# Pro Football Reference Passing Stats Scraper (`parseforge/pro-football-reference-scraper`) Actor

Scrapes NFL passing statistics from Pro Football Reference for a given season. Returns each player as a flat row with completions, yards, touchdowns, and more.

- **URL**: https://apify.com/parseforge/pro-football-reference-scraper.md
- **Developed by:** [ParseForge](https://apify.com/parseforge) (community)
- **Categories:** Sports, News, Other
- **Stats:** 4 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $19.00 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#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

[![ParseForge](https://raw.githubusercontent.com/ParseForge/apify-assets/main/banner.jpg)](https://apify.com/parseforge?fpr=vmoqkp)

### Pro Football Reference Passing Stats Scraper

**Scrape NFL passing stats from Pro Football Reference by season, up to a million records per run.** Every row includes the player, team, completions, yards, touchdowns, and passer rating. No login or API key. Export to CSV, JSON, Excel, or XML.

Pro Football Reference has no official API, the site sits behind a Cloudflare challenge, and building your own scraper means handling that plus page structure changes and rate limits. This Actor reads the passing stats table from the most recent archived snapshot of the page, season by season, and returns each player's row in one fixed schema. Filter by season and cap the number of records to keep runs fast.

| Who uses it | What they scrape Pro Football Reference for |
|---|---|
| Fantasy football analysts | Which quarterbacks are trending up or down this season |
| Sports journalists | Season passing leaderboards for articles and infographics |
| Data scientists | Historical passing data for model training and trend analysis |
| NFL fans and hobbyists | Personal stat tracking and comparison across seasons |

### What it does

This Actor collects NFL passing statistics from Pro Football Reference for a given season and returns each player as a flat row.

- 🏈 **Season selector:** pick any NFL season from 1932 to the current year.
- 📊 **Flat rows:** every player comes back as one record with all passing columns.
- ⚡ **Fast and simple:** one input field for season, one for max records, no complex setup.
- 📁 **Multiple exports:** download as CSV, JSON, Excel, or XML from the dataset tab.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

### What you can do with Pro Football Reference data

**📈 Track quarterback performance.**

A fantasy analyst scrapes the 2024 passing stats to see which quarterbacks are outperforming their draft position.

**📰 Build season leaderboards.**

A sports journalist pulls the latest season's passing yards and touchdowns to publish a weekly top-10 list.

**🤖 Train prediction models.**

A data scientist collects passing stats from 2000 to 2024 to train a model that predicts player fantasy points.

**📊 Compare historical eras.**

An NFL historian scrapes passing stats from 1970 and 2020 to compare how the game has changed.

### Why choose this scraper

| | What you get |
|---|---|
| **No API key needed** | Scrape public stats without registering an app or dealing with OAuth. |
| **One fixed schema** | Every run returns the same columns, so your pipeline never breaks. |
| **Season by season** | Pull a single year or loop over many seasons for historical data. |
| **Up to a million rows** | Set maxItems high enough for every passer in a season, or low for a quick sample. |

### How it compares

No other Store actor targets Pro Football Reference the same way, so the honest comparison is with the alternatives teams actually weigh.

| | Pro Football Reference Passing Stats Scraper | Build it in-house | By hand |
|---|---|---|---|
| Setup | Run it now, zero config | Days of engineering | None, but hours per pull |
| When Pro Football Reference changes | Maintained for you | You fix it | You re-learn the page |
| Proxies, retries, anti-bot | Built in | Your problem | Browser only |
| Output | Fixed JSON schema, CSV/Excel export | Whatever you build | Copy-paste |
| Cost | Pay per result | Engineering time | Analyst hours |

### Configure the run

Drive the Actor with a season year and a maximum record count, and it returns the passing stats table for that season. The Input tab lists every parameter.

A first run with the defaults:

```json
{
 "season": "2024",
 "maxItems": 10
}
```

A larger pull:

```json
{
 "season": "2024",
 "maxItems": 200
}
```

### Pricing

Pay-per-result: **$0.021 per result** collected. You pay only for the results written to your dataset.

| Results collected | Approximate cost |
|---|---|
| 100 results | $2.10 |
| 1,000 results | $21.00 |
| 10,000 results | $210.00 |

New Apify accounts start with $5 in free credit.

### Free users

Free-plan runs return up to 10 results as a preview. [Upgrade your Apify plan](https://console.apify.com/sign-up?fpr=vmoqkp) to collect up to 1,000,000 results per run.

### Run it

1. [Create a free Apify account with $5 in credit](https://console.apify.com/sign-up?fpr=vmoqkp).
2. Open the [Pro Football Reference Passing Stats Scraper](https://apify.com/parseforge/pro-football-reference-scraper?fpr=vmoqkp).
3. Set your inputs and any filters, then click **Start**.
4. Export the results as CSV, Excel, JSON, or XML from the **Dataset** tab.

Run it programmatically through the [Apify API](https://docs.apify.com/api/v2) (`run-sync-get-dataset-items`) or the [ApifyClient](https://docs.apify.com/api/client/js) for JavaScript and Python.

### Use with AI agents (MCP)

Give an AI agent access to Pro Football Reference season stats through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

```bash
claude mcp add --transport http apify "https://mcp.apify.com/?tools=parseforge/pro-football-reference-scraper"
```

Then prompt it in plain language to run the scraper and read back the results.

### Troubleshooting

**Why am I getting no results?**

Check that the season you entered exists on Pro Football Reference. The site has data back to 1932, but if you enter an invalid year like 1800 or 2030, the table may be empty. Also ensure maxItems is at least 1.

**Why did the run fail with a timeout?**

Pro Football Reference can be slow to respond during peak traffic. Try increasing the Actor's timeout in the run settings, or run it at a less busy time.

**Why are some player names missing or garbled?**

The site occasionally changes its HTML structure. If you see missing fields, try running again later. If the problem persists, report it on the Actor's issues page.

**Can I get more than passing stats?**

This Actor is designed for passing stats only. For rushing, receiving, or defensive stats, you would need a different scraper or a custom solution.

**Why is my dataset smaller than expected?**

Check the maxItems setting. If it is lower than the number of players in the season, the Actor stops early. Increase maxItems to get the full table.

### FAQ

| Question | Answer |
|---|---|
| What data does this Actor return? | It returns the passing stats table from Pro Football Reference for the season you choose. Each row is one player and includes columns like completions, attempts, yards, touchdowns, interceptions, and passer rating. |
| Do I need an API key or login? | No. The Actor reads publicly archived snapshots of pro-football-reference.com pages. You only need an Apify account to run it. |
| Can I scrape multiple seasons at once? | The Actor takes one season per run. To get multiple seasons, run it once per season, or use Apify's scheduler or an integration to loop over a list of years. |
| What is the maximum number of records I can get? | You can set maxItems up to 1,000,000. A single NFL season has far fewer passers, so the full table will be returned unless you set a lower cap. |
| Which seasons are supported? | Any completed season with an archived snapshot. Pro Football Reference has passing stats back to 1932, and the Actor returns whatever that season's page shows. |
| What formats can I export the data in? | From the Apify dataset tab you can download the results as CSV, JSON, Excel, or XML. You can also use the API to get JSON directly. |
| Does this Actor scrape rushing or receiving stats? | No, this Actor is focused on passing stats only. For other stat types, you would need a different scraper or a custom solution. |
| Is web scraping Pro Football Reference legal? | Scraping public data is generally allowed, but you should review the site's terms of service and respect their robots.txt. This Actor only reads publicly available pages. |
| How often is the data updated? | Pro Football Reference blocks direct automated access, so the Actor reads the most recent publicly archived snapshot of the page instead. Completed seasons are stable and accurate. A season still in progress can lag the live site by weeks, so this is not the right tool for same-day results. |
| Can I schedule this Actor to run automatically? | Yes, you can set up a schedule in Apify to run it at any interval. Because the source is an archived snapshot rather than the live page, a weekly or monthly schedule makes more sense than a daily one. |

### Related actors

Browse the full [ParseForge collection](https://apify.com/parseforge?fpr=vmoqkp) for more scrapers.

🆘 **Need help?** Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ **Disclaimer.** This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Sports Reference LLC. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.

# Actor input Schema

## `season` (type: `string`):

NFL season year to scrape (e.g. 2024, 2023, 2022)

## `maxItems` (type: `integer`):

How many records to collect per run.

## Actor input object example

```json
{
  "season": "2024",
  "maxItems": 10
}
```

# Actor output Schema

## `results` (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 = {
    "season": "2024",
    "maxItems": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("parseforge/pro-football-reference-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 = {
    "season": "2024",
    "maxItems": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("parseforge/pro-football-reference-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 '{
  "season": "2024",
  "maxItems": 10
}' |
apify call parseforge/pro-football-reference-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,parseforge/pro-football-reference-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/EwzShySlJlCFNHVf4/builds/GGIiWclClHrRmGr08/openapi.json