APY & ROI Metrics

Overview

The APY & ROI endpoint provides standardized return metrics for your validators, broken down by execution layer (EL) and consensus layer (CL) contributions.

API Endpoint: This guide uses /api/v2/ethereum/validators/apy-roi for aggregated return metrics.

When to use APY/ROI vs BeaconScore: APY and ROI measure absolute returns in ETH/percentage terms. BeaconScore measures relative efficiency normalized for luck (see residual luck factors). For comparing validator performance across operators, BeaconScore is recommended.

See Also: For detailed per-epoch missed reward analysis (which duty types are causing losses), see Analyze Missed Rewards. This endpoint focuses on aggregated return metrics.

Understanding the Metrics

This guide focuses on choosing a window and interpreting the metrics in an operational comparison. See the APY & ROI API reference.

APY is an extrapolation based on the selected evaluation window. Past performance does not guarantee future results, especially for execution layer rewards which are highly variable.

Quick Start: Fetch APY & ROI

curl --request POST \
  --url https://beaconcha.in/api/v2/ethereum/validators/apy-roi \
  --header 'Authorization: Bearer <YOUR_API_KEY>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "chain": "mainnet",
  "validator": {
    "dashboard_id": 123
  },
  "range": {
    "evaluation_window": "30d"
  }
}
'

Response

{
  "data": {
    "execution_layer": {
      "roi": "0.00125",
      "apy": "0.0152"
    },
    "consensus_layer": {
      "roi": "0.00285",
      "apy": "0.0347"
    },
    "combined": {
      "roi": "0.0041",
      "apy": "0.0499"
    },
    "finality": "finalized"
  },
  "range": {
    "epoch": { "start": 407453, "end": 414202 },
    "timestamp": { "start": 1763285975, "end": 1765877974 }
  }
}

Evaluation Windows

Choose a window that matches the reporting period, and use the same value for every comparison. See the APY & ROI API reference.

Longer evaluation windows provide more stable APY estimates. Short windows are heavily influenced by luck (block proposals, MEV).

APY vs BeaconScore

Metric	Use Case	Affected By
APY	Absolute return calculation	Luck (proposals, MEV), network conditions
BeaconScore	Performance comparison	Primarily validator behavior (normalized for luck; some residual factors remain)

A validator with lower APY might still have a higher BeaconScore if they were unlucky with block proposals. BeaconScore largely removes luck from the equation, making it ideal for comparing operator performance. Some residual luck factors can still influence scores over short windows.

Best Practices

Use 30d+ Windows

Short windows are noisy. Use 30 days or longer for meaningful APY estimates.

Track EL Separately

EL rewards (MEV) are highly variable. Track them separately from CL rewards.

Compare Apples to Apples

When comparing validators, ensure they use the same MEV-boost configuration.

Use BeaconScore for Ranking

For comparing validator quality, BeaconScore is more reliable than APY.

Monitor Validator Performance — BeaconScore metrics
Analyze Missed Rewards — Quantify lost earnings
Calculate Validator Rewards — Detailed reward breakdowns

Introduction

V2 API Docs

V1 API Docs

Overview

Understanding the Metrics

Quick Start: Fetch APY & ROI

Response

Evaluation Windows

APY vs BeaconScore

Best Practices

Use 30d+ Windows

Track EL Separately

Compare Apples to Apples

Use BeaconScore for Ranking

​Overview

​Understanding the Metrics

​Quick Start: Fetch APY & ROI

​Response

​Evaluation Windows

​APY vs BeaconScore

​Best Practices

Use 30d+ Windows

Track EL Separately

Compare Apples to Apples

Use BeaconScore for Ranking

​Related Resources

Overview

Understanding the Metrics

Quick Start: Fetch APY & ROI

Response

Evaluation Windows

APY vs BeaconScore

Best Practices

Related Resources