Precisions and Assumptions
Evaluate the sources and accuracy of our tokenomics data
Overview
The Problem: Unlock Data Lacks Consistency
Crypto projects report release schedules without any standardized enforcement. Data can be spread across blog posts, whitepapers, on-chain contracts, and multisigs, leading to ambiguity and making it difficult for users to trust the information they find.
Our Solution: Precision & Assumption
We introduce the Precision & Assumption framework. For every token we track, we show you where our data comes from (Assumption) and how accurate its timing is (Precision). This framework gives you the clarity to assess the transparency of a release schedule.

Methodology
Definitions
Assumption (Data Source Types): Indicates where the release schedule data originates.
Precision (Release Time): Indicates how precise the release timing is.
Assumption (Data Sources)
Public Project Data & On-chain Verified
The release schedule was publicly announced by the project and verified by us on-chain.
Public Project Data
The release schedule was publicly announced by the project (e.g., in a blog post).
Vesting Contract
The release schedule is derived directly from a time-lock smart contract.
Private Project Data
The release schedule was confirmed privately by the project's team.
Inferred On-chain
The release schedule is interpreted by our team from on-chain behavior.
Precision (Release Timing)
Second
The release occurs at the exact second specified.
Block
The release is tied to a specific block number.
Hour
The release can occur at any time within the specified hour.
Day
The release can occur at any time within the specified day.
Week
The release can occur at any time within the specified week.
Month
The release can occur at any time within the specified month.
To Be Determined
The release time is not yet known (see TBD Locked Supply).
Example Cases
Example 1: Vesting Contract with Exact Timestamps
Scenario: A vesting contract is deployed on-chain with parameters specifying exact unlock times down to the second (e.g.,
2025-01-01 00:00:00 UTC
).Analysis: Because the contract itself dictates the precise timing, the data source is both transparent and verifiable on-chain. Users can independently confirm the schedule without ambiguity.
Our Categorization:
Vesting Contract
with precision Second (the unlock will execute exactly at or very close to that timestamp).
Example 2: Whitepaper with Monthly Unlocks
Scenario: A whitepaper states that 10% of tokens unlock "monthly" (e.g., January, February, March) without specifying days or hours.
Analysis: The data is official, but without finer time granularity. The unlock could occur on the 1st, 15th, or 30th of the month.
Our Categorization:
Public Project Data
with precision Month (the unlock can occur at any point during the specified month).
Example 3: Private Confirmation from Project
Scenario: The team privately shares aspects of their vesting schedule with Tokenomist but does not publish it publicly.
Analysis: While the source is direct, it lacks public verifiability. Confidence depends on the team’s reliability rather than on-chain guarantees.
Our Categorization:
Private Project Data
with precision Day (if the team specifies exact dates, but not timestamps).
Accessing Precision & Assumption
You can find the Precision & Assumption details on every token page. It is located in a dedicated Tokenomics Reference section underneath the release schedule that clearly displays the source and precision for each of the token's allocations.
Using Precision & Assumption
1. Evaluate Reliability of Unlocks
A Cliff Unlock for an Investor allocation with a
Vesting Contract
+Second
precision is highly reliable, near-certain.An unlock with
Inferred On-chain
+Month
precision is far less reliable and should be treated cautiously.
2. Compare Allocations Across Sources
See how different allocations within a project vary in reliability — some may be contract-verified while others are only privately confirmed.
3. Incorporate into Risk Assessment
Before acting on vesting data, always check its Assumption and Precision to gauge confidence.
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