# GOAT Sneaker Price Scraper (`spry_frame/goat-scraper`) Actor

Scrapes sneaker listings and size-by-size pricing from GOAT.com — lowest price, instant ship, last sold, retail price, release date, and more. No API key required.

- **URL**: https://apify.com/spry\_frame/goat-scraper.md
- **Developed by:** [COSENT GROUP](https://apify.com/spry_frame) (community)
- **Categories:** E-commerce, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## GOAT Sneaker Price Scraper

Extract sneaker listings and pricing from [GOAT.com](https://www.goat.com) — the world's largest authenticated sneaker marketplace. Search by keyword, brand, gender, and price range. Filter for in-stock or under-retail deals. Export to JSON, CSV, or Excel.

No GOAT account or API key required.

### What it scrapes

Each listing includes:

| Field | Description |
|---|---|
| `title` | Full sneaker name including colorway (e.g. *Air Jordan 1 Retro High OG 'Chicago'*) |
| `brand` | Brand name (Nike, Adidas, New Balance, etc.) |
| `silhouette` | Shoe model / silhouette line |
| `gender` | men / women / youth |
| `releaseDate` | Original release date (YYYY-MM-DD) |
| `retailPriceCents` | Original retail price in cents |
| `lowestAskCents` | Current lowest ask price in cents |
| `instantShipCents` | Lowest instant-ship price in cents |
| `inStock` | Whether any size is currently listed |
| `underRetail` | Whether the lowest ask is below retail |
| `pictureUrl` | Product image URL |
| `url` | Direct link to the product page on GOAT |
| `scrapedAt` | ISO timestamp of when the record was collected |

> **Note:** All prices are in cents. Divide by 100 to get dollars (e.g. `20500` → `$205.00`).

### Use cases

- **Deal hunting** — filter `underRetailOnly: true` to find sneakers priced below retail
- **Price tracking** — schedule daily runs to monitor a keyword or brand over time
- **Market research** — compare release date vs. current resale price across silhouettes
- **Inventory checks** — use `inStockOnly: true` to see what's actually available to buy

### Input

| Parameter | Type | Default | Description |
|---|---|---|---|
| `keywords` | String | `""` | Search term (e.g. `"Air Jordan 1"`, `"Yeezy 350 V2"`) |
| `brands` | Array | `[]` | Filter by brand. Options: Nike, Jordan, Adidas, New Balance, Asics, Converse, Vans, Puma, Reebok, Salomon, etc. |
| `gender` | String | `""` (All) | `men`, `women`, `youth`, or empty for all |
| `minPriceCents` | Integer | `0` | Minimum lowest-ask price in cents. `0` = no filter |
| `maxPriceCents` | Integer | `0` | Maximum lowest-ask price in cents. `0` = no filter |
| `inStockOnly` | Boolean | `false` | Only return sneakers with active listings |
| `underRetailOnly` | Boolean | `false` | Only return sneakers priced below original retail |
| `sortType` | Integer | `1` | 1 = Most Popular · 2 = Lowest Price · 3 = Highest Price · 4 = Newest Release · 5 = Most Recent |
| `maxResults` | Integer | `100` | Max listings to return. `0` = no limit |

#### Example inputs

**Find under-retail Air Jordan 1s, cheapest first:**

```json
{
  "keywords": "Air Jordan 1",
  "underRetailOnly": true,
  "sortType": 2,
  "maxResults": 50
}
```

**Browse all New Balance releases from newest to oldest:**

```json
{
  "brands": ["New Balance"],
  "sortType": 4,
  "maxResults": 200
}
```

**Find women's sneakers under $150:**

```json
{
  "gender": "women",
  "maxPriceCents": 15000,
  "inStockOnly": true,
  "sortType": 2
}
```

### Output sample

```json
{
  "id": "447905",
  "slug": "air-jordan-1-retro-high-og-chicago-lost-found-dz5485-612",
  "title": "Air Jordan 1 Retro High OG 'Chicago Lost & Found'",
  "brand": "Air Jordan",
  "silhouette": "Air Jordan 1 Retro High OG",
  "gender": "men",
  "releaseDate": "2022-11-19",
  "retailPriceCents": 18000,
  "lowestAskCents": 20500,
  "instantShipCents": 22000,
  "inStock": true,
  "underRetail": false,
  "pictureUrl": "https://image.goat.com/750/attachments/product_template_pictures/images/...",
  "url": "https://www.goat.com/sneakers/air-jordan-1-retro-high-og-chicago-lost-found-dz5485-612",
  "scrapedAt": "2026-08-18T05:50:56.000Z"
}
```

### Notes

- Results match what you'd see on GOAT's website — same ranking, filters, and availability
- GOAT shows ~36 listings per page; the scraper pages automatically until `maxResults` is reached
- Scheduling a run daily or weekly is the best way to track price trends over time

# Actor input Schema

## `keywords` (type: `string`):

Search term (e.g. 'Air Jordan 1', 'Yeezy 350', 'Nike Dunk Low'). Leave empty to browse all sneakers.

## `brands` (type: `array`):

Filter by brand name. Options: Nike, Jordan, Adidas, New Balance, Asics, Converse, Vans, Puma, Reebok, Salomon, etc.

## `gender` (type: `string`):

Filter by gender: men, women, youth, or leave empty for all.

## `minPriceCents` (type: `integer`):

Minimum lowest-ask price in cents (e.g. 10000 = $100). 0 = no filter.

## `maxPriceCents` (type: `integer`):

Maximum lowest-ask price in cents (e.g. 50000 = $500). 0 = no filter.

## `inStockOnly` (type: `boolean`):

If enabled, only returns sneakers that currently have listings available.

## `underRetailOnly` (type: `boolean`):

If enabled, only returns sneakers priced below original retail price.

## `sortType` (type: `integer`):

Sort order for results. 1 = Most Popular, 2 = Lowest Price, 3 = Highest Price, 4 = Newest Release, 5 = Most Recent.

## `maxResults` (type: `integer`):

Maximum number of sneaker listings to return. 0 = no limit.

## Actor input object example

```json
{
  "keywords": "",
  "brands": [],
  "gender": "",
  "minPriceCents": 0,
  "maxPriceCents": 0,
  "inStockOnly": false,
  "underRetailOnly": false,
  "sortType": 1,
  "maxResults": 100
}
```

# Actor output Schema

## `id` (type: `string`):

GOAT internal product template ID.

## `slug` (type: `string`):

URL-friendly product identifier.

## `title` (type: `string`):

Full sneaker name including colorway.

## `brand` (type: `string`):

Brand name (e.g. Nike, Adidas, Jordan).

## `silhouette` (type: `string`):

Shoe model/silhouette (e.g. Air Jordan 1, Yeezy 350).

## `gender` (type: `string`):

men, women, or youth.

## `releaseDate` (type: `string`):

Original release date (YYYY-MM-DD).

## `retailPriceCents` (type: `string`):

Original retail price in cents.

## `lowestAskCents` (type: `string`):

Current lowest ask price in cents.

## `instantShipCents` (type: `string`):

Lowest instant ship price in cents.

## `inStock` (type: `string`):

Whether the sneaker has active listings.

## `underRetail` (type: `string`):

Whether the lowest ask is below retail price.

## `pictureUrl` (type: `string`):

Product image URL.

## `url` (type: `string`):

Direct link to the product page on GOAT.

## `scrapedAt` (type: `string`):

ISO timestamp when this record was collected.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "brands": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("spry_frame/goat-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "brands": [] }

# Run the Actor and wait for it to finish
run = client.actor("spry_frame/goat-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "brands": []
}' |
apify call spry_frame/goat-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,spry_frame/goat-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/MxGOgikyhSxVAMQGO/builds/1FT9pljjc7qHL1K7A/openapi.json