What if you could calculate the probability of a team scoring the next goal? Data-driven sports predictions is an emerging area that has continued to change the way people predict.
In the same way, people can use simple online calculator tools to compute their taxes, loans, body mass index, and debts, you can also calculate the probability of a shot becoming a goal.
So, what is xG, and how does it work?
What does XG mean?
Expected goals (xG) is a metric used to mathematically analyze and calculate the quality of chances in a match that could lead to a goal. Every attempt at a goal is allocated a value that tells the probability of that shot finding the back of the net.
The probability values are between 0 and 1. The higher the value, the more likely the shot will result in a goal. For example, an xG value of 0.1 indicates a 10% chance of the shot finding the back of the net. Likewise, as the value tends north, for example, an xG value of 0.9 indicates a 90% chance of the shot resulting in a goal.
As simple as this sounds, it is essential to note that arriving at these probability values are a function of multiple variables and shot history between the two participating teams. Who is taking the shot? What is the distance from the goal? What part of the body was used to take the shot? Answers to these questions are used to calculate the xG probability for any particular chance.
How is xG calculated?
Calculating a scoring chance takes into account many factors. For example, in a football game, an average football lover knows the player’s capabilities in a team. For instance, whose pass is more likely to result in an assist or the player that will most likely convert the chances?
When calculating for a team, you need the goal scoring history from previous games. With that information, you can predict the probability of the team scoring in the next game. For example, a team has averaged 200 shots in the past two football seasons of 76 league games. Meanwhile, they only managed to score 90 goals from those shots. Based on this info, the xG is 0.45. This means there is only a 45% chance that the team will score a goal from any shot in a match.
Likewise, the same approach applies to individual players and shot types. There are high-quality opportunities known as “big chances.” In such cases, a player is often expected to score. Like in a one-on-one situation, a very close-range tap-in, or a penalty.
Such chances come with very high xG probabilities, and it gets better when the player involved also has high stats. For example, the combined xG for a penalty shot when it is to be taken by Cristiano Ronaldo is much higher than when it is to be taken by Zlatan Ibrahimovic. That’s because Zlatan has missed more big chances from the spot than Ronaldo.
How can this data benefit you
Generally, football is a low-scoring sport. Hence, it is difficult to determine which team will score and by what margin. You can find a way to turn things around in your favor with data-driven approaches.
Many tipping sites use this model to carry out their predictions. So, you can also use it to increase your chances of winning. When using a bet calculator, you can use the data to add multiple events to your slip. That way, you can look at many teams and use the accumulator feature for as many events as possible.
Some calculators also integrate other features like access to different betting markets. You can access Asian bookies, US Sportsbooks and many more. You can also switch odds from decimals to fractions so it’s easier to understand the results of your calculations.
In the end, the xG model can be pretty tricky to master. However, if you crunch the data over history, and use the best tools available, you will have more joy. Data is a key part of football, used by punters and coaches alike, therefore you can utilize it to your advantage.
