The Three Expected Metrics: Understanding xG, xA, and xT

In today’s issue of Football Progression Path, I’ll explain the differences between three expected metrics commonly used in football.

Understanding the nuances of these metrics is crucial for scouts and analysts. Metrics like expected goals (xG), expected assists (xA), and expected threat (xT) are utilised daily in the game. They serve distinct purposes but are often misunderstood.

Many people mistakenly believe xG is a predictive measure indicating a game's outcome or a player’s finishing ability. Additionally, xT is somewhat disregarded by the general public and those in the game due to its name.

Whether you're an aspiring analyst or a professional scout wanting to deepen your understanding of data, it’s essential to grasp metrics and their real-world applications.

• xG is not a metric for finishing ability
• xA measures the likelihood that a pass will result in a goal
• xT assess the impact of moving the ball

Expected Goals (xG)

Expected goals have become a staple in football analysis.

This metric evaluates the quality of a scoring chance based on the location and context of a shot. It is widely used in post-game analysis and is frequently featured on football programs and social media.

• Definition: xG represents the probability of a shot resulting in a goal from a particular position on the pitch. For instance, a shot from the penalty spot with no defenders in the way will have an xG of 0.78, indicating a 78% chance of scoring.
• Misinterpretation: Many assume xG measures a player's finishing ability or a team's overall quality. However, it is more accurately described as "chance quality", reflecting the likelihood of a shot being successful.
• Application: Use xG to assess the quality of chances created by players or teams, rather than predicting match outcomes.

Expected Assists (xA)

Closely related to xG, expected assists quantify the likelihood that a pass will result in an assist.

It also depends on the model, for example StatsBomb’s model relies on there being a shot to calculate it. This makes it very similar to xG. Other models such as OPTA’s (StatsPerform) calculates the metric without the need of a shot, making it more like xT.

• Definition (depending on data provider): xA measures the expected goals value of a shot resulting from a player's pass. If a player passes to a teammate at the penalty spot, resulting in a shot with an xG of 0.78, the passer receives an xA of 0.78.
• Clarification: xA does not indicate the number of assists a player should have. Instead, it reflects the quality of the chances they create.
• Application: Use xA to evaluate a player's ability to create high-quality scoring opportunities for teammates - even if those shots are missed.

Expected Threat (xT)

Expected threat has been around for 10+ years now but is still considered a newer metric.

It assesses the impact of moving the ball between different areas of the pitch.

• Definition: xT measures how much a pass or action increases the probability of scoring. Unlike xG and xA, xT considers all actions, not just shots.
• Example: A pass from the right wing into the penalty box might have a high xT value, while a backward pass from midfield to defence would have a low xT value.
• Application: Use xT to understand which players and actions contribute most to advancing the ball into dangerous areas.

All three metrics have somewhat of a similar relationship.

The same can be said for other football metrics, and there are also differences across data providers in regards to names and definitions. This highlights the importance of not just understanding metrics, but putting them into game context.

The football professionals who will continue to thrive are those who properly understand different metrics, from various providers within that football context.

I hope this helps you on your football journey and gives you inspiration to drive into more metrics.

Have a great week and go well.

Liam

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