# Maximum time to leave

### 📌 **What is it?**

This metric shows the **maximum estimated time** a node could remain in the active validator set **before potentially being rotated out**, based on current network conditions.

It is displayed in a **human-readable format** (e.g.`9 days, 3 hours`) and is designed to offer a reference for both:

* **Node Operators**, to anticipate their potential exit from the active set.
* **Bond Providers**, to gauge when their bonded RUNE could become unlockable if the node exits.

### 🧠 **How is it calculated?**

The estimate is based on:

* The node's **relative age** compared to other currently active nodes.
* The **churn interval**, which occurs approximately every **72 hours**, with an aritificial **additional delay of up to 24 hours** to account for processing time during churn only addded to compute this metric (this additional dealy it's not a THORChain parameter).
* The assumption that **one node** is rotated out per churn cycle.
* The number of nodes **older** than the target node (excluding those who’ve already requested to leave).

The basic formula is:

> number of older active nodes (excluding those marked to leave) × (churn interval + potential delay)

Where:

* **Churn interval** = 72 hours
* **Potential delay** = up to 24 hours per churn
* Nodes who have signaled their intent to leave (`requested_to_leave = true`) are not counted as competition — they will exit at the next churn and effectively shorten the queue ahead of your node.

### ⚠️ **Important disclaimer**

> **This is not a guarantee.**

This value should be seen as a **reference**, not a definitive prediction. The actual time a node remains active can **shorten or extend** due to:

* Nodes voluntarily requesting to leave
* Forced removals or slashing
* Operational delays in churn execution
* Network-level decisions or exceptional events

Because of these factors, **the real unlock window could occur earlier or later** than estimated.

### ✅ **Why it matters**

Understanding this value helps:

* Plan **bonding and unbonding strategies** more effectively
* Anticipate **liquidity availability** for bonded RUNE
* Make **informed operational decisions** regarding node management


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