Sports Scores & Betting Odds API: NFL, NBA, MLB, NHL, Soccer

Get sports scores, schedules and betting odds as clean JSON: one row per game for the NFL, NBA, MLB, NHL, WNBA, college football and basketball, the Premier League, La Liga, Serie A, Bundesliga, Ligue 1, MLS, the Champions League and more. Each row has the matchup, start time, live or final score, period scores, venue, TV channels, and the posted odds: point spread, over/under total, and moneylines for home, away and (in soccer) the draw, with the opening line next to the current one. Data comes from ESPN's public scoreboard. No login, no API key, no browser. $1.00 per 1,000 games.

Why this one

• Scores and odds in one row. No second call to join a game to its line: homeTeam.score, awayTeam.score, odds.spread, odds.overUnder, odds.homeMoneyline are in the same record.
• Opening and current lines. odds.open holds the opening spread, total and moneylines, so you can see line movement without running a scheduler.
• Past, live and future days. Pick a date range to pull final scores for backtesting or upcoming games with odds for a model. Leave the dates empty for the current scoreboard.
• 21 leagues, one input. Multi-select the leagues; every row says which league it came from.
• Plain HTTP, no proxy needed. It reads ESPN's public JSON from Apify's servers and was tested from Apify's datacenter IPs.
• You cap the cost. maxGames limits the rows, and a maximum total charge on the run stops it cleanly.

Minimal input

{"leagues": ["nfl", "nba"], "maxGames": 50}

An empty input runs a built-in example: the current scoreboard of one league, at most 5 games.

Sample output row

A real row from ESPN's NFL scoreboard on 2026-10-21 (before kickoff, so no score yet):

{
  "league": "nfl",
  "leagueName": "NFL",
  "sport": "football",
  "eventId": "401873010",
  "name": "New England Patriots at Chicago Bears",
  "shortName": "NE @ CHI",
  "startTime": "2026-10-23T00:15:00Z",
  "status": "scheduled",
  "statusDetail": "Thu, October 22nd at 8:15 PM EDT",
  "period": null,
  "clock": null,
  "season": 2026,
  "week": 7,
  "neutralSite": false,
  "venue": {"name": "Soldier Field", "city": "Chicago", "state": "IL", "country": "USA"},
  "broadcasts": ["Prime Video"],
  "homeTeam": {"id": "3", "name": "Chicago Bears", "shortName": "Bears", "abbreviation": "CHI", "score": null, "record": "4-2", "winner": null, "linescores": [], "rank": null},
  "awayTeam": {"id": "17", "name": "New England Patriots", "shortName": "Patriots", "abbreviation": "NE", "score": null, "record": "4-2", "winner": null, "linescores": [], "rank": null},
  "odds": {
    "provider": "Draft Kings",
    "details": "CHI -3",
    "favorite": "CHI",
    "spread": -3.0,
    "overUnder": 50.5,
    "homeMoneyline": -155,
    "awayMoneyline": 130,
    "drawMoneyline": null,
    "homeSpreadOdds": -102,
    "awaySpreadOdds": -118,
    "overOdds": -115,
    "underOdds": -105,
    "open": {"homeMoneyline": -120, "awayMoneyline": 100, "drawMoneyline": null, "homeSpread": -1.5, "awaySpread": 1.5, "homeSpreadOdds": -105, "awaySpreadOdds": -115, "total": 47.5, "overOdds": -110, "underOdds": -110}
  },
  "espnUrl": "https://www.espn.com/nfl/game/_/gameId/401873010/patriots-bears",
  "scrapedAt": "2026-10-21T15:50:02Z",
  "input": "nfl"
}

What does Sports Scores & Betting Odds API do?

• Reads ESPN's scoreboard for each league you choose, for today or for each day of a date range.
• Returns one flat, typed row per game: scores as numbers, times in ISO 8601 UTC, odds as numbers (American moneylines such as -155 and +130).
• Marks each game scheduled, in progress, final, postponed, canceled, suspended, forfeit or abandoned, with ESPN's own text in statusDetail ("Final/OT", "Halftime", "5:12 - 3rd Quarter").
• Optionally keeps only games that have odds posted (onlyWithOdds).

Typical uses: sports betting models and odds comparison inputs, fantasy and DFS research, score and schedule widgets, Discord and Telegram bots, sports data for LLM agents, historical results for backtests, line-movement tracking (schedule it daily and compare odds).

Leagues

Input value	League
nfl, nba, mlb, nhl, wnba	NFL, NBA, MLB, NHL, WNBA
college-football	NCAA football, FBS (all games of the day)
mens-college-basketball, womens-college-basketball	NCAA basketball, Division I
eng.1, eng.2	English Premier League, Championship
esp.1, ita.1, ger.1, fra.1	La Liga, Serie A, Bundesliga, Ligue 1
usa.1, mex.1	MLS, Liga MX
ned.1, por.1, sco.1	Eredivisie, Primeira Liga, Scottish Premiership
uefa.champions, uefa.europa	Champions League, Europa League

Also accepted as shortcuts: epl, mls, ncaaf, ncaab, ncaaw, laliga, serie-a, bundesliga, ligue-1. UFC and golf are not included in this version: they have fight cards and leaderboards, not home/away games.

Input

Field	Type	What it does
leagues	list of choices	One or more leagues from the table above. Prefilled with nfl and nba.
dateFrom	date, YYYY-MM-DD	First day (ESPN schedule day, US Eastern). Empty with an empty dateTo means the current scoreboard.
dateTo	date, YYYY-MM-DD	Last day. Empty means the same day as dateFrom. Up to 92 days, one request per day per league.
onlyWithOdds	yes/no	Default no. Keep only games with odds posted.
maxGames	number	Default 500 (prefill 10). Stops after this many rows in total; also your cost cap.
requestDelaySeconds	number	Pause before each request, default 0.2.
proxyConfiguration	object	Optional Apify Proxy. Default none; ESPN answers Apify's servers without it.

{
  "leagues": ["nfl"],
  "dateFrom": "2026-10-25",
  "dateTo": "2026-10-26",
  "onlyWithOdds": true,
  "maxGames": 50
}

What "current scoreboard" returns

With no dates, ESPN returns its default window for each league: today's games for the NBA, NHL, MLB and soccer leagues, and the whole current week for the NFL and college football (for example the NFL's week 7, Thursday to Monday). Use dates when you need an exact window.

Output

One row per game. Every key is always present; a value is null when it does not apply.

• Game: league, leagueName, sport, eventId, name, shortName, startTime, status, statusDetail, period, clock, season, week, neutralSite, venue (name, city, state, country), broadcasts, espnUrl.
• Teams: homeTeam and awayTeam, each with id, name, shortName, abbreviation, score, record, winner, linescores (points or goals per quarter, half, period or inning) and rank (college poll rank).
• Odds: odds with provider, details, favorite, spread (from the home team's side: negative means the home team is favored), overUnder, homeMoneyline, awayMoneyline, drawMoneyline, homeSpreadOdds, awaySpreadOdds, overOdds, underOdds, and open with the opening values of the same lines.
• Run info: scrapedAt and input (the league that produced the row).

What to expect in each field:

• Scores are null before a game starts, period is null until play begins, and clock is filled only while a game is in progress. winner is set once a game is final.
• Odds are null when ESPN shows no line for the game. ESPN posts odds for upcoming and live games and usually drops them after the game ends, so past dates mostly give scores without odds. Lower leagues and far-future games often have none. Use onlyWithOdds to skip those.
• Odds come from the sportsbook ESPN names in odds.provider, one provider per game. This is not a multi-book comparison.
• drawMoneyline is filled for soccer only.
• season is ESPN's season number (the 2026-27 NBA season is 2027). week is filled for the NFL and college football.

Empty input runs the built-in example: the current scoreboard of the first of NFL, NBA, NHL, MLB, Premier League, college football or MLS that has games, at most 5 rows. The input prefill (nfl and nba, 10 games) runs the same way with a limit of 10.

Pricing

Pay per event: $1.00 per 1,000 games ($0.001 per game), charged for each game row written to the dataset. Platform usage is included in that price; you pay nothing else for this Actor. Apify subscribers on the Silver plan pay 15% less and Gold 30% less.

Worked example: a full NFL week (about 14 games) is $0.014. A whole 380-game Premier League season is $0.38, and a full 1,230-game NBA regular season is $1.23. Pulling today's NBA, NHL and MLB boards every morning is roughly 15 games, about $0.45 a month.

Set maxGames or a maximum total charge on the run and the Actor stops cleanly when it is reached; everything collected up to that point is kept.

Limits

• Data is as fresh as ESPN's scoreboard, which updates live scores within seconds to a minute. Schedule the Actor to poll; it is not a push feed.
• One request per league per day. ESPN's scoreboard no longer accepts date ranges in one call, so the Actor asks for each day separately. A 30-day range for 3 leagues is 90 requests, usually under a minute. Ranges are capped at 92 days.
• Odds are limited to what ESPN publishes: one provider, with spread, total and moneylines. No player props, no alternate lines, no line history beyond the opening line.
• College football returns FBS games, college basketball Division I games. Smaller divisions are not included.
• ESPN can change its JSON. If a field disappears, rows still come back with it null and the run does not fail.

Use with Python

# pip install apify-client
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("datagleaner/sports-scores-odds").call(
    run_input={"leagues": ["nfl"], "onlyWithOdds": True, "maxGames": 20}
)
for g in client.dataset(run["defaultDatasetId"]).iterate_items():
    o = g["odds"]
    print(g["shortName"], g["startTime"], o["details"], "total", o["overUnder"])

This run returns at most 20 games, so it costs at most $0.02.

Use with JavaScript / Node.js

// npm install apify-client
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('datagleaner/sports-scores-odds').call({
    leagues: ['nba'],
    dateFrom: '2026-10-20',
    dateTo: '2026-10-21',
    maxGames: 20,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
for (const g of items) console.log(g.shortName, g.status, g.awayTeam.score, g.homeTeam.score);

Use it from n8n, Make, Zapier or an AI agent

Actor ID: datagleaner/sports-scores-odds

Minimal input:

{"leagues": ["nfl", "nba"], "maxGames": 20}

Each tool below runs this Actor with your own Apify API token.

• n8n: add the Apify node (@apify/n8n-nodes-apify). On n8n Cloud you install it from the community node registry. Choose Run an Actor and get dataset, set Actor to datagleaner/sports-scores-odds and paste the input above.

• Make: use the Apify app's Run an Actor module, then Get Dataset Items to read the results. Watch Actor Runs can trigger a scenario when a run finishes.

• Zapier: use the Apify action Run Actor, then the search Fetch dataset items. The trigger Finished Actor run starts a Zap when a run ends.

• AI agents (MCP): connect to https://mcp.apify.com?tools=datagleaner/sports-scores-odds. Without a token, an agent can still find the Actor with the search-actors tool, but running it needs your Apify account. In Claude Code:

    claude mcp add --transport http apify "https://mcp.apify.com?tools=datagleaner/sports-scores-odds"
  

  Then run /mcp to sign in to Apify in your browser. Or pass a token instead:

    claude mcp add --transport http apify "https://mcp.apify.com?tools=datagleaner/sports-scores-odds" --header "Authorization: Bearer YOUR_APIFY_TOKEN"
  

  Claude Desktop, Cursor and other clients that use an mcpServers config can run the server locally:

  {
      "mcpServers": {
        "actors-mcp-server": {
          "command": "npx",
          "args": ["-y", "@apify/actors-mcp-server"],
          "env": { "APIFY_TOKEN": "YOUR_APIFY_TOKEN" }
        }
      }
    }
  

  Then ask in plain language, for example: "Use the sports scores and odds Actor to get this week's NFL games with spread, total and moneylines, and give me a table of matchup, kickoff time, favorite and over/under."

• LangChain (Python):

# pip install langchain-apify, then set APIFY_TOKEN in your environment
import json
from langchain_apify import ApifyActorsTool
tool = ApifyActorsTool("datagleaner/sports-scores-odds")
result = tool.invoke({"run_input": json.loads('{"leagues": ["nfl"], "maxGames": 20}')})

FAQ

Is this a sports odds API? It works as one: call it through the Apify API, the clients above or MCP and get JSON back. It needs no ESPN account and no sportsbook key, only an Apify account. The odds are the lines ESPN publishes from one sportsbook, not a feed from many books.

How do I get NFL odds for this week? Set leagues to ["nfl"], leave the dates empty and turn on onlyWithOdds. You get each game's spread, total and moneylines, plus the opening line in odds.open.

How do I get NBA scores for a date range? Set leagues to ["nba"], dateFrom and dateTo. Past games come back as final with scores and period scores in linescores. Odds are mostly empty for finished games.

Why is odds null? ESPN shows no line for that game: it is finished, too far ahead, or in a league without odds. Upcoming games in the major leagues almost always have one.

What does a negative spread mean? spread is from the home team's side. -3.0 means the home team is favored by 3 points. details repeats it in ESPN's wording, such as "CHI -3", and favorite names the favored team.

Can I track line movement? odds.open against the current odds shows the move since the line opened. For more, schedule the Actor (hourly or daily) and compare runs by eventId.

How do I get live scores? Run the Actor on a schedule for today's date. Games in progress show status: "in progress", period, clock and the running score.

Is it legal to use? The Actor reads public data that ESPN serves without a login. You are responsible for how you use it, including ESPN's terms for any redistribution and the gambling laws where you live.

Responsible use

The data is public and provided for analysis, research and display. It is not betting advice, and odds can change or be wrong; check a sportsbook before you rely on a line. If gambling is a problem for you or someone you know, call 1-800-GAMBLER in the US. This Actor is not affiliated with or endorsed by ESPN or any league or sportsbook, and the names are used only to say where the data comes from.