A modern action-valuation framework that scores every on-ball event by how much it changed the probability of the team scoring or conceding within the next 10 actions.
VAEP is a machine-learning framework developed at KU Leuven (Decroos, Bransen, Van Haaren, Davis 2019) that assigns a value to every on-ball action β pass, dribble, tackle, shot. The value is calculated as the change in scoring probability minus the change in conceding probability over the next 10 actions, conditioned on game state.
A through-ball that splits the defence might be worth +0.08 VAEP; a sideways pass in the centre circle might be worth +0.001. Crucially, defensive actions get values too: an interception that prevents a likely scoring attempt is rewarded similarly to a shot that creates one.
VAEP, OBV (Opta's On-Ball Value), and SPADL-derived metrics are all addressing the same problem: xG only values shots, but most football is non-shot actions. VAEP/OBV close that gap by valuing the build-up, the press, the recovery β turning every event into a contribution score. They're increasingly used in scouting and player ratings (FotMob, FBref player pages, club analytics departments).
xG (Expected Goals)
A metric that scores every shot by its probability of resulting in a goal, based on factors like shot location, angle, and assist type.
OBV (On-Ball Value)
A composite metric that assigns a value to every on-ball action β passes, carries, dribbles, shots β based on how much it increases or decreases the probability of scoring.
Progressive Passes
Passes that move the ball significantly closer to the opponent's goal β a key indicator of a team's attacking play style.
Progressive Carries
Ball carries that advance the ball at least 10 yards toward the opponent's goal β measuring a player's ability to drive forward with the ball.
Stat Padding
When a player accumulates impressive-looking numbers in low-leverage situations β late in won/lost games, against weak opponents β without those numbers reflecting genuine impact.
VAEP in Football: Valuing Actions by Estimating Probabilities
VAEP rates every on-ball action by how it changes the probability of scoring or conceding. We explain how it works, what it captures that xG misses, and where to find it.
StatsBomb IQ: A Complete Guide to the Football Analytics Platform
StatsBomb IQ is a paid football analytics platform used by elite clubs and analysts. We explain its features (events, 360, OBV, scouting), pricing tiers, and who should use it.
mplsoccer: The Python Library That Powers Football Visualisations
mplsoccer is the open-source Python library powering most football visualisations on Twitter, Reddit, and analyst blogs. We explain what it does, who built it, and how to start using it.
For informational and educational purposes only. Disclaimer