained and how the current pool parameters compare to the rest of the market.

All of the staked SOL can be redeemed from Marinade by burning mSOL and waiting for one or more epochs to end depending on the unstake volume. For those who can’t (or won’t) wait that long, they can opt to instantly unstake, which in practical terms is simply a swap of mSOL to SOL. Marinade Finance has its own liquidity pool to enable instant unstaking, but as with any pool, swapping assets comes at a cost.

The pool parameters are set to charge a flat fee of 0.03% while the SOL liquidity is above a current liquidity target of 100k. When liquidity drops below that, the fee will linearly increase to a maximum fee of 3%. More info on pool mechanics in the docs.

The counterparty to Marinade’s pool in this report will be made up of all the other mSOL-SOL pools aggregated from the swap transactions over the same period.

Assuming that the Marinade pool uses the true value of mSOL based on the accrued staking rewards of the underlying staked SOL, that will be the price used as a reference to calculate unstake premiums on both the Marinade pool and all others.

All of the data can be further inspected and interacted with using the live dashboard:

https://app.flipsidecrypto.com/dashboard/nmQFX8

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Pool Liquidity Balance

Because the pool parameters take a more unusual approach by placing a hard cap at 3%, it can end up in a situation where it can be depleted at much lower costs than alternative pools, making it difficult to be replenished during periods of high demand.

When this happened right after the FTX and Alameda collapsed, the Marinade pool quickly lost most of its SOL liquidity and was left at virtually 0 for several days.

We can see that right before being emptied, most of the unstake volume was coming through the Marinade pool, allowing it to capture swap fees that are split between liquidity providers and the Treasury.

But just because Marinade didn’t have any more liquidity to service users, it does not mean trades did not continue elsewhere. Over the following two days, on November 9 and 10, we can see high unstaking that has no other option but to use the other liquidity pools that offer in many cases a much lower price.

II. Liquidity Crunch

Below we can see how the pool parameters kick into action as liquidity sharply decreases. The liquidity crunch is visibly present in the other available pools as well and we see a price action similar in size and timing. As a result, the price of mSOL drops in comparison to SOL for those wanting to instantly unstake and users have to effectively pay a premium to do so.

For the Marinade pool, it is a straight journey to the bottom set by the maximum fee, where for the most part it remains until Nov 12 when new liquidity can start to build up in the pool. Up until that point, the much more attractive price in comparison to the rest of the market leads to every drop of liquidity to be quickly gobbled up the moment it got added.

But while this seems like a very dramatic event, on the weekly scale it did not have have a strong impact in the average prices due to the significantly lower volumes traded during that period.

The price change induced by the dwindling liquidity, while the underlying value remains unchanged, can be translated as a premium paid by those who want to immediately trade mSOL to SOL.

While Marinade has that premium capped at 3%, we see the market comfortably going much higher and paying double. In extreme cases, the premium goes as high as 16% on a trade and around 12% as an hourly average.

Interestingly, between November 12 and 13, liquidity providers earn less on the other pools, yet liquidity is slow to return back to Marinade, where the maximum fee is maintained for almost a day longer.

Conclusion

Undoubtedly the events highlighted how the Marinade owned liquidity pool for instant unstaking can be depleted and leave one of the main value propositions of the protocol in the hands of the open market, all the while missing out on additional fees for the Treasury.

Considering these events, Marinade Governance proposed and successfully passed a proposal to adjust the parameters of their pool. Following the implementation of the proposal, the liquidity target will be set at 150k and the maximum fee increased to 9%.

This change is expected to make the pool more reactive and resistant in times of great demand, as well as more attractive for liquidity providers. At the same time however, this increases the burden of maintaining a positive loop of sufficient liquidity to attract users and sufficient trading activity to make liquidity stay.

At this point, the community had two options to choose from: kill it or give it a new life. In a grand display of coordination and solidarity, a few smaller teams joined forces to deploy a functioning fork of the Serum v3 DEX program during the same day, now named OpenBook.

In this report we will have a closer look at the activity and liquidity accumulated in the two weeks that have passed since its launch.

We are going to mainly focus on only two aspects, key to an order book protocol:

• New orders

• Markets liquidity

Note: New orders can be placed directly through the supported UIs or through an aggregator. When aggregated, the process of deposit > order > match > withdraw is automated, but otherwise users must settle funds or can keep on trading them on the platform.

All the charts, data and queries can be further inspected and interacted with through the live dashboard below:

https://app.flipsidecrypto.com/dashboard/open-book-activity-dashboard-PHlEPw

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Program Activity and New Orders

We can see activity starting to roll in immediately after deployment and then shoot up as its release became public. Somewhat cyclical so far, the number of daily transactions peaked at over 730k on Nov 23, but for most of the time the count stays in a range of 300k - 500k.

Out of all transactions, we see that only a small proportion of them are actually New Orders being placed, where a positive net amount of tokens is being added to the order book. Unsurprisingly, there are a lot of other transactions being made on the side of that as many other components have to work together to make sure the book is kept in good order, create new markets, manage accounts and so on.

On the upside, we see that there are a lot more wallets using the protocol for what it is and place new orders to the book. The two categories do not mean a wallet exclusively does one action or the other, and the addresses might overlap.

The number of wallets placing orders peaked early on Nov 18, but daily counts have remained in a stable range, although slightly downward trending over the last week. Given the circumstances of its launch, in the wake of the FTX collapse, from the ashes of a potentially compromised protocol and with a backdrop of a year-long crypto winter, it’s a rather encouraging user base. Although still a young deplaoyment, it received a lot of support from the wider ecosystem that had it integrated with protocols such as the Jupiter aggregator and Raydium, which are responsible for most of the transacting wallets the protocol had so far.

Out of the 37 markets currently open, we can see just a handful of them bringing in most of the new orders. Unsurprisingly, even out of that small group, the most orders by far are being made on the wSOL-USDC market, one of the quintessential pairs of the ecosystem. Since launch, it accumulated over 470k new orders, with over 790M USDC (quote asset amount) and 33M SOL (base asset amount) flowing in through orders.

By the number of orders placed in the period, the market is followed by mSOL-USDC with 174k, scnSOL-USDC with 84k and wETH-USDC with 56k.

Although the new orders activity started out strong, it’s starting to slow down as the order books get filled and many of the listed pairs are currently trading in a more stable range.

A full list of markets and the orders placed during the period can be found in the full dashboard. A transaction can place both a SELL and a BUY order at the same time, so one transaction does not always equal one order.

II. Markets Liquidity

The asset being paired the most on OpenBook is USDC with 25 markets currently open, followed by wSOL and USDT. As we’ve also seen in the previous section, these are the tokens with the most orders across their markets as well so we will focus on the liquidity accumulated on the order book by these assets.

The liquidity overview will be split into two categories: one for stablecoins and one for SOL and its derivative tokens such as mSOL and stSOL.

*Note: The liquidity represents the total token amount balance of each OpenBook vault of the selected asset. They include open orders and unsettled funds.

SOL & Derivatives

In the beginning there was only wSOL, and it pretty much stayed that way for the first few days. Then we can see mSOL being added and making up ~20% of the liquidity in this token category for a short period. Soon after stSOL and scnSOL were also introduced to the order book, but throughout the observed period wSOL remained the dominant asset.

The total token amount had modest beginning and during the first few days it peaked at only a few thousand SOL, after which it fell down to a little over 1k. The reluctance or hesitation to add a large amount of funds to a protocol that went live just a few days before is understandable, but market makers were quick to get past that as OpenBook proved to run efficiently received more support from the Solana DeFi ecosystem.

The token amount in this category reached a peak of over 17k tokens and has maintained a somewhat stable range between 13k and 17k over the last week.

Stablecoins

In the case of stablecoins, we can see again a precautious start but followed by a more gradual and sustained increase to the current level of over 1.57M tokens. With the exception of the first day when both tokens had a total balance of a little over 1k, USDC has represented the dominant stablecoin on the order book.

We see for this category that the amount of tokens stored in OpenBook vaults is still on a positive DoD Change Rate streak, but slowing down over the last week.

A complete table of all the other markets and current vault assets can be found in the live dashboard:

Conclusions

• Following the successful fork and deployment of the Serum v3 DEX into OpenBook, we can see activity quickly building up, although only a small share of transactions are actual orders but only as a side effect of how the protocol is built.

• When filtering for user actions, we see many of the transacting wallets actually placing orders and making real use of the protocol, but the overall count is rather small. In its defense however, it is a protocol being launched in the wake of the FTX collapse, from the ashes of a potentially compromised protocol and with a backdrop of a year-long crypto winter.

• As one might expect, most of the orders so far were made on wSOL and stablecoin-paired markets, coinciding with the largest count of currently open markets by asset.

• There are over 16k SOL and SOL derivative tokens being held in OpenBook market vaults as open orders and unsettled balances, a level within a relatively tight range that was maintained over the last week.

• In the case of stablecoins, there are over 1.5M USDC and USDT tokens sitting in vaults, with the asset category being on an upward trend since the begining, albeit one that’s been slowing down over the last week.

• Current activity on OpenBook, although modest at first sight, already puts it in the top 5 Solana DEXs based on recent activity according to DeFiLlama. As more of the ecosystem pitches in to shape the future of the protocol and integrate it into their own products, OpenBook is likely to earn a permanent spot among the top sources of liquidity on Solana.

https://zrk5xm.xyz/

In this report we’ll have a look at Solana staking pools and their users activity in response to recent events.

When a user deposits tokens through a liquid staking provider, they receive tokens representative of their stake (mSOL, stSOL etc.) that they can then use as they please. Most providers offer two unstaking options: fast or slow. Usually the fast option instantly unlocks the staked tokens and send them to the user for a fee, while in the slow option has no fee but tokens go through the normal unstaking process through the end of the epoch.

For simplicity, both the fast and slow unstakes will be grouped under the WITHDRAW label as their initiation burns the representative tokens and the stake is no longer part of active stake pending withdrawal.

The time frame used in this report starts on November 6 at the start of the FTX and Alameda downfall and spans to the current_date at the time of writing, November 14. The time frame can be adjusted using the dashboard parameters start_date and end_date.

All of the data and queries can be further explored and interacted with in the live dahsboard below:

https://app.flipsidecrypto.com/dashboard/dHYmkE

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Staking Pools Activity

For the first couple of days we see just under 300 daily transactions and around 200 users, but starting on November 8, as the financial trouble rumors about FTX and Alameda were turning to more than rumors, users reacted and activity spiked across all liquid staking providers. Following the market share split of providers, most activity can be observed on Marinade and Lido, in almost equal proportions over the observed period.

The daily activity peaked on November 10 and gradually decreased over the following days as people seem to have either exhausted their options or wait to see where the market will go next before they make any other actions.

Unsurprisingly give the current context, most of the activity was the result of users trying to withdraw their staked SOL and presumably reduce their exposure to the asset. Over the observed period only BlazeStake had a net increase of staked tokens, whereas all other protocols had a lot of tokens withdrawn. In the case of Marinade, withdrawals were exceeded deposits by 2.3M SOL, followed by Lido with a similar difference of 1.9M tokens.

Although we’ve see the most activity on November 10, the most $SOL was withdrawn two days before that, on November 8. This shows that larger stakers were quicker to react to the news and positioned themselves accordingly.

We can see however that across the board it’s not been a one sided week, but there have been a lot of deposits as well. Furthermore, we can see that initially both deposits and withdrawals were ramping up, but deposits hit a break on November 10, as the insolvency news of FTX and Alameda discouraging users from staking their tokens.

Over the last few days however we see withdrawals have considerably slowed down and deposits are ramping back up, with Lido leading the charge.

II. Price Reaction

The price activity we can observe above have given $SOL traders and users a huge price range to take action.

We can see a lot of volume being withdrawn just under the $30 price point, most likely shortly after the rumors started to spread, and on November 8 when we could see the most volume. As the price went down and more people became aware and their concerns grew, we see a lot more transactions and volume, especially withdrawals between $12 and $20.

*There are a few withdrawals and deposits made at $40 and $50+ but they are very likely price anomalies as the on-chain $SOL swap price at the time of each transaction is being used as a reference.

Using the distribution of transacting users below, we see that most users only reacted once the price fell below the $20 price from its average price of $36 at the start of the observed period. The over 40% decrease in such a short amount of time seems to have been their trigger to finally withdraw their stake.

Interestingly, the number of depositing users does not change all that much after that point, and we can see a lot of depositing users on the way down, indicating that perhaps many of them saw what was happening as nothing more than news meant to scare the market and quick to blow over. Unfortunately for them, the news proved to be a lot more serious and with higher consequences over the price of $SOL.

III. Swapped Tokens

Just as with deposits and withdrawals, we can see swapping activity of liquid staked SOL spiking as the price fell below the $20 price point. By the number of transactions, there has been a lot of arbitrage being made thanks to the large swap volumes we can see on the right, which open a lot of such opportunities across exchanges.

But by volume of tokens (all of them being worth more or less 1 $SOL), arbitrage swaps only represent a small slice of the activity over the observed period. Instead, we can see a lot of regular swaps being made and a surprisingly tight difference between the amounts bought and sold over most of the price range in this period.

The swap activity overwhelmingly went through the Jupiter aggregator as it is one of the most convenient method of finding a good exchange rate and sufficient liquidity, especially as liquidity was spread pretty thin given the sudden surge in demand.

After the gradual ramp-up in transactions from November 6 to November 10, the overall activity decreased by around 40% but remained at a high level. At the same time, volume did follow a similar ascending trend over the first few days, but swap volumes have been considerably lower over the last few day, resembling the activity at the start of the observed period.

The most traded tokens by volume were stSOL and mSOL, the two making up almost the entire volume. Their swaps distribution is similar across the price range of the period.

Similar to what we saw in the case of direct interactions with liquid staking platforms, we see quite a lot of buying activity right under the $30 price, with people probably trying to catch “the dip”. However, as the price of $SOL maintained its downward trend, the amount of tokens being sold substantially increased.

Now that we’ve been in the $13-$16 price range for a few days, we see swap volumes consolidating in that range.

Conclusions

• Most stake pool users were pretty slow to react to the events that went on after November 6 and overwhelmingly made the decision to withdraw their stake once the price of $SOL decreased more than 40% in a matter of days to under $20.

• The most withdrawal volume was recorded on November 8, two days before most users took any action. The “smart money” were quick to react to the news and position themselves accordingly.

• The two largest stake pools, Marinade and Lido had huge withdrawals since November 6, exceeding deposits by 2.3M SOL and 1.9M SOL respectively. Only one out of the 7 providers included in the report, had a net increase in stake over the period with deposits exceeding withdrawals by 5k SOL.

• After peak withdrawal hysteria on Nov 10, withdrawals slowed down considerably and deposits are increasing again.

• Swap activity spiked under the $20 price point, progressing to a peak of activity and volume over a similar timeline to direct stake pool interactions.

• Almost the entire swap volume was made by stSOL and mSOL, which traded in similar ways over time and over the observed price range of the period.

• Now that the price has been in a more or less stable range for a few days, we see stake pool users regrouping and activity shifting more towards deposits. However, this shift is still modest as many previous users have already suffered losses of up to 40% depending on their entry price and for this reason they will likely be more patient before repositioning and reentering a stake pool.

https://zrk5xm.xyz/

The network had plenty of time to develop a diverse ecosystem of applications, but as a whole, Solana can only fallback on one asset, the native $SOL token used for transaction fees, network security through staking and of course, the trading currency of NFTs. The survival of the network depends on the survival of the token itself.

In this report we will have a closer look at the on-chain actions following the Nov 6 events and track the flow of value to/from the $SOL token.

• The price of $SOL used throughout this report is calculated using the on-chain swap activity, which might differ to the prices reported on centralized exchanges over the same period. The general labeling of the token in the FlipsideCrypto tables used for this is WSOL referring to the wrapped version of the token, and this is the label that will be present throughout the charts.

• Transfers between a Centralized Exchange’s own wallets or between CEXs will be excluded from the inflow/outflow analysis as these funds never actually leave a centralized entity, thus they don’t represent funds that join or leave the blockchain.

• On the same topic of CEX transfers, it is entirely possible that many transfers and reserves are not being included in the dashboard as this relies entirely on the accuracy and completeness of the FlisideCrypto solana.core.dim_labels table. Furthermore, CEX wallets that had no token movements in the last 4 months will also not have their balances included in the reserves calculations. However, upon close inspection of wallets in this situation, they are often rotated by exchanges and emptied out before being abandoned, and only sometimes they still contain extremely small amounts of $SOL. Because of this there is a reasonable expectation that dormant wallets will not make a significant difference in the CEX reserves if being left out.

• The time frame used in this report starts on November 6 and ends on the date of writing, November 11. The default time frame of the live dashboard is set to a value of 3 but can be adjusted using the days parameter.

All of the data and underlying queries can be found in the live dashboard below where all charts and tables can be further explored and interacted with:

https://app.flipsidecrypto.com/dashboard/sol-on-chain-fallout-5z6xQa

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. SOL Price

After an excellent performance in the week before, we can see the price of $SOL starting a slow descent for about a day and a half, after which the price becomes much more volatile. After a bit of indecisiveness in the market through Nov 7, while FTX and Alameda were still trying to play things cool, the price started a steady descent from a price range of $30 down to $10 (and a bit lower even for a short while).

Right now the price has gone up since by a little, currently sitting in a price range above $15, but the fallout of the recently announced FTX bankruptcy might just be starting to manifest.

We can see the on-chain trading volume frequently spiking after Nov 8, when it became clear that FTX and Alameda were insolvent and that will most likely result in a liquidation of their assets, and most importantly, of $SOL.

Between Nov 8 and Nov 10 we see a lot of trading volume that is in line with the rapidly changing price of the token and shows how people were rushing to be more than just innocent bystanders in the middle of this all. We can see a lot of transactions (purple) being made just under the $30 price, as people were starting to grasp that they’re not going to have just a small correction. A lot of the volume is not being concentrated in the $15-$20 price range as the market tries to figure out which way to go next.

II. SOL Swap Activity

Unsurprisingly, much of the trading volume throughout this period has been between $SOL and stablecoins. Out of the stablecoins available to traders, close to 60% of the trading volume was made using the long-time favorite stablecoin of the Solana blockchain, $USDC.

Besides stablecoins, we can see a lot of volume between $SOL and liquid staked $SOL such as $mSOL of Marinade Finance, or $stSOL of Lido.

*Swaps can be executed with many intermediary steps and between multiple liquidity pools. For this reason, some swaps will start and end with the same token, in a form of arbitrage. Hence, one of the tokens swapped to/for sol visible in the chart below is WSOL.

Since Nov 6, a net amount of more than $6M went out of the token through on-chain swaps. With the exception of $USDC, most other token pairs have a negative swap balance to $SOL, telling us two things:

1. $SOL holders and traders overwhelmingly swapped their tokens to an asset they perceive as safe and reliable.

2. All the other tokens, including $USDT, were funneled to $USDC through $SOL. As things were rapidly evolving and CEX deposits/withdrawals were under question, users flocked to one of the most reputable and reliable stablecoins in the space.

But while this has been a difficult period and a lot of people certainly lost some money, massive price action also opens up a lot of opportunity for skilled traders (or their bots). The most active traders swapped lots of $SOL, many of them at average prices under $20.

However, there isn’t a consensus on the direction of the trade and both buyers and sellers are still betting big, which we can see by the profit they’ve made in $SOL and in $USD (the $USD profit is based on the value of the sold tokens at the time of the transaction). Some of them chose to sell their tokens for an immediate dollar profit, while other continued to stack $SOL and wait for greater price increases.

*It is important to remember that the above section only follows the on-chain trading activity of these accounts, while on closer inspection we can see some of these addresses transferring their assets to other accounts, making CEX deposits and even bridging out of Solana.

III. CEX Inflow/Outflow

In light of recent events users have a difficult choice to make if they want to move their funds between blockchains, deposit/withdraw from/to fiat etc. Still, one of the easiest, fastest and most liquid ways of doing so is through a Centralized Exchange (quite ironic). On the other hand, because of the same events, users might feel the need to withdraw their funds from CEXs to make sure they still own their assets. Not your keys, not your coins amirite?

It seems however that this time people have massively withdrawn their funds from CEXs, perhaps realizing the little transparency they actually offer in regards to not only their reserves, but also in regards to their financial situation and/or what their deposits are being used for. Overall, it’s been a moment of awakening for Solana users.

It is also worth noting that users could just as easily sold their tokens and withdraw to any other blockchain, but they still have sufficient trust in Solana. Over this period, a net amount of more than 15M $SOL was brought back home from CEXs.

Up until Nov 8, we can see a lot of withdrawals coming from FTX, just as we would expect, but on that same day withdrawals were halted. Because users were simply unable to withdraw anything from the exchange, we see it being responsible for just a little over 21% of the total $SOL withdrawn in this period, whereas we would expect a lot more volume otherwise.

Even so, withdrawals did not stop, and we can actually see a lot more tokens coming out of Coinbase, with the largest withdrawals being made just recently, on Nov 11.

What is slightly insane to observe before Nov 8 is the amount of $SOL still being deposited to FTX, in spite of all the news coming out about it. However, some of the largest deposits in that period were coming from wallets identified as being owned by Alameda (which would seem obvious), but they also stop after Nov 8.

A few other large deposits were made since to various CEXs, but $CEXs are really flooded by new $SOL. But given our previous findings about it being primarily swapped to $USDC, it’s very likely that users changed their behavior to first make their actions on the blockchain and then use the CEX just as a way of withdrawing to fiat.

At the moment, Kraken seems to be holding the greatest token reserves of 3.2M $SOL worth around $56.6M, significantly more than any other of the exchanges included.

IV. Staked SOL

The $SOL token plays a vital role for the Solana blockchain as it is the stake in its Proof of Stake consensus mechanism. Therefore, the price of the token is important not just for speculative reasons, but also because lower prices mean a lower cost to attack the network, making it less secure. This is doubled by the fact that a depreciating $SOL token makes existing stakers more likely to unstake, again impacting the overall security of the network.

Generally there isn’t too much going on around staking at this stage of Solana’s existence, at that remains the case pre Nov 8 as well. However, as soon as people realised that the possibility of a lot of $SOL hitting the market in the near term, activity spiked.

Delegations continue at regular levels, but things substantially increase in the opposite direction. Once a stake is deactivated, the stake account owner can withdraw the tokens at the end of the Epoch.

The amount of $SOL being deactivated continues to ramp up after Nov 8 and peaks on Nov 10, awaiting the end of the Epoch, when users were finally able to withdraw. Over the same period, the almost 60M tokens of deactivated stake stirred a lot of speculation and controversy. Almost half of the amount included tokens delegated by the Solana Foundation, which redelegated the tokens and postponed withdrawal to avoid any further speculation.

Until now, the net amount of $SOL staked has increased by over 17M tokens when considering the amounts being delegated and withdrawn.

However, this is not the end of the story and the net amount changes if we consider the amount of tokens deactivated that can be withdrawn or have already been withdrawn at the end of the last epoch. This time the staked $SOL amount turns negative, and the PoS network can lose up to 33M tokens, representing around 10% of the staked $SOL.

V. Bridge Activity (Wormhole)

So if not through CEX, how else is value going to escape the imminent threat of FTX and Alameda being liquidated? Through the Wormhole, of course. As many of the target chains don’t support native $SOL or wrapped versions, users of the platform are compelled to use other assets to bridge in/out. Therefore, in this section all bridged assets are included.

Just as in most other charts we looked at until now, bridge activity spikes after Nov 8. Even at its peak, the number of transactions is not extremely high, with only up to 150 transfers in+out per hour. There is however an interesting shift in direction as time passes. First, transactions are mostly outgoing, starting on Nov 8 and up to Nov 10. After that date, transactions start to shift to incoming transfers, signaling that people have felt reassured by how the handled its first sell-off wave.

Most transactions were made with $USDC which plays a dominant role on both directions thanks to its reputation and popularity as a stablecoin, as well as its widespread availability across blockchains.

In terms of value, we can see a similar story as the one told by the number of transactions. However, we can now see another layer of all those transactions and assess how much value was bridged away.

Over the observed period, a net amount of assets worth over $90M has left the blockchain through the wormhole, although it’s recovered a little over the last day.

While many of the transactions were made with $USDC, most of the value crossing the bridge is in $SOL, regardless of direction. All the other tokens were bridged in insignificant amounts, and even $USDC only represents around 10% of the overall volume.

Conclusion

• The Solana blockchain is facing a difficult situation where one of the partners with a lot of stake and connections in the ecosystem will have to be liquidated, putting a lot of pressure on the $SOL token, vital to the existence of the network itself.

• As more information came to light about the liquidation risk of FTX and Alameda, people have tried to take shelter on-chain by swapping away from $SOL to other assets, withdrawing their stake and bridging away.

• Notably, this time people were not too keen to deposit their $SOL to a CEX and instead there have been massive token amounts withdrawn to the blockchain.

• A large amount of tokens has been deactivated, which if fully withdrawn can reduce the stake of the network by up to 10%. Luckily this number is very dynamic and new $SOL is being added back to validators.

• Bridge activity has spiked after the events of Nov 8, with a lot of back and forth transactions, first away from Solana, and more recently mostly back to it.

• There is still a lot of uncertainty as to how things will develop in over the following days, but on-chain usage, swap volumes, staking activity and bridging activity all indicate that users feel slightly more confident about the likelihood of Solana surviving this incident and they return to pick things back up.

https://zrk5xm.xyz/

The Optimism L2 network is one of the scaling solutions that captured a lot of users and projects from the Mainnet, while succeeding to incubate its own ecosystem of native apps. But if DeFi as a whole is dead, what else is there to do?

In recent weeks, months even, Optimism has been pushing more toward NFTs and experimenting with possible use cases. It ran quests, rewards programs, learn-to-earn campaigns and perhaps the most daring step in this direction, it launched an NFT bridge in collaboration with Quix, the leading NFT marketplace on Optimism.

In this report we will look at the growth of the Optimism network and the role NFTs have played in it over the last month.

The most prominent use of NFTs over the last year has been tying digital assets to them, generally art, but these tokens can be issued to represent much more, such as identity credentials, stake, LP positions and so on. This report will consider interactions with all kinds of non fungible tokens under the label of NFTs.

The default parameters we will e using for the data analyzed in this report are set to months = 3 and date_trunc = week.

All of the data and underlying queries can be further explored and interacted with in the live dashboard:

https://app.flipsidecrypto.com/dashboard/op-nft-activity-pEJ4_T

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. NFT Transactions and Events

Over the last 3 months, the overall activity on the Optimism network has been on the rise and the weekly transactions have increased by more than 50% compared to the start of the period. However, we can see that during the same period so did the number of transactions where NFTs were involved and they represent an increasing share of the weekly transactions.

It’s also worth noting that even in the case of a hardcore NFT Trader, a lot of transactions will still be made to move funds around, swap tokens etc., so it is expected to have a big difference between the two categories.

The number of NFT transactions quickly accelerated in mid September, a period when the Optimism Foundation launched the Optimism Quests, a onboarding campaign that would reward participants with an NFT to celebrate their achievement. This is one of the first campaigns where NFTs are used to rewards participants and thanks to its success many other were launched.

Many of the campaigns since have rewarded users with NFTs, so it’s unsurprising that most of the transactions were minting events. Especially because these NFTs are freely distributed and campaigns are running, there is little value for them in the secondary market, so although there is a large number of NFTs in user wallets, this does not and likely will not lead to a lot of sales activity.

But the Optimism Foundation is aware of this and worked to fix it. More on this later.

The number of minting transactions skyrocketed in the second half of September and so did the number of users minting NFTs. There are two quick things we can learn about the activity in the last three months from the graphs and table below:

1. Most of the minting activity was centered around rewards programs such as Optimism Quests that are rewarded through Project Galxe, Optimism Explorer and others.

2. Most of the top minted NFTs were free to mint. However, we see a lot of value going into Uniswap v3 positions which are represented through NFTs. Most of that DeFi activity was concentrated in early September and has steadily cooled down ever since.

NFT sales had a similar journey by the number of transactions and users, but this time we see a lot more sales volume being made after the busy month of September. This shows that while rewards are free, the onboarded users brought along their capital which they are happy to spend on even more NFT and continue to explore the ecosystem on their own.

Much of the volume can be seen however to go into collections that were free to mint, such as Early Optimists or Optimistic Explorers which might be indicative of users trying to just make some trading volume to earn even more rewards. There are however community projects that were able to make it on the leaderboard, such as Optimistic Ape Yach Club (OAYC), or Motorheadz.

The Month-over-Month change rate of transactions where NFTs were involved has been far greater than other type of transactions. In September, when the Optimism Quests were launched, but also when Opensea landed on the network, there’s been a >100% increase compare to August. Although the month of October did not have the same performance, it’s nonetheless impressive at just under 80% and shows that Optimism had the right intuition to expand their involvement in NFT-related initiatives.

II. Users

By the number of users interacting with NFTs vs Other transactions types, the difference is much smaller. In fact, there is even one week in early October where there were more users interacting with NFTs than with anything else. Over the last three months, there have been almost as many NFT users as for anything else, once again proving the popularity of digital assets on the Optimism network.

MoM we can see again NFTs increasing in popularity and doing so in a much more accelerated manner than for all other aspects of the L2.

Narrowing things down to just NFT users, we see a healthy amount of new users hopping on the NFT train. Considering the nature of many of the NFT campaigns however, it’s actually good to see that many of the transacting users are actually repeat (existing) users, pointing toward a successful onboarding following their initial interaction with one of the increasing number of NFT projects they can choose from.

III. Bridgooors

Remember what I was saying about free mints that won’t lead to a lot of sales? There are two solutions to that:

1. Community projects native to Optimism

2. Projects from the Ethereum Mainnet

The second option is technically difficult, but that did not stop the Optimism Foundation and Quix to build their own NFT bridge that users can use to send digital assets back and forth Optimism and the Ethereum Mainnet.

While there have been a lot of bridges functioning between the two networks for as long as the L2 itself, the launch of the NFT bridge proved to be extremely in demand. Over the observed period, we can see the Quix bridge occasionally having as many transactions as the rest of the bridges combined, despite being launched just a little over a month ago, on October 5. Since then, transactions on it represent almost a quarter of all bridge transactions.

And this success is not by the number of transactions either. In fact, it can be said it’s even more successful by the number of users, second only to the Optimism native bridge for this period.

With the bridge still being so new, it’s unsurprising that many of its users are new. However, despite its success, we don’t see a lot of recurrence for bridge users who mostly only bridge one NFT and then rarely come back over the following weeks.

So far there have been a lot of collections bridged from the Mainnet, but only a small percentage of their collection size has hit the L2. At the same time, we can’t yet see any of the largest collections crossing over the bridge and it is somewhat understandable. Bridges have been the victim of many hacks over time and the NFT community of Ethereum, despite the apearances, is not too keen to make any risky moves with their most valued NFTs.

In the limited time we can observe since launch, we see there’s been a lot of initial excitements to test the bridge but that faded off a little over the last week. But as time goes by, the Optimism NFT market develops and the Bridge continues proves its reliability, so we can expect more activity from users looking to prevent getting caught in the gas wars that plagued previous NFT cycles on the Mainnet.

Conclusions

• NFTs play an increasingly prominent role in the activity of the Optimism network by the number of transactions and users interacting with the tokens. Furthermore, NFT interactions have much greater MoM growth rates than for the rest of the ecosystem.

• Much of the growth in NFT interactions was fueled by the many onboarding campaigns ran by the Optimism Foundation and its partners that rewarded users with free mints.

• NFT as artwork, identity and rewards are not the only use cases users interacted with, and we can see a lot of activity around Uniswap v3 LP position NFTs. However, the activity around DeFi NFTs gradually slowed down over the last three months.

• The free mints system does not lead to a lot of secondary market activity but users continue to explore the ecosystem, leading them to eventually interact with native NFT collections and the rest of the projects that Optimism has to offer.

• Doubling down on the NFT use case of the network, the Quix NFT bridge proved itself to be an effective way of bringing over users from the Ethereum Mainnet and onboarding them to the L2.

• Optimism was right in identifying NFTs as an in-demand use case for blockchains that would be a lot more accessible on a fast, inexpensive network and we can expect this sector to continue to fuel growth on the L2 in the following period.

https://zrk5xm.xyz/

The current data set includes swaps executed on two Near DEXs: Ref Finance and Jumbo Swap. As more DEXs are launched and indexed in the FlipsideCrypto tables the dashboard is set up to include them also*.

*Due to an issue with the ez_dex_swaps table at the time of writing, an alternative route of parsing the transaction logs was used which should still capture any new exchange protocols as long as they follow a similar core logic. Alternatively the CTE responsible for the base swaps data can be easily replace with the curated data in the ez tables when a fix becomes available. KUDOS to TheLaughingMan for sharing the base query for extracting swaps data.

The default parameters, and the ones used for this report, are set to date_trunc=day and months=3 but they can be adjusted and applied by the user. All of the data and underlying queries can be further explored and interacted with in the live dashboard:

https://app.flipsidecrypto.com/dashboard/near-swap-outflows-grCtFu

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Swap Activity of $NEAR Pairs

Before jumping into the core issue of the report, $NEAR outflows, we should first have a look at the broader picture concerning DEX swaps where tokens are paired with $NEAR.

Over the last three months activity slowed down by the number of swaps and volume although there have occasionally been days when activity spiked back up. In total the 312k swaps executed so far generated a swap volume of $536M.

At the same time however the number of users making swaps oscillated more or less in a constant range and ends the observed time frame with daily swapper counts similar to the start of the period. In total, over 12k distinct users made a swap to or from $NEAR.

There was a constant stream of new swapping users over this period but they were only responsible for a tiny percentage of the overall activity. Furthermore, new users make fewer swaps and in lower volumes on average than existing users do. So while the new users certainly help maintain an active swapping activity around the token, much of it is being sustained by the efforts of long time Near swappers which over the long term might lead to a depletion of capital and result in a sharp drop in volume that will also have a negative impact in the value of $NEAR.

II. $NEAR Sold and Bought

So how much $NEAR is actually being moved back and forth by all this activity? Over 47.5M tokens worth $197M (using their value at the time of the swap). Much of this activity however has been on the sell side, resulting in a net loss of value for the token of $6M in the last 3 months. This isn’t necessarily a loss for the token overall as much of the value went into other tokens of the ecosystem and thus continue to generate more value for the Near ecosystem, which $NEAR’s value is more dependent on.

As we might have expected thanks to the data in the previous section, the amount of $NEAR in each swap, regardless of what side it sits on, has significantly decreased compared to what it was in early August at the start of the time frame.

Although amounts have been sliding downward on both sides, we see that actually there’s a bit more pressure on the sell side, where more swaps were made with larger $NEAR token amounts than on the buy side.

As a bonus takeaway, we can see there are also arbitrage swaps going on for the token, where the $NEAR token is being traded back and forth in the same transaction where multiple swaps are being executed inside of the transaction between multiple pools. While they’re not being made with extremely large amounts, they have swaps counts comparable to regular swaps in the <$100 range.

III. $NEAR Outflow

The $NEAR token has been swapped for a long list of tokens over the last three months, but for most of the time we can see just a handful of tokens making up most of the swap volume. Among them we can spot the usual suspects $USDC, $USDT, $USN (the algorithmic stablecoin of Near) and $WBTC. Their share of the daily swap volume has remained more or less constant throughout the observed period.

Next to these projects we can also spot a newcomer that was able to push its way into the top 5 daily tokens swapped TO, and that token is $SWEAT of Sweatcoin. We can see it pop up in the daily rank in early September shortly after its launch on the blockchain and it maintains a significant daily share of volume for the month. Although it still manages to come back up to the daily top 5 after September, that only happens sporadically.

Another token that has lost some of its prominence in the swap volume with $NEAR is $ETH. It’s not only a sign that less funds are being bridged from Ethereum to Near, but also that users would much rather swap their tokens to something that is more related to the Near ecosystem while on the Near blockchain.

Something that we could spot in the graphs above as well is that there is quite a bit of a difference between what tokens $NEAR is being swapped to when we rank them by swap value and by number of swaps.

Even if for the period there were more swaps from $NEAR to $USDC, around 19% of all swaps, they only make up 21% of the total value of the tokens swapped in this period. Instead, most of the $NEAR tokens were swapped to $USDT in a proportion of 43% of the $NEAR tokens swapped in this period.

Given the market conditions of the last months, it is not very surprising that a lot of the trading volume, even in the case of $NEAR swaps, goes to stablecoins. However, there certainly is sufficient interest for other projects’ tokens as well despite having a lot less volume. Some of the tokens that $NEAR was sold for most often in the last three months are $ETH, $WBTC, $REF, $SWEAT, $AURORA, $OCT and $USN.

Conclusions

• The number of swaps and swap volume with $NEAR have been declining over the last three months.

• There are still new users making swaps with the token but not in huge numbers. Furthermore, they swap less often and smaller amounts. The long-term lack of new capital in the market could negatively affect the value of the token.

• There’s been significantly more value being extracted from the token in the observed time frame resulting in a net loss of value for $NEAR worth $6M.

• Both by value and swap counts, the $NEAR token has mostly been swapped to a handful of tokens over the last three months. Despite the consistency of what tokens it was being swapped for, $SWEAT was able to break through and be one of the top 5 tokens for most of September.

• By value, stablecoins represent over 70% of the outflow, with just $USDT being responsible for a little over 43%.

• By swap count, stablecoins still make up a lot of the outflow but in a much smaller proportion. Instead we see a lot more diversity and interest in other projects native to the blockchain.

https://zrk5xm.xyz/

In this report we’re having a look at the first destination of users crossing over the bridge from Ethereum to Optimism and track how that has changed over time.

There are many bridges now that can be used to make the journey, but we will only include 4 of the most active: the Optimism native bridge, Hop, Stargate and the Quix NFT bridge. The first destination of users is determined by the first transaction executed by the same user following their successful bridge from the Ethereum Mainnet.

The primary time frame used for the analysis is 1 month wide, from the end of September to the end of October using a daily granularity. These two parameters can be adjusted in the dashboard using the month and date_trunc fields at the top of the page.

All of the visualizations and tables, as well as the underlying data and queries can be further explored and interacted with in the live dashboard:

https://app.flipsidecrypto.com/dashboard/op-bridger-destinations-kZFRLX

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Bridge Inflow to Optimism

Before we can dive into the destination of users, we should first have a quick look at what the bridging activity looks like.

The number of daily users and the transaction count have very close values, indicating that most users only cross the bridge once a day as we might have expected. Over the last month, those values started strong at around 2k a day, followed by a quick decrease to around 600 for a couple of weeks, but they both rose back up and hit over 4k on Oct 28.

Although all bridges have recovered some of their activity, most of the rebound can be attributed to the newest of them, the Quix NFT bridge. On some occasions, its volume is more than half of the daily bridging activity despite only being launched on Oct 10.

II. First Destination of Bridge Users

The identity of users destination relies on the dim_labels tables of FlipsideCrypto, which although very comprehensive, still lack labels on around 14% of the first destinations of the last month. Apart from that, we can see that just a handful of protocols are responsible for most of the first destination transactions, with varying shares of the daily activity over time.

Over the last month we can see a lot of protocols coming in and out of the top 10 daily destinations, while others constantly draw first interactions. The most successful protocol is by far Uniswap v3, with its router attracting close to a third of the first interactions of bridge users over the last month. However, it is not the only exchange people go to and we can spot others such as Matcha and Velodrome, as well as Slingshot and Curve occasionally.

The MoM change rate of many of the top destinations of the last month had considerable transactions increase compared to the previous month. In the case of Uniswap v3, it had 45% more first transactions than the month before, simply continuing an amazing growth streak that peaked a month ago with a 156% change rate compared to August.

One thing we can quickly spot from the chart is that many of the top attractions in October had their worst performance 3 months ago in July. For Hop, there were 86% less first transactions in that month compare to June.

While many of the top destinations have been active long enough to go through the bad and the good, some have only just been created a few months ago. One platform attracting a lot of first interactions is RabbitHole with two of its NFTs issued to its earn-and-learn community.

Just as we could conclude from the previous section, DEX protocols make up a large portion of the first destinations over the last month, with the rest of the pie being split between NFTs (category includes NFT contracts and NFT protocols such as marketplaces), DAPPs, DeFi and other Layer2 protocols like Ren, Synapse and ChainHop that connect the L2 to other networks.

When interpreting this type breakdown it is important to remember that there is a thin line between the types and they can change buckets based on their use cases. Furthermore, current categorization is dependent on the accuracy of labels which is not yet as reliable and comprehensive as for other chains with more resources dedicated in this direction such as the Ethereum Mainnet.

In the last month we can see the DEX, NFT and DAPP categories making large strides and growing the number of first transactions coming their way. Even at its current share and top positions for most of the time, the DEX category increased its first transaction count by 52%.

However, the greatest increase for the last month has been the NFT category with a 179% increase compared to October, where projects such as RabbitHole, Optimism Quests and Galxe leverage the fast and inexpensive minting process of the network to reward and engage users. Furthermore, the NFT sector is boosted by the efforts of Quix to bring over more collections and their communities to Optimism using its own NFT bridge.

Conclusions

• After a mid October slump, the bridging activity from Ethereum to Optimism partially recovered but it also got a big activity boost from the newly launched Quix NFT bridge.

• For most of the month DEXs were the main first destination for the majority of users, with the category representing around 40% of first transactions over the last month.

• Out of all DEXs, Uniswap v3 is by far the most popular. In October it continued to increase its popularity as a first destination and had 45% more first transactions than in September.

• Some of the most popular destinations in October were protocols centered around issuing NFTs to their members such as RabbitHole, Galxe and Optimism quests.

• The NFT category had the greatest MoM growth with 6k first transactions, a 179% increase compared to September.

https://zrk5xm.xyz/

The dashboard below contains all the graphs included in the report which can be further interacted with and explored. The default parameter values used are months = 1 and date_trunc = day but they can all be adjusted and experimented with using the parameter fields at the top of the dashboard.

https://app.flipsidecrypto.com/dashboard/optimism-de-xs-uniswap-v-3-velodrome-sushiswap-ul_F_k

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Transactions & Volume

Over the last month we can see that out of the three DEXs, Uniswap and Velodrome operate on a similar scale, while Sushiswap has considerably less activity.

Uniswap v3 and Velodrome closely resemble each other both by transaction counts and the overall trend they’re following. We can see the two having a decline in transactions in the middle of the observed period, but that quickly recovered and they both currently have activity levels similar to the start of the period. In total, Uniswap executed 700k transactions and Velodrome 454k over the last month.

Although Sushiswap seems like it is just getting started (it is also the last of the three to move to Optimism), this past month looks promising. It went from and average of 70-80 daily transactions to now over 160-170, doubling its activity, and continues to push even further on a well sustained uptrend. In total, Sushiswap executed 3.7k transactions in the last month.

On a weekly basis, we see Uniswap and Velodrome having the most activity at similar time intervals, mainly during weekdays, but not within regular hours. In the case of Sushiswap we see quite the opposite, having most of the activity on weekends.

Looking at swap volumes, we’re being told a similar story about their activity over the last month. However, while we’ve seen Velodrome not far behind Uniswap in terms of transactions, by volume they’re operating at completely different scales. On most days Uniswap has double the swap volume of Velodrome. In total, Uniswap had a volume of $650M and Velodrome just over half of that at $356M.

Sushiswap shows in this case as well that it continues its ascension, having started a strong upward trend in volume in the first half of October. Its daily average volume increased from just $8k to around $25k. Over the last month it had a swap volume of 494k.

All the differences in transactions and volume can once again be spotted by plotting the two dimensions in the scatter plot below, but we also gain a new perspective over the strong point of each.

Velodrome and Uniswap have had a very similar activity, but we see Velodrome executing more transactions in the <$1k range. From that point on, Uniswap stands out as the leader, which also helps to explain the difference in volume we’ve seen despite the similar transactions count.

Sushiswap finds itself in a difficult spot, competing for the <$1k range, but it’s still quite early to judge whether it will be squashed by a defeated competitor of the >$1k range or if its way will be cleared up by the other two pushing on to increase trade sized they can acommodate on their platforms.

II. Swappers

This is yet again a segment where Uniswap shows it’s been able to gain the most traction, constantly having swapper counts much higher than Velodrome and Sushiswap. However, we can see that this constant high level of swappers is something that’s only started to shape up during the observed month, with the 30d moving average at the start of the period sitting at much lower at about 4.5k. Nonetheless this is an impressive performance. Over 82k distinct users swapped on Uniswap in the last month.

Velodrome occasionally has swapper spikes hitting over 6k daily users, but that is a lot more inconsistent and oftentimes swapper counts sit under 3k. Over 40k distinct users swapped on Velodrome in the last month.

The increase in usage we’ve seen for Sushiswap in previous sections seems to be fueled by a steady increase in the number of users over the last month. This means that the growth it had in this period is not an overstretch of an existing user base, but a sustainable increase across the board.

Uniswap is very successful with users that swapped <$1k in the last month but it’s in very close competition with Velodrome for larger users.

Sushiswap on the other hand has not yet had users trading more than 30k during the observed period but it’s building itself up as a worthy competitor in the <$100 range.

III. Tokens & Pairs

Although all three DEXs have a very diverse list of tokens listed, in all cases it is just a handful of tokens driving almost all of the volume. Those tokens are mainly WETH, OP, USDC, DAI and USDC. Naturally, the pairs with the most volumes are combinations of these tokens.

It’s only on Velodrome where we see volumes being a bit more balanced between the top tokens, as opposed to Uniswap and Sushiswap where just WETH and USDC make up around 90% of the swap volumes. This means that although Uniswap seems to be in the lead by many aspects, it’s current success relies on just two or three assets, whereas Velodrome has a stronger footing across many projects, prepping the exchange for success whenever the Optimism ecosystem takes off.

Conclusions

• Uniswap v3 had the most transactions, volume and swappers over the last month. In many cases, its activity was double that of its closest competitor.

• Velodrome is setting itself up to challenge the supremacy of Uniswap and already is extremely competitive by the number of transactions that go through the platform, as well as the size of the users on the platform.

• Sushiswap although in its early days and far behind the other two, has had an extremely successful last month during which it more than doubled it transaction counts, swapping volumes and number of daily swappers.

• On all three exchanges most of the volume is driven by just a handful of tokens and pairs. The only one with a slightly more diversified and balanced split of volume is Velodrome, which puts it in a position to become the market leader on Optimism when more of the projects traded on it take off.

https://zrk5xm.xyz/

In this report we will have a look at the wash trading on both platforms and compare this activity over the last month to see whether either of them is more fertile ground for practicing the black art of boosting collection trading volumes.

Taking the Investopedia definition of wash trading:

Wash trading is a process whereby a trader buys and sells a [NFT] for the express purpose of feeding misleading information to the market. In some situations, wash trades are executed by a trader and a broker who are colluding with each other, and other times wash trades are executed by investors acting as both the buyer and the seller of the security.

In this report we are dealing with two types of marketplaces, each of them requiring different strategies in order to wash trade. For Hadeswap, the user always sells/buys to/from the collection pool, so there is no need for another address. They can simply sell, buy, repeat. For MagicEden, both a seller and a buyer account are needed to make a trade. Sometimes users try to obfuscate wash trading by transferring the NFT to other addresses or routing it through other marketplaces before ending up back in the initial wallet to repeat the cycle.

However, the end result of each method and the most certain way of identifying colluding users in the context of on-chain anonymity is by the fact that they each end up buying and selling the same mint more than once in a relatively short time frame.

In this report a default wash trade time interval of 1 day is used, meaning that repeat trades (sales/purchases) in the span of 24 hours from the previous transaction with the same mint by the same user address will be counted as being a wash trade.

The interval can be experimented with in the live dashboard by modifying the wash_days parameter.

All of the data and queries can further be explored and interacted with in the FlipsideCrypto dashboard below:

https://app.flipsidecrypto.com/dashboard/solana-nft-wash-trading-hadeswap-magic-eden-xY2Urd

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Washtrade Volume

The amount of wash trading on Magic Eden far exceeds that on Hadeswap. Over the last few weeks we can see average wash trading volumes of over $600k on ME and riding an upward trend since mid October. This current volume of wash trades oftentimes exceeds the entire trading volume going through Hadeswap. For its part, we see much lower wash trading volumes of under $5k over the last week and following a strong downtrend.

So if Hadeswap has 0% platform fees and 0% creator fees (royalties), why is it not the premiere platform to wash trade on? There are a few reasons.

First, it lacks the extremely large catalogue of collections MagicEden has so it naturally draws a lot fewer users (or potential victims).

Secondly, while those two fees are indeed set to 0% (for the time being), the platform is not particularly designed to facilitate wash trading or allow users to purchase at lower prices than anywhere else. Instead it is designed to maximize profitability for Liquidity Providers who can set their own swap fees (spreads) and a bonding curve for the price to follow. These LP set parameters often times result in a higher cost for users who exclusively trade on the platform.

Third, when ME users choose to pay 0% royalties, that amount is subtracted from the price of the item, leaving traders with just the 2% platform fee. This makes wash trading on ME more manageable and predictable in terms of cost, plus it benefits from a larger user base.

A direct volume comparison is not fair as HS is a recently launched platform and ME the long-established market leader.

Comparing the share of volume by its type, we see however that ME still has more of its daily volumes coming from wash trades. This got accentuated on October 15, the day it introduced optional royalties and when the platform had more than half of its volume marked as wash trading. Since then the share decreased a little, but without a doubt it contributed to the monthly wash trading ratio of 21% we can see in the pie chart.

The average value of wash traded NFTs has remained somewhat constant throughout the observed period, between $30 and $60.

Hadeswap on the other hand has very daily shares of wash trade volumes, oftentimes representing less than 1%. Since its launch almost a month ago on September 25, only 2.33% of its volume has been marked as wash trading.

The average value of wash traded NFTs has seen a lot of variability but seems to have been decreasing over time, currently in a range of $50 to $150.

II. Transactions

The transactions section of the dashboard tells a very similar story. MagicEden has a lot more wash trading on its platform by sheer size and most of the time the number of wash trading transactions alone is higher than the overall transaction count on Hadeswap.

But once again we see that wash trades make up a larger proportion of MagicEden’s activity, with almost a third of transaction being wash trades. In the case of Hadeswap, a little over 2.5% of the transactions since launch have been wash trades.

On average, 10 to 16 wash trades are made on Hadeswap every day over the last week and the trend line points downwards. On MagicEden there are around 20k wash trade transactions every day over the last week. This count does not seem to have changed too much following the Oct 15 optional royalties release.

III. Wash Traders

There are naturally some users who push wash trading to the limit and in the charts below we can see who the top wash trading users are based on their wash trade volume.

On Hadeswap, two accounts managed to surpass all other users in just 5 transactions where they managed to user the platform to trade mints back and forth with each other. Because both the sale and purchase of the mint were executed in the same transaction, the $31.5k volume is attributed to both addresses. The accounts were exclusively used for these 5 transactions.

For the rest of wash traders we see they weren’t created with the sole purpose to wash trade, but most of their activity and volume is nonetheless marked as such. Their activity is made up of regular interactions with the platform, unlike the unusual transactions executed by the top two addresses.

On MagicEden we see the top wash traders being responsible for up to 10 times more volume, with the first spot having generated over $444k wash trading volume with 390 transactions over the last month. The users here are split between being used primarily to wash trade or just casually doing it despite the large volumes.

Below we can see a distribution of wash traders based on the volume they have generated over the last month. Magic Eden wash traders are far more numerous and wash trade much greater volumes than those on Hadeswap.

IV. Wash Traded NFT Collections

The most wash traded collections on Hadeswap over the last month are Degenerate Ape Academy, followed by ABC and Critters Cult.

For Degen Apes, the wash trading volume represents almost 30% of the total volume they’ve had on the platform over the observed period, a lot higher than all the other projects in the top 10. Other collections with high wash trade volume share are Pawnshop Gnomies and FRAKT with 9.8% each, Netrunner with 8.5% and SoDead with 7%.

The most wash traded collections on MagicEden outsize again Hadeswap, with the top collections being Critters Club, y00ts and DeGods. Critters Club had a wash trading volume of close to $1M over the past month, but even so it represents just 15% of the total volume the collection had on the marketplace.

While most other collections in the top 10 have a similar share of volume, three collections stand out with almost all their volume being marked as wash trading. Those collections are NFTrees Solana with 92%, Copetown with 96% and Greedy Giraffes with close to 100% of the volume on ME being just wash trade.

What is even more shocking in the case of these three intensely wash traded collections is that they achieved these volumes using just a handful of NFTs out of the entire collection. NFTrees, a collection of 10k items, has a washtrading volume of $300k using just 622 distinct mints.

Conclusion

Hadeswap not only has less wash trading by volume and transactions, but they represent a smaller proportion of the overall activity on the platform and the trend continues to head downward. On MagicEden however, wash trade volume got a boost as soon as optional royalties were introduced on Oct 15. Even before that, the marketplace had a lot of wash trading going on and while transaction counts seem to slow down, wash trade volumes are holding up.

Another way they differ is by the type of users that wash trade and their budgets. Magic Eden wash traders are far more numerous and spend much more on wash trading.

The same difference in size can be observed when we look at the most wash traded collections. While the most wash traded collection on Hadeswap, Degenerate Ape Academy, barely goes over $60k in volume, the most wash traded collection on MagicEden, Critters Club, almost reached $1m.

Although we might be tempted to think that 0% fee platforms might be the most inviting for wash trading, there are more aspects that come into play such as spreads, liquidity and user base. Because wash trading is a short lived illusion, those who try it benefit from larger marketplaces with a diverse catalogue of collections, larger audience and preferably no additional fees. As it turns out, Magic Eden is just the place for that with over 90% of the market share on Solana by pretty much all metrics and with recently introduced optional royalties.

Edit: After a data refresh on Oct 24, new transactions were included in the solana.core.fact_nft_sales tables used for the Hadeswap transactions which resulted in considerable additional volume for the date of Oct 9. Most of the volume is associated with unlabeled/unknown collections but a brief analysis links many of the transactions to the LunarNFT project.

Although the volume and number of transactions are significant for that particular date, they do not have a big impact over the rest of the analysis and observations.

https://zrk5xm.xyz/

The observed time frame is of 90 days. For Terra Classic that means the last 90 days before the first blockchain halt on May 12 2022. For Terra 2.0 that means the last 90 days to the current date.

The default granularity we will be using is set to date_trunc = day, but it can be changed to week or month using the parameter field in the dashboard.

https://app.flipsidecrypto.com/dashboard/terras-recovery-ZalsQf

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Terra Population

Over the last three months, the daily number of users transacting on Terra 2.0 did not at any point even come close to the number of users Terra Classic had during its last 90 days. In total, Terra 2.0 had close to 70k distinct users active over the observed time frame, but that only represents around 5% of the 1.282M users that used Terra Classic over the same length of time.

This shows that despite Terra being praised by developers and users as being a great blockchain, the events of May 2022 resulted in a loss of trust for a huge share of the community and that has not yet been restored.

What stand out however is that two thirds of the addresses that have used Terra 2.0 over the observed time frame have also been using Terra Classic before its crash. While this can stand to show that there still are a handful of users who have remained loyal and still see the blockchain as viable, it also reveals that it’s been unable to attract a lot of new users ever since its speedy launch on May 28.

With the exception of the days of May 8 onward, when people were understandably trying to remove their assets off the chain, the average number of transacting users on Terra Classic ranged between 40k and 50k with a slight uptrend. That is far higher than the sub 2k range the average on Terra 2.0 has been in, with just a few exceptions.

Looking at the number of Weekly Active Users (WAU), the difference is even greater. While Terra Classic saw counts of over 13k consistently, Terra 2.0 is still far behind and only has a few hundred WAU every week. This means that Terra Classic users used to transact more often than Terra 2.0 users, which is not a big surprise considering the much smaller ecosystem users can interact with.

There is however a light of hope as the count has been consolidating slightly higher over the last few weeks at around 500 WAU.

Even at its height, Terra Classic would still be a attracting a lot more new users than Terra 2.0 does. Overall, in its last 90 days before the crash, less than a quarter of users had already made a transaction outside of the time frame. In the case of Terra 2.0, users are split between new and existing, showing once again that it has lower success in attracting new users to the chain.

II. Blockchain Activity

The number of transactions confirms once again that Terra 2.0 is still far behind its predecessor, with 644k transactions executed over the last 90 days, around 1% of the transactions on Terra Classic.

We can see however that a slight uptrend is forming in the number of transactions executed on the Terra 2.0 blockchain, although in earlier weeks things were going in the opposite direction. Surprisingly, the chain behaves more like a new chain in this regard, where it does have a small but loyal user base that uses it, yet its fate is not yet decided and activity can radically change course over short periods of time.

While most of the other indicators compare the quantity of either users or transactions, there is another aspect about the activity on both blockchains that has shifted.

The activity on Terra Classic was more evenly spread throughout the day, with higher average transaction counts usually during weekdays between 12:00 and 20:00 UTC and not as much during weekends. For Terra 2.0 however, a lot of the transactions are concentrated on Fridays between 10:00 and 16:00 UTC. For the rest of the weekdays activity also shifted earlier in the day but there is still not much activity during weekends.

Although it’s unclear why so much activity is concentrated on Fridays, the shift in activity to earlier time intervals suggests that activity shifter from a more heavily US-located user base, to one that could be located in Asian countries.

Conclusion

The Terra Classic blockchain outperforms in all aspects the current state of the Terra 2.0 blockchain. This applies to the number of users transacting, WAU, acquisition of new users, transaction counts and diversity of user base. Undoubtedly Terra has not been able to overcome the overall sentiment of users following the events of May 2022 that led to the collapse of a once thriving ecosystem.

Its speedy efforts to salvage anything that was still standing resulted in a small but active user base that migrated over from the original chain, but it is hard to tell how likely they are to remain active in such great numbers if the ecosystem does not engage more users and dapps to come transact on the blockchain.

There are a few signals that things could be moving upwards, but the trends we can spot are still very early and fragile. In many ways the Terra 2.0 behaves like a new chain, presenting both opportunity and risk for those who choose to come join in early.

https://zrk5xm.xyz/

The activity included in this report will only look at the activity of Weekly Active Users (WAU) during the weeks they were labeled as active. For an address to be considered as active, it must have made a transaction for at least 4 days of every week.

Only addresses making swaps, entering or exiting a liquidity pool are being included.

All the data and queries can be further inspected and explored in the live dashboard:

https://app.flipsidecrypto.com/dashboard/osmosis-active-users-O8uUga

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Weekly Active Users

After a rough month with WAU declining, last week’s users count of over 6.4k is again on the rise and in a similar range to the months of July and August. This represents a week over week increase of 38.5%.

For the last three months, we can see these Weekly Active Users being the most active during the middle of the week, on Tuesdays, Wednesdays and Thursday, during a narrow time interval between 17:00 and 20:00 UTC.

The majority of these users have generally made up to 12 transactions during the weeks they were active. There are some however that have over 21k transactions during a single week and we can be fairly certain the addresses in those range are actually bots.

II. Swap and LP Activity

Unsurprisingly, there are almost twice as many users making swaps than there are depositing or withdrawing liquidity from pools on any given week. For the last week, 2.7k distinct addresses have managed an LP position, while 6.2k distinct addresses swapped tokens.

On average an user who adds or removes liquidity from a pool did so between 7 and 8 times each week it was active. On the extremes, that count can go over 10 and under 2.

In the case of swaps there is a bit more variability but average and median swap counts per user per week have stayed in a similar range throughout the three months period observed below, despite having lower values at the 75th percentile. On average, WAU make between 7 and 9 swaps each week.

III. Flow of Funds

In this section we’re looking at the tokens transferred to Osmosis by the Weekly Active Users during the weeks they were active. Below we can see there are a lot of origin chains for the tokens transferred over the observed period, and volumes resemble the number of active users. However, there are just a few chains and tokens that make up most of the funds being brought over to Osmosis.

The largest origin chain by value throughout the last three months has been Cosmos, which naturally brought over a lot of its native token $ATOM.

It is surprising however that the second biggest origin chain by volume has been Axelar, a chain that was relatively recently launched and has been integrated with Osmosis in late September. In this case however it is not $AXL, the native token of the chain, being the most transferred but the $USDC that the network enables and is specifically designed for.

When segmented by week (left), Weekly Active Users make a transfer of tokens to Osmosis at a time interval between 0.5 and 1.3 days, effectively meaning they make transfers in consecutive days.

When we look at the number of days between transfers for active users over the entire period (right), the median number of days remains at 0, with an average time difference of 0.88 days (or 21 hours). There are nonetheless many other users who go to a time difference of up to 79.

Conclusions

• The number of WAU had a WoW change of 38.5% and seems to be pushing again to levels similar to the months of July and August.

• Most activity of users happens in the 17:00 - 20:00 UTC interval.

• The majority of users make up to 12 transactions each week.

• There are twice as many users making swaps than adjusting LP positions.

• Over 63% of the funds transferred to Osmosis come from the Cosmos blockchain through the $ATOM token.

https://zrk5xm.xyz/

In this report we will have a look at how sudoswap assigns new roles to participants, the new price considerations for buyers and sellers, as well as the impact it had on the royalties collected by projects.

With creator fees bypassed and sudoswap functioning as an AMM for NFTs, buyers and sellers only have to pay two fees:

1. Gas fee / network fee: Paid to the Ethereum blockchain to process the transaction and add it to the blockchain. The amount varies based on how busy the network is. Paid by the buyer on top of the price.

2. Platform fee: A flat 0.5% fee on the amount paid for any item sold on sudoswap. Deducted from the price of the item.

However, there is a third hidden fee that users are exposed to:

1. Spread / Swap fee: Set by the creator of each pool, it represents the difference between the buy and sell price quotes. The maximum swap fee is 90%.

All of the data we will look at in this report can be further interacted with and explored using the live dashboard below:

https://app.flipsidecrypto.com/dashboard/nft-trading-fees-sudoswap-RYiDhL

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Overview

Since late June, over 102k transactions were made on sudoswap with a total volume of $60M which cost traders close to $1M in fees.

Most of the activity and volume can be observed between the months of August and September, which is when all three indicators spike. However, the overall activity on the platform gradually to decreased ever since its peak in mid August and seems to be continuing its descending trend.

II. Fees Breakdown

Throughout the observed period, most of the fees users had to pay were going to the network miners/validators, while the flat 0.5% platform fee applied to all trades accounts for close to a third of all the fees.

This is a larger proportion than in all the other cases we’ve looked at, such as OpenSea, LooksRare and X2Y2. Once again, we can see that when users don’t have to pay a certain fee anymore, they are going to reallocate that amount to another fee. In this case they don’t have to pay royalties so perhaps the purchase price is lower, so they are willing to pay a little more on gas.

Having a closer look at the fees paid per transaction, we see that the gas fees are in a similar range to what we could see on other platforms. However, the platform fees are considerably lower, even compared to X2Y2 which has the same 0.5% fee on all trades.

This naturally means that the value of the transacted tokens is generally lower on sudoswap than on other platforms. And indeed, when we check the platform itself we see that not many of the top collections by market cap are listed, such as CryptoPunks, Art Blocks or Doodles. Even when large cap collections are listed, they generally don’t have a lot of liquidity provided (NFTs or tokens), such as BAYC, MAYC, Moonbirds or Cool Cats.

Compared to NFT marketplaces, it’s even more difficult for sudoswap to collect a lot of platform fees considering that the AMM model disregards traits and rarity and trades all items at the floor price.

Traders on sudoswap are most likely to buy or sell a token when the gas fees add up to 1% on top of the base price. When the gas cost goes beyond that percentage, we can see the number of transactions that occurred rapidly decreasing. Because the platform looks at all tokens as being the same, its likely that sudoswap traders do too, which removes some of the urgency to purchase a certain token regardless of gas fees.

III. Spreads vs. Royalties

The hidden fee. According to sudoswap, the price they are willing to sell a token with represents the floor. In practical terms users always buy the floor but can only sell below it. The difference between the buy and sell price quotes is the spread of the pool and appropriately labeled for liquidity providers as a swap fee.

So while regular marketplace sellers set a price with creator royalties taken into account, sudoswap liquidity providers can list at the same price but with a swap fee, effectively rerouting the royalties to themselves. This makes sudoswap an extremely profitable platform for liquidity providers, but strips NFTs of their creators and artistic attributes, turning them all into simple financial instruments.

Alright, regardless of how you feel about all this, let’s look how sudoswap spreads compare to creator fees (royalties). We’re going to use the collections being swapped on sudoswap and compare their default royalties on Opensea, LooksRare and X2Y2 to the average pool spread for each project on sudoswap.

What we can observe is that in many cases liquidity providers are setting higher spreads on sudoswap than the royalties asked by projects on the three marketplaces.

Each collection can have multiple pools created, each with its own parameters. On sudoswap we can see most pools being set with a spread between 0%-10%, the same range we would normally see for project royalties. But while royalties set beyond that are extremely rare, on sudoswap we see a lot of pools having 20%, 25% or 50% spreads, with some going up to the maximum share of 90%.

IV. Skipped Royalties

Using royalties percentage of collections on marketplaces and their trading volume on sudoswap, we can project the amount of royalties projects could expect to collect from the trading activity of their tokens.

Out of the three, OpenSea has the lowest amount of expected fees, but that is because many of the collections traded on sudoswap are either not listed or have not had any sales on the marketplace.

We can however see a lot of overlap with LooksRare and X2Y2, marketplaces that either allow buyers to pay “flexible royalties” or are notorious for enabling wash trading with their rewards/incentive programs. Either way, if the royalties of each marketplace would be respected by their users, we can see projects are actually missing out on tens of millions of dollars each week.

Across all three marketplaces, the project that missed out on the most royalties is Webaverse Genesis Pass with close to $300k, followed by DigiDaigaku with over $250k.

The rest of the list varies by marketplace, but we can see that many projects have missed out on tens or hundreds of thousands of dollars since June.

Conclusions

• After a mid August peak of activity and volume, sudoswap has been on a gradual downtrend which naturally reflected in the amount of fees users have paid over the same period.

• Most of the fees users are paying when buying or selling NFTs are gas fees, with the platform fees only accounting for a third of the total.

• Although gas fees are comparable to NFT marketplaces, the value of items traded through the platform is smaller, which helps to explain the gas/platform fee ratio.

• Although sudoswap sales bypass royalties, prices remain the same compared to NFT marketplaces where royalties are enabled. The difference created by this is instead covered by spreads/swap fees.

• Spread ultimately are not benefiting NFT buyers despite paying less fees, and neither does benefit NFT sellers who are forced to sell below the floor price. It does however benefit Liquidity Providers that now redirect to themselves what used to be a project’s royalties.

• Spreads set by LPs are often times greater than the royalties set by projects on NFT marketplaces.

• The 0% royalties trading on sudoswap deprives projects of potentially millions of dollars each week.

https://zrk5xm.xyz/

Having a few days of activity to explore already, let’s look at the projects and users traversing the bridge.

https://twitter.com/qx_app/status/1579926590821085185

The live dashboard and underlying queries can all be further explored in the dashboard below:

https://app.flipsidecrypto.com/dashboard/quix-optimism-nft-bridge-yk_hBl

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Overview

In its fourth* day after launch, we can see the bridge continuing its growth of activity and with plenty of time left of the day, it’s preparing to have its best day yet by both users and bridged NFTs.

Over this period, the 50 users sending their NFTs through this journey have experienced fees ranging between $2-$9 and waiting times of around 10 minutes with only slight variations.

*The first transaction was actually a few days earlier, on October 5, with the first NFT crossing the bridge being Robotos (ROBO) #7675.

https://qx.app/asset/0x34612b73660cC040A99740D4D0077C5E409799D4/7678

II. Collections

So far there have been tokens from 19 different collections bridged to Optimism. Many of these collections only have one token being sent over so far, but we can see some being sent over in droves.

Some of the collections leading the pack are:

• iNFT Assets by Alethea AI

• Consensys: TheMerge

• MEV Army

• Chain Runners

However, the collection with the most tokens sent over by far is Aiko Virtual (AIKO), with 75 tokens (or 0.64% of the collection) already on Optimism.

All of the bridged collections and a summary of their activity can be further explored in the live dashboard table of section II. Furthermore, these tables contain the NFT contracts on both the L1 Ethereum Mainnet and the L2 Optimism network.

III. Users

Still during its first week, it is not a surprise to see that most of the bridge users are new users, but it is good to see that an ever-expanding number of users are interacting with the bridge.

One key aspect here is whether users return to use the bridge after their first day. We can see a few users doing so during these days, but the activity continues to be led by new users. It is important to be aware though that it’s likely we will not see a lot of recurring activity since NFTs are in more limited supply than fungible tokens and certain utility tying them to the mainnet might be a temporary deterrent until all projects adjust to properly connect with the bridged items.

In terms of collections driving the activity, we see familiar projects once again, such as TheMerge, Aiko Virtual and MEV Army.

The most active user has already sent over 22 tokens, all from one collection, you guessed it, Aiko Virtual. However, there are several others sending multiple NFTs over the bridge, as well as some who have sent tokens from more than one collection.

Conclusions

• The bridge continues to increase in activity in its fourth day after the public announcement.

• The bridging transaction is inexpensive and relatively fast.

• Multiple addresses have already sent tokens from 19 different collections over the bridge and their activity continues to diversify.

• The bridge continues to attract an increasing number of new users, but is yet to see a lot of returning users.

https://zrk5xm.xyz/

In this report we will have a look at the crossover between the top 10 NFT collections by Market Capitalization and then fan out to explore their holder’s presence among the rest of the projects. In the process we’re hoping to gain a better understanding of the top performing collections, how tightly knit their communities are and their reach throughout the Optimism NFT world.

The collections we will be using for this analysis are the top 10 NFT collections based on their Market Cap. This will be calculated using the collection floor price at the time of publishing multiplied by the number of items in the collection.

Once we get past the crossover between these top 10 communities, we will be looking at all the other projects their users minted, purchased or held over the last 6 months.

All the data and underlying queries can be explored in the live dashboard below👇:

https://app.flipsidecrypto.com/dashboard/op-nft-communities-crossover-1N8-Nm

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Top Projects by Market Cap

The leading NFT project, with almost twice the market cap of the runner-up, is Optipunks, a 10k pfp derrivative of the OG NFT collection of the Ethereum mainnet, CryptoPunks. Other projects that have started off on Optimism and enjoy a top 10 market cat are Apetimism, Bored Town and Motorheadz.

Many of the other collections we see in this ranking are related to Optimism free mints and rewards for being active network participants. Because they’re mostly awarded for surpassing certain activity thresholds on the network, we can see they generally have a much higher count of holders than the other projects.

II. Holders Crossover Between the Top 10 Projects

The disparity of holders between projects also distorts the number of crossover holders in each collection. As many of those collections are awarded for being active, and some specifically for actively trading NFTs, there is no surprise that we have a lot of their holders crossing over and owning an item from at least one other top 10 projects.

In the case of the reward NFTs, the most common crossover bin holders fit in is 1. For the other projects, like Optipunk, Apetimism, Bored Town and Motorheadz, although they have fewer members, more of them own 2 or more other projects from the top 10.

Plotting the crossover of members in a scatterplot we can better visualize which communities have greater overlap and how they compare among each other. As expected, we can see that in most cases projects have a lot of members overlap with the reward projects, while community projects rank lower in terms of crossover.

One thing standing out is the crossover percentage of OP Orcas holders with Early Optimists. Over 70% of the OP Orcas holders, wallets that have spent 1 ETH on Quixotic, are among the 36k first traders of the marketplace.

Similarly, 65% of the OP Orcas holders have at least one OP Quest NFT, rewarded for completing various activities across the Optimism ecosystem.

III. Projects Outreach: Minting Participation

The claiming process of the rewards NFTs we’ve seen already is actually a minting event. Therefore it’s unsurprising that many of the top projects holders have participated in the minting of at least one other project. In fact, when we put holders into mint count bins, we can see that most of them only minted one other project, while the rest fall in the higher bin of 1-10.

However, there are two collections that stand out with a large percentage of their holders, around 80%, participating in minting events. Those two are Motorheadz and OP Orcas.

IV. Projects Outreach: Buy-In Signal

Here we’re going to look at the purchases made by holders of the top 10 projects. Furthermore, we will check whether the mass buy-in signal coming from holders correlates with a higher floor price multiplier in the present compared to the price at the time of their purchase.

As a buy-in signal we will consider the first day when the holders of a top 10 project decide to purchase the NFTs of another collection. The proportion of project holders making the same move on the same date represents the signal strength in this case. Then, the floor price at the time of the signal is compared to the current floor price to decide whether the buy-in signal led to a POSITIVE or a NEGATIVE outcome.

In the first plot we can see that some of the greatest price multipliers were achieved when only a small proportion of the holders of a project buy-in into a collection, whereas when many know about the opportunity they were still able to achieve great results but only a lot less often than when they failed. This can be more clearly seen in the second scatterplot that color codes signals based on the outcome.

All of the top 10 projects and their holders have a buy-in signal success rate under 50%, with some of the worst success rates registered by OP Delegatoors and OP Quest holders. This is also perhaps because they are more likely to accommodate less experienced NFT traders since their initial distribution is specifically aimed at incentivising new users.

Simulating a scenario in which we purchase one NFT of each collection the top 10 collections holders did at the time of the signals we’ve explored above, we can check whether blindly following their moves could prove to be beneficial over the long term.

Although we’ve already seen that most of their signals had a negative outcome, it is still possible that the successful trades redeem all their mistakes and it’s certainly something that happens in other cases. In this situation however, the profitable signals were not sufficient to lift our scenario from under the water except for a few brief periods of time.

V. Diamond Hands

With all the minting and buying we’ve seen, it’s good to ask what are the holders doing with all the NFTs? Do they sell them? And if so, how long do they hold them before doing it?

There’s no significant difference between NFTs minted or purchased. In most cases, they’re never sold. When they are sold, it most often happens less than a month after it’s been acquired.

Conclusions

• The leading NFT project by market cap is Optipunks, a CryptoPunks inspired 10k pfp collection. Many of the other top 10 projects are distributed as free mints for active Optimism network participants.

• Most crossover can be observed between rewards collections, indicating that the campaigns are successful and engage users to interact with more of the ecosystem.

• The collections with the most active holders in minting events are Motorheadz and OP Orcas. Across the top 10 collections, the majority of holders participated in just one minting event.

• Holders of rewards projects have generated some of the most unsuccessful buy-in signals for other collections. However, all of the top 10 collections have success rates under 50% and following their holders’ buy-in signal did not prove to be a profit generating strategy over the long term.

• After having minted or bought an NFT, the holders of the top 10 collections have generally kept them and never sold. When they did sold, they did so most often in less than 1 month after acquiring them.

https://zrk5xm.xyz/

On Oct 7, 50 CryptoPunks officially traveled through the Wormhole bringing the OG NFT collection from Ethereum to Solana. In this report we will look at this exciting step in the direction of a cross-chain NFT universe and how it was accomplished.

https://twitter.com/wormholedpunks/status/1578353611469266947

I. The PUNKS

ID: 794, 880, 927, 983, 1561, 1776, 1803, 2055, 2172, 2210, 2397, 2582, 2679, 2686, 3376, 3470, 3802, 3842, 3950, 4014, 4197, 4286, 4416, 4443, 4454, 5043, 5380, 5570, 5904, 6259, 6560, 6641, 7148, 7392, 7408, 7454, 7650, 7758, 7824, 7857, 8034, 8167, 8591, 8653, 9041, 9157, 9533, 9828, 9857, 9958

Each of the CryptoPunks listed above were first wrapped into a Wrapped CryptoPunk to change their format from ERC-20 to ERC-721 so they can preserve their metadata and be compatible with the Wormhole Portal. All of the Punks were sent consecutively to Solana over the course of 1.5 hours and spending a total of just $68 on gas.

To commemorate the journey, an NFT was minted on Ethereum displaying the brave travellers:

https://rarible.com/token/0x87a6f25a05f57f0a4f06844eebd9fb1921da3832:30487125950840462775623003956441361625052787996030445638104789154183020680261?tab=overview

On their arrival, each WPUNK was minted using Metaplex and they now all sit in the 2Hr3qdi5VpzBhBNtt3nmbpxFtD7Zirr4Mw9cTt6reWy8 wallet. Although since then there has been no movement, the Twitter page behind this says they will be traded on the recently launched Hadeswap NFT AMM.

*The full list of WPUNK mints on Solana can be found in the Appendix.

II. Captain of the Ship

There is no one currently taking credit for this action publicly, but by checking the origin of the PUNKS and trading history we can at least come closer to the groups behind this.

First, all NFTs were freshly wrapped and then wormholed by the same address: 0x505d79c7379ee65b6c2d6d18a0e7ab901b00756c. This address currently has an ENS domain registered as sos1usd.eth. Using its transaction history and OpenSea account, we can trace the address back to the @sos1usd3 handle on Twitter.

The account is not very active and does not have any clear affiliation with any project, besides rocking a PudgyPenguin profile picture. More on that in a minute.

sos1usd.eth purchased 41 of the PUNKS directly off the market at an average price of $198,231 per NFT. Most of them were purchased in January, February and March of 2022, with the most recent one being purchased on June 14.

The remaining 9 PUNKS were transferred to sos1usd.eth from a different address. Before the transfer, these were purchased off the market at an average price of $332,423 per NFT in the second half of 2021 and one in January of 2022.

The sender is 0x8c0d2B62F133Db265EC8554282eE60EcA0Fd5a9E with the ENS domain 9x9x9.eth which we can trace back to the @9x9x9eth handle on Twitter, a core member of @The_OpenDAO, an organisation looking to create “a digital native community centered around leveling the playing field for both creators and collectors” and having as a massive milestone on their roadmap the launch of an NFT AMM.

As it happens, @9x9x9eth is the alt account of @HGE.SOL, the person behind Hadeswap. All this simply reveals that the whole trip is most likely a marketing stunt ran by @HGE.SOL using his own PUNKS to generate buzz around Hadeswap and entice the Ethereum folks to make the same journey themselves, if not with their own NFTs, at least with token liquidity for the chain.

Conclusions

• The 50 PUNKS had to be Wrapped and then Wormholed to Solana.

• On arrival the WPUNK NFTs were minted using Metaplex.

• They have not been deposited into Hadeswap yet or moved from the wallet.

• The original PUNKS were purchased by 2 alt accounts of @HGE.SOL throughout late 2021 and early 2022.

Bonus Fact:

• The first CryptoPunk to cross the Wormhole bridge is PUNK #9326 almost one year ago, on October 21, 2021. 4uU8r6LR8FNMvxQLZMdYjLFrBL5M6wPtjxpYZhnRcy8L

Appendix

• Wormhole Transactions from Ethereum to Solana

• Solana MINTS of bridged WPUNK

• Market buys of 41 PUNKS by sos1usd

• Market buys of 9 PUNKS by 9x9x9x

• Transfers from 9x9x9.eth to sos1usd.eth

• CryptoPunks wrapping transactions

https://zrk5xm.xyz/

In this report we will have a closer look at the fees paid while trading on the X2Y2 marketplace and what impact does the Flexible Royalties feature have on the fees creators would expect to collect.

While it has its quirks, the platform functions like any other one for the most part and traders have to pay the following fees:

1. Gas fee / network fee: Paid to the Ethereum blockchain to process the transaction and add it to the blockchain. The amount varies based on how busy the network is. Paid by the buyer on top of the price.

2. Platform fee: A flat 0.5% fee on the amount paid for any item sold on X2Y2. Deducted from the price of the item. All of the fees are charged in WETH and then redistributed to stakers of $X2Y2.

3. Creator fee / royalties: Each project is able to set a unique creator fee percentage on collections listed. Deducted from the price of the item. Here is where the Flexible Royalties kick in, a feature that allows users to select 1 of 3 levels to pay: 100% (default), 50% or 0% of royalties.

• The platform also allows users to make private transactions where the seller chooses a specific buyer and they pay 0% creator fees and 0% platform fees by default. Private sales are not included in the report.

The data can be explored more closely using the live dashboard below 👇:

https://app.flipsidecrypto.com/dashboard/nft-trading-fees-x-2-y-2-gTun-O

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Overview

As we could expect, the trading volume took a massive dive over the last couple of months, dragging the amount of generated fees along with it. However, the number of transactions did not have the same fate, and it even seems to sit on a slight uptrend, although very inconsistent.

Over the last six months the platform executed over 640k transactions worth over $3.1B and generated close to $35M in fees split between miners/validators, the platform and the creators.

II. Fees Breakdown

Throughout the observed 6 months traders paid a cumulative $15M in platform fees, $14M in gas fees and just a little over $5M in creator fees. As we know that the platform fee represents only 0.5% of the price of any item sold, we can assume that this incredible imbalance is due to collections with a 0% creator fee or trades where buyers chose to pay none of the royalties through the Flexible Royalties feature.

If we look a little further into the size of trades being execute, we can see that this is indeed the case, with a median creator fee value of $0 over the entire period.

We can dig a bit deeper still and we can see that the distribution of trades based on the creator fees paid is by far the most common transaction type. Besides this category, we can spot trades being made where users still choose to pay up to 10% in royalties, but they have considerably less transactions.

Moving on to gas fees, buyers are most likely to make purchase when it adds between 1% to 3% on top of the base price, with transactions rapidly decreasing for values above that. In the case of OpenSea and LooksRare we could see a more linear decrease in the correlation between gas fees and transaction count, but on X2Y2 this only accelerates past the 3% point. This is perhaps a result of the creator fees that they can bypass. But if that is the case, it also reveals that buyers are still willing to spend the same amount to make a purchase, but they just spend it on a different fee.

Despite having a lot of activity concentrated around 0% creator fees trades, there are still many projects that receive their royalties.

When it comes to the platform fees however, we see that only a handful of projects generate most of the platform fees. Because of the 0% creator fee and trading rewards combination, X2Y2 is oftentimes a place of high volume wash trading from users trying to game the system and they focus on trading projects with the highest trading rewards based on the platform criteria for awarding them.

III. Fees Redistribution

The $X2Y2 token was distributed based on the allocation split detailed in their tokenomics documentation. While some of it was split between different groups that helped bootstrap its launch, 65% of the total supply was allocated as staking rewards and continue to be distributed to this day.

Out of the total circulating supply we can see that almost 40% of the tokens are currently in the staking contract. These tokens along with the Presale tokens and the two vesting contracts for the team and development are eligible to receive the daily accumulated platform fees on X2Y2. In total, they make up a little over 54% of the current supply.

While over this entire period the amount of tokens that receive rewards continued to increase, we’ve already seen that the platform fees declined abruptly after their peak in July. This way, a user staking 10k $X2Y2 went from earning $26 (0.0097 $WETH) weekly at the peak in May to earning just around $5 (0.0043 $WETH) over recent weeks.

This change in the organic yield for token stakers makes participation a lot less attractive and puts the sustainability of the program in question once the bonus tokens program ends.

IV. Flexible Royalties

Ah yes, the user’s choice. Before we can look at what creators are actually receiving, let’s first have a look at the distribution of collections traded on X2Y2 based on the creator fees set by the projects.

The vast majority of projects have a default creator fee of 0%, bringing the overall platform average at just 0.5%. When we exclude that bin, the distribution is a lot closer to what we would see on a marketplace like OpenSea, but otherwise the platform is definitely the place for 0% creator fee projects to go to.

Alright, but because 0% royalty projects don’t generate creator fees anyway, they will be excluded from this point on.

Below we can see the trading activity and volume on the marketplace based on the amount of the royalties users choose to pay when making a purchase. Although they have three options to choose from, we can see that the 50% of royalties option is barely ever selected, with buyers choosing to either pay it in full or not at all.

Most of the trades and volume over the last 6 months comes from trades where users choose to pay 0% of creator fees and that only slightly changed over the last few weeks.

Because so much of the trades were made with no royalties paid, creators missed out on a lot of fees they would have normally collected from this activity. Although the difference between what creators would expect to collect and the actual amount became a lot smaller, below we can see that the amount expected for 100% of the royalties is over 9 times greater than what was actually paid by users.

All the while X2Y2 continues to collect the 0.5% platform fee on all sales based on the price of the item with 100% of the creator fee regardless of the Flexible Royalties user choice.

Conclusions

• Despite having a steady transaction count throughout the observed period, the platform faces the same struggle of dwindling volumes over the recent weeks. The decrease in volume dragged down the generated fees along with it.

• Most of the fees users paid trading on X2Y2 were either platform or gas fees. Combining the trading rewards program with the option to avoid royalties resulted in most transactions paying 0% in creator fees.

• Because users save on creator fees, they are willing to spend the saved amount on slightly higher gas fees instead if necessary.

• Most of the platform fees are generated by a handful of projects with 0% creator fees.

• The platform fees collected daily are being redistributed as rewards to 54% of the $X2Y2 token supply, currently being either staked or sitting in vesting contracts.

• While the fee receiving token supply continues to increase, the actual fees continue to decrease, making the rewards program less attractive and facing it with an existential threat once the bonus $X2Y2 rewards run out.

• Most of the collections listed on the marketplace have a default creator fee of 0%.

• Even for collections that have a creator fee higher than 0% we can see a lot of activity and volume being generated in transactions where users chose to pay no royalties using the Flexible Royalties option.

• The amount of royalties expected to be collected by creators is 9 times greater than the actual amount paid by traders over the course of the last six months.

https://zrk5xm.xyz/

https://app.flipsidecrypto.com/dashboard/axl-axelar-osmosis-pool-activity-OSokPQ

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Pool Actions: Deposits and Withdrawals

Shortly after the creation of the pool we can see activity starting to pick up. During the first hour we can see 8 actions being made in the pool, adding a net amount of 1.29M $AXL and 560k $OSMO. Over the following hours the asset volumes are considerably lower but there are a lot more actions being made, pointing to smaller liquidity providers starting to join the pool.

Although volumes decrease significantly, they never cross into a negative zone, meaning that liquidity continues to flow into the pool.

This is being confirmed when we look at all the actions being made with each asset of the pool and there have only been a couple of withdrawals made over the last 24 hours.

As another layer to the activity and volumes we’ve seen previously, we can now look at the amount of LP tokens minted by each provider for the assets they provided. Almost 90% of all the liquidity comes from just one address out of the 200 that have joined the pool so far, with all others having only thin slices at most.

II. Swaps: AXL Trading on Osmosis

Osmosis enables users to swap assets that don’t have a pool of their own, so this section will include swaps that might interact with other pools before completion and is not limited to just $AXL/$OSMO swaps.

Just as in the case of pool actions, we can see the most trading activity closely after the creation of the pool. With the volumes and activity winding down in a similar way to pool actions, we can assume some of the swaps were made in order to obtain the $AXL needed to become a liquidity provider.

Not only volumes dropped, but so did the size of each individual swap. The downward trend is likely to continue in the short term as the launch hype cools off, but as with any newly launched asset, it is also very sensible to news and that can boost overall activity, volume and size.

There is no particular preference for a trade size, but we can see most of the amounts swapped in are worth under $100, with the swaps counts quickly decreasing at greater values. The token being traded in does not correlate with volume or frequency over the observed time frame.

Most of the volume is being made by trading $OSMO for $AXL as we might expect. There are many other tokens being swapped to/from $AXL from the #812 pool, but the only other one making significant volumes is $ATOM. The full list of assets being swapped can be further explored in the live dashboard.

tl;dr

The Osmosis pool quickly became active and had much of its current liquidity deposited in the first hours after its creation. Over the following hours we could see more but smaller providers joining in and swapping activity following along on a similar curve.

Since launch, over 1.74M $AXL and 0.81M $OSMO were added to the Osmosis pool. However, much of it belongs to just one provider while all other addresses share a little over 10% of the total liquidity.

Although current activity is significantly lower than what the early hours were signaling towards, liquidity is not yet leaving the pool and there have only been a couple of withdrawals in the last 24 hours.

So far, the total swapping volume of the pool sits at $1.3M. Taking advantage of the Osmosis capabilities, traders are not limited to swapping just the assets of the pool. While there have been many tokens swapped for/to $AXL, the main counterpart remains $OSMO, but we can also see significant volumes being made with $ATOM.

https://zrk5xm.xyz/

For the most part, LooksRare functions as a regular NFT marketplace on the Ethereum blockchain. On every trade there are three fees users have to pay:

1. Gas fee / network fee: Paid to the Ethereum blockchain to process the transaction and add it to the blockchain. The amount varies based on how busy the network is. Paid by the buyer on top of the price.

2. Platform fee: A flat 2% fee on the amount paid for any item sold on LooksRare. Deducted from the price of the item.

3. Creator fee / royalties: Each project is able to set a unique creator fee percentage on collections listed. Deducted from the price of the item.

The difference however comes from what happens with the collected platform fees. To incentivize usage and boost retention rates, LooksRare redistributes 100% of the platform fees to the stakers of its own $LOOKS token. The amount of $WETH distributed to each staker is based on the platform fees generated over the last 24 hours and proportional to the amount of tokens staked at the date.

*In addition to $WETH, the marketplace boosts rewards with additional $LOOKS token emissions based on a predetermined schedule. We will only look at the redistribution of platform fees in this report.

The data can be explored more closely using the live dashboard below 👇:

https://app.flipsidecrypto.com/dashboard/nft-trading-fees-looks-rare-1pwPjb

☝️ The dashboard can be updated on-demand by pressing the refresh button 🔄 in the top right corner of the page.

I. Overview

All of the fees mentioned above are here bundled under the term Trading Fees. The 90.5k transaction executed over the last 6 months, trading assets of close to $3B, traders paid a cumulative $81.8M in fees.

We can see that all three indices plunged to significantly lower levels after their high in late March. In other cases we’ve seen a similar decrease in trading fees as well as in trading volume, which can be attributed to the broader downturn of cryptocurrency prices that most projects are denominated into. However, in the case of LooksRare, transaction counts have also been on a continuous downturn ever since May and have not yet regained upward momentum. This puts the marketplace in a position of not only dealing with external factors but also with attracting and retaining users on both side of the trade.

II. Fees Breakdown

Over $4.2M paid in gas fees by buyers to the blockchain, and $17M in royalties collected by creators, but by far the largest amount and with the most significant share of total fees are those paid to the platform, amounting to just under $60M over the last 6 months.

The all-dreaded gas fees to the Ethereum network have only represented a little over 5% of all the fees paid in the observed time frame, while creator fees were just under 22%. The unbalanced share of fees is not due to exorbitant platform fees as we might naively think since in this case they charge a flat 2%, lower than on OpenSea, on the price of any sold item. Therefore what this points to (and we will verify later in the report) is that many of the collections traded on the platform have creator fees set lower than the regular 10% and perhaps even 0%.

Below we can see the size of the fees paid over time and their aggregated statistics. This way we can confirm that lower fee volumes are not just the result of less trades, but the values of the traded items also decreased since earlier this year.

What else we can observe from this is the divide between the average and median values in the case of creator and platform fees. This points to an uneven distribution in the value of traded collections, where there are either extremely large (and LooksRare famously sells BAYC, MAYC and other large cap collections) or they are extremely small. In either case, the maximum values still register higher values, indicating that the marketplace itself does not yet struggle with bringing together sellers and buyers for expensive items.

Let’s start to dig into the relationship between fees and trades being made.

First, creator fees. As expected, most of the sales are made with items that have a creator fee set at 10% or lower, with anything over that rarely registering any activity. But while sales on OpenSea would primarily happen closely around the 10% mark, on LooksRare we can see a lot of them being made for items with lower royalties and even 0%.

This plays into the dynamic introduced by the platform fees redistribution program that given the right circumstances can make traders profit on that alone. Because of this, there were many discussions around wash trading and LooksRare had to make adjustments to its program to ensure that it is very unlikely for wash traders to profit.

There have been a fair amount of trades that appear to be made for the sole purpose of farming LOOKS trading rewards, notably on collections with zero royalties. We’re confident that with time and enough volume it would become unprofitable to trade this way, but scrapping the limits and open up rewards for all is one way to prohibit that kind of activity even sooner. Source

Then there are gas fees. Because there is nothing to earn back from transaction fees, we see a normal preference of buyers to make a purchase when the gas fees add up to 10% to the price of an NFT. Just as in other cases though, buyers are still willing to pay a lot of gas for a highly sought-after item, which can sometime represent multiple times the base price.

Creators are aware of the user preference when it comes to the amount of royalties to pay on an item, and we can see that the vast majority of collections have a creator fee set between 0% and 10%. However, as we could guess earlier, the collections traded on LooksRare have unusually low creator fees and many of them fit in the 0% category.

Looking at the collections that generate both creator and platform fees, we can observe that the marketplace heavily relies on just a handful of projects. The low number of collections being traded and the discrepancy between their sizes is apparent again when looking at the share of creator fees collected by just the top 10 collections.

On the other hand, we can see the top 10 platform fees generators being responsible for almost 90% of all the trading fees, and therefore are responsible for the sustainability of the entire $LOOKS value proposition.

III. Fees Redistribution

Here is where LooksRare changes its approach compared to traditional marketplaces like OpenSea. Instead of directly pocketing the platform fees generated through trading, they redistribute 100% of it as $WETH rewards to users who either:

• Stake their $LOOKS

• Were distributed $LOOKS and have fees sharing enabled

In the second category we’re looking at the Team Vesting wallet, Treasury Vesting wallet, and a Private Sale wallet. All of these tokens are more or less locked for a certain period of time as outlined in the $LOOKS Tokenomics and Allocation announcement.

Below we can have a closer look at this allocation and understand how much each wallet weights in the rewards program. With the current amounts those wallets hold, a little over 80% of all $LOOKS is eligible to receive the platform fees redistribution.

Alright, so let’s look at what you can get for your $LOOKS. An immediate observation is that while we’ve seen already that the amount of fees to be redistributed continued to decrease over the last few months, the amount of tokens eligible to receive the rewards gradually increased. This naturally doubled the pressure on the rewards program and we can see the weekly rewards per 10k staked $LOOKS going from a high of almost 0.09 WETH ($300) in late March, to just 0.0043 WETH ($5.7) in late September.

Conclusions

• Trading fees generate a sizeable but unsteady income stream for the involved parties. Because volumes can be unpredictable, the platform and creators might be incentivized to keep fees higher to account for periods of low activity.

• Most of the fees paid on LooksRare over the last 6 months have been platform fees, with creators and gas fees representing a little over a quarter of them combined. While the gas fees cannot be influenced too much by the platform itself, the low share of creator fees is due to collections’ preference for low to 0% fees.

• The low fees preference can be attributed to the platform fees redistribution program through which $LOOKS stakers receive $WETH rewards.

• Most of the platform fees are generated by 0% creator fees collections and just a handful of them are responsible for almost 90% of them. This creates a lot of risk for the rewards program and the $LOOKS economics as their main funding source is not very diverse.

• A little over 80% of the $LOOKS supply is eligible to receive the platform fees rewards.

• While the token supply continued to increase over the observed period, the accumulated platform fees continued to decrease, creating a double impact on the amount of rewards distributed per staked $LOOKS.

• Although the system is meant to relieve some of the costs associated with NFT trading and reward loyal users, it does not fix all the struggles of creating a successful marketplace with active traders and a wide selection of projects.

https://zrk5xm.xyz/