Using Expected Goals (xG) to Handicap Soccer Matches

Successful soccer handicapping requires analyzing more than just final scores or recent team form. One of the most valuable metrics in modern soccer analytics is Expected Goals (xG). In this article, we will explore what Expected Goals is, how it is calculated, and how you can use it to handicap soccer matches. We’ll provide real-world examples to illustrate its application and discuss whether xG applies to teams or individual players—or both. Additionally, we’ll explore whether this metric is useful in other sports like hockey and where you can find xG data online. Lastly, we will offer a few ways you can incorporate Expected Goals into your own handicapping formulas.

What is Expected Goals (xG)?

Expected Goals (xG) is a metric that estimates the probability of a shot resulting in a goal based on various factors. These factors include shot location, shot type, defensive pressure, and other situational details. Unlike traditional statistics that focus on goals scored, xG provides a more accurate representation of a team’s or player’s scoring opportunities.

How is xG Calculated?

So, how is xG calculated? Well, basically, the xG calculation relies on historical data from thousands of past shots to determine the likelihood of a goal being scored from a particular position. Each shot is assigned an xG value between 0 and 1, with 1 representing a certain goal and 0 indicating a highly unlikely chance. For example:

• A penalty kick typically has an xG value of about 0.75, meaning a player is expected to score 75% of the time.
• A shot from outside the penalty box may have an xG value of 0.05, indicating a 5% chance of scoring.
• A header from a crowded six-yard box might have an xG value of 0.30, reflecting the difficulty of scoring from that position.

By summing these individual xG values, analysts can evaluate team performance over a match or an entire season.

An Example of xG Calculation

Consider a match between Team A and Team B where Team A had the following shots:

• A close-range shot (xG: 0.40)
• A long-range shot (xG: 0.05)
• A penalty kick (xG: 0.75)

The total xG for Team A would be 1.20 (.40 + .05 + .75), meaning they were expected to score about 1.2 goals. If Team A lost 0-1 despite having a higher xG than their opponent (who, for example, only had an xG of 0.50), it suggests that Team A either had bad luck or missed good chances to score.

xG for Teams vs. Players

Expected Goals for Teams

xG can be used to analyze entire teams by summing up their total xG over multiple matches. This allows handicappers to assess whether a team is consistently creating quality scoring chances or merely overperforming in terms of goal conversion.

Expected Goals for Players

On an individual level, xG helps evaluate a player’s scoring efficiency. Let’s say a striker has an xG of 10 over a season but has only scored 5 goals, it would suggest he is underperforming relative to his chances. Conversely, a player who has scored 15 goals from an xG of 8 might be overperforming and due for regression.

Is xG Limited to Soccer?

So, is xG used to only handicap soccer matches? Well no, hockey has an equivalent metric known as Expected Goals (xG) in advanced analytics. Similar to soccer, hockey xG measures the probability of a shot resulting in a goal based on shot quality, location, and other variables. As in soccer, handicappers can use xG in hockey betting as well – predicting which teams or players are likely to regress or improve.

Where to Find xG Data

Several websites provide comprehensive xG data for soccer and hockey, including:

• FBRef (fbref.com) – Extensive xG stats for soccer teams and players.
• Understat (understat.com) – xG models for top European soccer leagues.
• Infogol (infogol.net) – xG-based match predictions and betting insights.
• Natural Stat Trick (naturalstattrick.com) – xG and advanced metrics for hockey.

How to Use Expected Goals in Handicapping Formulas

There are several ways you can integrate xG into your betting strategy:

Comparing xG vs. Actual Goals – If a team is scoring significantly more than their xG suggests, they might be overperforming and due for regression.

Analyzing xG Trends – Look at xG trends over multiple games to determine if a team is improving or declining.

Expected Points (xP) Model – Combine xG with defensive stats to estimate how many points a team should have earned based on performance.

Conclusion

Expected Goals (xG) is a powerful tool that can give handicappers an edge by revealing insights traditional stats miss. By understanding how to use expected goals in soccer betting, you can assess whether a team or player is overperforming or underperforming, predict future trends, and refine your betting strategy. Whether you’re analyzing soccer or hockey, xG can be a solid metric to place into your handicapping routine.

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