Match Momentum: A New Metric in Football Analysis (Patreon)

Football is a game that has been played for centuries, but the way we analyze it has drastically changed over the years. With the advent of technology, we can now measure a game's nuances more accurately, and that has led to the introduction of advanced metrics like expected goals (xG), possession value, and Match Momentum.

Match Momentum is a relatively new metric that looks to provide a more holistic view of a game. Rather than just looking at events in isolation, it takes into account every on-ball action and allows us to see how dangerous each team was as the match unfolded, painting a more chronological story to the reader.

So, what is Match Momentum? It measures the swing of the match and which team is creating more threatening situations at certain points in time. It does this by measuring the likelihood of the team in possession scoring within the next 10 seconds. In other words, it tells us which team is on the front foot and creating the most dangerous opportunities.

Match Momentum is derived from another Stats Perform Qwinn Model called possession value. Possession value measures the impact each individual event on the pitch has on changing the probability of team scoring within the next 10 seconds. For example, carrying or passing the ball into dangerous areas around the opposition penalty box are valued much higher than passive possession around the halfway line.

We can then aggregate these individual actions to the team level, allowing us to see which team had the more dangerous possessions. Each minute, match momentum compares the two most threatening situations each team had leading up to that minute, measured by possession value, to see which team was the most likely to score at that time.

To calculate Match Momentum, we look at the maximum possession value for each team in every minute of the game so far (capped between zero and 0.1). The threat of each team is then a combination of these values, weighted for how recently they occurred, with the most recent minutes having more influence on the final value. Only the most recent three to four minutes have significant impact here. The momentum for a given minute then takes the difference between these values for each team to see who was more dominant. The capping of the values and smoothing of the highest value actions over time avoids large fluctuations in momentum between each minute.

The aim of Match Momentum is to quantify which team is more likely to score at a certain moment. Other advanced metrics like expected goals can measure this but are only captured when a team takes a shot. Momentum, through the possession value model, takes into account every action so we can still measure a team's threat if they get into dangerous areas but don't convert this into a shot.

Match Momentum is another tool to add to our statistical arsenal. In a football match, teams enjoy different periods of dominance, and Match Momentum now gives us a way to show that. It also allows us to look beyond just the scoreline and see which team was truly in control at certain points in the game.

Match Momentum has already been implemented by some football analysts and media outlets, and it's only a matter of time before it becomes more widespread. As with any new metric, there will be debates about its accuracy and usefulness, but it's a step forward in our understanding of the game. With Match Momentum, we can now measure not just what happened in a game but also when and how it happened.

Reference: Opta Analyst