Data and statistical analysis have become a huge part of football in recent years. No longer are football fans using just the scoreline and performance of their team as a way of understanding form; nowadays, they are using a wealth of football statistics, such as expected goals (xG). So, what is expected goals?
Using Expected Goals to Better Evaluate Your Team’s Fortune
History of Expected Goals
The statistic of expected goals became a regular conversation among football fans when the BBC’s flagship football show, Match of the Day, started to use it during the 2017/18 campaign.
Its use in football can be traced back to Opta’s Sam Green who, in April 2012, tried to assess the performance of Premier League goalscorers using a model inspired by one used in American sports.
The team at Opta looked at more than 300,000 shots and a number of variables – including the angle of the shot, assist type, shot location, the proximity of defenders and how far away from the goal the chance was.
By doing this they are able to assign an xG value, usually as a percentage, to any attempt on goal. The more matches are played, the more accurate the xG model becomes.
What is Expected Goals?
Expected Goals (xG) is a statistic used to describe the number of goals a player or team should have scored when considering the number and type of chances they had.
It means that supporters can provide concrete evidence to support claims such as “he should have had a hat-trick” or “he should have put that away”.
Expected goals uses a range of characteristics from scoring chances, with historical data of such types of shots, to predict the likelihood of a player scoring a specific shot.
It is simply a rough probability of a shot being scored, meaning that a team or player could outperform or underperform their xG value. This simply means that the player, or team, could be scoring chances that most would miss – or they are failing to convert from opportunities that tend to end in a positive result for the attacking side.
If a chance is given an xG rating of 0.5, it means that the chance is scored 50 per cent of the time. When the ball ricocheted off a player to leave Sunderland’s Lamine Kone an almost completely open goal against Everton (above), the chance was so good it was rated 0.91xG – it was such a good opportunity that it was converted 91 per cent of the time.
Why Is xG A Useful Statistic To Analyse a Team?
Expected goals can be used to understand more easily how a team is performing. Juventus, for example, won just three of their first 10 games of the 2015/16 season. Their expected goals statistic was high, but this was not mirrored by their goal conversion rate. Put simply, they had chances to score but were failing to do so.
More recently, Nottingham Forest had an expected goals rate of 17.81 after 12 games (1.48 per game). This was the fourth-highest in the Championship; however, the Reds had only scored nine goals from 12 games. The Midlanders were producing the number of goal-scoring chances that could have seen them in the play-off spots but, instead, they were caught up in a relegation scrap.
Similarly, if your team is performing above expectations then a look at your club’s expected goals may tell you whether that run is likely to last.