StashSage for POE2

v0.5.14 (07/29/2026)

Machine Learning by Budodude

Web Scraping by NocKtuRn4L

Auto ML to instantly price for Path of Exile 2 items.

Join our Discord and try the free API!

Download for Windows (.zip) Download Linux Build (.zip) Join Discord

Windows portable ZIP: extract the whole ZIP to a folder, then run StashSage.exe from there. Keep StashSage.exe and the _internal folder together; create a shortcut if you want it on your desktop.

Requires approximately 2.2 GB of disk space on Windows.

No data is ever shared with StashSage; all operations are local to your desktop.

StashSage prediction overlay showing price estimates and comparable Path of Exile 2 items

Top 10 Mods for Item Value

Browse trained models (collapsed by default)
Importances are normalized per model. Values shown as percentages.

Why StashSage

Does this sound like you?

  • You pick up items that could be good, but aren't quite sure
  • Your stash fills up with "I'll price this later" items
  • Pricing through the in-game trade UI feels tedious, so you avoid it
  • Typing mods, comparing rolls, and overthinking prices takes more effort than it's worth
  • You don't need a perfect price - you just want a smart starting point
  • One hotkey, instant comparable items, list it, and get back to mapping

No Single Ground Truth

There is no single "right" answer for an item's price. Demand changes with every league and patch, so yesterday's completed sales may not represent today's market.

Trading Reality

The data we see is from items that haven't yet sold. Expensive listings linger while good deals disappear, so raw trade results are noisy and unreliable on their own. If anything, they may represent a price ceiling.

How We Measure Value

StashSage focuses on practical shortcuts instead of perfect accuracy. We look for tools that help you:

  • Judge a reasonable listing price in seconds.
  • Track and encode market dynamics.
  • Avoid obvious price trolls or stale posts.
Bottom line: our goal is faster choices. If you spend less time scrolling trade listings and more time playing, the system is doing its job, even if some items never sell.

Explore Features

Discord API

  1. Select or hover over the item in game for which you'd like to see price predictions.
  2. Press CTRL+C to copy the item's in-game description.
  3. Paste the description to StashSage Serve bot in our Discord channel to receive your predictions.
  4. Note: some features such as mod value filtering and visualizations not available on Discord API

Discussion

  1. Models are trained on current, unsold listings, so the data can be noisy. Even reasonably priced items may not sell.
  2. Models #1 (XGBoost) and #2 (KNN) use different approaches, so their predictions may sometimes disagree. Both provide useful perspectives on an item's potential value.
  3. The Model #1 visualization shows how an item's predicted value compares with other items in the same category.
  4. XGBoost is a tree-based model that evaluates the value of each modifier and how modifiers interact with one another. It uses patterns from all items in the dataset—their modifiers and listed prices—to estimate how the target item's complete set of stats may affect its value.
  5. KNN uses XGBoost's modifier weighting to identify the items in the dataset most similar to the target item. These “nearest” items do not need to match perfectly; they can still provide useful comparisons even when some modifiers differ. The mean and median prices of these comparable items are then used to estimate the target item's value.
  6. Careful when using Model #2 (knn) to price items with less than 6-mods, comparing to 6-m items can be tricky. Ask yourself, is a 4-m item more similar to (a) a 4-m item with the same 4-m but very different values, or (b) a 5-m item with 3 of the exact same mods and values, and 2 non-overlapping mods?
  7. Models trained to price rare items, not magic or unique.
  8. Overlay is optimized for Windowed Fullscreen only.
  9. New models trained every few days and posted for download.

Notes

  1. The model ignores "mark of the abyssal lord", "allocates passive", "on corruption" mods.
  2. The model ignores socketables as they are not considered an underlying modifier.
  3. Items with quality and socketables have had their modifier values normalized to their base values.
  4. Armour, evasion, energy shield mods are represented in the base stat values.

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