It’s the first international break of the season. Everyone’s a bit bored, nobody’s that arsed about the Nations League, and there’s no FPL. Due to the lack of FPL activity, people have moved onto something else: xG.

Stats like xG and xA have been a big talking point over the past week. Some people think they’re a load of bollocks, while others think that they’re a valuable method of evaluating player performances. I’ve personally used them in recent FPL gameweek reviews looking at players who have particularly high xG scores across all of their chances so far this season.

So, are they a load of shite? Are they valuable? Scrap that, what the bloody hell are they? Here’s a quick look at stats like xG and how they can be used in FPL.

What is xG? 

xG refers to Expected Goals. This is essentially a metric that analyses each goalscoring chance a player has had, evaluating the quality of the chance. If a shot has a low xG, it indicates that there was a low probability that it would result in a goal.

If a shot has an xG of 0.5, it would generally result in a goal 50% of the time. An xG of, say, 0.95 would indicate that it would be bloody difficult to miss that chance.

Looking at individual chances, let’s take a look at two of Jamie Vardy’s goals from the 17/18 season.

Here’s his xG/shot map from that campaign:

Jamie Vardy xG Map - 17/18 Saeson

Credit: Understat

Each green dot represents a goal, with the size representing the quality of the chance. Let’s take the one closest to the goal. This was a tap-in from a few yards out in open play, which had an xG of 0.82. If that precise situation were to happen 100 times, it’d likely result in a goal 82 times.

Then, there’s the one just inside the box, towards the left-hand side. This was his famous volley against West Brom, one of the goals of the season.

This goal had an xG of 0.06. Basically, good luck doing that again.

It’s a way of identifying how good a shooting chance really was, based on how likely similar chances were to result in a goal. This is calculated based on the analysis of historical shot data, stemming from Opta’s database.

Various factors go into determining the quality of the chance, such as:

  • Distance from goal
  • Was the shot taken from a rebound?
  • What angle was the shot taken from?
  • Was it a one-on-one with the keeper?

Here’s a video which shows the anatomy of an expected goal, looking at the factors that are taken into account when calculating xG:

It’s also worth noting that xG is based on all historical data, not each individual player. If and Harry Kane and Joselu both took the same shot under the same circumstances in the same part of the pitch, their xG for that chance would be the same.

There’s also xA, which refers to Expected Assists. It’s the same model, just instead analysing the creation of the chance. It measures the chance that the pass would result in a direct assist, taking into account factors such as the type of pass and the location of the pass.

These metrics can also be applied to teams as a whole. We can use xG and xA to see which teams take and create the highest volume of higher-quality chances. For example, Man City had an xG of 91.43 last season, with the next best being Liverpool’s at 77.49. This indicates that they created far more chances than any other team, and at a higher level of quality.

xG and xA, as well as xGA (expected goals against) are particularly helpful with evaluating and predicting overall team performance.

Last season, Crystal Palace had an overall xG of 56.75, though they only scored 45 goals. They created chances, though they didn’t put them away. That’s what having Christian Benteke up front will do for you, I guess.

How Can xG and xA Be Used?

These stats are generally used to see if players, and teams, are creating + taking quality chances.

In FPL terms, if we see that a player generally has a high xG on their chances, it could indicate that they’re a threat, with them getting into good goal scoring positions. Though, it could also indicate that they’re not good enough to finish them.

Here’s a look at the top 10 players for xG in the 17/18 Premier League season:

Premier League Top xG 17/18

We can see which players had the highest xG, along with the number of goals they scored that season. The number next to their respective xG would be the difference between their xG and actual goals scored. Harry Kane and Mohamed Salah both hit the 30 goal mark but had expected returns of 25/26 goals. Jamie Vardy scored 20 goals but had an xG of 15.27.

This can help indicate that a player is simply a bloody good finisher, as they’re able to score from lower-quality chances – more helpful over a much longer period of analysis. As we saw with Vardy, one of his goals had an xG of 0.06, with it being one of the best finishes I’ve ever seen.

Raheem Sterling and Gabriel Jesus both stand out here. Looking at Sterling in particular, he improved massively last season in terms of end product, with his xG essentially matching his final returns.

Here’s his individual xG map from the 17/18 season:

Raheem Sterling xG Map - 17/18 Season

He took plenty of his chances from within the 6-yard box, with him being on the end of a lot of City’s attacking play last season. Most of the higher-xG chances were tap-ins from open play. This could be correlated with other stats to determine his quality as an FPL choice, as we’ll look into later on.

Essentially, in FPL terms, xG can be used as one way of identifying the kind of shots players are taking. If a player is routinely getting into good goalscoring positions, that’d put them on the radar at the very least.

Looking over a longer period of time, if a player is underperforming in terms of xG, it could indicate that they’re just a poor finisher. If someone is overperforming over a longer period of time, they’re likely a better finisher. They’re all just parts of the analytical machine, as other factors need to be taken into account.

Should xG be Used as a Lone Metric in FPL?

No, it shouldn’t. Whether for FPL or just in general, xG can be used as one of many different ways of evaluating player performance.

Essentially, if we have a player who is outperforming their xG, this could mean that:

  • They’re a top class player that is capable of finishing difficult chances
  • They’re scoring at an unsustainable rate

If we have a player that’s underperforming in terms of xG, it could mean:

  • They’re getting good goalscoring opportunities and are a threat.
  • They can’t finish their chances.

Seems a bit confusing, doesn’t it? Well, xG and xA should be just part of the analysis conducted when you’re choosing players for your FPL side. As we saw earlier from last season’s stats, the players with the highest xG were generally the top performers in terms of end product. Some players underperformed, such as Joselu and Alvaro Morata – we can see that these lads just couldn’t finish their dinner.

If we’re looking at a striker, I’d want to know more precise information such as:

  • Total shots
  • Shots in the box
  • Touches in the box
  • Big chances 

These may well be taken into account when calculating a player’s total xG, but I want the entire picture, not just a single number.

There’s also the biggest one of all: watching the player actually play. Stats are massively valuable in FPL, as is watching the players each week.

These methods can all be combined when evaluating a player. If I see a player that has a decent xG, has had a fair few shots in the box and looks good on Match of the Day? He’s on the radar.

Take Aleksandar Mitrovic, for instance. He’s looked good for Fulham and is joint-third for both overall shots (20) and shots in the box (12). He’s also got an overall xG of 2.90. A number of his shots have been headers, which are generally lower in terms of xG.

So, there’s a high volume of shots being taken, with a number of them being of at least decent quality. Fulham have also averaged 15 shots per game, the joint-fifth highest of any team so far, indicating the overall attacking intent of the team. All signs look good, with xG playing a part in an overall analysis of the player.

In my view, xG and xA isn’t a load of bollocks. It’s a helpful way of partially evaluating player performance. It shouldn’t be completely cast aside, nor should it be the main way of analysing a player. It’s also more valuable over a longer period of time, so it’s not the be-all-end-all just 4 weeks into the season.

 

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