The Brief: Advanced Soccer Metrics
What it is, why it matters, and what it could mean for Fort Wayne FC.
Advanced soccer metrics are statistical measurements that evaluate the quality of chances, shots, passes, and results in a match, beyond what the final score shows. The most widely used are expected goals (xG), post-shot expected goals (PSxG), expected points (xPoints), and expected assists (xA), the foundation of modern soccer analytics. Any fan who has walked out of a goalless draw convinced their team deserved to win has already run this math by eye. Data helps support the evidence.
What Are Advanced Soccer Metrics?
Every advanced metric starts from the same idea: a chance has a value even when it does not become a goal. Analysts have logged hundreds of thousands of shots and tracked how often each type goes in, factoring in the distance from goal, the angle, whether the ball came to a player’s stronger foot or his head, and how the chance arrived, whether an open-play move, a corner, or a breakaway. From that history, every new chance can be assigned a probability.
That probability is the foundation. Build on it in different directions and you get the family of metrics covered below. One measures the quality of the chance and another the quality of the strike. A third translates a full match of chances into the result it probably deserved, and the last credits the pass that made the chance possible. Each answers a question the scoreboard ignores, and together they describe what actually happened on the field with a precision the final score cannot offer. All of them deal in likelihood rather than certainty, which is exactly how the sport behaves.
Why It Matters
The scoreboard is the worst liar in soccer. Goals are rare, margins are thin, and a single bounce can send three points the wrong way. Over a season, the table and the actual quality of play can drift surprisingly far apart. These four numbers are how analysts, recruiters, and increasingly broadcasters tell the difference. Learn them once and every match you watch afterward gets richer with insight.
xG (Expected Goals)
Expected goals measures the quality of a scoring chance as a number between 0 and 1: the probability that an average shot from that exact spot, in that exact situation, ends up in the net. A tap-in from two yards might carry 0.85 xG, a goal roughly eight or nine times out of ten. A hopeful strike from 30 yards might carry 0.03. Add up every shot a team takes in a match and you get its xG for the day, a measure of how many goals its chances were worth. xG is the most widely used number in modern soccer because it answers the question that matters most: were these the kinds of chances that usually become goals? When you see a team win the xG battle and lose the match, you are looking at either a finishing problem or plain bad luck, and one match rarely tells you which.
PSxG (Post-Shot Expected Goals)
Post-shot expected goals measures the quality of the shot itself, after it leaves the boot. Where xG grades the chance, PSxG grades the strike, because it factors in where the ball is actually heading. It only exists for shots on target. A ball drilled toward the top corner carries a high PSxG. The same chance scuffed straight at the keeper carries a low one, even though both began as the identical xG. That makes PSxG the goalkeeper’s stat. A keeper who faces shots worth two goals by PSxG and concedes none has had a brilliant night, and this is the number that proves it. When you see a modest chance produce an unstoppable shot, PSxG is how the credit lands on the right player: the striker for the hit, or the keeper for somehow getting there anyway.
xPoints (Expected Points)
Expected points takes the chances both teams created and translates them into the result the match probably deserved. A win is worth three points, a draw one, a loss none. xPoints runs through every plausible scoreline the two teams’ chances could have produced and settles on the points a team would earn on average from a performance like that. This is the number that puts language to the robbed feeling. A team can dominate a goalless draw so thoroughly that its xPoints lands near two and a half, the math saying a performance like that wins far more often than it draws. Over a full season, xPoints often reads truer than the standings, because results swing on luck while the quality underneath stays steadier. When the table and the xPoints column disagree about a team, trust the xPoints column to predict what happens next.
xA (Expected Assists)
Expected assists measures the quality of a pass that sets up a shot: the probability that a given ball played to a teammate leads to a goal. A perfectly weighted through ball that springs a striker in alone carries high xA. A square pass 40 yards from goal carries almost none. xA matters because it credits the players who make goals happen without finishing them. A playmaker can go weeks without an official assist purely because teammates keep missing the chances he manufactures, and the scoresheet would call that a quiet month. xA tells the truer story. When you want to find the most dangerous creator on the field, check the xA column before the assist column. The assists catch up to the work eventually.
One more you will hear: PPDA, passes allowed per defensive action, a team-level number that measures pressing. A low PPDA means a team hounds the ball high up the field and rarely lets the opponent string passes together. A high one means the team sits back and absorbs. When a commentator says a side presses aggressively or sits deep, PPDA is the math underneath the description.
What This Means for Fort Wayne FC
Data and numbers give us a shared language. Advanced metrics allow fans, staff, and players alike to understand the game around the same set of measurements. They align everyone on what could be working and what might not be, and they let us analyze a match through the same lens. The supporter in the stands, the analyst in the office, and the midfielder in the film room can look at the same numbers and have a real conversation about the same match. Individually, each one layers their own unique experience onto the data, and that is where the conversation starts. Data is data. It tells a story, but not quite the full story.
The eye test fills in the rest. The numbers do not know a striker was carrying a knock, that the wind was swirling, or that a chance the model rated highly actually came through a forest of legs and never had a real path to goal. There will be nights when a chance grades out modest on paper and watching it live, you know it was the cleanest look of the match. Both can be right; you and the data. They measure different things, and the fan who holds both reads the game better than the fan clinging to either one alone.
Our club is built on the same principle. Advanced metrics allow the coaching staff to win the next match before it’s ever played. The club staffs for it: a dedicated Sports Data Analyst sits under Football Operations, a full-time role devoted to translating our game model into measurable metrics and mapping players worldwide to find the ones who fit what our coaches want to do on the pitch. And the club has been clear about how that work gets used. The data narrows the search and the eyes confirm it, because some things can only be learned by watching a player. Data is an advantage, and having an experienced coaching staff who can decipher the numbers and match patterns gives us a competitive advantage. And no matter if you’re in the press box or the stands, advanced soccer metrics can bring a new level of insight to your viewing experience. How you use and interpret the data is up to you.
A tip of the cap to American Soccer Analysis, where all four metrics this Brief teaches are published free for USL League One. The numbers behind our coverage start there.