Expected goals (xG) is a metric in football betting that quantifies the likelihood of a shot resulting in a goal. For punters that engage in EG betting, this statistical model takes every goal attempt created in a game and compares them to thousands of similar historical chances. It then assigns a figure from 0 to 1 to each chance based on its probability of achieving a goal. This figure is the expected goal or xG. For instance, an xG value of 0.2 means the shot is scored 20% of the time based on historical data analysis of opportunities with similar characteristics.
Understanding how this metric is calculated is essential to ensure better winning chances for your expected goals bets. While there are various machine learning models to calculate expected goals, they all work with a common approach. As mentioned, this involves evaluating the quality of a scoring attempt by analyzing vast chunks of historical data of similar opportunities (shots from the same location on the pitch).
However, beyond the position of play of the shot, these models are trained on a range of other variables, depending on their complexity. It is to ensure an extreme level of accuracy for expected goals wagering.
These factors include:
For instance, in a matchup of Arsenal against Manchester United, a short pass from Gabriel Jesus on his right foot in the 18-yard box will have a significantly higher xG than a corner kick. After the match, the expected goal value for each team is collated, and you may see the total xG displayed as:
There are several variations of xG, and it is essential to understand the most important ones to bet on expected goals more accurately.
(xG/90) refers to the expected goal (xG) of a team or player in the 90 minutes of a football match. This metric doesn’t consider xG of shots outside of the official duration.
xGF is a statistic used to measure the expected number of goals a team will likely score in a match based on the quality of their goal-scoring opportunities. This metric can be highly valuable when placing an xG bet on goal-related markets, including totals, correct score, BTTS, etc.
While xGf measures the likelihood of a team scoring based on the quality of their attacking chances, xGa assesses the number of goals a team is expected to concede in a match.
xA is a metric that quantifies the likelihood that a specific pass will lead to a goal-scoring opportunity based on distance, angle, and pass type. It can be highly valuable when analyzing expected goals bet on assist-related markets.
npxG is a variation of the expected goals (xG) metric that does not consider penalty shots. To calculate this, you must deduct the xG for penalties in a match from the total xG.
xPts measures the number of points that a team is expected to get from a match based on the total xG data (quality of all the chances created)
Having understood what xG is and how it is calculated, let’s examine how to use it for football betting offers. The xG model provides a more accurate representation of a team’s performance beyond traditional metrics like possession, shots on goal, shots on target, and goals scored. These basic stats only provide how many chances and goals there are and are not enough to judge a team or player’s performance.
Conversely, betting on expected goals (xG) helps you dive deeper into the quality of those shots. It evaluates who was better in a match regardless of the actual results. Thus, it eliminates luck and randomness.
Let’s examine how to use the xG metric in betting:
Let’s examine some xG betting tips on using this metric to increase your success in sports wagering.
There are many xG statistical models online that punters can easily access. However, using a reliable and robust one that considers as many factors as possible is crucial for increased accuracy. It should also cover various leagues, competitions, and teams.
In your chosen xG model, select the football league or competition you’re interested in betting on.
After selecting the league, pick the teams you want to bet on to view their statistics. To ensure better accuracy in your expected goals betting, you can even check for the home and away xG records differently.
Analyze the records and identify which teams create more quality goal-scoring chances and concede fewer opportunities.
Use the data to make informed predictions in your betting.
| PROS | CONS |
|---|---|
|
PROS
|
CONS
|
The xG model was introduced in 2012 by Sam Green, an advanced data analyst from Opta. Motivated by similar models being applied in American sports, he used the expected goals model to assess the performance of goalscorers in the Premier League. The xG model gained more popularity in the 2017/18 PL season when renowned pundits started discussing and using it in BBC’s Match of The Day.
Expected goals betting offers a sophisticated and data-driven approach to football wagering. It is widely used at the biggest sports betting sites. By incorporating statistical models that consider the quality of scoring opportunities, punters can gain a more nuanced understanding of team and player performances and match dynamics.
However, as with any betting strategy, combining xG analysis with contextual factors and practicing disciplined bankroll management is essential.
