# UFC Stats Scraper - Fight Results, Strikes, Takedowns & Odds (`datawright/ufc-stats-scraper`) Actor

UFC fights with winner, method (KO/TKO, submission hold, decision), round, time and DraftKings odds; per-fighter fight stats (knockdowns, sig. strikes by target/position, takedowns, control time); events and fighter profiles (reach, stance, gym). Any event, date range or season.

- **URL**: https://apify.com/datawright/ufc-stats-scraper.md
- **Developed by:** [Datawright](https://apify.com/datawright) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 row of data

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## UFC Stats Scraper - Fight Results, Strikes, Takedowns & Odds

**UFC data** as clean JSON, CSV or Excel - flat rows, ready for models and spreadsheets:

- 🥊 **Fights** - every bout with **winner, method** (KO/TKO, submission with the hold, decision type), **round and time**, weight class, card segment, bout order and **DraftKings odds**: opening and closing moneyline, rounds over/under
- 📊 **Fight stats** - one row per fighter per fight: **knockdowns, total and significant strikes** (by head/body/leg and distance/clinch/ground), **takedowns**, reversals, submission attempts and **control time** - plus the fighter's reach, height, stance, age, gym and the **method-of-victory odds** (KO/TKO, submission, decision)
- 📅 **Events** - every card with venue, city, number of fights and the main-event result
- 👤 **Fighters** - profiles: nickname, record, weight class, height, reach, stance, age, nationality, gym

Latest event, any date range or **a whole season** (including Dana White's Contender Series). Built for **MMA betting models, fantasy MMA, fight analytics, journalism and AI agents**. No API key, no browser.

### Quick start

The latest event:

```json
{
  "dataType": "fights"
}
```

Every fight stat line of the season, main cards only:

```json
{
  "dataType": "fightStats",
  "season": "2026",
  "mainCardOnly": true
}
```

One fighter's fights over several years:

```json
{
  "dataType": "fightStats",
  "dateFrom": "2024-01-01",
  "fighters": [
    "Malott"
  ]
}
```

The next card with opening odds:

```json
{
  "dataType": "fights",
  "includeUpcoming": true
}
```

### Output

Fight row:

```json
{
  "eventId": "600060773",
  "event": "UFC Fight Night: Buckley vs. Malott",
  "eventDate": "2026-10-17T21:00Z",
  "venue": "Meta APEX",
  "city": "Las Vegas, USA",
  "fightId": "401919643",
  "boutOrder": 13,
  "cardSegment": "Prelims",
  "weightClass": "Bantamweight",
  "scheduledRounds": 3,
  "isMainEvent": false,
  "status": "Final",
  "completed": true,
  "method": "Submission",
  "methodDetail": "Kimura",
  "endRound": 3,
  "endTime": "4:19",
  "fighter1": "Cody Chovancek",
  "fighter1Id": "5282412",
  "fighter1Record": "9-1-0",
  "fighter1Country": "Canada",
  "fighter1Moneyline": -125,
  "fighter1MoneylineOpen": -148,
  "fighter2": "SuYoung You",
  "fighter2Id": "5044361",
  "fighter2Record": "17-4-0",
  "fighter2Country": "South Korea",
  "fighter2Moneyline": 105,
  "fighter2MoneylineOpen": 124,
  "winner": "SuYoung You",
  "loser": "Cody Chovancek",
  "result": "win",
  "roundsOverUnder": 2.5,
  "roundsOverOdds": -210,
  "roundsUnderOdds": 160,
  "oddsProvider": "DraftKings"
}
```

Fight-stats row (positional strike breakdowns omitted here for brevity - they are included in your data):

```json
{
  "eventId": "600060773",
  "event": "UFC Fight Night: Buckley vs. Malott",
  "eventDate": "2026-10-17T21:00Z",
  "venue": "Meta APEX",
  "city": "Las Vegas, USA",
  "fightId": "401919643",
  "boutOrder": 13,
  "cardSegment": "Prelims",
  "weightClass": "Bantamweight",
  "scheduledRounds": 3,
  "isMainEvent": false,
  "status": "Final",
  "completed": true,
  "method": "Submission",
  "methodDetail": "Kimura",
  "endRound": 3,
  "endTime": "4:19",
  "fighterId": "5044361",
  "fighter": "SuYoung You",
  "nickname": "Yoo-Jitsu",
  "country": "South Korea",
  "heightIn": 66,
  "reachIn": 65,
  "weightLbs": 135.5,
  "stance": "Orthodox",
  "age": 30,
  "dateOfBirth": "1995-12-11",
  "gym": "Von Jiu Jitsu",
  "record": "17-4-0",
  "opponent": "Cody Chovancek",
  "opponentId": "5282412",
  "outcome": "W",
  "moneyline": 105,
  "moneylineOpen": 124,
  "oddsKoTko": 1400,
  "oddsSubmission": 600,
  "oddsDecision": 185,
  "knockDowns": 0,
  "totalStrikesAttempted": 95,
  "totalStrikesLanded": 82,
  "sigStrikesAttempted": 7,
  "sigStrikesLanded": 5,
  "takedownsAttempted": 8,
  "takedownsLanded": 6,
  "takedownsSlams": 0,
  "takedownAccuracy": 0.75,
  "targetBreakdownHead": 0.8,
  "targetBreakdownBody": 0,
  "targetBreakdownLeg": 1,
  "posBreakdownDistance": 0.667,
  "posBreakdownClinch": 0,
  "posBreakdownGround": 0.75,
  "advances": 0,
  "advanceToHalfGuard": 0,
  "advanceToSide": 0,
  "advanceToMount": 0,
  "advanceToBack": 0,
  "reversals": 1,
  "submissions": 1,
  "slamRate": 0,
  "controlTimeSeconds": 720,
  "sigStrikeAccuracy": 0.714
}
```

`moneyline` is the closing (or current, before the fight) American line; `moneylineOpen` the opening line.

### Pricing

Pay per row delivered - see the **Pricing** tab. A full season is roughly 50 events and 550-650 fights (twice as many fight-stat rows). Use filters, *Max rows* and the run's maximum cost to cap spending.

### FAQ

**Which events?** All UFC events on ESPN: numbered cards, Fight Nights and Dana White's Contender Series.

**How fresh?** Results and stats appear minutes after each fight; odds are DraftKings' as published on ESPN.

**Round-by-round stats?** Fight totals are included; round-by-round splits are not.

### Disclaimer

Not affiliated with, endorsed by or connected to the UFC, ESPN or DraftKings. Provides publicly available factual fight results and statistics. It only reads publicly accessible data and grants you no rights in it: you are responsible for making sure your use complies with the data source's terms of use and applicable laws (including copyright, database and privacy laws).

# Actor input Schema

## `dataType` (type: `string`):

Choose the shape of the data.

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

Whole year, e.g. "2026". Leave empty and use dates instead (or neither for the latest event).

## `dateFrom` (type: `string`):

YYYY-MM-DD. Overrides season.

## `dateTo` (type: `string`):

YYYY-MM-DD, inclusive.

## `lastEvents` (type: `integer`):

With no season or dates: the N most recent events.

## `includeUpcoming` (type: `boolean`):

Also return the next scheduled card (with opening odds).

## `events` (type: `array`):

Keep only events whose name contains any of these, e.g. UFC 334, Fight Night, Contender.

## `fighters` (type: `array`):

Keep fights involving these fighters (partial names are fine).

## `weightClasses` (type: `array`):

e.g. Lightweight, Women's Strawweight.

## `mainCardOnly` (type: `boolean`):

Skip the prelims.

## `onlyCompleted` (type: `boolean`):

Drop scheduled fights.

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

Stop after this many rows (0 = no limit).

## Actor input object example

```json
{
  "dataType": "fights",
  "lastEvents": 1,
  "includeUpcoming": false,
  "mainCardOnly": false,
  "onlyCompleted": false,
  "maxItems": 200
}
```

# 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 = {
    "maxItems": 200
};

// Run the Actor and wait for it to finish
const run = await client.actor("datawright/ufc-stats-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 = { "maxItems": 200 }

# Run the Actor and wait for it to finish
run = client.actor("datawright/ufc-stats-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 '{
  "maxItems": 200
}' |
apify call datawright/ufc-stats-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datawright/ufc-stats-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/z7wpTOMsLLdadQryD/builds/3s0sOERgOxaY6Rkbl/openapi.json