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Expected Goals (xG): The Football Metric Changing Analysis, Betting, and Fan Engagement 

By: Joaquim Matcham
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Expected Goals, or xG, is a breakthrough football analytics metric that was pioneered by Stats Perform and calculates the probability of each chance resulting in a goal being scored. By providing an objective assessment of shot quality using advanced AI and historical data, xG gives teams, bettors, and fans deeper insight into match results and on-field performance.

What Is Expected Goals (xG)

Expected Goals, abbreviated as xG, estimates the likelihood that any chance becomes a goal. Leveraging advanced machine learning trained on nearly one million historical shots, xG integrates over 20 variables such as distance from goal, angle, defensive pressure, and goalkeeper location. Each shot is rated from 0 (no chance) to 1 (certain goal).

For example:

  • A penalty carries an xG of 0.76
  • A shot from 30 yards might have an xG of 0.03

Adding up these values over a game or season shows whether a team or player should have scored more or less, revealing patterns invisible in traditional goal counts.

Why Does xG Matter

  • For Football Analytics: xG exposes the real quality of chances created and conceded, giving a clearer picture of performance than basic stats.
  • For Coaches and Analysts: xG pinpoints tactical strengths and weaknesses, helping optimise strategy and training.
  • For Media and Fans: xG enriches commentary, highlights dominant or unlucky teams, and brings data-driven storytelling to life.
  • For Betting and Bookmakers: Bookmakers use xG to set odds and markets that reflect actual chance quality, powering smarter and more engaging bets.

The AI Power Behind Opta’s xG

Opta uses proprietary AI technology to analyse up to 20 context factors per shot, including assist type, goalkeeper position, and whether the shooter was under pressure. This ensures xG values mirror match realities and offer maximum predictive value for professionals, operators, and fans.

For women’s football, Opta’s specialised models use unique competition data to ensure accuracy for the women’s game, reflecting different scoring and tactical patterns.

Real Match Example

Consider the recent Premier League clash on April 21st, 2025, where Tottenham Hotspur faced Nottingham Forest, ending with a 2-1 victory for Forest. Opta’s xG metrics show Tottenham generated 2.14 expected goals, reflecting their dominance with 22 shots and 6 on target. However, their low conversion rate left them with just 1 goal. Nottingham Forest, with only 4 shots and 3 on target, achieved an xG of 0.48 but capitalised efficiently, scoring 2 goals. This discrepancy highlights how xG can reveal Tottenham’s missed opportunities and Forest’s clinical finishing, offering fans and coaches valuable insights into the match dynamics.

How xG Powers Football Betting

Sportsbooks and oddsmakers use goal expectancy models like xG as a signal to build and track the probabilities underpinning their models. Sportsbooks are also increasingly displaying live xG within their apps to help bettors quickly gauge whether one team has an underlying superiority that might not be reflected in the actual score. Equally if a player generates high xG but has not yet scored, informed bettors may see increased opportunity that he or she will get further chances to find the net.

How Fans and Media Use xG

Commentators, fantasy leagues, and digital fan platforms rely on xG for deeper engagement:

  • Pundits and coaches use xG to explain performances and quantify how lucky or unlucky they were in the game.
  • Fantasy players use xG to help evaluate a player’s quality in front of goal, especially if it signals that they’re over or underperforming.
  • Social platforms buzz with hashtags like #xG as a concise, objective way for fans to debate team selections and player performances, driving wider conversation and data literacy

The Future of Football Analytics

Opta is developing advanced metrics like Expected Goals on Target, (xGOT), and Expected Threat (xT), delivering sharper insights into finishing, creation, and match momentum. These developments are reshaping betting, coaching, and fan engagement worldwide.

Want to bring advanced analytics to your site, broadcast, or team and player analysis? Contact Stats Perform to explore Opta APIs for authoritative, real-time football data that sets your coverage apart.

xG measures chance quality, letting betting operators price markets by actual probabilities rather than guesswork.

Opta’s model uses a vast historical dataset and considers more context variables than competitors, leading to best-in-class accuracy.

Not directly, but over time, teams with higher xG tend to score more, allowing for smarter analysis and betting.

Opta’s xG is available via APIs, stat widgets, and real-time feeds for clubs, platforms, and fans.