Understanding Graph Network Delegators Behavioural Analysis

Sharing interesting analysis on Graph network delegators and delegation activities. Delegation Behavioural Analysis is essential for understanding the actions of delegators in The Graph network.

  • This analysis provides insights into trends, popular days and times for delegations, and more.

  • It assists indexers in optimizing their operations, ensuring they run at maximum efficiency.

  • Comprehending delegation behavior also allows token holders to make informed decisions about their delegation strategies and optimize their returns.

Most Active Days and Times for Delegations

This section provides insights into the days and times when the majority of delegations occur in the Graph Protocol. It helps indexers understand when they can expect the highest level of activity and adjust their operations accordingly.

  • Most delegations happens on weekends(Saturday/Sundays)
  • Tuesday saw a slight increase in the past four weeks

  • 9:00 PM UTC leads with 1206 delegations overall
  • 7:00 PM and 11:00 PM UTC close runners-up

Total Amount of Delegations

This section provides information on the total amount of tokens delegated to indexers on the Graph Protocol. It helps track the growth of the network and highlights the days when the highest amount of tokens are being delegated.

  • Thursday: highest overall delegation at 462M $GRT
  • Monday taking over in the past four weeks at 26M $GRT

It seem whales prefer delegation on mid week.

Delegators by Number of Indexers

This section provides information on the number of delegators and the number of indexers they delegate their tokens to. It helps understand the distribution of delegators and the network’s concentration level.

  • 8,900+ delegators delegated to 0-1 indexers
  • 1,476+ delegators delegated to 2-3 indexers
  • 178 delegators delegated to 4-5 indexers
  • 82 delegators delegated to 5+ indexers

Delegators GRT Average and Median by Indexers

This section provides information on the average and median amount of tokens delegated by delegators to indexers. It helps understand the distribution of token holdings among delegators and the level of decentralization in the network.

  • GRT Av. 141k / GRT Median 2,8k
  • GRT Av. 263k / GRT Median 7.8k
  • GRT Av. 1.1M / GRT Median 25k
  • GRT Av. 4.9M / GRT Median 63.9k

Delegators by Delegation Range

This section provides information on the number of delegations made by delegators and the range of days over which they have made them. It helps understand the level of engagement and activity of delegators in the network.

  • 8.9k+ delegators delegated to 0-1 indexers
  • 966+ delegators delegated to 2-3 indexers with a range of 1-50 days
  • 134+ delegators delegated to 2-3 indexers with a range of 51-100 days
  • 377+ delegators delegated to 2-3 indexers with a range of 100+ days
  • 90+ delegators delegated to 4-5 indexers with a range of 1-50 days
  • 17+ delegators delegated to 4-5 indexers with a range of 51-100 days
  • 71+ delegators delegated to 4-5 indexers with a range of 100+ days
  • 28+ delegators delegated to 5+ indexers with a range of 1-50 days
  • 7+ delegators delegated to 5+ indexers with a range of 51-100 days
  • 47+ delegators delegated to 5+ indexers with a range of 100+ days

Dashboard:

Track these metrics IRL: Graph Network - Delegator Behavioral Analysis Dashboard

Data Source: Graph Network Mainnet Subgraph

Graph Network Other Dashboards

Thanks @kyleArojas for suggestion on metrics.

Conclusion

In conclusion, The Graph Delegation Behavioural Analysis provides valuable insights into the actions of delegators and indexers on the network. By understanding delegation trends, popular days and times, and the number and value of active delegations, token holders can make informed decisions about their delegation strategies. The findings also highlight the importance of data analysis in optimizing network operations and maximizing returns for token holders. Join the decentralized revolution with The Graph!

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Wow Abhay thanks for this great work.

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Dapplooker just keeps producing great work for our ecosystem. Tracking and analyzing user behavior will help you evaluate what users find value in, and enable you to improve their experience. User Behavior Analytics: How to Track and Analyze

4 Likes

Awesome work from Dapplooker!

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Excellent work @napolean !!! :clap: :clap:

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Great work , the Graph has started the new decentralized revolution and it truly amazing. :clap:

1 Like

Great work indeed.!!

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