FollowScores Scraper for football data.

What it collects

• Today’s matches, with each match’s live status and, once it has kicked off, its score.
• Results for every day in a date range of up to 31 days.
• Team profiles: summary, squad, past results and upcoming fixtures.
• Coverage: Süper Lig, 1. Lig, Premier League, Championship, LaLiga, Serie A, Bundesliga, Ligue 1, Eredivisie, Liga Portugal and the UEFA Europa League — 214 teams.

How it works

FollowScores Scraper fetches football data for 11 top European competitions and pushes it to your dataset as structured JSON. There is no browser automation, no HTML parsing and no proxies to manage. Pick one of three modes with option, and it queues exactly the requests that mode needs, respecting your maxItems cap and pay-per-event budget as it goes.

You pick leagues and teams by name in the input form, not by hunting down internal IDs. Each match reports a live status — not_started, in progress or ended — with scores once available at the time of the run. Run the Actor again, or schedule recurring runs on Apify, to refresh your dataset. One selection returns a team’s full profile, with no extra configuration.

Use cases

• Sports dashboard builders — scoreboards and results feeds refreshed through repeated or scheduled Actor runs.
• Fan and fantasy-football apps — team squads, upcoming fixtures and results to power app content.
• Betting-odds and sports-data researchers — structured match and team datasets for modeling.
• Content and media sites — automated match-day and weekly results roundups.
• Data analysts — historical results across a date range for trend and performance analysis.

Competitions and teams

These are the competitions and teams the input form offers, and nothing else can be selected. Pick them by name in the form; through the API, send the ID.

Teams by competition

Each team with the ID the Actor’s input takes.

Input

Set these in the Actor’s input form on Apify, or send them as JSON through the API.

• option — The mode, asked in the form as “What do you want to fetch?”: todayMatches (“1. Today’s matches”, the default), dateRange (“2. Results by date range”) or teamInfo (“3. Team info”). Only the fields under the chosen mode are used. The others are ignored, so it’s safe to leave stale values in them.

Option 1: Today’s matches

Every match being played today across all 11 competitions, or narrowed down to specific leagues. Each match reports its live status and, once kicked off, its running score.

• todayLeagues — Optional league filter, from the 11 competitions. Empty means every league.

Option 2: Results by date range

The same fixture data, but for every day across a range, optionally filtered to specific leagues and teams. A range covers up to 31 days per run, and each day is its own query.

• dateRangeFrom dateRangeTo — Start and end dates, both required for dateRange. Up to 31 days per run.
• dateRangeLeagues — Optional league filter. Empty means every league.
• dateRangeTeams — Optional team filter: only matches involving these teams. Empty means every team.

Option 3: Team info

Pick one or more of the 214 supported teams and get each one’s full profile in one go: summary, squad, past results and upcoming fixtures, with no separate view picker.

• teams — At least one of the 214 teams, required for teamInfo. Each returns its summary, squad, results and upcoming fixtures.

Every mode

These two apply whichever option runs.

• maxItems — Maximum dataset items for the whole run. 0 or empty means unlimited. The input form pre-fills 1,000.
• customMapFunction — Optional JavaScript function that takes each output object and returns a transformed object. It must not be used for filtering. Leave it empty to store items unchanged.

Input tips

Build a live scoreboard

Use todayMatches with no league filter: one query gets every match being played today across all 11 competitions.

Build a results archive

Use dateRange, and set dateRangeLeagues or dateRangeTeams to narrow it down. Filtering happens after the fetch, so it reduces the items stored but not the per-day query cost.

Research specific clubs

Use teamInfo with exactly the teams you need. Each team costs the same four queries regardless of squad size, so batch every team you’re interested in into one run rather than several small ones. Through the API, pass team IDs; this input asks for Galatasaray:

{
  "option": "teamInfo",
  "teams": [
    "3061"
  ]
}

Output

Each run writes its results to an Apify dataset. Every item carries queryType, the query that produced it, and inputSource, the date or ID that was queried; everything else is the underlying data, untouched. Today’s matches and date-range results store one item per match. Team info items carry fields that vary by view. In Apify Console, the dataset’s Overview shows match rows as Kickoff, League, Home, Away, Status, Query and Input columns, and team info items fill fewer of them.

These are the main fields of an item.

• queryType — The query behind the item: todayMatches, dateRangeResults, team:summary, team:squad, team:results or team:upcoming.
• inputSource — The date or team ID that was queried.
• fixtureID seasonID — Match and season IDs.
• competitionID competitionName countryName — The league and its country.
• homeTeamID homeTeamName awayTeamID awayTeamName — Both teams.
• status startTime — not_started, in progress or ended, with score fields once a match has kicked off; kickoff in ISO 8601.
• teamID teamFullName teamName — On a team summary, the team’s ID, full name and short name.
• noResults — true when a query came back empty. The item then carries only queryType and inputSource.

{
  "fixtureID": "10000001",
  "competitionID": "17",
  "competitionName": "Premier League",
  "countryName": "England",
  "seasonID": "100001",
  "homeTeamID": "1001",
  "homeTeamName": "Example Home FC",
  "awayTeamID": "1002",
  "awayTeamName": "Example Away FC",
  "status": "not_started",
  "startTime": "2026-10-03T14:00:00Z",
  "queryType": "todayMatches",
  "inputSource": "2026-10-03"
}

{
  "teamID": "1001",
  "teamFullName": "Example Home Football Club",
  "teamName": "Example Home FC",
  "countryName": "England",
  "queryType": "team:summary",
  "inputSource": "1001"
}

{
  "noResults": true,
  "queryType": "team:results",
  "inputSource": "1001"
}

Field reference

Every documented key of a dataset item, with its JSON type.

How to run it

1. Open the Actor on Apify, listed as “Followscores Scraper”, and sign in. You need an Apify account.
2. Fill in the Input tab, then click Start.
3. When the run finishes, open the Output tab and click Export to download the dataset as JSON, CSV or another format.

Or send the same input to the Apify API. This call runs the Actor and returns its dataset items. Replace $APIFY_TOKEN with the API token from your Apify Console.

curl -X POST \
  "https://api.apify.com/v2/actors/batscrape~followscores-scraper/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"option":"todayMatches"}'

The call waits up to 300 seconds. For a longer run, start it asynchronously and read the dataset when it finishes. Read the Apify API reference.

New to Apify? See how BatScrape Actors run on Apify. To run it on a schedule, or send results on when a run finishes, see schedules and webhooks.

Pricing

Pay per event. Each run is charged an Actor start event, then a list query for today’s matches, for each day of a date range, and for each of a team’s squad, results and upcoming fixtures, and a single-item query for each team’s summary. Each dataset item stored is charged as well. Every query and item is checked against the run’s charge budget before it’s spent, so a run stops cleanly instead of overspending. See current rates on Apify .

Limitations

• Only the 11 competitions and 214 teams listed in the input form are covered.
• A date range covers at most 31 days per run, and each day is a separate query. League and team filters reduce stored items, not those queries.
• Team info always runs four queries per team: summary, squad, results and upcoming.
• Team info fields vary by view; inspect a run’s dataset for the full shape. An empty squad, results or upcoming view is stored as a noResults item, not an error.
• Match items gain score fields once a match has kicked off. The README does not name them, so inspect a run’s dataset for their keys.
• A run stops when it reaches maxItems or your charge budget.

FAQ

Answers from the Actor’s README on Apify.

Why did a run return few or no results?

Check these first:

• maxItems: the run stops once it’s reached.
• The charge budget: a run that can’t afford another dataset item stops cleanly rather than erroring.
• For dateRange, that both dateRangeFrom and dateRangeTo are set. Both are required.
• For teamInfo, that at least one team is picked in teams.

Why does team info cost more than I expected?

Team info always queues four queries per team, one for the summary and three list queries for the squad, results and upcoming fixtures, regardless of how much data comes back. That is on top of each run’s Actor start charge.

How do I keep the cost of a run down?

Three settings help:

• Use todayLeagues, dateRangeLeagues or dateRangeTeams to reduce stored items. For dateRange, this doesn’t reduce the per-day query charge.
• Keep date ranges as short as you need: every extra day is another query.
• Set maxItems to a hard cap that matches your budget.

Why is some team data missing?

team:squad, team:results and team:upcoming can legitimately come back empty for a team with no current squad data, no past results yet this season, or no fixtures scheduled. This is stored as { noResults: true, … }, not an error.

Related reading

• What to check before budgeting an Actor run — Understand the questions behind a scraping budget: the Actor’s current pricing, your input limits, sample output, and the effect of retries or incomplete runs.
• Planning predictable output for our Apify Actors — How we’re approaching output schemas for BatScrape: explicit fields, example records, and clear change notes before consumers build on a dataset.
• Planning a scraper around the data you need — A practical starting checklist for a scraping task: define the records, inspect a sample, identify useful fields, and make the output easy to validate.
• How to use BatScrape Actors on Apify — Run an Actor in Apify Console or through the API, export its dataset, schedule runs and pass results to automation tools.

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