SoccerAnalytics

Category · 19 articles

Stat Explainers

What the numbers actually measure, in plain language.

Every few years a new metric jumps from analytics Twitter to the broadcast graphics, usually with no explanation of what it means or how it was built. This is where those metrics get unpacked — not just the definition, but the data and the maths underneath, and the situations where each one quietly misleads you.

If you've ever wondered how an expected-goals model is actually trained, why raw tackle counts flatter passive teams, or what PPDA is really counting, start here.

  1. Do Football Goals Follow a Poisson? Testing the Standard Model on All 64 Games of 2022

    Every scoreline prediction in football rests on the Poisson. We fit it to all 64 games of 2022 — it gets the shape right, but real goals are overdispersed.

    · 7 min read

  2. Aerial Duels and Heading Data: Reading Win Rate Without Getting Fooled by Volume

    Aerial-duel win percentage, why raw counts mislead, and where aerial dominance actually matters — set pieces, target men, and defending crosses.

    · 6 min read

  3. Expected Points (xPts): Turning Shot-Level xG Into a Fairer Table

    Expected points (xPts) simulates a match from its shot-level xG to get win, draw and loss odds — points that reward chances created, not goals that went in.

    · 7 min read

  4. Goalkeeper Distribution and Playing Out From the Back: Reading the Numbers Behind Buildup

    Short versus long goalkeeper distribution, launch %, pass completion under pressure, and how a keeper's distribution choices shape a team's buildup.

    · 6 min read

  5. Field Tilt as Territorial Dominance: Measuring Who Owns the Final Third

    How field tilt is actually computed from event data — the measurement choices nobody documents, what the number predicts, and the three ways it fails.

    · 8 min read

  6. The Long Throw-In: A Set Piece Hiding in Plain Sight

    A long throw-in into the box functions like a corner you can take from anywhere down the touchline. Why it works, and the xG case for and against it.

    · 7 min read

  7. Game-State Effects on Stats: How the Scoreline Bends Possession, Shots, and xG

    A field guide to score effects in the data you actually have: which metrics are worst hit, how to spot the distortion without event data, and what survives.

    · 9 min read

  8. PPDA and Pressing Intensity: Reading the Number That Measures How Hard a Team Presses

    A PPDA number lands in front of you. Which way does the scale run, what counts as high, and what can you honestly conclude from it?

    · 7 min read

  9. Possession Value and VAEP Explained: Scoring Every Action on the Pitch

    xG only values shots. Possession-value models score every action - a pass, a carry, a tackle - by how much it changes the odds of scoring. How VAEP works.

    · 7 min read

  10. Defensive Actions: Why Tackle and Interception Counts Mislead

    A defender who makes lots of tackles might be badly positioned. Why raw tackle and interception counts mislead, and how to read defensive actions in context.

    · 6 min read

  11. Field Tilt and Territory Explained: Whose Final Third Is the Game Being Played In?

    You can dominate the ball and still play it nowhere dangerous. Field tilt measures territory — whose final third the game is actually being played in.

    · 7 min read

  12. SCA and GCA Explained: Crediting the Two Moves Before a Shot

    Shot- and goal-creating actions credit the two moves before a shot; expected assists and expected threat measure the creativity raw assist counts miss.

    · 13 min read

  13. Game State and Score Effects: Why You Can't Read Match Stats Without the Scoreline

    A team dominating possession might just be losing. Why you can't read match stats without the scoreline — and how good analysis adjusts for game state.

    · 6 min read

  14. Set-Piece xG Explained: Why Corners Feel Deadly and Mostly Aren’t

    Corners feel dangerous and mostly aren't: what a set piece's expected-goals value really is, and the trade-offs of zonal, man and hybrid marking.

    · 14 min read

  15. xGChain and xGBuildup Explained: Crediting the Whole Possession

    Most of the players who create a goal never touch it last. xGChain and xGBuildup credit the whole possession - here's how they work and who they reveal.

    · 6 min read

  16. Expected Goals (xG) Explained: The Stat That Changed How We Watch Football

    A plain-language guide to expected goals — what xG measures, how the model is trained on shot features like distance and angle, and how to read it.

    · 5 min read

  17. Possession-Adjusted Stats: Why Raw Tackle Counts Lie

    Raw tackle and interception counts mostly measure how little a team has the ball. Possession-adjustment fixes that: the problem and a worked example.

    · 7 min read

  18. PPDA Explained: How Analysts Quantify the Press

    PPDA - passes allowed per defensive action - is how analysts put a number on pressing. What it measures, exactly how it is computed, and where it misleads.

    · 7 min read

  19. Progressive Passes and Carries: The Stats Behind Ball Progression

    Progressive passes and carries measure who actually moves the ball toward goal. The definitions, and why centre-backs and deep midfielders dominate.

    · 6 min read