Free Sports Datasets 2026: Open Data for Models & Backtesting
The open datasets we actually point people to in our Discord: play-by-play, historical results, and the rare free source of closing odds.
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Datasets vs APIs: You Probably Need Both
Free sports datasets are static downloads: seasons of play-by-play, decades of results, sometimes historical odds, packaged as CSVs or database files. They are how you train a model, backtest a strategy, or learn a sport's data structure without paying anyone.
What they are not is current. Every dataset ends at its last update, and none of them will tell you tonight's lineup or the odds that just moved. That half of the problem belongs to sports APIs, which is what the rest of this site compares. The typical betting project uses both: open data to build and validate the model, then a live odds API to run it against the market.
This page is the dataset half: the free sources we keep recommending in our Discord because they are maintained, documented, and genuinely free to download. One licensing note before you build a business on any of them: free to download does not always mean free for commercial use or redistribution. Read each dataset's terms; most are short and clear.
For the current season with no download step, several leagues and apps expose a free JSON feed. We tested and documented the ESPN API, the MLB Stats API, NHL API, NFL API, theScore API, Sleeper API, FPL API and F1 API, each with its endpoints, fields and terms.
The Best Free Sports Datasets by Sport
nflverse — NFL Play-by-Play
What you get: Community-maintained NFL play-by-play going back to 1999, plus rosters, schedules, and advanced metrics like EPA, with first-class R and Python packages.
Best for: NFL win-probability and player models. This is the default starting point for football analytics, and the ecosystem around it is the most active of any sport.
football-data.co.uk — Soccer Results With Closing Odds
What you get: Decades of European soccer results across the major leagues, in plain CSVs, with closing odds from multiple bookmakers attached to each match.
Best for: Backtesting betting strategies. Free closing odds are genuinely rare, which makes this the single most useful dataset on this page for betting projects. For odds history beyond soccer, see our historical odds guide.
StatsBomb Open Data — Soccer Event Data
What you get: Professional-grade, event-level soccer data (every pass, shot, and pressure) for selected competitions, including World Cups, released free with an attribution requirement.
Best for: Learning modern soccer analytics on the same data structure the pros use. Coverage is selective rather than comprehensive; treat it as a masterclass, not a complete history.
Football Charts: Soccer Results and Goal Timing, 92 Leagues
What you get: 76,991 matches from 92 club leagues in 42 countries (February 2023 to July 2026) in one 10 MB CSV, with half-time and full-time scores and the minute of every goal. It reaches lower divisions and four women's leagues, it is released under CC BY 4.0, and it comes with a Dixon-Coles starter notebook. It carries no odds.
Best for: Goal-timing and in-play models, and lower-division soccer that most free sources skip. It covers only the last three seasons, so pair it with football-data.co.uk for longer history and closing odds.
Retrosheet — MLB Play-by-Play History
What you get: Volunteer-digitized MLB play-by-play and box scores reaching back over a century, the deepest free historical record in any sport.
Best for: Serious baseball research and long-horizon modeling. Pair it with the Lahman database when you want season-level stats in an easier shape.
Jeff Sackmann — Tennis Match Charting Project
What you get: shot-by-shot records of pro matches, charted by volunteers: 7,566 men's and 4,264 women's matches from the 1960 Roland Garros final to September 2026, one row per point, under CC BY-NC-SA 4.0. The results and rankings repositories (tennis_atp, tennis_wta) returned HTTP 404 when we checked in November 2026, so they are no longer listed here.
Best for: serve and rally analysis, and point-level models. For live scores and rankings, the free routes are on our tennis API page. When your model needs market prices, that is API territory; the directory lists a tennis-focused feed.
MoneyPuck — NHL Shot Data
What you get: Shot-level NHL data with expected-goals values, downloadable per season, from one of the best-known public hockey models.
Best for: xG-based hockey modeling without building your own event pipeline first.
Bet Better: AFL Player Match Statistics
What you get: 206,722 AFL player-match rows (4,670 games, 2000 to 2023) in one 60 MB CSV, with scores, venue, attendance, weather, the full box score, advanced tracking stats like pressure acts and contested one-on-ones, and AFL Fantasy and SuperCoach scores. It is released under CC BY 4.0, so commercial use only needs attribution, and it carries no odds.
Best for: AFL player-prop and fantasy projections, plus weather and venue effects. Check coverage before you train: weather starts in 2010 and the advanced stats in 2012, so the early seasons carry the core box score only. The same publisher runs a free model API, covered in our Bet Better review.
FiveThirtyEight Data Archive
What you get: The archived datasets behind FiveThirtyEight's sports models: soccer SPI ratings, NFL and NBA Elo histories, and forecast data. No longer updated, still downloadable.
Best for: Ready-made team-strength ratings as model features, and studying how a published forecasting operation structured its data.
Kaggle — Community Sports Datasets
What you get: Thousands of community-uploaded sports datasets, searchable by sport, with notebooks showing how others used them.
Best for: Finding a starting point for sports the curated sources above skip. Quality varies widely; check the upload date and provenance before trusting anything for real money.
From Backtest to Live: Adding Odds to Your Data
A betting model is only as good as its comparison to the market, and that comparison needs odds. Free datasets mostly give you results without prices; football-data.co.uk is the notable exception. If your backtest needs closing lines for US sports, opening-to-closing movement, or player prop history, that data lives with commercial providers. Our historical odds guide explains what exists and who carries it.
And once the backtest works, the pipeline flips: you need today's games and live prices, which no static dataset provides. That is when you pick an API. The directory compares every provider we track on free tiers, WebSocket support, sportsbook coverage, and MCP servers, and several offer free tiers generous enough to develop against before you spend anything.
Frequently Asked Questions
Model Built? Time for Live Data
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