Tactics

Football Analytics: Understanding xG, xA, and Modern Metrics

A beginner-friendly guide to football analytics: what xG means, how it is calculated, and how data is changing the way we understand the game.

By Marcus Thompson•9 min read•2026-04-10

What Is xG (Expected Goals)?

Expected Goals (xG) measures the quality of a chance based on historical data. Every shot is assigned a value between 0 and 1 representing the probability of it resulting in a goal.

Example: A penalty has an xG of approximately 0.76 (76% conversion rate historically). A shot from 30 meters out might have an xG of 0.03 (3% chance).

How Is xG Calculated?

xG models use machine learning trained on hundreds of thousands of historical shots. The key variables:

  • Distance from goal: Further = lower xG
  • Angle to goal: Tighter angles = lower xG
  • Body part: Headers are lower xG than feet
  • Assist type: Through balls create higher xG than crosses
  • Game state: Open play vs set piece
  • Goalkeeper position: Is the keeper set or moving?
  • Defensive pressure: Number of defenders between shot and goal

    • Reading xG Data

    Player Level

  • xG vs Actual Goals: If a player scores 20 goals from 15 xG, they're "overperforming" — either very clinical or somewhat lucky
  • Consistent overperformers: Elite finishers (Haaland, Messi) consistently outperform their xG
  • Underperformers: Players scoring well below their xG may be in poor form

    • Team Level

  • xG difference: xG created minus xG conceded = true team quality
  • xG trend: A team creating high xG but not scoring will likely improve
  • Defensive xG: Low xG against = excellent defensive structure

    • Beyond xG: Other Key Metrics

    xA (Expected Assists)

    Measures the quality of chances a player creates, regardless of whether the recipient scores:

  • A player with 3 assists but 10 xA is creating excellent chances that teammates waste
  • xA rewards creation quality, not finishing quality

    • Progressive Passes

    Passes that move the ball significantly (at least 10 meters) toward the opponent's goal:

  • Measures a player's ability to advance play
  • Central midfielders with high progressive passes are "line-breakers"

    • Progressive Carries

    Dribbles that move the ball forward under pressure:

  • Different from progressive passes — requires individual ball-carrying
  • Identifies players who drive forward and beat pressure

    • PPDA (Passes Per Defensive Action)

    Measures pressing intensity:

  • Lower PPDA = more aggressive pressing
  • Average Premier League PPDA: 10-12
  • Liverpool/City when pressing: 6-8 PPDA

    • xT (Expected Threat)

    Measures the increased probability of scoring based on where the ball is moved:

  • A pass from the halfway line to the penalty box increases xT significantly
  • Captures the value of progressive actions that don't end in shots

    • How Clubs Use Analytics

    Recruitment

  • Identifying undervalued players through xG/xA analysis
  • Finding players who create quality regardless of teammate finishing
  • Statistical profiling to find replacement targets

    • Tactical Analysis

  • Identifying where teams are vulnerable (low defensive xG zones)
  • Pressing trigger optimization
  • Set piece design based on delivery zone xG

    • In-Game Decisions

  • Half-time substitution based on underperformance vs xG
  • Real-time pressing intensity adjustment
  • Identifying opponent patterns to exploit

    • The Limitations of Analytics

  • Context blindness: xG doesn't capture emotional moments (derbies, cup finals)
  • Small samples: Individual match xG can be misleading
  • Quality gaps: A Messi shot from 20m is not the same as an average player's shot
  • Defensive metrics lag: Defending is harder to quantify than attacking
  • Can't measure leadership: Intangibles remain unmeasurable

    • How to Access xG Data

    Free sources for fans:

  • FBref.com: Comprehensive player and team xG data
  • Understat.com: Shot maps and xG for top 5 leagues
  • FotMob app: Per-match xG and player ratings
  • StatsBomb (via FBref): Advanced metrics including xA, progressive actions

    • Written by Marcus Thompson, UEFA B Licensed Coach. Methodology based on StatsBomb and Opta xG model documentation.

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