Pass Maps

Definition

Visualizations of passing patterns showing the origin and destination of passes as arrows, lines, or aggregated directional summaries on a pitch representation. Pass maps reveal how a player or team distributes the ball, the preferred directions and distances, and the spatial structure of possession.

History & Origins

Pass maps emerged in the football analytics blogging scene in the early 2010s, as Opta event data (which includes pass origin and destination coordinates) became more accessible to independent analysts. Early pioneers like Colin Trainor and various writers on StatsBomb (the blog, before the company) published detailed pass maps that went far beyond what broadcast graphics offered.

The concept evolved significantly with the introduction of pass sonars (also called pass radars), popularized by Eliot McKinley around 2019–2020. Pass sonars were inspired by wind rose diagrams from meteorology and show the direction and distance distribution of a player's passes as a polar plot, offering a compact fingerprint of a player's passing profile.

StatsBomb (the company) advanced pass visualization further by integrating pass data with their freeze-frame information, allowing analysts to see not just where a pass went but what the defensive setup looked like at the time.

Types

Individual Pass Maps

All passes by a single player in a match or over a season, drawn as arrows from origin to destination. Typically colored by outcome (completed vs. incomplete) or by type (Progressive Passes & Carries|progressive, key pass, cross, etc.).

Progressive Pass Maps

A filtered view showing only Progressive Passes & Carries|progressive passes — passes that move the ball significantly toward goal. The common threshold is 10+ meters forward or passes that enter the final third/penalty area.

Pass Sonars / Pass Radars

A polar plot centered on a player's average position (or on a grid of zones), showing:

Direction of passes (angle on the plot)
Frequency (length of the bar in that direction)
Distance (sometimes encoded as bar width or shade)

This creates a visual "fingerprint" of how a player distributes the ball. A deep-lying playmaker will have a sonar pointing mostly forward; a fullback's will skew sideways and forward along the flank.

xT-Colored Pass Maps

Passes drawn as arrows but colored by the xT - Expected Threat|Expected Threat value added. This combines spatial visualization with value: high-xT passes stand out visually, making it easy to identify the most dangerous ball progressions.

Passing Lanes / Flow Maps

Aggregated visualizations showing the most common passing corridors for a team, sometimes using line thickness to represent frequency. These reveal team-level patterns: does the team build through the left side? Do they bypass midfield with long balls?

Key Properties

Show both individual and collective passing behavior
Can be filtered by type, outcome, zone, time period, or value metric
Reveal tactical patterns invisible in aggregate statistics (e.g., a team always progresses through the left halfspace)

Limitations & Debates

Clutter: a full-match pass map with all passes can be unreadable — filtering is essential
Missing context: a completed pass into the box looks the same whether it led to a goal or was easily cleared
Static snapshots: pass maps don't convey timing, tempo, or the sequence of passes — a five-pass buildup and a direct ball look the same when drawn individually
Progressive Passes & Carries|Progressive pass definitions vary: different analysts use different thresholds (10m forward? enters final third? bypasses a line of pressure?), making comparisons tricky
Bias toward volume: players who pass more will have denser maps, which can visually overstate their contribution without normalization

Related Metrics

xT - Expected Threat — used to color passes by value added
xA - Expected Assists — values the final pass before a shot
Progressive Passes & Carries — threshold-based filtering for forward passes
Packing Rate — alternative: counts defenders bypassed

Related Visualizations

Pass Networks — aggregated graph view of team passing structure
Heat Maps — density alternative showing where passes originate or end

Notable Implementations & Resources

StatsBomb — detailed pass maps with freeze-frame context
Eliot McKinley — popularized pass sonars
mplsoccer (Python) — pass plotting functions including sonars
Between the Posts — football analytics site known for detailed pass map analysis

Tags: #football #analytics #visualization #passes