Data as of Aug 16, 2026 · Based on 291 AI responses from ChatGPT Search and Google AI Mode · See how Parse measures this
Best single starting tool: 
L2BEATBrands AI recommends here
Best when you need a free, cross-chain view of TVL, fees, and protocol revenue to compare liquidity and ecosystem growth; not a replacement for bespoke SQL dashboards or labeled wallet flows.
Best for treating protocols like companies — revenue, fees, and price-to-sales comparisons — when you want standardized financial metrics; it focuses on financials, not raw on‑chain user queries.
Best when you need bespoke, community-built SQL dashboards to track unique depositors, bridge netflows, or retention — excellent for custom metrics but requires query skills or community scripts.
Best for Layer‑2 decisions: compares TVL, security models, fees, and tech stacks to evaluate L2 risk and maturity; it’s L2‑focused and won’t replace cross‑chain TVL aggregators or financial comparators.
DeFiLlamaSource | Citation share |
|---|---|
 Measuring growth in crypto: What’s different, what matters, and what needs to be adapted - a16z cryptohttps://a16zcrypto.com/posts/article/measuring-growth-in-crypto/ | 3.3% |
 Crypto Fundamental Data On altFINS: Identifying Projects with Real Traction - altFINShttps://altfins.com/knowledge-base/fundamentals-filters-on-altfins/ | 2.9% |
 What is fundamental analysis in crypto and stocks? Definition, approach & use caseshttps://www.cointracker.io/learn/fundamental-analysis | 2.7% |
 20 Popular Blockchain Analytics Tools and Companieshttps://coinmarketcap.com/academy/article/20-popular-blockchain-analytics-tools-and-companies | 2.6% |
Metrics | Token Terminalhttps://tokenterminal.com/explorer/metrics | 2.0% |
 TVL, TPS, Token unlock, revenue… key blockchain metrics ...https://coinshares.com/us/insights/knowledge/tvl-tps-token-unlock-revenue-key-blockchain-metrics-you-need-to-know/ | 1.9% |
 Analytics Hub | AltPathshttps://altpaths.io/crypto-education/fundamental-analysis | 1.6% |
 Top 10 On-Chain Analysis Tools for Crypto Traders: Free List for 2026https://bingx.com/en/learn/article/what-are-the-top-on-chain-analysis-tools-for-crypto-traders | 1.4% |
 10 Best Crypto Analysis Tools | Koinlyhttps://koinly.io/blog/crypto-analysis-tools/ | 1.2% |
 Six Fundamental Metrics to Evaluate DeFi Assetshttps://bitwiseinvestments.com/crypto-market-insights/six-fundamental-metrics-to-evaluate-defi-assets | 1.1% |
For a long-term L1/L2 investment, I’d treat TVL, revenue, and active users as three pieces of a larger fundamental picture—not as standalone buy signals.
The framework I’d use is:
Economic activity → users → capital → fees/revenue → token value capture → valuation
| Metric | What it tells you | What I look for |
|---|---|---|
| Active users / addresses | Is there real usage? | Persistent growth, not one-off spikes |
| Fees | What users actually pay | Growing fees without relying entirely on incentives |
| Revenue / tokenholder revenue | How much economic value reaches the protocol/token | Revenue growth + credible value accrual |
| TVL | Capital committed to the ecosystem | Sticky TVL, ideally diversified across apps |
| Stablecoin supply | Economic liquidity available on-chain | Sustained growth |
| DEX volume | Trading/economic activity | High volume relative to valuation |
| Transactions | Network utilization | Growth accompanied by meaningful users |
| Developers | Future ecosystem/product pipeline | Sustained core + ecosystem development |
| Token supply/inflation | Dilution | Low/declining net issuance |
| FDV / market cap | What you're paying | Cheap relative to fundamentals and peers |
One important distinction: TVL is not revenue. DeFiLlama defines TVL as the value of assets held in protocols, while fees are what users pay and revenue is the portion retained by the protocol rather than distributed to liquidity providers.
TVL is useful, but it can be misleading.
For example, a chain could have $10B TVL because of heavily incentivized liquidity, while another has $3B TVL generating dramatically more organic activity and fees.
I'd therefore examine:
TVL → stablecoin TVL → TVL growth → fees/TVL → users/TVL
That tells you whether the capital is actually being used.
A particularly interesting signal is TVL per active user. A huge number can mean wealthy/high-value users—or simply mercenary capital. You need to investigate which.
Don't blindly use DAU.
A chain can manufacture millions of transactions with bots, arbitrage, inscriptions, games, or incentive farming.
I'd look at:
Artemis, for example, tracks DAU, DAU over $100 balances, transactions, fees, revenue, stablecoin capitalization, developers, commits and contracts deployed.
That gives you a much better picture than "X million transactions this month."
For a token investor, I ultimately want to know:
Does increasing network usage create economic value for the token?
That's different from asking whether the blockchain generates fees.
For example:
Users ↑ → transactions ↑ → fees ↑ → token burned / stakers compensated / treasury receives value → token economics improve
is much more compelling than:
Users ↑ → fees ↑ → sequencer/operator captures everything → token holders receive nothing
Artemis has specifically expanded its revenue framework to distinguish revenue accruing to tokenholders from other economic activity, including active vs. passive revenue.
This is one of the most important distinctions for L1/L2 investing.
L2s require special treatment because the economics are different from L1s.
I'd examine:
L2 revenue
L2 costs
Then:
L2 gross revenue − L1/data-availability costs = approximate economic surplus
And then ask:
How much of that surplus accrues to the token?
That's crucial because an L2 can have enormous transaction activity while its token captures little or none of the economics.
For L2s I'd also track:
Rather than looking only at revenue, I like comparing economic activity against valuation.
Artemis has proposed Total Economic Activity (TEA), combining chain fees & MEV, settlement volume and application fees. Their argument is that looking at a blockchain as an economy captures activity that pure fee/revenue metrics can miss.
I wouldn't treat TEA as gospel, but the concept is useful:
How much economic activity am I buying for every dollar of market cap?
That's often more informative than simply asking which chain has the largest TVL.
Best for:
It's my starting point for almost every L1/L2 screen.
Particularly useful for:
Artemis explicitly supports comparative analysis across chains and protocols.
I'd use it when you want to compare:
Its project dashboard is explicitly designed around financial/usage metrics such as fees, active users, TVL and valuation.
Especially useful for:
For L2 investing, I'd consider this close to mandatory because economic metrics without technical/security context can produce terrible conclusions.
For every candidate L1/L2, I'd create something like:
Fundamentals
Quality
Token economics
Valuation
Then I'd rank the chains based on growth + quality + value capture + valuation, rather than picking whichever has the highest TVL.
For a long-term portfolio, I'd start around:
25% — sustainable user growth
20% — fees/revenue growth
15% — token value capture
10% — stablecoin + liquidity growth
10% — developer/ecosystem strength
10% — token supply/unlocks
10% — valuation
And I'd apply a "fake activity" penalty for chains where users/transactions are growing much faster than economic activity.
The biggest mistake I'd avoid is:
TVL ↑ + users ↑ = buy
Instead:
Organic users ↑ + economic activity ↑ + fees/revenue ↑ + token value capture ↑ + dilution manageable + valuation reasonable = accumulation candidate.
That combination is much harder to fake and is much closer to what I'd want as a multi-year fundamental thesis.
Evaluating Layer 1 (L1) and Layer 2 (L2) tokens requires looking past hype and digging into fundamental economic activity. For a long-term accumulation strategy, you want to measure real usage, economic sustainability, and ecosystem momentum.
Essential Fundamental Metrics
Best Analytics Tools to Use
If you'd like, let me know:
I can help you apply these metrics to build a customized evaluation framework.
For a long-term L1/L2 investment, I’d treat TVL, revenue, and active users as a starting point—not as the thesis itself. The key question is:
Is the network generating durable economic activity, and does the token actually capture some of that value?
| Metric | Importance | What I look for |
|---|---|---|
| Revenue / tokenholder value capture | ⭐⭐⭐⭐⭐ | Growing organic revenue, not mostly incentives |
| Stablecoin supply | ⭐⭐⭐⭐⭐ | Persistent growth and real economic use |
| Active users | ⭐⭐⭐⭐ | Consistent users, especially repeat users |
| Economic/transaction volume | ⭐⭐⭐⭐ | Growth that isn't dominated by bots/incentive farming |
| TVL | ⭐⭐⭐ | Growing, diversified, sticky capital |
| Fees | ⭐⭐⭐ | Users actually paying for blockspace |
| Developer activity | ⭐⭐⭐ | Sustained builders/contracts, not just GitHub noise |
| Token valuation | ⭐⭐⭐⭐⭐ | FDV/market cap relative to actual economics |
| Token supply/unlocks | ⭐⭐⭐⭐⭐ | Low dilution and manageable future emissions |
TVL is useful because it indicates capital deposited into an ecosystem, but it can be highly incentive-driven. A chain with $10B TVL and declining organic activity can be less attractive than one with $2B TVL and rapidly growing users, stablecoins and fees.
I particularly like:
TVL growth + stablecoin growth + DEX volume + active addresses
moving together.
DefiLlama is excellent for this because its chain dashboards combine TVL, fees, revenue, volume, stablecoins, bridges and other metrics.
This distinction is critical.
Fees = what users pay.
Revenue = what the protocol/network actually retains.
Token Terminal explicitly separates these metrics and also tracks expenses, cost of revenue, gross profit and earnings.
For an L2, for example, I'd want to know:
sequencer revenue − L1 settlement/data-availability costs = economic profit
A network generating $20M of fees but spending $18M to operate is fundamentally different from one generating $20M while retaining $15M.
Then ask the most important token question:
How much of that economic value accrues to the token?
A great network can still have a mediocre token if the token captures little of the economics.
Daily active addresses are useful, but raw addresses can be misleading.
I prefer looking at:
Artemis provides DAU, transactions, fees, revenue, stablecoin market cap and developer metrics, among others.
One particularly useful ratio is:
Transactions / active address
because it gives you a rough indication of how intensely users are actually using the chain. Artemis specifically discusses this as a way to distinguish increasing activity per user from simple address growth.
For an L1/L2, I'd put stablecoin supply and stablecoin transaction volume surprisingly high on the list.
Why?
Stablecoins represent economic liquidity that can actually be used for:
A chain accumulating stablecoins while users, DEX volume and lending activity also increase is much more interesting than a chain whose TVL rises primarily because its native token price increased.
Millions of cheap transactions don't necessarily mean millions of dollars of useful economic activity.
Artemis has argued for looking at Total Economic Activity (TEA), which combines things such as settlement volume, DEX/NFT/P2P transfers, chain fees and MEV.
For comparing L1s/L2s, I'd therefore track:
Economic activity / market cap
and
Economic activity / FDV
rather than simply transactions/day.
This is where many crypto investors stop too early.
Suppose:
Chain A
Chain B
I'd probably investigate B much more aggressively.
Useful valuation metrics include:
Token Terminal explicitly provides valuation metrics such as P/F and P/S on both circulating-market-cap and FDV bases.
1. DefiLlama — ecosystem screening
Best for quickly comparing:
I'd start here to generate the shortlist.
2. Token Terminal — financial analysis
Best for standardized financial metrics across chains/protocols. It covers 100+ chains and thousands of projects and standardizes metrics such as fees, revenue, active users and expenses.
This is probably my favorite tool for answering "is this network actually becoming a business?"
3. Artemis — usage and ecosystem analysis
Excellent for:
It is particularly useful for comparing chains on a standardized basis.
If I were building a long-term accumulation model, I'd roughly weight it:
30% — economic growth
20% — users
15% — capital
15% — token economics
10% — valuation
10% — moat
I'd be cautious when I see:
Conversely, my favorite setup is:
Users ↑ + stablecoins ↑ + economic volume ↑ + fees/revenue ↑ + developers ↑ + token dilution ↓ + valuation still reasonable.
That's the combination I'd want before making a large long-term accumulation decision.
One final point: don't compare L1s and L2s using exactly the same accounting framework. An L2 can have enormous user activity while paying substantial costs to Ethereum for settlement/data availability, whereas an L1 has a different cost structure. Token Terminal's cost-of-revenue framework explicitly accounts for things such as L2 settlement costs, which makes this distinction particularly useful.
If you're building an actual portfolio, I can also give you a 10–15 metric L1/L2 fundamental scorecard with specific thresholds for "accumulate / watch / avoid" and show how I'd apply it to ETH, SOL, SUI, AVAX, NEAR, ARB, OP, BASE, etc.
For a long-term altcoin investor, evaluating Layer 1 (L1) and Layer 2 (L2) tokens requires shifting focus from speculative hype to economic reality . The most robust evaluation framework combines Total Value Locked (TVL) to measure liquidity moats, Protocol Revenue (fees retained minus incentives) to gauge sustainable business models , and Daily/Monthly Active Users (DAU/MAU) to verify organic product-market fit rather than sybil or mercenary farming activity . Crucially, you must cross-reference these metrics with fully diluted valuation (FDV) and upcoming token unlock schedules to ensure growth isn't offset by heavy supply inflation.
Key Fundamental Metrics for L1/L2s
Essential Analytics Tools
| Tool | Core Strength | Best Used For |
|---|---|---|
| DeFiLlama | Real-time ecosystem data | Tracking macro TVL, bridge inflows, and multi-chain liquidity distribution. |
| Token Terminal | Financial statement format | Evaluating P/E ratios, protocol revenues, and active user growth trends. |
| Artemis | Cross-chain fundamental data | Comparing developer traction, transaction counts, and stablecoin metrics across L1s/L2s. |
| Dropstab | Vesting and tokenomics | Auditing future supply inflation, cliff events, and unlocking schedules. |
| Dune | Custom SQL analytics | Drilling down into granular user behavior, smart contract retention, and real-world asset metrics. |
If you'd like, let me know:
I can put together a tailored fundamental breakdown for those assets.
For a long-term L1/L2 altcoin investor, I would treat TVL, revenue, and active users as starting points—not investment theses. The strongest projects usually show a combination of:
A useful framework:
| Category | Metrics to track | Why it matters | Red flags |
|---|---|---|---|
| Liquidity | TVL, stablecoin liquidity, bridge inflows | Shows capital trust and ecosystem depth | High TVL from incentives, mercenary capital |
| Usage | Active addresses, transactions, retention, fees paid | Shows real demand | One-day activity spikes from airdrops |
| Revenue | Protocol fees, chain revenue, earnings | Shows monetization | Revenue disappears when incentives stop |
| Token economics | FDV, inflation, unlock schedule, staking yield | Determines investor returns | Massive unlocks, weak value capture |
| Developer activity | GitHub commits, contributors, apps launched | Predicts ecosystem durability | Few builders despite hype |
TVL is probably the most common L1/L2 metric because it measures capital deployed in DeFi. Dashboards such as DeFiLlama metrics dashboard track TVL, fees, revenue, volumes, and chain comparisons.
However, I would not rank chains purely by TVL. Ask:
A better metric:
TVL / Market Cap
Example:
The second may be more attractively valued, assuming the TVL quality is comparable.
For long-term investing, revenue matters because blockchains are businesses competing for users.
Track:
Token Terminal is commonly used for comparing crypto networks using financial metrics such as revenue and valuation ratios.
Questions to ask:
A chain generating $50M/year but with a $100B valuation may be expensive. A smaller chain generating $20M/year with a $1B valuation may deserve more investigation.
Daily active addresses can be misleading.
Look at:
A chain with:
is usually weaker than:
Security
Economic activity
Developer ecosystem
Pay special attention to:
Ask:
"Would users still use this L2 if incentives disappeared?"
A good network can still be a bad investment if the token is overpriced.
Track:
Lower can indicate cheaper valuation.
Useful for comparing consumer-oriented chains.
A great chain can underperform if billions of tokens are released into the market.
Check:
DeFiLlama
Best for:
Token Terminal
Best for:
Artemis
Best for:
Dune Analytics
Best for:
Nansen
Best for:
If I were screening L1/L2 tokens for a multi-year hold, I would roughly weight:
40% — Adoption
25% — Economics
20% — Ecosystem strength
15% — Token design
A high-quality L1/L2 candidate often looks like:
✅ TVL growing without excessive incentives
✅ Stablecoin supply increasing
✅ Revenue increasing over multiple quarters
✅ Users returning after incentives end
✅ Developers building consistently
✅ Token valuation reasonable relative to usage
✅ Clear reason the token captures ecosystem growth
The biggest mistake is buying the chain with the most hype. The better approach is usually finding networks where usage is growing faster than valuation expectations.
Evaluating Layer 1 (L1) and Layer 2 (L2) tokens requires looking past hype and assessing the actual economic engine of the chain. As a long-term investor, your focus should be on sustainable demand, security budgeting, and user retention.
Essential Fundamental Metrics
Top Analytics Tools
If you'd like, let me know:
I can break down a customized evaluation framework for those networks.
As a long-term altcoin investor navigating Layer 1 (L1) and Layer 2 (L2) ecosystems, evaluating protocols through a fundamental lens helps cut through market noise. Relying on core metrics and robust analytics tools prevents you from falling for speculative hype alone.
Essential Fundamental Metrics
Best Tools for L1/L2 Analysis
Would you like me to dive deeper into how to calculate real economic value (revenue minus emissions) for a specific L1/L2, or do you have a shortlist of chains you are currently comparing?
For a 5–10+ year L1/L2 investment horizon, I would treat crypto more like venture investing than momentum trading. The best opportunities typically emerge when network usage grows faster than token price, not the other way around.
I generally rank fundamental metrics like this:
| Importance | Metric | Why it matters |
|---|---|---|
| ⭐⭐⭐⭐⭐ | Revenue & Fees | Shows people are actually paying to use the network. Sustainable demand matters more than subsidized growth. defillama.comarxiv.org |
| ⭐⭐⭐⭐⭐ | Active users (daily/weekly active addresses) | Indicates adoption. Consistent growth is usually a better sign than short-lived TVL spikes. www.artemis.xyz |
| ⭐⭐⭐⭐☆ | Stablecoin supply on-chain | Often a leading indicator of liquidity and future activity. |
| ⭐⭐⭐⭐☆ | TVL | Useful, but can be inflated by incentives or leverage. Use it with caution. defillama.comarxiv.org |
| ⭐⭐⭐⭐☆ | Developer activity | Healthy ecosystems keep attracting builders. |
| ⭐⭐⭐☆☆ | Transaction count | Good only if paired with real users and revenue. Bots can inflate this. |
| ⭐⭐☆☆☆ | Token price | Usually a lagging indicator. |
This is the first question.
Look for:
A chain with:
is often more attractive than one whose token simply doubled.
This is probably the biggest differentiator today.
Many chains have billions in TVL but collect very little protocol revenue.
Instead, ask:
Growing revenue is far harder to fake than growing TVL. DefiLlama distinguishes between fees (what users pay) and protocol revenue (what the protocol actually retains).
TVL alone is one of the most misunderstood metrics.
Bad TVL:
Good TVL:
Academic work has also highlighted that reported TVL can involve double counting and may overstate underlying economic value.
This is critical.
Ask:
The best networks create a clear link between growing usage and growing token value.
My starting point for almost every project.
Use it for:
It's one of the largest open-source DeFi data aggregators.
Excellent for L1/L2 analysis.
Tracks:
Many professional crypto analysts use it to compare blockchain fundamentals.
Closest thing crypto has to Bloomberg.
Useful metrics:
Best for custom dashboards.
You can answer questions like:
Useful for:
A "green flag" profile looks something like:
That's often a more attractive setup than a token that's already rallied sharply.
Be cautious if you see:
When comparing L1/L2 tokens, I often weight categories roughly as follows:
This approach emphasizes whether the network is becoming more useful and economically valuable over time, rather than relying on price performance alone.
Evaluating Layer 1 (L1) and Layer 2 (L2) tokens through a fundamental lens requires looking past social sentiment and focusing on economic reality, capital retention, and real user adoption.
1. The Essential Fundamental Metrics
Total Value Locked (TVL) vs. Native Liquidity / Stablecoin Supply
Revenue vs. Fees (The Sequencer / Gas Spread)
Active Users & Transaction Dynamics
2. The Best Analytics Tools
3. Red Flags & Pitfalls to Avoid
If you have a specific subset of L1 or L2 tokens in mind (e.g., comparing Arbitrum vs. Optimism vs. Solana), I can walk you through a side-by-side fundamental breakdown using their current revenue and valuation metrics.
For long-term investing in L1/L2 tokens, I would avoid optimizing for a single metric like TVL. The strongest networks tend to show multiple reinforcing signals: increasing economic activity, user growth, sustainable fee generation, and token value capture.
Here's the framework I'd use.
| Metric | Why it matters | What to look for |
|---|---|---|
| TVL | Capital committed | Consistent growth, not one-time spikes |
| Fees | User demand | Rising fees without relying on incentives |
| Protocol revenue | Sustainable business | Revenue growing faster than emissions |
| Active users | Network adoption | Steady DAU/MAU growth and retention |
| Transactions | Usage | Organic transaction growth (filter out spam) |
| Stablecoin supply | Liquidity | Growing stablecoin balances usually precede ecosystem growth |
| Developer activity | Long-term innovation | Consistent commits and ecosystem expansion |
| Ecosystem diversity | Resilience | DEXs, lending, RWAs, gaming, AI—not just one app |
TVL is useful because it shows how much capital trusts a chain.
However, TVL has limitations:
Academic research has shown that TVL can substantially overstate underlying economic value because of double-counting and leveraged assets.
Instead of raw TVL, I'd examine:
Traditional investing asks:
Does this business make money?
Crypto should ask the same.
Distinguish carefully between:
Those definitions are widely used in crypto analytics.
For L1/L2s, I prefer:
Transactions are easy to manipulate.
Active addresses are harder (though still imperfect).
Look for:
A chain with
is usually less attractive than
because it suggests broader adoption.
One of the best leading indicators is:
Stablecoin market cap on the chain
Why?
People bridge stablecoins before they:
Growing stablecoin liquidity often precedes ecosystem expansion.
A healthy L1/L2 shouldn't depend on a single protocol.
I want to see:
If 70% of TVL comes from one protocol, ecosystem risk is much higher.
Developers create future value.
Metrics:
Developer growth often leads user growth by months.
This is where many investors lose money.
Questions:
A great chain can still have a poor investment if the token captures little of the network's value.
Best for:
It's usually the first dashboard I open.
Best for:
This is the closest thing crypto has to Bloomberg or FactSet.
Excellent for:
Its supported metrics include active users, TVL, fees, and revenue.
Best for custom dashboards.
You can track:
For Ethereum L2s, this is essential.
Track:
Useful for:
When evaluating an L1/L2, I'd score each category from 1–5:
A chain scoring 40+/50 would warrant deeper research. One scoring under 25 is often missing a key ingredient, even if the token has strong short-term momentum.
The biggest mistake long-term investors make is focusing on market cap alone. Durable winners tend to compound because users generate fees, fees generate revenue, and—if the tokenomics are designed well—that revenue ultimately accrues to token holders.
