Using Betting Data and Statistics Sites: Best Resources for Bettors

A practical guide to the best football data sites -- Understat, FBref, WhoScored, and more -- and how to use their statistics for smarter betting.

intermediate7 min readLast updated: March 5, 2026Editorial Team
ET

Editorial Team

Betting Expert

Key Takeaways

  • ✓Free data sites like Understat, FBref, and WhoScored provide the same underlying data bookmakers use -- the edge is in how you interpret it.
  • ✓Expected goals (xG) is the most valuable single metric for football betting -- it measures chance quality rather than just results.
  • ✓Combine multiple data sources: use xG from Understat, passing data from FBref, and match context from Transfermarkt for a complete picture.
  • ✓Historical data lets you spot regression candidates -- teams overperforming xG are due for a correction, creating value on opponents.
  • ✓Data without context is noise. Always pair statistics with match-watching and qualitative factors like injuries and managerial changes.

Data-driven betting starts with knowing where to find the numbers. The good news: the most valuable football statistics are available for free.

Top Free Football Data Sites

Understat

Best for: Expected goals (xG), expected assists (xA), shot maps

Covers the top five European leagues plus the Russian Premier League. Understat's xG model is one of the most cited in football analytics. Use it to compare a team's xG to their actual goals -- the gap reveals over- or underperformance.

FBref (powered by StatsBomb)

Best for: Comprehensive stats, passing data, defensive actions

The most complete free football statistics database. FBref provides per-90 stats, advanced possession metrics, and shot-creating actions. The StatsBomb xG model is considered industry-leading.

WhoScored

Best for: Player ratings, match event data, team form

WhoScored aggregates match statistics and provides composite player ratings. Useful for quick form checks and head-to-head history.

Transfermarkt

Best for: Squad values, injuries, transfers, contract information

Not a pure statistics site, but essential context. Knowing a team is missing three key players or just signed a new striker changes your assessment of the odds.

Football-Data.co.uk

Best for: Historical results, odds data, CSV downloads

Offers match results and closing odds from major bookmakers going back decades. Perfect for backtesting betting strategies.

How to Apply Data to Betting

Step 1: Identify Regression Candidates

Teams significantly over- or underperforming their xG will typically regress. A team with 10 goals from 6.5 xG is scoring at an unsustainable rate.

Step 2: Compare to Market Odds

Check whether the bookmaker's odds reflect the underlying data. If the market prices an overperforming team as strong favourites, value may lie on the opponent or the draw.

Step 3: Layer Multiple Data Points

Do not rely on a single metric. Combine xG, defensive quality (xGA, PPDA), home/away splits, and injury context for a rounded view.

Building a Simple Data Workflow

  1. Download weekly xG data from Understat or FBref
  2. Calculate xG difference (xG - actual goals) for each team
  3. Flag teams with extreme positive or negative differences
  4. Cross-reference with upcoming fixtures and bookmaker odds
  5. Bet only when your data-informed view diverges meaningfully from the market

Frequently Asked Questions

What are the best free football data sites for betting?+
The top free resources are Understat (xG data for top European leagues), FBref (comprehensive stats powered by StatsBomb), WhoScored (ratings and match data), and Transfermarkt (squad values, injuries, transfers). Each offers unique data angles.
What is xG and why does it matter for betting?+
Expected goals (xG) measures the quality of chances created, assigning each shot a probability of being scored based on distance, angle, and assist type. A team creating 2.5 xG but scoring 1 goal is unlucky. Over time, results tend to regress toward xG, creating betting value.
Is paid data worth buying for betting?+
For most recreational bettors, free data is sufficient. Paid sources like Opta, StatsBomb, or InStat provide more granular data (event-level, player tracking) that is valuable for model-building but overkill for casual analysis.
How do I use statistics to find value bets?+
Compare a team's underlying metrics (xG, xGA, shot quality) to their actual results. If a team has conceded few goals but has a high xGA, their defence is likely to regress -- back more goals in future matches. The market often prices based on recent results, not underlying quality.
Can I build a betting model with free data?+
Yes. Many profitable bettors use spreadsheets fed by free data from FBref and Understat. A basic model might use xG, xGA, home/away splits, and recent form to generate probability estimates for match outcomes, then compare to bookmaker odds.

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