AI Summary
5 min read"Just because you don't have the ball or just because you're not close to the goal necessarily in this moment, you do not have a potential threat on the opposition." That is the core insight behind FIFA's match momentum visualization, a live graphic that debuted prominently during the 2026 World Cup broadcasts. In this episode, FIFA data scientists Juan Busso and Aaron Ackerman explain how they built a metric that captures the true flow of a match — and why simple possession stats miss most of the story.
What match momentum actually measures
Match momentum is not a measure of who has the ball. It is a measure of who is creating danger, regardless of possession. The metric is built on a "layer cake" of calculations, all derived from a single data source: player tracking data captured at 50 frames per second (every 20 milliseconds). No event data — no pass counts, no shot tallies — is used.
Continue reading the full summary in the app — free to try.
Read Full Summary →Free • No credit card required
Never miss an episode of From First Principles
Get every new episode summarized in your inbox — free, ~5 minutes to read.
No spam. Unsubscribe anytime.
What you'll learn
- 1 Timestamped Navigation Outline
- 2 (00:30) **Introduction & Guest Setup** - Host Lester Nare introduces the episode, guests Juan Busso (Senior Football Data Scientist) and Aaron Ackerman (Team Lead for Football Performance Analysis), and frames the conversation around FIFA's match momentum visualization
- 3 (03:22) **How FIFA's Data Science Team Operates** - Juan and Aaron describe their roles within FIFA and how data science integrates with football expertise and broadcast production
- 4 (06:55) **The Problem Match Momentum Solves** - The team explains what motivated the development of match momentum and the storytelling gap it fills
- 5 (10:44) **Definition: Threat Metric as the Foundation** - Juan explains the layered architecture of the threat metric that underlies match momentum
- 6 (13:08) **How Momentum is Derived from Threat** - Juan explains the algorithm that converts frame-by-frame threat into the momentum visualization
- 7 (14:55) **Data Sources and Processing Architecture** - The team describes which data feeds into match momentum versus the broader FIFA data ecosystem
+ Full timestamped outline available in the app
Show Notes
In this special interview episode, Lester Nare speaks with Juan Busso, Senior Football Data Scientist at FIFA, and Arron Ackerman, FIFA’s Team Lead for Football Performance Analysis, about the data science behind the Match Momentum visualization featured throughout the 2026 World Cup.
What does “momentum” actually mean in football—and how can it be measured without reducing the game to possession or shots? Juan and Arron explain how FIFA translates football principles into mathematical models, validates those models with coaches and technical experts, and turns complex tracking data into a graphic that fans can understand at a glance.
We break down the underlying “threat” model, including kinetic pitch control, player speed and acceleration, ball trajectories, defensive spacing, distance to goal, sight lines, and the creation of space. Match Momentum is calculated from player-tracking data captured 50 times per second, allowing the model to recognize when a team is becoming dangerous even without dominating possession.
The conversation also covers FIFA’s wider data ecosystem—including event data, skeletal tracking, and the connected match ball—why offside positioning can still create threat, whether hydration breaks alter momentum, and the next generation of football analytics focused on player energy and physical effort.
Guests
Juan Busso — Senior Football Data Scientist, FIFA
Arron Ackerman — Team Lead, Football Performance Analysis, FIFA
Support the show
Donate: FFPod.com/donate
Follow: @FFPod on X / Instagram / TikTok / Facebook
More from this podcast
From First Principles →