# Sports Scores & Odds Monitor — 19 Leagues, Live (`brick_joey_yto/sports-scores-odds-monitor`) Actor

Live scores, results, standings and betting odds across 19 leagues — EPL, La Liga, NFL, NBA, MLB, NHL, tennis, UFC, F1 and more. Unified JSON from official keyless APIs — no login, no API key. Schedule it for live-score monitoring. From $1/1,000 rows.

- **URL**: https://apify.com/brick_joey_yto/sports-scores-odds-monitor.md
- **Developed by:** [William Billings](https://apify.com/brick_joey_yto) (community)
- **Categories:** Developer tools, Automation, News
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$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/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

## Sports Scores & Odds Monitor — 19 Leagues, Live Data

Live scores, results, standings and betting odds across **19 leagues in one unified schema** — the Flashscore/livescore data feed without the scraping fragility. Powered by official keyless APIs: **no login, no API key, no headless browser.**

Covers soccer (Premier League, La Liga, Serie A, Bundesliga, Ligue 1, MLS, Liga MX), NFL, NCAAF, NBA, NCAAB, WNBA, MLB, NHL, ATP/WTA tennis, UFC, F1 and PGA — one actor instead of one scraper per sport.

### What you get per event

- **Teams + scores** — home/away names, abbreviations, scores, quarter/period linescores, records, winner flag
- **Live status** — `pre` / `in` / `post` state plus detail ("2nd Half 67'", "Final", "Top 5th")
- **Betting odds** — provider, spread details, over/under, home/away/draw moneylines where published
- **Venue + broadcasters** — stadium, city, TV networks
- **Standings rows** — rank, W/L/T, points, differential, streak + full stat map per team

### Modes

| Mode        | What it returns                                             |
| ----------- | ----------------------------------------------------------- |
| `scores`    | Today's events across chosen leagues (default = all 19)     |
| `live`      | Only in-progress games right now — for real-time monitoring |
| `results`   | Finished games by `date`, plus `daysBack` for date ranges   |
| `odds`      | Events that carry betting lines (spread, O/U, moneyline)    |
| `standings` | League tables — W/L/T, points, differential, full stats     |
| `watch`     | Events filtered to your teams (name or abbreviation match)  |

### Example input

```json
{
  "mode": "scores",
  "leagues": ["epl", "nfl", "nba"],
  "date": "2026-10-03"
}
```

```json
{
  "mode": "watch",
  "teams": ["Arsenal", "Lakers", "Chiefs"],
  "leagues": ["epl", "nba", "nfl"]
}
```

```json
{ "mode": "results", "leagues": ["epl"], "date": "2026-09-28", "daysBack": 6 }
```

### Use cases

- **Live-score monitoring** — schedule `live` mode and feed a real-time event stream to your app, bot or dashboard
- **Betting research** — `odds` mode returns spreads, totals and moneylines for scheduled games across leagues
- **Results pipelines** — `results` + `daysBack` backfills finished games for models and archives
- **Team tracking** — `watch` on your club(s) across all competitions, on a schedule
- **Standings sync** — league tables with full stat maps, refreshed daily

### Why this actor

Single-sport scrapers force you to run a different actor per league, and UI-scrapers break whenever the site changes. This monitor reads the same official keyless feed ESPN serves its own site — stable schema, no Cloudflare, one row format across every sport. **$0.001/row.**

### Notes

- Odds appear only where the league/provider publishes them — many scheduled pro games have them; lower-tier events may not
- Tennis/F1/Golf events are matches/races nested under tournaments — they're normalized into the same row shape
- Rows are emitted per event per league; schedule frequent `live` runs for near-real-time latency

### Example output

```json
{
  "recordType": "event",
  "league": "epl",
  "leagueName": "Premier League",
  "eventId": "401879268",
  "name": "Leeds United at Arsenal",
  "date": "2026-10-10T11:30Z",
  "status": "STATUS_SCHEDULED",
  "statusState": "pre",
  "statusDetail": "Sat, October 10th at 7:30 AM EDT",
  "completed": false,
  "home": {
    "id": "359",
    "name": "Arsenal",
    "abbreviation": "ARS",
    "score": "0",
    "record": "4-0-1",
    "winner": false,
    "linescores": []
  },
  "away": {
    "id": "357",
    "name": "Leeds United",
    "abbreviation": "LEE",
    "score": "0",
    "record": "2-3-0",
    "winner": false,
    "linescores": []
  },
  "venue": "Emirates Stadium",
  "venueCity": "London"
}
```

### Pricing

Pay per dataset row — **$1 per 1,000 results**. No subscriptions, no setup fees; you only pay for rows returned.

### FAQ

**Does Sports Scores & Odds Monitor need a login or API key?** No — every row comes from public endpoints. Provide a proxy only if your network is heavily rate-limited.

**How do I monitor on a schedule?** Attach the actor to an Apify Schedule (daily/weekly) and use the watch/monitor mode if present — each run emits a fresh, diff-able dataset.

**What does each row contain?** See the output fields table above; every row carries a `scrapedAt` timestamp so datasets can be deduped across runs.

**Is it legal to scrape this data?** The actor only accesses publicly available data — the same pages/APIs a browser sees. Scraping public data for research, monitoring, and analysis is common practice, but platform Terms of Service and the rules in your jurisdiction still apply to how you use it. Consult legal counsel for your specific case.

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# Actor input Schema

## `mode` (type: `string`):

scores = today's events per league · results = finished games (past days via daysBack) · live = in-progress right now · odds = events with betting lines · standings = league tables · watch = filter events by team names.

## `leagues` (type: `array`):

League codes to include — empty means all 19. Codes: epl, laliga, seriea, bundesliga, ligue1, mls, ligamx, nfl, ncaaf, nba, ncaab, wnba, mlb, nhl, atp, wta, ufc, f1, pga.

## `date` (type: `string`):

YYYY-MM-DD — used by scores/results/odds/watch. Empty = today.

## `daysBack` (type: `integer`):

Results mode only — also fetch this many days before `date` (0 = just that day).

## `teams` (type: `array`):

Watch mode only — team names or abbreviations (e.g. 'Lakers', 'Arsenal', 'KC'). Matches either side.

## `season` (type: `integer`):

Standings mode only — season year override (e.g. 2025). Empty = current season.

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

Cap on total rows emitted.

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

Not usually needed — the source API is public and permissive. Only set this if your region blocks it.

## Actor input object example

```json
{
  "mode": "scores",
  "leagues": [
    "epl",
    "nfl",
    "nba"
  ],
  "daysBack": 0,
  "teams": [
    "Arsenal",
    "Lakers"
  ],
  "maxResults": 500
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset containing event, standing and error rows

# 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 = {
    "leagues": [
        "epl",
        "nfl",
        "nba"
    ],
    "teams": [
        "Arsenal",
        "Lakers"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("brick_joey_yto/sports-scores-odds-monitor").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 = {
    "leagues": [
        "epl",
        "nfl",
        "nba",
    ],
    "teams": [
        "Arsenal",
        "Lakers",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("brick_joey_yto/sports-scores-odds-monitor").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 '{
  "leagues": [
    "epl",
    "nfl",
    "nba"
  ],
  "teams": [
    "Arsenal",
    "Lakers"
  ]
}' |
apify call brick_joey_yto/sports-scores-odds-monitor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,brick_joey_yto/sports-scores-odds-monitor"
        }
    }
}
```

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/fYt2V3rjtlNhkenkA/builds/POVrIP0OS49yyJftm/openapi.json