It is very much the zeitgeist way in which to analyse football teams and matches, but you should get used to Expected Goals (xG) entering the common lexicon of the beautiful game.
It’s been used by data junkies and stat nerds for a couple of years, and has finally found its way into the mainstream with both Match of the Day and Sky Sports using the metric in their post-match analysis.
Expected Goals is simply a method of calculating how good a team’s chance creation was in a specific match. The idea is that a side can be creating ‘big chances’ on a regular basis, and that would ultimately seem them become successful.
On the flipside, there is the notion that teams can get ‘lucky’, with a poor xG count identifying the underlying story even when the league table suggests a team is going well. You only need to look at the example of Ipswich Town in the Championship earlier this season. They won their first four matches despite being on the losing end of the xG count in each. It was obvious to those in the know that the Tractor Boys were punching above their weight, and so it proved as they lost their next pair of matches.
This information is invaluable to punters, as betting on teams that are undervalued by the bookies – or betting against those overvalued for that matter – is crucial in attaining long term profit. Just ask Mathew Benham, the professional gambler and owner of Smartodds, who uses xG. He’s made enough money to buy not one but two football clubs!
If you are unsure about how to calculate Expected Goals, don’t worry as this information is readily available online for most of Europe’s top divisions.
But you’re a smart punter seeking value in the lower reaches of English football. So, like the good people we are, we’ve opened the vaults to our spreadsheets and are happy to share Expected Goals tallies for League 1 and League 2 thus far. You’re welcome!
What the Data Tells Us
Firstly, here’s a quick overview of how to read the data. The numbers across the top are the Gameweek numbers, with the ratings listed alongside the team name. From Week 1, for instance, we can see that Blackburn played Southend in League 1 as their data matches. This gets trickier to follow down the line where teams have missed games, but the idea generally sticks.
The colour coding is just a visual guide: a score in green denotes that the team enjoyed an xG supremacy of 1.0 or greater, while red indicates a ‘loss’ of 1.0 or more. Blue is supremacy of 0.1-0.9, and the purple denotes concession by 0.01-0.9.
Now you know how to read the data, a few interesting items will reveal themselves:
There are a number of teams in both divisions who are going about their business very efficiently. Wigan in League 1 and Exeter and Coventry in League 2 are fully deserving of their lofty league placings.
Lucky….For How Long?
We spoke about Ipswich earlier, and the crown of lucky blighters in League 1 and League 2 goes to Shrewsbury and Luton Town respectively.
The Shrews top their division despite only claiming xG supremacy in one of their last four outings – a regression in their results is likely to come sooner rather than later. Luton, meanwhile, have only gained supremacy in one of their last five, but are sitting pretty in fourth regardless. Perhaps they are currently punching above their weight?
Just take a look at Cheltenham Town. They have absolutely bossed their last four games, and yet have only won one of those outings and remain in relegation peril in 21st.
But they were priced at 13/10 to beat Colchester last week and if you’d had the xG data to hand you’d have known what a fantastic price that was.
So now it’s up to you. Use this data wisely and give the bookies a good old bashing.