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

A winger drops a shoulder, beats his man, and slides a pass to the eight. The eight takes a touch and threads it to the striker, who scores. The striker gets the goal; the eight gets the assist; the winger — whose dribble pulled the whole defence out of shape — gets nothing. Shot-creating and goal-creating actions exist to fix exactly that kind of accounting, by paying not just the player who made the assist, but the player who made the pass before it.

What SCA and GCA actually count

Shot-creating actions (SCA) and goal-creating actions (GCA) are a pair of metrics popularised through the public-analytics ecosystem — you will most often meet them on FBref, built on StatsBomb’s detailed event data. The idea is disarmingly literal. Take any shot. Now look at the two offensive actions immediately before it by the attacking team. Each of those two actions earns its player one shot-creating action. If the shot becomes a goal, the same two actions instead earn a goal-creating action.

The key word is two. Conventional credit stops at the assist — the single pass that set up the shot. SCA and GCA reach one step further back, to the action before the assist. That second action is where ball-carriers, line-breaking passers, and the players who win free-kicks finally show up in the box score.

The qualifying actions are a small, fixed menu. An action counts toward SCA or GCA if it is one of the following, and it is the last or second-last team action before the shot:

• A live-ball pass — a pass in open play that helps create the shot.
• A dead-ball pass — a pass from a set-piece such as a free-kick or corner.
• A dribble (take-on) — beating a defender to carry the move forward.
• A drawn foul — being fouled in a way that leads to the shot, including winning the free-kick that is then delivered.
• A defensive action — a tackle or interception that wins the ball back and begins the move.
• The shot itself in the rebound case — a shot whose rebound or block leads directly to another shot.

A move, broken down (illustrative)

Numbers make this concrete, so here is a deliberately simple, made-up sequence — chosen to show the mechanics, not drawn from any real match.

Imagine a four-touch move. A full-back wins the ball with a tackle. He plays it to a winger. The winger beats his marker with a dribble and passes inside to the striker, who shoots and scores. Four players acted: the full-back (tackle), the winger (dribble), and a pass in between, ending with the striker’s shot.

That example also exposes the metric’s defining limit, which we’ll return to: it credits the winger twice for one move and the full-back not at all, purely because of where each action fell in the count.

Why this widens the credit beyond the assist

The reason analysts reach for SCA is that the assist is a famously blunt instrument. It rewards one pass and ignores the action that made that pass possible — the carry that broke the lines, the dribble that committed a defender, the dead-ball delivery that fell to the assister. Across a season, two very different players can have near-identical assist totals while doing completely different jobs: one finishing moves with the final ball, the other repeatedly supplying the player who supplies the finish.

SCA pulls those two roles apart. A deep creator or a dribbling wide player who consistently makes the penultimate action will accumulate a high SCA total even with a modest assist count, because they are involved in the build-up of chances whether or not they make the final pass. It is the difference between asking “who set up the shot?” and “who were the last two players to move the ball toward this shot?” The second question has two answers, and that is the whole point.

Reading it per 90, and its place among creative metrics

Raw SCA and GCA totals are volume figures, so they reward minutes and they reward playing in a team that takes lots of shots. The standard fix is the same as for most event metrics: divide by minutes and quote them per 90. SCA per 90 tells you how often a player is one of the last two contributors to a shot in a typical match; GCA per 90 does the same for goals, but because goals are far rarer than shots, GCA per 90 is a small and noisy number over short samples — closer to a sanity check on SCA than a standalone leaderboard.

It helps to place SCA and GCA next to the creative metrics they complement rather than replace. Expected assists (xA) values the quality of the chance a player creates — the xG of the resulting shot — but only for the single creating pass. SCA values the act of creation for the last two players, but treats every shot as one unit regardless of how good the chance was. And xGChain and xGBuildup go to the opposite extreme, crediting every player in a possession with the full xG of the shot it produced, no matter how many actions back they were.

Read together, the three answer different questions. xA asks how dangerous your creation was; xGChain asks whether you were involved at all; SCA and GCA sit in between, asking whether you were one of the final two hands on the ball. A scout looking at a wide player would want all three: high SCA tells you they are repeatedly near the end of moves, xA tells you whether the chances they help make are any good, and xGChain tells you whether they matter to the build-up beyond those last two touches.

The caveats worth keeping

SCA and GCA are useful precisely because they are simple, and most of their problems are the flip side of that simplicity. First, the hard two-action cut-off is arbitrary: it credits the assist and the pass before it, but a brilliant third-action carry that set the whole move in motion gets nothing, while a trivial square pass that happens to fall in the last-two window gets full credit. The metric measures position in the sequence, not value.

Second, both are volume- and team-dependent. A player in a side that takes twenty shots a game has far more chances to register SCA than the same player in a side that takes eight, so cross-team comparisons need care and per-90 framing at a minimum. Third, GCA inherits all the noise of goals themselves — it depends on finishing, which the creating player does not control, so a low GCA next to a high SCA usually says more about teammates’ conversion than about the creator.

The honest way to use them, as with most of these numbers, is as a lens rather than a verdict. SCA and GCA do one valuable thing well: they drag the penultimate action into the light, and with it the players who quietly make chances without ever making the assist.

Sources & further reading

• Free textbook: Chapter 9: Expected Threat (xT) and Ball Progression — the theory behind this, at DataField.dev.
• FBref — SCA and GCA leaderboards and definitions, with the action breakdown by type.
• StatsBomb — the event-data model the creating-action metrics are built on.
• Understat — xG, xA and possession-credit tables for the major European leagues.
• The Analyst — explainers on chance creation and advanced attacking metrics.