Under the headlines ESPN runs a working sports database with stable ids for every league, season, game, team and player. Collect that and the scores come along for free.
ScrapeIt runs the ESPN scraper as a managed service. You name the sports, competitions and seasons; we build the pipeline, pace it inside the crawl rules the site publishes, and deliver CSV, JSON, Excel or a load straight into your warehouse.
The plumbing is part of the job, because ESPN answers automated clients unevenly and its edge decides what you see: anti-bot handling, proxy rotation and CAPTCHA solving are included, and we hold the exit region steady so broadcast and odds rows keep their meaning between runs. Nothing behind a sign-in is touched. Player data is professional sporting information about public figures; contact details, injury and medical notes, private life and fantasy users' own profiles stay out. ESPN content is rights-protected, so the output is built for analysis rather than republication - take the use case to your own counsel first, especially where it feeds a betting product.
The event record is the spine of any ESPN data export: event id and uid, sport, league, season year, season type, week or matchday, start time in UTC with the local kickoff kept beside it, the short ATL @ GB form of the name, the long form, and a status block with period, clock, display clock and a state of pre, in or post.
Around that sit the blocks buyers actually ask for:
Team records carry franchise, venue, coaches, groups, depth charts, transactions, awards, season statistics, leaders, ranks, against-the-spread records and odds records. Athlete records carry athlete id, full and display name, jersey, position, height, weight, age, date of birth, birthplace, college, draft round, pick and year, years of experience, active status and current team, with per-season statistics and a game-by-game log behind their own references. Standings arrive as conference groups with divisions nested under them, each row holding wins, losses, ties, percentage, points for and against, and streak. Every row we hand back carries its league, season, season type and collection time, because a score without a season type is a guess, not a fact.
ESPN is not one storefront. The same host serves a different edition depending on where the request lands, switched by country and language parameters and labelled espn-en-us, espn-es-mx, espn-pt-br, espn-en-au and so on, while several editions also answer on their own domains: espn.co.uk, espn.com.au, espn.com.br and africa.espn.com. The switcher carried fourteen storefronts in September 2026, among them a Spanish-language Deportes edition, the UK, Australia, India, the Philippines and five Latin American ones.
The differences are not cosmetic. The UK edition leads with the Premier League, darts and cricket; the Australian edition carries AFL, NRL, NBL, netball and the A-Leagues beside the American sports, and swaps season-long fantasy for tipping games; the Spanish and Portuguese editions translate labels and reorder competitions. Broadcast rows follow the same logic: a Premier League fixture returns US carriers for a US region and nothing at all for a UK one, because those rights are not ESPN's to list there. Listings for a market have to be collected as that market, and we pin that per feed.
Fantasy is a separate system with its own host, path shape and season labels. Games are coded ffl, fba, flb and fhl for football, basketball, baseball and hockey, addressed by season and scoring period, with a public player universe holding roster slots, default position, pro team and ownership percentage. Pick'em, Survivor, Win Totals and Playoff Predictor are versioned by year in their own paths. Individual leagues need a sign-in, so that is where we stop: aggregate ownership is public, managers are not.
ESPN publishes sport, but underneath the articles it runs a working sports database, and that database is the part worth collecting. The public index carries seventeen sports - football, basketball, baseball, hockey, soccer, golf, tennis, racing, rugby, rugby league, cricket, MMA, lacrosse, volleyball, water polo, field hockey and Australian football - and each one holds its own league list, from a single league under Australian football to 219 soccer competitions in September 2026, coded with dots: eng.1, esp.1, ger.1, usa.1, uefa.champions, fifa.world.
Addressing is regular once the shape is clear. Everything hangs off sport, then league, then season, then season type, then a week or a calendar date, then an event. Season types separate preseason, regular season, postseason and off season, and tables exist only for the first two. Playoff rounds are modelled as weeks named Wild Card, Divisional Round, Conference Championship and Super Bowl, so a bracket is rebuilt from round-labelled events rather than read out of a bracket object. Ids are numeric and travel with a compact uid: s:20~l:28~t:9 is a team, where 20 is the football sport and 28 the NFL, while soccer sits under sport 600 with the Premier League as league 700.
Web pages reuse the same ids. A gamecast is /nfl/game/_/gameId/ plus the event id. A club page is /nfl/team/_/name/gb/green-bay-packers, with roster, depth chart, schedule, stats, injuries and transactions tabs beneath it. A player is /nfl/player/_/id/ plus the athlete id, carrying stats, splits, gamelog and bio. Football uses /soccer/match/_/gameId/. The trailing name in the path is decoration; the id is the stable handle.
Get a Quote
Developers
Customers worldwide
Pages extracted
Hours saved for our clients
€199 / one-time
setup fee - included
€169 / mo
setup fee €499
€229 / mo
setup fee €499
€349 / mo
setup fee €499
€549 / mo
setup fee €799
The first reason to scrape ESPN is not the scores, which exist in plenty of places. It is the identity layer underneath them. A single numeric athlete id runs from the fantasy player universe through the match leaders block to the player page; a single team id runs from the scoreboard through standings, depth charts and transactions. Anyone stitching several sports sources together spends most of the budget matching names; starting from ESPN ids turns that into a lookup.
The second reason is breadth from one grammar. The same sport, league, season and event path serves an NFL Sunday, a LaLiga round, an NHL night, a college volleyball fixture and a UFC card, so adding a competition is a configuration change rather than a new collector. That is what makes wide coverage affordable.
The third is material that sports data vendors normally sell separately, sitting in the same payload as the score: broadcast listings, sportsbook lines and a matchup projection with a win percentage for each side. A rights analyst or a media planner needs to know which carrier has a given week's game - Prime Video, FOX, CBS, NBC, Netflix, ABC or ESPN itself - and almost no scores feed carries that.
Historical depth is real but lopsided, and scoping it honestly saves money. The American leagues reach a long way back: the NFL season list starts in the 1920s, baseball earlier still, college football earlier again. Soccer competitions here begin around the turn of the century. Backfill on the deep leagues is a one-off, so the recurring cost is only the live half.
Learn how to use web scraping to solve data problems for your organization
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt is a managed web scraping agency, not a self-serve tool. A named engineer owns the job end to end: scoping the sports and competitions with you, building the extraction, watching it when the site changes shape mid-season, and repairing it before your dashboard notices. Delivery lands on the schedule you asked for, in the format your systems already read, and the support channel is staffed by the people who wrote the collector. Start with a paid sample, test it against what you expect to see, then scale the competition list.
Not in any usable public form. The old documented v1 service refuses requests without a key, and the developer portal that once issued those keys no longer serves anything. The endpoints the site itself calls - the site and core sports hosts, and the fantasy read host - answer without a key, but they are undocumented, unversioned and unsupported; internal host names even leak into their own cross-references. They change without notice and break quietly, so we treat them as one input among several, monitor for shape changes and fall back to page collection. A licensed feed from ESPN or a rights holder is a different product with guarantees attached, and this is not it.
Seventeen sports are addressable, each with its own league list: soccer is by far the deepest at 219 competitions, followed by MMA, rugby, basketball, baseball, golf, hockey, racing and the rest. In practice nobody needs all of it. We agree the competition set at the start - say the four North American majors, college football and basketball, and thirty soccer leagues - and price the live half against that list. Adding a competition later is a configuration change, not a rebuild, because every league sits behind the same path grammar.
Per phase, not uniformly, because that is what keeps the bill sensible. Fixture lists and rosters move on a daily or weekly pass. Odds and lineups tighten in the hours before a start. Live score and event state runs at minute level, and only for the fixtures on your list, then stops the moment a game is final. Completed seasons are collected once and never revisited, since a finished box score never changes. We set the cadence per competition and per phase and show you the request volume each choice implies before anything is built.
CSV, JSON, Excel, Parquet, or a direct push into your warehouse or object storage - Snowflake, BigQuery, Postgres, S3 and GCS are all routine. Events, teams, athletes, standings and incident streams come as separate related tables joined on ESPN ids, so you can load the lot or only the slice you use. Runs are incremental with change records, timestamps are UTC with the local start kept alongside, and the schema is agreed up front and versioned, so a downstream model does not break when we add a column.
We collect what the site renders publicly, at a polite rate, inside the crawl rules it publishes - which on this source means leaving the disallowed soccer lineup, commentary, match-stats and video paths alone and taking those from the competition's own site instead. We do not sign in, so subscriber video and private fantasy leagues are out of scope, and we do not work around geographic restrictions. Athlete records are professional sporting information about public figures; injury and medical notes, contact details and private life are excluded, as are fantasy users' profiles. ESPN content is rights-protected, so the dataset is for analysis, not republication. Bring your use case to your own counsel before the build.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
Scrapeit Sp. z o.o.
10/208 Legionowa str., 15-099, Bialystok, Poland
NIP: 5423457175
REGON: 523384582
