'Expected goals' (xG): What is it, and how does it show Man City should win the Premier League this season?

The original article can be found at here

 

What are “expected goals” (xG)?
 

To work out a team's “expected goals” (xG) for a match, every shot must be analysed and given an "Expected goal value" (EGV). 

EGV is the probability that any given shot will end up as a goal. 

As Patrick Lucey, director of data science at STATS, explains, EGV is based on a number of factors, such as where the shot was taken from, the proximity of defenders, the nature of the attack (i.e a direct free-kick or a penalty). The EGV of a shot assumes it is being taken by someone of average ability in the league, so it expects for instance that a shot from 10 yards out plum in front of goal with no defenders nearby has a high chance of ending up as a goal. 

 

From an analysis of every shot's EGV in a match, an "expected goals" (xG) figure can be placed on each team from that match. If a team has a higher xG figure than actual goals scored, it will broadly be because of wasteful finishing or good goalkeeping, or both. Likewise if a team is scoring more than its xG then it could be down to moments of individual brilliance from an attacker or say a goalkeeping error. 

 

 

Why is xG useful?
 

xG's value is that it gives an indication of whether a team's results are based on sustainable factors like the consistent creation or denial of chances, or whether it is down to less sustainable factors like freakishly high chance conversion or sensational goalkeeping.

 

It also gives a far more reliable picture as to us the results of individual matches reflected the pattern of play. Take Germany's 7-1 win against Brazil in the 2014 World Cup for instance, in which Brazil actually had more shots and possession, but were way down on xG compared to their opponents. 

xG can be thought of as effectively evaluating "chances", whereas "shots on goal" does not discriminate between a 35-yard sighter and a missed open goal from close range. 

 

By analysing every shot from last season and the season before, the STATS team have been able to identify a number of patterns, which we can use to inform how this season might pan out. 

 

 
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