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Shot Maps and Heat Maps on RubiScore: How the Visuals Work

Shot maps and heat maps are the two most recognisable spatial graphics in football, and RubiScore renders both for the matches it covers — plotting every shot at the exact point it was struck, and aggregating positional data into colour-graded territory maps that update as a game unfolds. Together they turn a stream of raw match events into two pictures that answer different questions: where the danger came from, and where the play actually happened.

Two Spatial Visuals, Two Questions

The two graphics are often mentioned in the same breath, but they describe opposite things and should never be read as substitutes for each other.

• A shot map is about events: it marks discrete moments — the shots — and encodes the quality and outcome of each one.
• A heat map is about presence: it smooths thousands of location points into zones, showing where time was spent rather than what was done.

Reading them side by side is what makes them useful. A heat map can show a team camped in the opponent's half while the shot map reveals that all that territory produced only a handful of weak efforts — the difference between dominance and the appearance of it. RubiScore presents the two near each other so that gap is easy to spot.

How RubiScore Builds Its Shot Maps

A shot map is only as good as the event data feeding it, and each shot on the platform carries several attributes captured the moment it happens. The position the attempt was taken from sets where the marker lands. Its expected-goals (xG) value sets how large the marker is drawn, so a clear opening looks visibly bigger than a hopeful long-range strike. Its outcome — goal, on target, off target, or blocked — sets the colour.

That three-part encoding lets a single image carry an entire match's attacking story. A cluster of large markers inside the six-yard box describes a side that worked the ball to high-value positions; a thin scatter of small dots around the edge of the area describes one reduced to shooting from distance. Because the markers are scaled by chance quality rather than counted equally, the shot map distinguishes a team that created real danger from one that merely accumulated attempts — a distinction the raw shot count hides entirely.

How the Heat Maps Are Generated

The heat map is built from a different data layer. Rather than discrete events, it aggregates a dense set of location points across the match, divides the pitch into a fine grid, counts the activity in each cell, and smooths the result into a continuous gradient running from cool colours to warm. The warmest zones mark where a player or team was most active.

One detail shapes how the graphic should be read, and the platform's display follows the standard convention: the shading is relative to that player's own distribution. A player's busiest area appears red even when their overall involvement was modest, so the colour shows where someone was most active relative to themselves rather than against everyone else on the pitch. Read at team level, the same map becomes a territorial summary — warmth pushed into the opponent's half signals sustained upfield pressure, closely related to the idea of field tilt, while warmth down one flank shows where a side preferred to build.

Reading the Two Together on the Platform

The real value appears when the shot map and the heat map are read as a pair, because each covers the other's blind spot. The heat map answers where the play happened; the shot map answers how dangerous it became. A side can dominate territory and still lose the chance battle, and only the two graphics together expose that.

A few combinations recur often enough to be worth recognising:

• Warm in attack, big markers in the box — genuine, converted dominance: a team both controlling territory and creating clear chances.
• Warm in attack, small scattered markers — sterile control: lots of territory, little real threat, usually a side being contained by a deeper block.
• Cool territory, large markers — efficient, direct threat: a team that saw less of the ball but struck hard when it did.

The Rubi Score display keeps both visuals close so these patterns can be read at a glance rather than reconstructed from separate screens.

Live, Not Just After the Whistle

What distinguishes a live-data service from a static report is that both graphics evolve in real time. As a match runs, each new shot drops onto the map at its location, sized by its xG and coloured by its result, and the heat zones deepen and spread as players cover ground. A viewer can watch a heat map tilt toward one goal during a spell of pressure, or see a flurry of large markers appear as a game opens up in its closing stages.

This live dimension changes how the visuals are used. Instead of explaining a result after the fact, they describe a match while it is still being decided — showing momentum shifting, a substitution changing where a team operates, or a side that has stopped creating despite still holding the ball. The platform refreshes both maps continuously for the fixtures it tracks, so the spatial story keeps pace with the match itself.

What Feeds the Visuals

Neither graphic is a drawing; both are direct expressions of structured match data. The shot map is an expression of event data — the logged record of each shot with its location, xG, and outcome. The heat map is an expression of positional data — the stream of location points that says where players were over time. The quality of the picture is inseparable from the quality of that underlying feed, which is why consistent, well-structured data collection matters more than the styling laid on top of it.

This is also why the two maps belong beside the rest of a match's numbers rather than in isolation. A shot map gains meaning next to the xG timeline that shows when the chances arrived; a heat map gains meaning next to the progressive-action and box-entry counts that say whether territory was converted into threat. The visuals are an entry point into the data, not a replacement for it.

Who the Visuals Are For

The same two graphics serve very different audiences without changing form. A casual viewer reads a shot map to settle whether their team was unlucky or simply beaten, and reads a heat map to see whether a favourite player was involved or anonymous. An analyst reads the identical images for finer detail — the exact zones a chance came from, the asymmetry that betrays a tactical instruction, the territory that never turned into a shot. A reporter pulls the same picture to anchor a match account in evidence rather than impression. One graphic, several depths of reading, which is much of why spatial visuals have spread so quickly across the way football is followed and discussed.

Why Spatial Visuals Matter

Football has spent the past decade learning to read the game spatially, and these two graphics are the most accessible products of that shift. They take concepts that once lived only in analysts' spreadsheets — chance quality, territorial control, shot location — and make them legible in a single glance, for casual viewers and serious researchers alike.

Used well, they correct the errors a scoreline encourages. The shot map shows whether a result was deserved; the heat map shows whether possession was meaningful; together they replace the question of who won with the more useful question of who played well enough to. RubiScore publishes both, alongside the xG values, event logs, and positional breakdowns that give them meaning, match by match on rubiscore.com — so the picture on the map can always be checked against the data beneath it.