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Web 3.0 Metrics
Protocol Metrics
Industry Evaluatin Metrics
Industry Evaluation Metrics


Protocol Metrics


1. Price of related tokens


2. Governance model and execution — might be hard to quantify


  • Number of members

  • Members who overlap with other DAOs

    • Which DAOs do they overlap with?​

  • Number of votes

  • Number of voters

  • Average votes per proposal

  • Token share

  • Proposals created


  • Groups that vote together

    • What percentage of votes are by coalitions?

    • How much weight do they have?

Voter participation

  • Number of members who actually vote


3. Network effect — unsure which law to use (Metcalfe, Reed, etc.)

4. Project Valuation Metrics

Open-source valuation metrics:

  • SLOCCount:

    • Compares the lines of code against industry estimates of programmer productivity to estimate the man hours and resources required to produce the project.

    • Could be integrated with data from sources such as DeepDAO or CryptoMiso — or their primary data sources.


    • Formula derived via logistic regression techniques on data from previous open-source projects

  • Product attributes

    • Required software reliability

    • Size of application database

    • Complexity of the product

  • Hardware attributes

    • Run-time performance constraints

    • Memory constraints

    • Volatility of the virtual machine environment

    • Required turnabout time

  • Personnel attributes

    • Analyst capability

    • Software engineering capability

    • Applications experience

    • Virtual machine experience

    • Programming language experience

  • Project attributes

    • Use of software tools

    • Application of software engineering methods

    • Required development schedule

  • Organic projects - "small" teams with "good" experience working with "less than rigid" requirements

  • Semi-detached projects - "medium" teams with mixed experience working with a mix of rigid and less than rigid requirements

  • Embedded projects - developed within a set of "tight" constraints (hardware, software, operational, …)

Data Sources and Tools Dao
Metric Analysis Dao
Case Study: Curve Finance

5. Software Quality Metrics




. . .


1. Stakeholders

  • Top stakeholders

  • Distribution


2. Data Sources and Tools


DeepDAO is an analytical service for DAOs, similar to CoinmarketCap for DAOs. They provide both financial and governance data on the top 100+ DAOs.

Data Sources and Tools


Case Study: Curve Finance

  • Brief Overview of Curve

  • Curve currently supports trading for the following stablecoins: DAI, USDT, USDC, GUSD, TUSD, BUSD, UST, EURS, PAX, sUSD, USDN, USDP, RSV, LINKUSD. Additionally, you can trade ETH, LINK, and a handful of tokenized BTC assets like wBTC and renBTC. Source: Uniswap%2C Curve is a, for trading stablecoins on Ethereum.

  • At its core, Curve is an automated market maker (AMM) protocol consisting of:

  • Liquidity providers

  • Liquidity pools

  • Traders swapping tokens with the liquidity pool — this creates buy and sell pressure which determines token prices

  • AMM algorithms price the tokens in liquidity pools


The presence of AMMs removes the need for counterparties (a counterparty is simply the opposite side of a trade, i.e. the buyer to a seller or buyer to writer in options).


Conversely to a DEX, centralized exchanges (CEX) use an order book which trades are made against, in this case, the CEX owns the assets on the book, and are the counterparty to every trade.


In the place of an orderbook, Curve crowdsources its liquidity, algorithmically determines the prices of liquidity pool assets, and enables traders to trade directly with the pool via smart contracts — no counterparties involved.


The benefits of Curve over platforms like Uniswap for stablecoins:


  • Low fees: 0.04% vs. 0.3%

  • Minimal slippage

  • Nearly no impermanent loss (stablecoins are not liable to impermanent loss as the phenomenon is accountable to price fluctuations in underlying assets)



Curve’s tokens:


  • CRV

  • The native utility token of Curve with four use cases:

  • Governance: Decisions made on the Curve DAO are voted on by CRV holders who vote-lock their tokens, converting them to veCRV

  • Rewards: LPs are paid in CRV based on poolshare

  • Token burn: Some of the CRV trading fees are not routed to LPs and are instead burned, reducing the supply.

  • veCRV: vote-escrowed CRV0, used for voting in governance, boosting rewards, earning trading fees, and receiving airdrops.

  • CRV can be time-locked, up to permanent. The longer you lock, the more veCRV you receive.

Liquidity providers are incentivized in the following ways:

  • Trading fees: fees accrued in a pool are distributed proportionally to an LP’s share of the pool.

  • Yield farming: unutilized liquidity in pools are deposited into other DeFi protocols to generate additional APY.


  • veCRV token: Locking CRV tokens converts them into veCRV which can be used to boost an LP’s deposit APY​

  • Boosted pools: Some pools offer additional incentives, particularly for LPs

Metric Analysis
  • Finance

    • Will need to look into other sources of financial info, none given for Curve through the tools listed.

  • Governance

    • Proposals

      • 197

  • Proposal creators

    • 136

  • Successful proposals

    • 11.2%

  • Participation

    • Proposals/voters ratio: 20.3 : 80.3

    • Total votes

      • 1,738

  • Voters

    • 537

  • Average votes per proposal

    • 8

  • Members

    • Can’t find much data on this either, will need to dig deeper.

  • Coalitions

    • Top 5 coalitions account for

    • 37.5% of all proposals

  • GitHub Stats (CRV DAO Token)

    • These stats are for CRV, not necessarily the whole DAO:

NFT Marketplace Fees
  • They also don’t seem accurate, it seems the GitHub repo has moved and CryptoMiso has not updated this yet.


  • Most of the usual trading metrics can be applied here to the game’s token as they operate similarly to any other tokens once put onto exchanges.

  • Underlying Asset Prices

  • Price

  • Trade Volume

  • Traders

  • Currently in circulation

  • Burn Rate — A high burn rate (consumption of the tokens through mechanics) indicates a decrease in supply and may drive up prices. (During bear markets, social media indicates that people want more burn mechanics hoping to counter the drop in prices)

  • Token Creation/Release Rate


  • Trade Volume

  • Traders

  • Sales

  • Market Cap

  • Average Price

  • Floor Price — (minimum returns)


Potential Earning Rate/Average Earning Rate — Split between NFTs and Tokens

  • Tokens earning rate is highly specific to the game, look at the mechanisms the game distribute its tokens

  • NFT earning rate is harder to quantify as different GameFi NFTs have different values. You can look at the average price of specific categories of NFTs over their difficulty of obtaining to create a general estimate

Earning Rate * Token/Asset Price = Average Earning

Token Supply = Currently in circulation + Token Creation/Release Rate — Token Burn Rate

Demand Factor =

Game’s Revenue and Account Balance — Relevant as this is an indicator for continual game development. If the game has no income coming in, even if the trading of the game’s assets is high, no update to the game will eventually lead to people abandoning the project.




  • APR and Adjusted APR

    • Staking rewards can be a factor of (and calculated from) original tokens dedicated as staking rewards, and percentage of revenue distribution for staking rewards

    • Adjusted APR simply takes the growth in total circulation supply into account

  • The token network effect is very strong in the GameFi sector. Blockchain games can create strong financial incentives to bootstrap people onboard the game. As the game value grows, there should be more entertainment value to draw people to the game. It should be obvious that a game with no entertainment value and only financial incentives to keep people playing will fail as hype would be the only thing keeping up the token and NFT prices.


NFT Marketplace Fees
Case Study: Axie Infinity

  • Ethereum Price — Used on the official Axie Infinity Marketplace (Axie Marketplace takes a 4.5% cut. Opensea takes a 2.5% cut but is riskier as people can sell banned Axies on it)

  • AXS and SLP Token

    • Price

    • Trade Volume

    • Traders

    • Potential Earning Rate/Average Earning Rate

      • SLP is earned in 2 ways, first through PVP battles, second through PVE battles. The earning from these can be averaged out as a baseline metric.

      • AXS is earned by owning land, or sending your Axies to mine other people’s neglected land. If you look at the average spawn times and how much is spawned, an average earning rate can be calculated. A percentage of the total amount is also sold publicly and privately.

  • Volume Burnt/Burn Rate

  • Fees

  • AXS Staking Returns

  • Axie Infinity NFTs (Axies, Land, Items) — Relevant metrics determining the returns of the NFTs

    • Trade Volume

    • Traders

    • Sales

    • Market Cap

    • Average Price

    • Floor Price — (minimum returns)

  • Axie Infinity Statistics

    • Active Users

    • Transactions

    • Volume

    • Community Treasury Balance and Revenue

  • AXS Staking Yield

    • Locking up your AXS tokens earns AXS tokens and maybe other rewards (game incentives)

    • Stakers are rewarded both a percentage of AXS tokens in the initial allocation and in a percentage of the Community Treasury. As the percentage of the AXS tokens initial allocation is lowered as time goes on, the increasing community treasury size should increase and make up for it.

  • APR (Annual Percentage Rate)

  • Adjusted APR (Adjusted for inflation of network supplies)


AXS Unlock Release Schedule : AXS-Deck-Delphi-Digital-Final-.pdf

Machine FI
Storage as a Service
Digital Asset/ Metaverse
Underlying Asset List and Prices
Risk Metrics
Data Marketplaces

. . .




1. Financial Metrics

  • Gas Fees

  • Gas fees for minting assets

  • Marketplace Fees

  • Cost of base token (e.g MANA)

    • Underlying Asset Prices

    • Token to ETH Pair Price

    • Token

      • Price

      • Trade Volume

      • Traders

      • Currently in circulation

      • Burn Rate (If Applicable)

      • Token Creation/Release Rate

  • Potential Earning Rate/Average Earning Rate — Split between NFTs and Tokens

    • Tokens earning rate is highly specific to the model, look at the mechanisms the game distribute its tokens

    • NFT earning rate is harder to quantify as different NFTs have different values. You can look at the average price of specific categories of NFTs over their difficulty of obtaining to create a general estimate

  • Earning Rate * Token/Asset Price = Average Earning

2. Earning in the Metaverse from in game mini-games


  • Extremely mini-game dependent, these mini-games are community developed, a lot of these include classic casino games

    • Tokens per Hour

      • Relates back to token price

    • NFTs per Hour

      • Relates back to NFT value

3. NFT Metrics

  • Trade Volume

  • Traders

  • Sales

  • Market Cap

  • Average Price

  • Floor Price — (minimum returns)


4. Land Metrics

  • Average/Median Land Price

  • Areas of Interest — Defined by areas with high land price

  • Price of Land Adjacent/Near Areas of Interest

  • NFT Metrics

  • Trade Volume

  • Number of Traders


5. Development Metrics

  • Active Community Members

  • Active Community Developers

  • Protocol Revenue

  • GitHub Metrics

  • Number of Pushes over time

  • DAO Metrics


6. Freelancing (Employed by other players)

  • Average Pay Rate by Job Type

    • 3D Marketing

    • Wearables

    • Coding

    • Making Videos

    • Artists

    • Marketing


7. Platform Token Metrics (if applicable)

  • If the Metaverse/ Game is built on a platform (eg. Enjin), the platform’s underlying token’s typical metrics are important metrics to consider. This is because the value of the tokens/NFTs minted with the underlying token is also “backed” by the token. In addition to the typical token metrics, some other metrics of consideration include

    • Average Aggregated Price of Minted Tokens/NFTs to Platform Token Price

    • Marketplace fees

    • Minting fees


. . .



Machine FI
Storage as a Service

1. Financial Metrics

  • Download Price/ TB

    • The cost in native tokens to download

  • Price Per TB/Month

    • The tender amount in native tokens to store 1 TB of Data per Month

      • Network Fees $

      • The transaction fees included in the protocol smart contract, this fee helps generate revenue for the protocol which can be used for R&D and maintenance.

  • Upload Price/ TB

    • The cost in native tokens to upload data to the protocols

  • Minimum storage time: Minimum amount of time to keep storage

    • Minimum duration of smart contract for data storage agreement

  • Contract Formation Fees

    • The one time fee for a contract to be established between a storage provider and user

  • Price of Ethereum

    • Most large data service providers are build on Ethereum and thus the strength of ETH will effect the stability of the protocol

  • Value of Native token

    • Underlying Asset Prices

    • Token

      • Price

      • Trade Volume

      • Traders

      • Currently in circulation

      • Burn Rate — A high burn rate (consumption of the tokens through mechanics) indicates a decrease in supply and may drive up prices. (During bear markets, social media indicates that people want more burn mechanics hoping to counter the drop in prices)

      • Token Creation/Release Rate

As transactions on the platform require the native token to execute transactions, the price of the token will influence the price of the service.

2. Performance Metrics

  • Upload Speed

    • Upload speed will be used similarly to download speed to understand how strong the infrastructure support.

  • Download speed:

    • How fast the download speed is for accessing data. This metric is used as a method of understanding efficiency

  • Storage Capacity: Indicates the total amount of storage available

    • The amount of total storage available across all active and inactive nodes


3. Usage Metrics

  • Storage Providers: The amount of storage providers available i.e., how much storage there is.

    • This is the individual amount of storage providers managing data.

  • Available storage:

    • Total storage — Storage used

    • This metric can be used to understand how much of the actual network is being used, compared to how much of the network is stagnant

  • Number of users

    • This metric will be used to determine the size of the network, of people who are actually participating on the network.

  • %Of Nodes connected

    • This is a metric for determining how many active nodes are on the network, which are actually participating in data storage.

  • Development Metrics

    • Commits

    • Forks

    • Releases

    • Contributors


. . .


Data Marketplaces


1. Financial Metrics

  • Price of Native token

    • The cost of Ocean token for governance

  • Price of Ethereum

    • As Ethereum is usually the blockchain used to build marketplaces the price of eth will effect gas fees and the price of native data token

  • Gas Fees

    • As each data source contains its own ERC-20 token, the cost to mint each individual token for a data set is vital

  • Transaction fee from protocol​

    • The transaction fees taken by protocol when data is traded

  • Staking reward percentage

    • The data provider determined staking reward for keeping ocean tokens in liquidity pool.


2. Performance Metrics

  • Download speed

    • How quickly data can be exchanged between users

  • Upload Speed

    • How quickly data sets can be uploaded to the system

  • Compute-to-data availability

    • The total number of nodes participating in compute to data

    • The total computation available to test AI models

  • TPS

    • The total number of transactions per second on each data token.


3. User Metrics


  • Size of liquidity pool

    • This is for users to gauge which data set is the most profitable

      • The total volume of ERC-20 data tokens minted from the pool

      • The amount of Ocean tokens within the pool

      • The cumulative cost of ERC 20 tokens staked in the pool

  • Available data sets

    • The total number of ERC 20 data sets available on the system. This can be either unique data sets vs curated data sets

  • Curated vs Raw data sets, this spread shows how many people are providing raw data and how many users are proving bundles of curated data


. . .


1. Economic Metrics

  • Native Price Ticker

    • Price ticker for native coin as transactions and data feeds are made through this native token

  • Total Nodes

    • The total amount of nodes connected to the blockchain, as each data device contributes a small amount of computation

  • Chain Structure

    • The type of blockchain used on the network, there are generally only two choices

      • Blockchain e.g., BTC, Ethereum

      • Traditional linear graph

  • Directed Acyclic Graph (DAG)

    • New technology employing acyclic graphs


2. Performance Metrics

  • Number of Devices Connected

    • Number of individual devices connected to the network, this shows how many devices are actively participating in the network.

  • % Of connected Devices:

    • Though there may be large number of devices connected, the number of active devices is a better reflection of protocol participation.

  • Number of users

    • The total number of data subscribers, i.e., people who are connected to the chain

  • Number of active users

    • How many users are active on the network


3. Usage Metrics

  • % Of Active users

    • What percentage of the protocol actively subscribes to data, ie the number of participants validating and subscribing to data

  • Transactions per second: Indicates speed

    • As IoT services generally use their own blockchain, and devices may need to communicate together and exchange data effectively the transaction speed is essential.

  • Transaction fee

    • The transaction fee model used by the protocol

  • Number of historical hacks:

    • Helps identify protocol security

    • Judges the integrity of the chain

  • DeFI​

  • ​Yield Farming

    • Metrics​ ​ ​



Underlying Asset List and Prices

Annual Percentage Yield

  • Measurement of interest earned

  • Takes into account compound interest

  • Calculates rate earned in one year

  • APY = (1+r/n)^n — 1 {r = period rate; n = number of compounding periods}

  • APY is also comprised of several sources of yield in many cases (see case study for example)


Annual Percentage Rate

  • A measurement of the interest charged which takes into account any fees or additional costs associated with a transaction

 Total Value Locked

  • The total value of assets in the pool

Trading Activity

  • Revenue sharing protocols rely on trading fees, and thus the trading activity in a pool dictates the revenue of LPs

  • In pools with their own tokens, volume / market cap may be a decent indicator

  • Fees

Pool Type

  • Lending and borrowing

  • Yield aggregator

  • Revenue sharing

Pool Strategy Information

  • Some protocols employ quite complex yield farming strategies, it would be useful to be able to grab a clear explanation of the strategy or strategies a pool operates by

Borrowing Demand

  • Borrowing demand increases and decreases in bull and bear markets respectively, an approximate borrowing demand may be derived from an index of market sentiment


Risk Metrics

Impermanent loss

Data Sources and Tools
Metric Analysis

Explained in more depth here

Cybersecurity Risks

  • Smart Contract Risks

    • Software bugs in smart contracts can lead to unwanted behaviors from users and the strategies themselves.

Composability Risks

  • Malicious agents may (and have) found exploits in the complex interconnected web of smart contracts that comprise yield farming.

Access Controls

  • How much control do the pool’s developers have over it their own protocol?


  • How well is the software documented?

APY Stability

  • How reliable is the current APY?


Liquidation Risks

  • When a strategy borrows tokens, if the value of collateral falls below a liquidation threshold, it is no longer deemed valuable enough to cover the amount of the loan that was taken. The borrower is liquidated and received the collateral minus the outstanding debt, as well as a penalty charge.

  • Stablecoins are less likely to liquidate


Lending and Borrowing Risks

  • If too many lenders may withdraw at the same time, some of them will be required to wait until other borrowers have paid back their outstanding loans.

Data Sources and Tools


Case Study: Yearn Finance V2 — Curve MIM Vault (01.02.2022)

“This token represents a Curve liquidity pool. Holders earn fees from users trading in the pool, and can also deposit the LP to Curve’s gauges to earn CRV emissions. This metapool contains 3Crv (DAI, USDC, and USDT) and MIM, a decentralized stablecoin collateralized with yVaults and other yield-bearing tokens on Abracadabra.”


Metric Analysis
  • Service design blueprints for the user journey of investing in a Yearn Vault:

Financial Metrics

Pool Type

  • Yield aggregator?


  • Convex Reinvest Supplies MIM-3LP3CRV-f to Convex Finance to earn CRV and CVX (and any other available tokens). Earned tokens are harvested, sold for more MIM-3LP3CRV-f which is deposited back into the strategy.


  • $77,173,421 USD equivalent


  • Net: 19.73%

  • Pool APY: 4.45%

  • Bonus Pool APY: 4.45%

  • Bonus Rewards APR: 0.00%

  • Base CRV APR: 6.01%

  • Boost 2.50x

  • Convex APR: 20.57%

  • Gross APR: 25.82%

  • Net APY: 19.73%

  • Earnings over time

  • $7,170,368.63 USD

Underlying Assets and Prices

  • DAI

  • USDC

  • USDT

  • MIM

  • A decentralized stablecoin collateralized with yVaults and other yield-bearing tokens on Abracadabra.

  • All approx. $1 USD


Fees (Yearn Fees)

  • Performance

    • 20% deducted from yield every time a vault harvests a strategy.

  • Management

    • 2%

    • The fee is extracted by minting new shares of the vault, thereby diluting vault participants.

  • Borrowing demand

    • This may not be the best way to do this:

    • Based on a crypto fear and greed index (which I believe uses sentiment analysis over various sources), as of the time of writing this, market sentiment is around 26/100, where 0 is the highest fear and 100 is the highest greed.

    • As such, we can say with some small quality that borrowing demand is on the lower end, and as the strategy deploys tokens to Convex finance, which in part generates revenue from interest, this may be of concern, though likely not a major indicator.

Trading Activity


  • Volume

    • $15,433,444

  • Volume / Market Cap

    • 0.01149


  • Volume

    • $448,700

  • Volume / Market Cap

    • The CMC team has not verified the project’s Market Cap. However, according to the project, its self-reported CS is 31,727,030 CVXCRV with a self-reported market cap of $102,446,891.

    • 0.00438

  • Impermanent Loss

    • While qualitative, the impermanent loss should be very low, as the strategy deals in stablecoins

  • Liquidation Risks

    • Stablecoins mean the risk here is low as well

  • Lending and borrowing risks

    • A large number of LPs probably lowers the risk of overdrawing

  • Need to look further into how this applies here

    • Cybersecurity risks

      • It is hard to say for the particular vault, but Yearn V2 itself has a very high rating on DeFiSafety; 93%

  • NFTs- Renting and as Collateral


Financial Metrics


Project Price

  • The average price of an NFT in the project

Active NFT Price

  • Tracking the best bid ask of a NFT and also price history of the NFT

    • This will make it easy for lenders and borrowers to determine the value of an NFT compared to

  • Ethereum Price Feed, as WETH is the base token and NFT price is based on Ethereum

    • The Ethereum price is essential as this is what drives

Transaction Fees

  • A portion of the revenue taken by the protocol, for their internal expenses. Transactions fees are included in the smart contract and are automated

  • Borrowing Rate

    • The borrowing rate is like the interest paid when an NFT is rented, this is paid to the lender of the NFT

  • Collateral amount

    • Collateral is the amount of money paid by the borrower as security if they are unable to return the load

  • Collateral coverage ratio

    • The collateral coverage ratio is the difference in value between the asset being lended and the collateral value.

Performance Metrics
Performance Metrics
  • Liquidation ratio

    • Percentage of contracts being liquidated

Usage Metrics
  • Number of Contracts Fulfilled

    • How many contracts where the NFT is returned to the lender, metric is similar to the last metric. Shows how many contracts were fulfilled if the renters of the contracts are actually paying back the lenders.

  • Percentage of rented NFTs

    • How many NFTs are actually being rented on the platform, this will be a metric to demonstrate activity on the platform. This can be determined by the number of transactions and the total number of NFTs available on the platform.

  • Number of Contracts Liquidated

    • This metric will asses how often the terms of the contract were not met and the lender’s NFT was taken and collateral was paid. This metric could suggest strange behavior. This metric can also be used as a risk management tool.

Usage Metrics


Project Volume

How many NFTs are produced by the project

  • Verification

    • These projects should have an aggregated verification system such as the one used on OpenSea. This is to ensure that NFTs which are on the platform are legitimate.

  • Type of Token

    • ERC standard of the token

  • ERC Ratio

    • Ratio of ERC-1155 tokens to ERC-721 tokens, this will identify weather users are renting for curation or renting for benefits of the token.

  • Total Value Locked

    • The total value of assets in the pool

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