# Sportlots Scraper - Sports Card Marketplace Listings (`lulzasaur/sportlots-scraper`) Actor

Scrape sports card listings from Sportlots.com. Search by player, set, or keyword and get card title, player, year, set, card number, condition/grade, lowest price, per-seller prices, quantity, seller feedback, listing URL, and image.

- **URL**: https://apify.com/lulzasaur/sportlots-scraper.md
- **Developed by:** [lulz bot](https://apify.com/lulzasaur) (community)
- **Categories:** E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 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

## Sportlots Scraper

Scrape sports card listings from **[Sportlots.com](https://www.sportlots.com)** — one of the largest online sports card marketplaces, with 80+ million cards across baseball, football, basketball, hockey and more.

Search by player, set, or any keyword and export structured data: card title, player, year, set, card number, condition/grade, lowest price, per-seller prices, quantities, seller feedback, listing URL, and image.

### What you get

**Summary mode** (default) — one record per unique card:

| Field | Description |
|-------|-------------|
| `query` | The search term that produced the record |
| `title` | Full card title (set + card info) |
| `player` | Player name parsed from the listing |
| `year` | Release year parsed from the set |
| `set` | Set name (e.g. "Bowman Chrome") |
| `cardNumber` | Card number (e.g. "157") |
| `variation` | Parallel / variation label, if any |
| `lowestPrice` | Lowest available price (number) |
| `lowestPriceText` | Lowest price as displayed (e.g. "$8.02") |
| `totalQuantity` | Total copies available across all sellers |
| `imageUrl` | Card image URL (null if no image) |
| `url` | Link to the card's detail page on Sportlots |
| `scrapedAt` | ISO timestamp of when the record was scraped |

**Detail mode** (`scrapeDetails: true`) — one record per individual seller listing, adding:

| Field | Description |
|-------|-------------|
| `seller` | Seller username |
| `sellerFeedback` | Seller feedback count |
| `condition` | Condition/grade (e.g. "Near Mint") |
| `conditionShort` | Short condition code (e.g. "NM") |
| `price` | This seller's price (number) |
| `priceText` | This seller's price as displayed |
| `quantityAvailable` | Quantity this seller has |
| `notes` | Seller notes on the listing |
| `hasFrontPic` / `hasBackPic` | Whether the seller uploaded card photos |

### Input

```json
{
    "searchQueries": ["Mike Trout", "2012 Bowman Chrome"],
    "maxResults": 100,
    "scrapeDetails": false,
    "proxyConfiguration": { "useApifyProxy": false }
}
```

- **searchQueries** — list of player names, set names, or keywords.
- **maxResults** — cap on total records (0 = unlimited). In detail mode each seller listing counts as one record.
- **scrapeDetails** — set `true` to expand each card into per-seller listings with condition, exact price, and seller info.
- **proxyConfiguration** — optional. Sportlots has no anti-bot protection, so a proxy is not required.

### How it works

Sportlots is a classic server-rendered site backed by a clean JSON AJAX API. The Actor resolves a search session id, pages through the result grid, and (in detail mode) pulls each card's per-seller inventory. No browser rendering is needed, so runs are fast and cheap.

### Use cases

- Card price research and arbitrage (compare against eBay / PSA / PriceCharting).
- Building sports-card price databases and alerting bots.
- Tracking inventory and pricing for specific players or sets.

### Pricing

Pay-per-result: a small charge per dataset item plus a tiny per-run start fee. You only pay for the cards you scrape.

# Actor input Schema

## `searchQueries` (type: `array`):

One or more search terms to run against Sportlots. Each can be a player name, set name, or free-text keyword (e.g. 'Mike Trout', '2012 Bowman Chrome', 'Michael Jordan rookie').

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

Maximum number of records to scrape across all queries. Set to 0 for unlimited. When 'Scrape per-seller details' is on, each seller listing counts as one record.

## `scrapeDetails` (type: `boolean`):

If enabled, opens each card to fetch every seller's individual listing (condition/grade, exact price, quantity, seller name and feedback). If disabled, returns one summary row per card with the lowest price and total quantity. Enabling this is slower and produces more records.

## `proxyConfiguration` (type: `object`):

Proxy settings. Sportlots has no anti-bot layer, so a proxy is not required. Enable Apify Proxy only for very large runs.

## Actor input object example

```json
{
  "searchQueries": [
    "Mike Trout"
  ],
  "maxResults": 100,
  "scrapeDetails": false,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

# 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 = {
    "searchQueries": [
        "Mike Trout"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("lulzasaur/sportlots-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 = { "searchQueries": ["Mike Trout"] }

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

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

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

```

## CLI example

```bash
echo '{
  "searchQueries": [
    "Mike Trout"
  ]
}' |
apify call lulzasaur/sportlots-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=lulzasaur/sportlots-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/UVcQS5xJBRgiHDzFY/builds/gSwBmiCjGh3ROXd5a/openapi.json