xG is one of the newest terms used in football, only becoming commonplace over the last few years. It stands for ‘expected goals’ and it is a metric that can be used in a number of different ways.
As computer analytics and AI advance, it is now possible for advanced logarithms to be created that takes the raw action from a football match, such as a goalscoring opportunity, and by its application calculate how likely it is that a goal would be scored from that situation.
The outcome is shown as a percentage in decimal format from 0.00 (0%) which would be a chance that has never resulted in a goal, to 1.00 (100%), which is a chance that has always resulted in a goal.
The outcome of that calculation is the xG for that chance. Combine all the different xG opportunities in a match, and you get the total xG for a team for any given half of football, or a complete match. Do that for both teams, and you get the xG for both teams in both halves for the entire game.
However, at the core of xG is the complex calculation. Understanding that is key to comprehending not just how an xG stat is created, but how the quality of that data is relevant for any sports enthusiast, coach, player or bettor.
So, let’s explore the xG calculation in more detail.
How is xG calculated?
There isn’t a simple equation or calculation that is used for xG. The logarithm used is based on a number of different aspects including:
- Historical data on positions in and around the penalty box where goals are scored from and the percentage of goals scored from that area compared to the total number of shots made in that position.
- Whether the shot is from a set piece, or open play.
- Whether the effort at goal is either a header, or shot.
- The distance and angle from goal.
- The build up play leading to the effort on goal.
- Whether the chance was created by good play, or an error by the defending team.
- The type of assist for the goal (pass, rebound from a goalkeeper save, cross etc).
- Quality of the strike.
Computer software will analyse all this information from live game data to come up with a rating between 0.00 and 1.00 as to what the xG is for any shot or attempt at goal.
A penalty, for example, has an xG of around 0.76, which means just over 3 out of 4 penalties are scored, with the other either saved or missed.
Shots from further out and from tighter angles have a higher xG compared to those closer in and right in front of goal.
Why does xG matter and how is it used?
Now that we understand how an xG score is calculated, what is its potential for football enthusiasts, fans, coaches, players and bettors?
In truth, xG can be used in many different ways, depending upon what your requirement is.
For football players, coaches, managers and similar, xG provides a clear data point for them to examine both the quality of the chances the team is creating for individual players, and the number of them in a game.
Additionally, it provides teams with individual player data on whether a player is taking the chances that are created for them well and is outperforming their xG, or if they are missing lots of chances and are under-performing compared to their xG.
However, the data can also be used not just for the team attacking. By checking the xG of opponents and opposing players, all members of a team can gain an insight into how effective their defending tactics are proving.
For fans and punters, using xG matters to them because they gain similar insights into players and teams that are effective or ineffective at creating quality chances and thereby likely to score goals. Similarly, they can use opposition xG in the same way football staff do to analyse how effective the team’s defence is at stopping easy chances in games.
Advantages of using xG
Can xG be useful to you when you are wagering on football betting sites? What other advantages does knowing xG offer football players, coaches, fans or punters alike? We take a look at some of the big advantages of using the xG data in different scenarios.
- Provides information on the effectiveness of a team’s attacking quality.
- Provides individual player data regarding taking chances.
- Provides data on how effective the teams defensive tactics and performance are as regards to teams creating chances.
- Provides data on goalkeepers performance when saving shots compared to xG.
- All the above data is also beneficial for football bettors when making decisions on football bets, especially those pertaining to goals being scored by a team, goals being conceded, or individual and team goalscoring bets.
The limitations of xG
While undoubtedly useful, xG also has a major limitation and that is the smaller the data set that is used to create the xG data, the more likely it is to be interpreted in a way that is not typical or representative of reality.
The accuracy of xG increases as more data is incorporated into the dataset. For example, if you compare how one team or player performs in one half of football in terms of xG, then you would likely get an unreliable view of how they perform compared to data analysed over several games, or an entire season.
Despite these limitations xG for players and teams and single games can still provide insights. It is up to the user to decide whether those insights are accurate or not!
An example of xG in action
A player has a shot at goal from the penalty box that is rated as having an xG rating of 0.20. That means that the xG has determined that there is a 20% chance (1 in 5) of the player scoring a goal.
That means for an average player, one shot from that position will result in a goal, whereas four will not.
An xG of 0.75 though is a much easier chance and means that 75% of the time (three in four) a player should score that opportunity.
Similarly, if a team is losing 1-0 at half time, but has created chances in the first half that average out of an xG of 1.54 and their opponent has an xG of 0.50. It shows that the winning team has taken a half chance, while the home team has failed to make the most of the chances that they have had.
Although a new stat in football, xG has given all those with a vested interest in the game a deeper understanding of how easy, or difficult, it is for a team or player to score the goals their teams need, and perhaps your bets need, to succeed!
