📌 Data Sources

• Major Flipside Tables:

  • solana.gov.ez_staking_lp_actions – native stake and deactivate events

  • solana.defi.ez_dex_swaps & solana.defi.fact_swaps_jupiter_summary – LST swaps interpreted as stake/deactivate

• Custom Reference Table:

  • LST token metadata (mint_address, validator_address, symbol, etc.)

• Sanctum API (external source) for deeper LST pool coverage

🧮 Metric Definitions

sol_amount Amount staked or unstaked in SOL

net_flow_amount Positive for delegations, negative for deactivations

event_type delegate (stake in) or deactivate (stake out)

stake_type Either native or lst (liquid staking token) - focus were on Individual lsts rather than stake pool lsts

lst_symbol Symbol of the LST token involved (e.g., LaineSOL)

switch_type Type of validator or stake-type transition: native_to_lst, lst_to_native, etc.

is_validator_switch Whether the delegator switched to a new validator

stake_duration_days Number of days stake was held before switching or deactivating

is_multi_validator_month True if a delegator interacted with more than one validator in the same month

📌 Why It Matters

• 🧭 Delegator Behavior & Switching
  Understand how often and why users switch validators or move between native and LST staking.

• 🧮 Validator Competition & Commission Sensitivity
  Analyzing flows by validator commission tiers and changes over time shows how sensitive stake is to fee structures.

• 🧑‍🤝‍🧑 Stake Distribution & Centralization Risks
  We can assess decentralization and ecosystem health using Gini coefficients and stake concentration metrics (e.g., top 10, 20, 100 validators).

• 🔀 LST Strategy Adoption & Protocol Dynamics
  Tracking stake flow between native and LST positions — by volume, count, type switch, and over time — uncovers how delegators balance liquidity vs returns and which LST protocols lead.

• 📊 Performance-Driven Delegation
  By correlating validator performance (epoch credits) with stake flows, we assess whether delegators reward high-performance validators.