Understanding expected goals (xG) can give you a leg up in spotting value bets across all kinds of football markets. And the best part? It’s dead easy to get your head around. Here, we’ll break down exactly what xG is, how you can use it to your advantage, and most importantly, how it can help you sniff out the best odds. Get it right, and you might just see a few extra quid coming your way.
What is xG (Expected Goals)?
Expected goals stats (xG) are basically a way of figuring out how many goals a team should have scored based on the chances they created. It looks at things like where the shot was taken from, how it was set up, and how likely that kind of chance usually ends up in the back of the net.
For betting, xG is a cracking tool because it tells you way more than just the final score. A team might have lost 1-0, but if their xG was sky-high, it could mean they were all over their opponents and were just unlucky. That’s useful if you’re looking at future match results, over/under goals, goal-scorer markets and more.
Plus, xG is super simple to grasp. It’s just a number between 0 and 1, and you can think of it like a percentage to evaluate the probable success of a single shot. For instance, an xG of 0.6 means there's a 60% chance of scoring. In short, xG helps you see past fluke results and spot teams that are quietly smashing it – and that could give you a tasty edge when placing your bets!
xG Applied to Other Statistics
There are several other variations of xG that dig even deeper into a team’s attacking and defensive performance. xGA (expected goals against), for instance, gives you an indication of how many chances a team is giving up at the back. If a team’s xGA is sky-high, their defence is leakier than a dodgy teapot, even if they’ve been getting away with it so far.
Breaking things down even further, xG Open Play and xG Set Play split chances into those created from regular play versus dead-ball situations. Some teams are brilliant at open-play attacks but struggle from corners and free kicks, while others thrive on set-piece opportunities. Non-Penalty xG removes penalty xG value from the equation, providing a clearer picture into a team’s goal-scoring ability without the boost of penalty kicks.
Expected Goals on Target (xGOT), also known as post-shot expected goals, takes xG to the next level by factoring in shot placement. While xG assesses the quality of a chance before a shot is taken, xGOT looks at what happened after the ball left the player’s boot. For example, a well-placed shot into the top corner gets more credit than a tame effort straight at the keeper. This makes xGOT brilliant for evaluating both finishing quality and goalkeeper performance.
All these stats work together to give you a proper read on how a team is really performing – not just what the scoreboard says. If a team’s scraping by with dodgy defending or a striker’s record this season doesn’t yet reflect their quality, xG and associated stats can help you spot it before the bookies do.
How to Analyse a Match Based on xG Stats?
You don’t need an expected goals calculator to understand xG stats – it’s super straightforward once you know what you’re looking for. With a quick glance and a little thought, you’ll be able to use xG to analyse matches and improve your betting strategy. Seeing is believing, so let’s walk through a real-life example to show you just how easy it is to apply expected goals to your bets.
| Manchester City | xG Statistics | Liverpool |
|---|---|---|
| 0.65 | Expected Goals (xG) | 0.71 |
| 0.40 | Expected Assisted Goals (xGA) | 0.50 |
| 0.58 | xG Open Play | 0.32 |
| 0.07 | xG Set Play | 0.38 |
| 0.65 | Non-Penalty xG | 0.71 |
| 0.41 | Expected Goals On Target (xGOT) | 1.38 |
Most stats here suggest that Liverpool had the upper hand and were more likely to score than Manchester City. For starters, Liverpool’s 0.71 xG compared to City’s 0.65 indicates a fair advantage in attacking threat. Despite City having the edge in Open Play xG (0.58 vs. 0.32), Liverpool’s overall performance across the other stats paints a clearer picture. They hold a significant advantage in Set Play xG (0.38 vs. 0.07), Expected Assisted Goals (0.50 vs. 0.40), Non-Penalty xG (0.71 vs. 0.65), and Expected Goals on Target (1.38 vs. 0.41).
When you put all these stats together, it’s clear that Liverpool was much more likely to win, based on five out of six criteria measured here. The final score of 2-0, on December 1st, 2024, in the Premier League, reflects how accurate these expected goals predictions were. There are several bets you could have placed based on these stats – whether it was Liverpool to win, win with a clean sheet, or score more than one goal – and in all cases, you'd be walking away with a tidy profit.
How is xG (Expected Goals) Calculated?
It’s important to keep in mind that different statistical models are used, but the top models are generally similar. For instance, a penalty xG value might range from 0.75 to 0.85. So, while there’s a slight variation in calculations, the results are close enough that they’ll still give you the same overall picture, as long as you’re using a reliable source.
That aside, how is expected goals calculated?
Top analysts study hundreds of thousands of shots and measure the quality of each chance using all factors they consider relevant. For instance, they’ll consider the distance from goal – generally, the closer you are, the higher the xG. The angle of the shot is key too, with more acute angles resulting in a lower xG. The type of shot matters as well, whether it’s from a strong foot, weak foot, header, volley, tap-in, or overhead kick.
Other factors include the passage of play – was it from open play or a set piece? How the chance was created, such as via a cross or a through ball, and whether the shot came after beating an opponent or from a rebound. The amount of pressure the shooter faces from defenders and the goalkeeper’s positioning also play a big role.
All these elements come together to provide a more accurate picture of a team or player’s true attacking threat. All very clever stuff, but all you need to know is how to read them. Once you think of them as percentages – from your standard expected goals to post shot expected goals – it all becomes clear. Get your head around these numbers, and you'll be able to analyse dozens of markets far better than most punters.
Team xG vs Player xG
What is xG in football? Well, to break it down a bit more, there are two types: team xG and player xG, and they’re just what they sound like. Team expected goals reflects the overall attacking potential of a squad based on the quality of chances they’ve created collectively considering a boatload on recent stats. On the other hand, player xG zooms in on an individual player's chances, helping you figure out how likely they are to score in an upcoming match.
Better still, both individual and team xG values work together to give you insights across a wide range of markets. Whether you’re picking goal-scorers, predicting match results, or deciding on over/under goals – it’s all pure gold when it comes to spotting those cheeky value bets.
Analysing a Player Through the Lens of xG (Expected Goals)
Alright, lads. We’ve had expected goals explained as a betting term and we should now easily understand the core concepts, so let’s put it into action. First, we’ll take a look at different players and see what xG and other stats can tell us about their chances. Have a gander at the following as an example:
| Player | Team | Goals | xG | NP Goals | NPxG |
|---|---|---|---|---|---|
| Mohamed Salah | Liverpool | 25 | 20.00 | 18 | 14.40 |
| Erling Haaland | Man City | 19 | 18.30 | 18 | 16.80 |
| Alexander Isak | Newcastle | 19 | 15.10 | 17 | 13.60 |
Looking at the numbers, we can see that Mohamed Salah has scored 25 goals, surpassing his xG of 20 by 5 goals. This suggests he's been clinical in front of the goal, potentially benefiting from good finishing or favourable circumstances in Liverpool's attack. It’s a strong over-performance, indicating that Salah has had a particularly efficient run in terms of converting chances.
Similarly, Alexander Isak has scored 19 goals, well above his xG of 15.0, and even more impressive considering his non-penalty xG is 13.60. This means he’s been outperforming expectations by a fair margin.
In terms of betting, this is a signal to proceed with caution. While both Salah and Isak have been in excellent form, consistently outperforming xG can be tough to maintain. Backing them to keep up this high-scoring rate might not be the safest bet in the long term, as it’s rare for this level of over-performance to be maintained all season.
On the other hand, Erling Haaland's stats, with 18 non-penalty goals and an xG of 18.30, show a much more reliable scoring rate, making him a safer bet to continue delivering at a similar level in future matches.
Analysing a Team Through the Lens of xG (Expected Goals)
What is xG in football, if not the perfect opportunity to understand our favourite teams better? Well, here’s the plan – we’re going to do exactly that. Instead of diving into a specific match, let’s have a general look at a few top teams and analyse their ability to create chances. This will show how you can apply such stats more broadly. Happy days!
| Team | Goals | xG | Goals Against | xGA | xGD |
|---|---|---|---|---|---|
| Liverpool | 64 | 59.40 | 26 | 24.50 | +34.80 |
| N. Forest | 44 | 33.90 | 33 | 31.70 | +2.20 |
| Man United | 30 | 35.70 | 37 | 40.20 | -4.50 |
It’s clear Liverpool are performing above their sky-high expectations, with 64 goals scored and an xG of 59.40, so they've been clinical in converting chances. Their xG difference (xGD) of +34.80 suggests an exceptional overall performance, even considering that they’ve conceded more goals than expected (26 goals against vs. 24.50 xGA). This indicates a solid attacking threat and stable defensive performance. In other words, if you’re looking at Premier League outrights, they’re in great shape.
On the flip side, Nottingham Forest’s goals (44) significantly outpace their xG of 33.90, showing they're over-performing in attack. Their xG difference of +2.20 suggests they're capitalising on more chances than expected, which is great for them but may be tough to keep up. Defensively, they’ve conceded only slightly more than expected (33 goals against vs. 31.70 xGA), which shows their defensive performance is likely to continue at this level.
Meanwhile, Manchester United are massively underperforming, with 30 goals scored, which is well below their xG of 35.70. Simply put, they’re not taking their chances like they should be. Their xGD of -4.50 tells the story further, suggesting their defence is also off. All in all, they’re a bit in shambles, with both attack and defence needing a serious rethink.
Where to Find xG (Expected Goals) Stats
It’s all well and good knowing how to read and apply expected goals stats, but you’ve got to have access to all the right info to get started. Don’t worry, we’ve got you covered. Our list of the 10 best football stats and analysis sites is a goldmine of resources. You’ll find everything you need to get to grips with expected goals, plus a whole load more.
Our stats centre has it all – assists, cards, shots, penalties, pass accuracy, fouls and possession. We’ve even got referee stats, for goodness sake! Whatever you need to make the most informed predictions, it’s all here.
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ThePuntersPage Final Say
We reckon that expected goals (xG) and its related stats are among the most useful resources to help improve your predictions, spot where the odds are off, and with a bit of luck, outsmart the bookies. They’re easy to grasp and implement, and the results are well worth the effort. Pair them with a solid operator and some top promotions, and you’re really cooking with gas.
Expected Goals FAQs
xG (expected goals) is basically a way of measuring how likely a shot is to find the back of the net, considering all sorts of factors like where the shot's coming from, the angle, and even the context of the play. The more likely the goal looks, the higher the xG value.
xA (expected assists) measures the likelihood of a pass leading to a goal, while xG (expected goals) measures the likelihood of a shot turning into a goal.
Expected goals, also known as xG, is a stat used to evaluate the quality of chances in a football match. It considers a broad range of factors to estimate how likely it is to result in a goal. It gives a more accurate picture of a team’s or player’s performance, going beyond just the final scoreline.
Penalties typically have an xG of around 0.75 to 0.85, depending on the statistical model used. This means a penalty has a very high chance of resulting in a goal compared to regular open-play shots.
Not specifically. However, you can use the insights gained from expected goals to better identify the best odds and increase your chances of making a winning bet. Combine this with various promotions, such as bet boosts or free bets, and you’ll give yourself even more opportunities to win or potentially land bigger returns if you get it right.
Because the insights gained from xG and other football stats are so valuable across various betting markets, you can pretty much choose from any of the top football betting sites. A few great options include bet365, BetVictor, Parimatch, Spreadex, Coral, Betfred, SBK, BoyleSports, 10Bet, and Sportingbet. These bookmakers offer a wide range of markets where xG data can really help sharpen your betting strategy.