League One: What can Performance Data tell us about the run in?

The business end of the League One season is now looming large on the horizon as teams prepare to negotiate for a position of relegation safety, mid-table comfort, a play off slot, or automatic promotion. Anxiety levels amongst fans are starting to climb as many begin to question whether their team is really capable of achieving what they had quietly hoped for earlier in the season and, with most teams having ~10 games remaining in their schedule (some having as few as 9, Rochdale still with 13), now would be a good time to take one final look at the performance data (collected and provided by Stratagem) to see what light we can cast across each team’s chances of achieving a successful finish to the season.

All the insights to be discussed below are anchored around the metric Expected Goals which, if you’re not acquainted with it, is explained pretty well in this article on BBC Sport. Expected Goals are a good indicator of team performance because, by and large, teams that create more, better chances more often than their opponents tend to finish higher in the table (conversely teams that concede more, better chances to their opponents than they are able to create themselves tend to finish lower in the table).

We’ll go through some bullet point analysis on every team but first, let’s look at the data in a visual format to build the foundations for what we’re going to dig into in more detail later in the piece. As we’ll be largely focusing on the form each team is showing coming into the final stages of the season, the data used to produce these is from 21st December – 11th March, with most teams having played 13-14 games in this time, which is also the run of games played since I last wrote about the state of play in League One (link). Clear? Let’s dine.


Expected Goal Difference:

xGDifference vs Actual GDifference

Here we can see every teams Expected Goal Difference per Game, displayed as the coloured bars, reflecting how well each team have played based on the quality of chances they’ve created and conceded over the time frame mentioned. The Black Diamonds show their Actual Goal Difference per game over that time, with some teams having clearly under or over performed. We’ll refer back to these in good time so have a quick glance, we’ll come back later.

Expected Goals Created vs Expected Goals Conceded:

Attack vs Defence


Looking left to right, teams towards the left haven’t been creating too much in attack, with teams to the right creating plenty.

Looking top to bottom, teams towards the top have been performing poorly defensively, with teams towards the bottom performing more solidly at the back.


Chances Created per Game vs Average Quality of Chance created.

Attack_ Volume vs Quality

The further to the right a team is, the higher quality of chance they create on average. The further to the left a team is, the lower quality of chance they tend to create on average.

A team placed high in the graph tends to create a lot of chances per game, with teams towards the bottom of the graph generally creating few chances per game.

Chances Conceded per Game vs Average Quality of Chance conceded

Defence_ Volume vs Quality


Teams further to the right concede chances of high quality on average. Teams towards the left tend to concede poorer chances on average.

Teams at the top concede a larger number of chances per game. Teams towards the bottom concede fewer chances per game.

Now we’ve got that out the way, let’s get stuck in to what these can tell us about each team, their performances, and what this may mean for the remainder of their respective seasons. We’ll approach this purely by the order of the table at the time of writing, starting at the top.


Blackburn (1st):

Perhaps not the best place to start, as there isn’t anything particularly insightful to say about them that you won’t already know – they’re a good team, playing good football, and rightly in the title conversation. Performance-wise, they’ve been part of an elite group of 3 over the period we’re covering with Wigan and Rotherham, and have been in unwavering form for a long time now. They’ve only lost 1 in 26, failing to score in only 2 of those games and scoring at least two goals in 20 of those games. It’s pretty unstoppable form which has seem them rise to the top of the table, made more impressive given they were 6th on 1st November, 12 points behind Shrewsbury and 11 behind Wigan.

Wigan (2nd):

Now it gets more interesting. What the data above doesn’t show when averaged out is that Wigan have been on a slight downward trend of performances for a while now, but particularly since beating Oxford 7-0 on December 23rd – a game that is included in this dataset. The Expected Goals scores for that game (3.72 – 0.52) have buffed their averages slightly and, if we were to take that game out, would paint a less pretty picture. They were highlighted in the last League One article (just days before they thumped Oxford, ironically) as a team whose performances weren’t reaching the same dominant levels they’d set earlier in the season and it’ll be interesting now to see whether they can claw the points back in the games in hand they have on Blackburn, as well as pick up more points than them over the remainder of the season. Unless performances improve, I wouldn’t be betting on that happening.

Shrewsbury (3rd):

The absolute masters of getting the most out of their performances – something they’ve been doing all season long. Since week 1, they’ve been earmarked as a team somewhere between 3rd – 8th in the data at various points through the season and every time they’ve achieved form that has exceeded their performance levels. Once again their attack has put up frankly silly numbers, creating the fewest chances per game in the whole league across the period from 23rd December, but creating the highest average quality of chance in the league – by some margin. It passes the eye test; most of Shrewsbury’s goals tend to come from around the 6 yard box, and this ability to create a game-winning chance in almost every league game allows them to nick the all important one or two goals from the tight matches that could teeter either way and therefore keep pace with Blackburn and Wigan in the title race.

Rotherham (4th):

The data’s been quite keen on Rotherham all season long, even when they went 7 without winning through October and November, as they’ve consistently posted strong attacking numbers. That said, their form has been streaky all season long, typified by their latest effort of winning 7 in a row followed up by consecutive losses to bottom 4 sides. There’s plenty of positives about this team though and it seems their defence has tightened up compared to earlier in the season where they had similar attacking numbers (which have been around league best level all campaign) but shaky defensive numbers, conceding chances at the rate of a mid table side. However, through this period they’ve had the best performing defence from an Expected Goals perspective, conceding just 7 chances per game and generally of a below-average quality, so we’ll see to what extent that holds up and to what extent this impacts on their form heading into the play offs, which they look dead certs to be a part of now.

Scunthorpe (5th):

Another team pretty much nailed on for the play offs since the get go are Scunthorpe, though that notion hasn’t been under as much threat as it is now with them in the middle of a run of just 1 win in 11. Solely looking at results that would be concerning, but actually performances have been good and, having drawn 6 of those 11 games, it seems their problem has come from finishing teams off when they’ve been the better team. It’s pretty clear this run of form has come off the back of a weird run of conceding goals – Scunthorpe’s Expected Goals Conceded has been 15.69 through this period, when actually they’ve conceded 27. That’s a wild discrepancy which I can’t comment on the reasons for without consulting the video but I’d definitely argue some level of misfortune has hit them on this run and actually they’re pretty fine. Should canter into the play offs without much trouble.

Peterborough (6th):

A very interesting team to keep an eye on going forward now with the sacking of Grant McCann and the hiring of Steve Evans. They’ve broadly been play-off-contending quality all season, with a pretty average defence masked over by good attacking output headed up by Jack Marriott. Now Evans is in charge, if he can improve performances, even just by tightening the defence slightly without maiming any of the attacking output, then they stand a good chance of making the top 6 and being a much more difficult opponent than they were under McCann. Their games have tended to be of a high pace, with lots of chances at both ends but mostly from sub-optimal locations, as reflected in the below-average chance quality both in attack and defence.

Plymouth (7th):

Enough’s been said about their remarkable run of results, but less about the remarkable turnaround in performances. For the first half of the season, Plymouth were consistently bottom 4 material, always having some of the worst defensive numbers in the league with pretty poor attacking numbers too – if I had more time I would absolutely try to look at what they’re doing differently because the defence has shored up (9th fewest Expected Goals conceded) and the attack is now looking much more potent (3rd most Expected Goals created). Interestingly, this looks to have been from a dramatic increase in the quality of chances they’re creating – the actual volume of chances they’re creating hasn’t changed much at all, but the quality of them has seen their average chance quality evolve from 0.11 to 0.14. Small on the surface, but on 11 chances a game that’s an increase on their Expected Goals created per game of roughly 0.33. The biggest improvement has been defensively though where they’ve reduced both quality and quantity of chances they’re conceding. This improvement has been the wave that has carried them all the way to the brink of the play offs and it looks like a shoot out between them and Peterborough for who claims the 6th spot.

Charlton (8th):

A case of a team who have been good at times, but also bad at times, and not nearly consistently good more often than they are bad to give them a realistic chance at a top 6 finish. Their numbers over this period reflect their current position in the table but the only wins they’ve had in this run have been over teams in the relegation conversation. They’ve had their injury issues as well as losing Ricky Holmes in January so it’s understandable they might not hit the standards they’d consider their best but, with 5 of the top 7 to play, they need an improvement in overall performances or else it seems likely they’ll fall short of a play off spot.

Bristol Rovers (9th):

Having only lost 3/14, results had definitely improved on earlier in the season where they were the cliched “consistently inconsistent”, looking play off material one weekend, bottom half fodder the next. This improvement is largely down to a tightening up defensively which has seen them post the 6th best Expected Goals Conceded per Game, though their attacking output has reduced too. It’s a complete turnaround from earlier in the season where they were creating a lot of chances but also conceding them too and it’s fair to say this change of tact has paid off so far for Darrell Clarke. The question is though, will it be enough to pick up more points than Peterborough, Plymouth, and Charlton between now and the end of the season to reach the play offs?

Bradford (10th):

I almost don’t want to say much about Bradford as they’ve suffered enough in recent months. Performances took a nose dive as did results and neither have really turned around yet under Simon Grayson, languishing as the 19th best performing team in this run. Their problems appear largely to be defensive ones, having the 4th worst defence through this period, so that would be a good place for Grayson to start, though the attack could do with a little work too. Can imagine most fans are just looking towards the season’s end by now knowing in the back of their minds that any promotion hopes are all but gone.

Gillingham (11th):

Another team, along with Plymouth, who were dead and buried before a remarkable run of form carried them to safety. Steve Lovell managed to eek their attack into league-average territory and has done a good job of padlocking the defence too with their effectiveness clear from the Defensive Volume vs Quality graph – Gillingham concede a lot of chances but are very good at keeping the quality of those chances poor and thus making it difficult for their opponents to score. They’re comfortably a mid-table outfit now but, referring to the Expected Goal Difference chart, contrast their form in this period with Fleetwood as they’ve supposedly been performing to similar levels but with dramatically different results in Actual Goal Difference.

Portsmouth (12th):

They hit play off form going into Christmas but performances dropped off and are now looking very much a mid table team. Another quirky team like Shrewsbury – defensively Portsmouth are very good at preventing opponents from generating chances against them. It’s just that, when the opponents do create chances, they tend to be pretty good one’s and that’s something for Jackett to come up with a solution for over the summer as they look to enter the top 6 next time around. They’ve lost more games than anyone else in the top half this season making a play off finish highly unlikely.

Southend (13th):

Archetypal midtable team right now and that seems where they’re destined to finish, too good to be dragged into the relegation picture, too late and not good enough to mount a serious play off push. It’s way too early to draw any conclusions on the tenure of Chris Powell, but their numbers haven’t really changed under him at all; the defence has tightened but so has their attack. There isn’t really much more to add about their prospects this season, it’s all about building a foundation to grow on next season now.

Blackpool (14th):

For a team that finished 7th in League Two last season, Blackpool have adjusted well to the step up in class and haven’t really looked in danger of relegation at any stage through the season. Performances remain solid enough – slightly below average in attack, slightly above average in defence – and they should be comfortable in keeping their heads above water, with a 7 point head start over the relegation zone at the start of the run in. The antithesis to Shrewsbury’s attack, they’ve created the 3rd most chances, with the 2nd worst average chance quality through the period.

Walsall (15th):

Looks to me like the sacking of Whitney came at the right time. Performances and form were always just good enough to avoid dropping into the relegation zone but their defence was starting to trend downwards (3rd highest Expected Goals Conceded) which simply isn’t good enough to sustain a positive run of form on. The new manager’s task is to simply tighten that up, try and keep more clean sheets, and they’ll be fine. Another positive is their form against teams below them in the table (P13, W8 D2 L3) with 5 games against teams in those positions to come. Their ability to beat teams worse off than they are should see them stay up.

Doncaster (16th):

Doncaster had solid numbers at the start of the season that benchmarked them as a top half team, but they haven’t maintained those standards more recently with a run of form reading P11 W1 D7 L3. Performances have been on the slide too with their previously solid defence starting to concede chances of a higher quality and they’ve actually had a run of good finishing through this run to carry them to more draws than may’ve been fair, scoring 21 goals off 13.75 Expected Goals. Systemically, something’s not quite working as well as it was at the start of the season and a finish in bottom half purgatory looks likely.

Oxford (17th):

Another team who had the spotlight thrown on them earlier in the season. Under Pep Clotet, the team were profiling pretty badly as they consistently showed an inability to prevent opposition chances, but I gave Clotet the benefit of the doubt saying they might improve with more time to adjust to his methods given he was only months into the job. Performances declined even more and Clotet was sacked. Their problem has never been in attack, which has actually been half decent, but defensively they are extremely poor – having had the worst defence in this period by a long chalk (a trend that remains even when taking the Wigan result out). They’ve got to be careful, still having 5 of the current top 6 to play.

AFC Wimbledon (18th):

Similarly to Doncaster, AFC Wimbledon were a team that always profiled well by the numbers earlier in the season – generally keeping a solid defence, in particular – but never picked up the results their performances were saying they should’ve done which has left them in the relegation conversation all season. They were conceding goals at a rate above expected which prompted Neal Ardley to change shape from a 4-3-3 to a 3-5-2 which hasn’t paid off, performance levels have decreased more in line with their position and they’ve started to concede a higher quality of chance where previously they were limiting the quality of chances created against them. Had Ardley stuck it out, might their luck have turned?

Oldham (19th):

Oldham have been yo-yo-ing up and down all season, they seem perenially stuck either in a winless run or an unbeaten run. They started the season very poorly, but the appointment of Richie Wellens (with the help of top scorer Eoin Doyle) got them playing some very effective football particularly in attack which helped propel them up the league. That didn’t last though (coinciding with Doyle’s injury) and they dropped back into the relegation threatened territory. Currently on a 5 game unbeaten run (coninciding with Doyle’s return from injury), it would seem they have enough about them to stay up. Doyle’s goals will be absolutely vital to that though with a defence that seems to have a soft underbelly (3rd highest average chance quality conceded).

Northampton (20th):

A curious case, Northampton, having profiled as one of the worst teams in the league since the very start and still profiled as the worst performing team over the latest period. They’ve particularly struggled in defence where their numbers have remained around 1.6 Expected Goals conceded per game for a long time but, they’ve only lost 2/10 so they must be doing something right as well as outperforming Expected Goals at both ends of the pitch, not by a massive amount but enough to swing results their way. The teams around them have significantly better goal differences which means those extra points are all the more important.

Fleetwood (21st):

Fleetwood almost seemed to sleepwalk into the relegation places off that horror run of 6 losses in a row and it’s a little surprising to see them in this much trouble. They’ve never been close to looking like a bottom 4 team, looking more like a lower-mid table team, but they find themselves in this position having forgotten how to win games, their last win coming on January 13th. Contrary to Northampton who are somehow swinging results in their favour, Fleetwood’s results seem to consistently swing against them even if they’ve played as well as their opponents. Their problem is clearly defensive given they’ve conceded the joint 2nd most goals in the league, John Sheridan seemed like a shrewd appointment to combat this but they need to start being more ruthless in both boxes in games where they’re matching their opponents to pick up results, points, and places in the table back on their rivals.

MK Dons (22nd):

Dan Micciche was a brave appointment not least because of his lack of previous managerial experience but also because he seems to be a long term appointment looking to instil a playing philosophy into the team whilst in the midst of a relegation battle. The sentiment is admirable enough but performances have yet to turn, too often being 2nd best in chances created to their their opponents and, most harmfully, having played most of the teams around them during this poor run. Their failure to put in performances and pick up points against these teams have probably been the final nail in their relegation coffin, but a 3-2 win against Rotherham on Tuesday (the data of which isn’t included in this) does give them a glimmer of hope. Maybe things are about to turn but is it too little, too late?

Rochdale (23rd):

By far the most interesting case to keep an eye on until the end of the season. They’re in a false position due to falling games behind (with 3 games in hand on most of their rivals) and also a run of poor away form. 9/13 games remaining are at home where they are a different beast, having conceded just 9 goals in 14 games and only having lost 3 of those 14. They’re 6 points adrift but *should* be absolutely fine and they’ll believe that now too having picked up 7 points in their last 3, all with clean sheets. The data puts them comfortably in mid table (even top half!) which is more down to their defence than their attack – the amount of chances and quality of chances they concede is in line with the likes of Shrewsbury, Blackburn, Wigan and Rotherham. Their attacking output could do with a slight bump to be absolutely sure of turning those 0-0’s into 1-0 wins which shouldn’t be an issue with so many games at home, the next two of which are crucial – at home to Wimbledon and then Fleetwood.

Bury (24th):

It’s not looking good for Bury who are 9 points from safety with 10 games to play. There are some positives to draw on recent performances though: they’re not playing like a relegation candidate at the moment, with the 12th best attacking output and 19th best defensive output, leading to a run of recent form of 2 losses in 9. Performances have improved, but need to continue to improve to put together a run of form that could drag them out of this. I also have concerns about what they’re attacking output is made up of, given they’re creating the most chances in the league at the moment but with the worst average quality of chance (as you can see at the top left of the Chance Volume vs Quality created graph), presumably meaning they’re taking a lot of shots from range. Shot quality has to improve or they’re just relying on sheer luck of several long rangers flying in to save them from relegation. In fairness it’d be a fun watch, but they need more than that.

Hopefully you’ll agree that there’s a few interesting trends within the league at the moment which will certainly be worth keeping an eye on as the season comes to a close. There’s still plenty to play for and it’s not unfair to say that results and far more important than performances at this crucial stage of the season.

On a side note, some of you may not know I also maintain a Shots Dashboard from the League One data as well, allowing you to look at all the chances your team has created through the season, the link to which I shall paste below. Have a play with it and see what you think. Any questions or comments or feedback, don’t hesitate to get it touch on here or Twitter (@olivermpw_). Otherwise, thanks for reading!


League One Shots Dashboard


This article was written with the aid of StrataData, which is property of Stratagem Technologies. StrataData powers the StrataBet Sports Trading Platform, in addition to StrataBet Premium Recommendations.



League One Mid-Season Data Round-Up

Just like the quarterly review you may have sat through at work recently or an end of term parents evening at school, it’s time to call in the middle tier in the EFL and give it a once over just before the schedule hits overdrive for the festive period. I know it’s not technically the half way point with most teams having played 22/46 games, but some teams are set to play 4 games in 12 days and, with work and general life at their busiest at this time of year, I thought it best to take advantage of the quiet before the storm and pen the 2nd instalment of my data-dives into League One.

For those who didn’t read the first instalment (link here) back in October, the aim of this article is to look under the hood at every teams’ performance this season. Rather than just looking at the league table and drawing conclusions from that, we can use data collected by  Stratagem Technologies to look more deeply at these performances – explicitly their chances created and conceded – and use that as an alternative source to draw conclusions from.

The piece will be split into two parts. First, the season to date; an update on how every team has performed in their matches from gameweek 1 through to now. Second, a quarterly review which will look at the teams performances in the 2nd quarter of the season, to act as a direct follow up to the October article. This will be used to see which teams have seen a rise or fall in performance and which teams are trending upwards or downwards.

The data used is correct up to the 20th December. As always, I’ll paste my brief, explanatory paragraph on the main concept of the piece, Expected Goals, below for those who aren’t familiar with it. If you are familiar, feel free to skip the paragraph and get your teeth into the piece.

Expected Goals is simply a method used to quantify the quality of chances created and conceded by a team throughout a game. It is calculated by taking a shot and looking at historical data (collected by companies such as my employer, Stratagem) to calculate the conversion percentage of shots from the past that had the same characteristics as the new shot. The basic theory is that 1) the closer the shot is to goal, the more likely it’ll go in, 2) a shot from a central location is more dangerous than a shot from a wide location, and 3) shots with feet are more dangerous than headers from the same distance. As an example, imagine Harry Kane has a header on goal from just outside the 6 yard box following a cross from Danny Rose. You’d look back at all headers from just outside the 6 yard box following a cross, to find it has a conversion percentage of 15%*. This would give Harry Kane’s header an Expected Goal value of 0.15. If you’d like to read more about why Expected Goals is useful information for teams and players, I recommend giving this by @OneShortCorner a read as it explains in simple terms what xG’s useful for and how to interpret it, and also this by Bobby Gardiner, a Q&A on how best to interpret xG.

*I pulled this number out of thin air.


Part 1: The Season to date.


As explained, in this first part this will look at all the underlying data from every match up to 20th December, so we can see how the League has been performing so far and get an idea about whether any teams have been performing better or worse than their results suggest. I’m going to keep the format to this largely the same as the first post so it reads easily as a nice follow up but also leads into future posts as well.

We’ll start off by comparing every teams Expected Goal Difference with their Actual Goal Difference as that can give us an idea of who’s been performing above, below, or at the expectations their performances have given.


Overall Team Performance


xGDifference vs Actual GDifference
Green-Yellow Bars = Expected Goal Difference. Black Diamonds = Actual Goal Difference.

Initially, we’re just going to speculate on what we can see here before moving onto more detailed analysis further down the line.

Starting from the bottom, Plymouth, Northampton, Bury, and Gillingham all make up 4 of the current bottom 6 in the “real life” League One table and it doesn’t look undeserved based on their performances so far as they’re ranked bottom 4 for Expected Goal Difference.

Slightly further up, Oxford, currently 9th in League One, appear to have been overachieving on their performances a touch as their chances created and conceded dictate that we’d actually expect to see them further down the table and more likely in the bottom half. They’re currently rocking the 6th best Actual Goal Difference compared with the 17th best Expected Goal Difference – it’ll be interesting to see which, if either, of these changes by the end of the season. Certainly performances will have to improve if they’re to realistically achieve top 6.

Moving into the top half and it’s impossible to ignore AFC Wimbledon who are clearly underperforming so far. It’s something that was apparent in the first instalment too and it doesn’t appear that much has changed. Now languishing 23rd in the League One table with the 22nd best goal difference, their Expected Goal difference is actually 7th best so far, an absurdly large discrepancy between performance and results. They continue to score less than expected based on their chances created and continue to concede more than expected based on their chances conceded.

Blackburn look ready to push Wigan in the title race as improved performances in recent weeks have seen them rise up the Expected Goal Difference table into 2nd and gain plenty of ground on the early leaders. Maybe I’m being overly dismissive, but it doesn’t look as though there’ll be another challenger to these two with Rotherham’s challenge never materialising before dropping down the table in recent weeks, and the quality gap between Shrewsbury and the top two perhaps too large. This is something we’ll go into in more depth later on in the piece.

Any football fan will know that good results will come from having a great defence or a great attack, with poor results coming from a poor attack or poor defence. Let’s look at how the teams shape up when we separate them into attacking and defensive performance.


Attacking & Defensive Output


Attack vs Defence
Hat-tip to Ben Mayhew (@experimental361) for providing the inspiration for the layout.

To read this graphic:

-Teams to the right have a good attack. Teams to the left have a bad attack.

-Teams towards the bottom have a good defence. Teams towards the top have a bad defence.

As we saw above, Wigan have so far profiled as the best team in the league and you can see here that’s been built on having the 3rd best attack in the league (3rd in from the right) paired with the best defence in the league (placed lowest on the graph). They’ve performed at a level above everyone else so far and are deservedly atop the table.

Shrewsbury continue to power their unlikely promotion charge on a solid defensive base. 11/13 of their wins have been by a one goal margin with 6 of those coming from a 1-0 scoreline and it’s easy to see why looking at this. Their attack isn’t the greatest but they are squashing their opponents attacks sufficiently to mean any goal they do score is likely to result in a win as they’re unlikely to concede too many with miserly defensive numbers like that. Doncaster and AFC Wimbledon continue to post similarly good defensive numbers which should still provide them with the base to win enough points from and retain their places in the division.

In the top left, there’s a cluster of teams who look like relegation candidates should performances not improve. Plymouth, Gillingham, and Northampton have already been mentioned but joining them are Bury, Blackpool, MK Dons, Rochdale, and Oxford. Oxford have enough points on the board already to not be concerned and it’s not impossible to imagine performances might pick up as Pep Clotet becomes more and more bedded in to the job. The same cannot be said of the others though and they’ll need to be careful not get dragged into the fight should their relegation peers improve their performances and results.

Oldham, in the October instalment, were placed amongst this relegation-elect but have since moved from the top left over to the top right as Richie Wellens’ impact since becoming manager in October is visualised having given their attack a massive bump. They join Peterborough and Bristol Rovers as teams to watch if open games full of chances are your thing.

So now we’ve gained a flavour of how each team’s performed, we need to move on and drill a bit deeper in order to gain more insight into each teams’ performance. Starting with the attack, lets look at the quality and volume of chances being created.


Attacking Style: Volume vs Quality


Attack_ Volume vs Quality

To read this graphic:

-Teams towards the right take a high quality chance on average. Teams towards the left take a low quality chance on average.

-Teams towards the top create a lot of chances per game. Teams towards the bottom create few chances per game.

Lets throw the spotlight on the teams with a poor attacking output first. From the previous graph we could see that Fleetwood and Bury were amongst the bottom 6 for attacking output, but looking here we can see that’s for very different reasons. Bury would definitely benefit from better shot selection as they have the lowest average chance quality in the league, but are actually 12th for number of chances created. Without having seen any of their games this season, the data suggests that they are too often wasting attacking possession by taking a poor quality chance when they would perhaps benefit from trying to work a better opportunity. Fleetwood are a different proposition; they clearly emphasise shot quality (7th highest average) which is great, but they’re only averaging 8.5 chances a game which just isn’t enough to consistently outscore teams and thus consistently win games.

Anyway, the place you want to be is at the top right of the graphic and be a team that is creating high quality chances and a lot of them. There are two clear outliers here – kudos to Blackburn and Rotherham – whose average chance quality is indicative that they’re consistently carving teams apart and creating quality goalscoring chances. Blackburn in particular look like they sacrifice a bit of volume (8th in the league) but that’s not a problem when they’re creating highly dangerous situations that, statistically speaking, are much more likely to result in a goal.

Wigan‘s attack continues to look good with an above-average chance quality paired with the highest volume in the league.

How about the same Volume vs Quality question, but for the defence?


Defensive Style: Volume vs Quality


Defence_ Volume vs Quality

To read this graphic:

-Teams towards the right concede a high quality chance on average. Teams towards the left concede a low quality chance on average.

-Teams towards the top concede a lot of chances per game. Teams towards the bottom concede few chances per game.

As always, it’s interesting to look at the outliers. The little dots that, for better or for worse, have separated themselves from the pack.

From a defensive point of view, AFC Wimbledon, Shrewsbury, Doncaster, and Wigan have separated themselves for the better as they are clearly the better defensive teams in the division (the same 4 that received this accolade in the first quarterly review). Wimbledon and Shrewsbury are strangling opponents chance quality, limiting them to poor chances, whereas Wigan are putting the brakes on opponents attacking possession before they even create a chance, conceding just 7 chances per game.

There’s quite a few poor defensive teams on this showing as the top right quadrant is pretty busy. Of the teams that have a decent attacking output, Peterborough and Bristol Rovers continue to limit their play off chances by failing to plug the holes in their defence. Rotherham aren’t far away from joining them but they are at least limiting the frequency of their chances conceded.

Gillingham are able to differentiate themselves from their fellow relegation candidates in that they’re top 6 for average quality of chance conceded i.e they tend to force their opponents into taking shots from poor quality chances. This comes at the cost of conceding the most chances in the league though.

So that’s how things look from games 1-22 but, as mentioned, I want to split the season into quarters so we can look at how the teams’ have been performing since the first article went out – it’ll give us a few things to keep an eye on over the winter before the 3rd instalment and will also give food for thought over which way the teams’ trajectories may be about to head.

Part 2: The Quarterly Review


Obviously these tables will differ from those above, they’ll feature the last 12 games played by each team and can be used to say clearly who’s experienced a change in performance since the first article back in October. It’s a chance for you, the fan, to run the rule over your team’s quarterly performance and decide whether things look to be heading in a positive or negative direction.


Overall Team Performance


xGDifference vs Actual GDifference (1)
Green-Yellow Bars = Expected Goal Difference. Black Diamonds = Actual Goal Difference.

A quick flashback to the October edition, Blackburn had actually started the season poorly, performance and results wise, profiling as the 9th best team in League One after 12 games. Across their most recent 12 games though, they’ve clearly improved their performances and have profiled as the best team in the league through this period and by a distance too, leading to a run of 6 straight victories and causing Wigan to put their champagne back on ice.

Wigan and Portsmouth are 2nd and 3rd in this table with an Expected Goal Difference of +6.5 from the last period. However, looking at the Actual Goal Difference accrued through this period – there’s a stark difference. Wigan have managed to score a +18 difference through these 12 games, whilst Portsmouth have managed +1. This is a perfect example of why it’s useful to look at the underlying performances as, based on the data, the two teams have been playing to an equal standard in this quarter whereas actual results are vastly different. Somehow that’s not the craziest thing to appear on this table though…

You’ll  have to excuse my French here, but what the fuck Oldham? 22nd in this table in the last quarter, their performance from this quarter has profiled more like a play off chasing team which has borne out in their results too – W5-D5-L2 through the last 12 games. Frankly, this is a ridiculous turnaround in results for a team that had 4 points from 9 games at the start of the season and is also a ridiculous turnaround in performance for a new manager to oversee in such a short space of time. We’ll see further into the piece how the new and improved Richie Wellens Oldham incarnation differs from the dour John Sheridan team.

Another bottom 4 team from the last quarter, Gillingham, have moved themselves into the top half of this graphic. Another team that has felt the benefit of an early season managerial change, as well as positive off-the-field news too (resulting in this, erm, unusual press release), if performances continue in this vein then they should be able to pull themselves clear from relegation danger as was projected in the last period.

Obligatory mention of AFC Wimbledon . The Wombles continue to profile like a team that should be picking up more points than they are (through this period, xGD is +1.94, Actual GD is -5). I’m really, genuinely curious as to why they’re going through this level of underperformance so consistently with no sign that results have turned around yet. Maybe that’s something I’ll get to looking at in more detail but I’d genuinely love to hear if Wimbledon fans share the opinion that they haven’t been as bad as their results this season.

Looking further down, Plymouth, Northampton, and Bury have yet to see a turnaround in performances that should see them start to pick up results consistently enough to pull clear of danger. Plymouth and Northampton have both picked up points in the last 8 games (14 & 13 points respectively) but both have been through favourable fixtures so the data isn’t convinced this will be a lasting change in fortunes to the same degree as Oldham’s, for example.

Let’s move on to the attacking and defensive breakdown.


Attacking & Defensive Output


Attack vs Defence (2)

To read this graphic:

-Teams to the right have a good attack. Teams to the left have a bad attack.

-Teams towards the bottom have a good defence. Teams towards the top have a bad defence.

So, sometime in October, Blackburn jumped aboard the good ship S.S Massive Attack and have sailed it back into title contention, scoring at exactly 2.0 Expected Goals per game in the last quarter. This has powered their recent run of 6 consecutive victories and Wigan will certainly be looking over their shoulders now, especially considering Wigan’s own attack appears to have dropped off lately. This could just be a blip, in which case they’ve done well to ride the wave and continue to score at the same rate as they have done all season, but if their performance stays at this level from now onwards then they certainly won’t be walking to the title like it looked like they were going to do back in October. It’ll definitely be interesting to see how this plays out in the 3rd quarter.

Oldham have shown the 2nd best attacking numbers in the last 12 games. That’s right. Oldham. 2nd best attack. You better believe it.

Portsmouth again look impressive, mixing the 4th best defence with the 6th best attack – strong numbers at both ends of the pitch. They’re worth keeping an eye on as, if they keep these numbers up then it seems very likely they’ll break into the top 6 before the season’s done.

Shrewsbury just look a little weird here as they’ve had the best defensive showing coupled with the 4th worst attacking showing. Strangely, their already-great defensive numbers from the last quarter have improved in this one, but their attacking numbers have fallen off quite a lot. There’s more to this which we’ll come to shortly.

A word on Walsall‘s attack which appears to have disappeared off the face of the earth. Maybe I didn’t get the memo that rather than creating actual chances, they really are just going to feed Erhun Oztumer the ammunition and rely on him to pop one in from 30 yards in every game for the rest of the season.

Northampton are giving themselves a lot to do from 1.88 xG conceded per game. That really needs tightening up if they’re to get pick up results on a consistent basis.

Not long left now, but first it’s time to look at what those attacking numbers look like under the hood.


Attacking Style: Volume vs Quality


Before we look at the Volume/Quality graph, I’m actually going to refer back to the October instalment and the ‘Attacking Volume vs Quality’ section from that piece. Shrewsbury were featured in the bottom-right “Low Volume, High Quality” quadrant on the upcoming graph back in October, and I had this to say about their attack:

“Their xG per shot is 0.16 which equates to the average quality of shot they take being a 1-in-6 shot. It’s the best in the league and means that despite their low shot volume, it’s irrelevant as they’re taking a shot of league-best chance quality when they do decide to pull the trigger.”

About a week ago I received this tweet from Salopcast, a Shrewsbury podcast, commenting on their attacking performance in recent weeks.

Good Take about Shrewsbury

With that in mind, it’ll be interesting to see where the Shrews are placing now.

Without further ado:

Attack_ Volume vs Quality (1)

To read this graphic:

-Teams towards the right take a high quality chance on average. Teams towards the left take a low quality chance on average.

-Teams towards the top create a lot of chances per game. Teams towards the bottom create few chances per game.

Salopcast are absolutely right and it’s interesting that what they’ve seen with their eyes is also clear in the data. In October, Shrewsbury were on 9 chances per game and 0.16 xG p/chance. This time it’s 9 chances per game and 0.11 xG p/chance. Those good shots just aren’t coming anymore. It’s a concerning drop off, unsurprisingly coinciding with their worst run of results so far this season, and if they’re to continue their unexpected promotion chase they’ll need to revert back to their previous levels of chance quality because their attack in this quarter is not a promotion winning attack, no matter how good your defence is.

Moving away from Shrewsbury, Blackburn are sitting in that golden zone of the ‘High Volume, High Quality’ quadrant, quite a long way better than everyone else. Creating the 3rd most chances per game and having the highest average quality of chance, it’s no wonder they’re scoring goals for fun at the moment. You’d need a really bad defence to prevent an attack this good from powering you to victory in most league games.

Moving clockwise, we find Plymouth at the bottom of the graph, indicating that they’ve created the least amount of chances per game in the league through this quarter. Their average chance quality isn’t actually at all bad (11th) but it’s the sheer lack of times they’re testing the opposition keeper which doesn’t bode well. If you’re not creating many chances, you can’t expect to score many goals.

Continuing round the clock, we come to Walsall. To be frank, it’s a poor profile. 18th in the league for chances created and 24th for average chance quality which has been terrible in this quarter and there’s some serious questions to be asked of their recent shot selection. It’s helped that the aforementioned Oztumer, scorer of many a worldy this season, has been taking a few of them resulting in some goals but relying on your star player to come up with a wonderstrike isn’t exactly a sound attacking strategy. Saddlers, you have been warned.

Moving round again, Bury are at least creating a lot of opportunities, but the quality of them is poor and there’s an argument that they might be better shaving a couple of those chances off their total in exchange for a better quality of chance.

Lastly, Oldham and Bradford look to be in full, creative flow – creating a slightly-above-average quality of chance and on a much more regular basis than their opponents.

Well done if you’ve made it this far and breathe a sigh of relief as this is the final section.


Defensive Style: Volume vs Quality


Defence_ Volume vs Quality (1)

To read this graphic:

-Teams towards the right concede a high quality chance on average. Teams towards the left concede a low quality chance on average.

-Teams towards the top concede a lot of chances per game. Teams towards the bottom concede few chances per game.

If Blackburn’s Attack is Yin, then Northampton‘s defence is definitely Yang. Containing more leaks than Julian Assange, they’ve conceded the 2nd highest average chance quality and the 3rd most chances per game in the last quarter. Not. Good.

Conceding a similar amount of chances per game are Gillingham, but the average quality of their chances conceded is nearly half that of Northampton. The volume’s not great but the Gills are giving themselves a chance by limiting the quality of opportunities they’re allowing to their opponents with a 0.08 xG per Chance equivalent to a 1-in-12 conversion rate shot.

Directly below Gillingham is Shrewsbury who are conceding 8 chances per game with an xG per Chance Against a shade over 0.08. Even if their attack has dropped off over the last quarter, their defence has remained outstanding – they’re not conceding many chances and the chances they are conceding are not good chances.

Wigan are taking a slightly different but equally effective approach to running an elite defence. Their xG per Chance Against is actually pretty average (12th) but where they are succeeding more than anyone else (and have done all season) is being absolutely miserly in the amount of chances they give up – only 6 per game over this period. ‘Tis the season for giving but Wigan are very much the Scrooge of the division on current form.

Hopefully this has been an intriguing look under the bonnet of the League One season but that brings us to a close. For those of you with an active interest in the League, I also keep a Shots Dashboard on the League which features every chance taken by every League One team, as collected by Stratagem, which you can view from the link below:

League One Shots Dashboard

Use it wisely.




This article was written with the aid of StrataData, which is property of Stratagem Technologies. StrataData powers the StrataBet Sports Trading Platform, in addition to StrataBet Premium Recommendations.

The Blades’ Sharpest Edge: A look at Sheffield United’s 17/18 Set Pieces.

Sheffield United are arguably the club with the most upward momentum in the entire country at the moment. After a wobbly start last season, they eventually steamrollered through League One, finishing as champions with l00 points on the board. They now sit 3rd in the Championship and continue to pick up points at the same rate as they did in League One – kind of absurd when you think about it – with Chris Wilder, the manager, and Alan Knill, Wilder’s assistant, rightly getting plenty of plaudits for this period of success as the Blades look fearless in their bid to complete their ascendancy back into the Premier League.

It’s rare a team coming out of League One adapts to the Championship with the ease that Sheffield United have and many people wonder quite how Wilder’s managed it. I’ve been lucky enough to watch them a couple of times this season and, tactically, they’re genuinely a really interesting team to watch – setting up in a 3-5-2 and pretty consistent with their attack-minded, high-energy, high-pressing approach, always playing on the front foot. Probably their most interesting tactical quirk is the occasional use of overlapping centre backs to provide an overload on the wing.

That’s a little gem for you to go and discover for yourself though as, in this article, I’m going to put a certain aspect of their play under the microscope, another aspect of their play I think they’re doing very successfully – set pieces. To add a bit of colour to this, I’ll first provide you with a quick bit of background on how Wilder & Knill initially grabbed my attention about two years ago now.


Part 1: The Back Story


To be honest, this part isn’t an obligatory read and you can skip down to Part 2 if you’re in the mood already and just want to see the analysis of Sheffield United. It’s not advised though – this is a good primer to get those juices flowing.

The Date: December 12th 2015. The Match: Luton Town vs Northampton Town.

Many of you won’t be aware that I’m a Luton fan first and foremost. On the date mentioned, I found myself in the stands and enjoying Luton’s game against Northampton who had started the season very well – joint-top of the League Two table at the time this match was played – and who were then managed by a certain Chris Wilder and Alan Knill. Who’d have thought. Luton took an early lead in the 9th minute before this happened in the 18th…


WILDER Northampton

Probably the best set piece routine I’ve ever seen in the flesh. Our defence was pretty clueless that season but, in fairness to them, I think this routine would’ve had even the wiliest of old-school Italian defences chasing shadows.


***Fast forward to the following season – 2016/2017.***


The Date: 24th September 2016. The Match: Scunthorpe United vs Sheffield United


To quickly fill you in on what occured for Wilder & Knill between the 12th December 2015 and 24th September 2016, Northampton went on to win 99 points and the League Two Title prompting Wilder’s boyhood club Sheffield United to come calling for his services, which Wilder enthusiastically accepted.

I wasn’t in attendance at the match this time, but rather sat on my sofa watching the highlights of the EFL goals the following morning. I do have a strong interest in all the goings on from the Championship down to League Two, but a match-up between Scunthorpe and Sheffield United was fairly unremarkable to me until this happened…


WILDER Scunthorpe
Time passes. Memories fade. Formations change. Managers leave. But hearts never forget.

Honestly, if I was impressed the first time, I was doubly so the 2nd time as I realised that Wilder & Knill (and I’m led to believe it’s mostly Knill) take their set pieces seriously. Anyone who can turn a regular, edge-of-the-box free kick situation into a one on one with the keeper has my attention. And with my attention held, this next match then happened…


The Date: 26th November 2016. The Match: Charlton Athletic vs Sheffield United


Slightly further into the 16/17 season, I’m in attendance at this match for work reasons and looking forward to watching a Sheffield United side who were looking like they might finally break out of League One after 5 years of failing to do so and underperformance on their budget and expectations. The away side take the lead with this:



There’s question marks over the goalkeeping, sure, but again it’s obvious this was another routine that had another defence dumbfounded and frozen in the headlights. Charlton’s defence didn’t know what to do once Mark Duffy makes his run into the right channel (aided by some clever blocking by Chris Basham #6). Even if Duffy doesn’t shoot, they’ve still managed to create a dangerous cut-back situation from a free kick many teams would opt to directly shoot from (only resulting in a goal ~5% of the time).

The rest, as they say, is history. Wilder took Sheffield United to the League One title (a 2nd successive title for him) with 100 points on the clock.

So now you have the backstory, you can better understand my motivation for taking a look at how Sheffield United have been getting on with set pieces this season, especially given the way they’ve started this season as Mr Midas-Touch himself (Wilder, as if I really needed to clarify) leads them to what’s looking like another successful campaign.

To get a general overview of how Sheffield United have been performing on set plays this season, we’re going to look at what the data says about their set pieces first, kindly provided by StratagemThis will be a brief but important overview, shaping the rest of the piece.

If you’re unfamiliar with the concept of Expected Goals/Chance Quality – give the paragraph below a quick read. If you’re comfortable with the idea, carry on.

Expected Goals (xG) is simply a method used to quantify the quality of chances created and conceded by a team throughout a game. It is calculated by taking a shot and looking at historical data (collected by companies such as my employer, Stratagem) to calculate the conversion percentage of shots from the past that had the same characteristics as the new shot. The basic theory is that 1) the closer the shot is to goal, the more likely it’ll go in, 2) a shot from a central location is more dangerous than a shot from a wide location, and 3) shots with feet are more dangerous than headers from the same distance. As an example, imagine Harry Kane has a header on goal from just outside the 6 yard box following a cross from Danny Rose. You’d look back at all headers from just outside the 6 yard box following a cross, to find it has a conversion percentage of 15%*. This would give Harry Kane’s header an Expected Goal value of 0.15. If you’d like to read more about why Expected Goals is useful information for teams and players, I recommend giving this by @OneShortCorner a read as it explains in simple terms what xG’s useful for and how to interpret it.

*I pulled this number out of thin air.


Let’s get going.


Part 2: The Data


To frame their season so far, Sheffield United have accrued 36 points from 18 games, putting them 3rd in the Championship table. For what it’s worth, I’ve also got them rated 3rd in my expected goals model generated from the Stratagem data, so they’ve been broadly getting the results they deserve so far and are already an elite Championship team.

As stated though, we’re focusing on set pieces so lets look at how The Championship looks in attacking set piece performance – the data is filtered to include only chances created from corners and free kicks (so doesn’t include direct free kick shots).

First up, the total chances created from set pieces this season.

DASH Set Piece Chances (1)

The Blades are sitting pretty in joint-4th for most chances from set plays this season with 24 chances created. So we can already see they’ve been active in that respect, as expected.

It’s a good trait to be creating a large number of opportunities from set plays, but what about the quality of chances created from those plays?

Here’s the total xG created from set piece situations.

DASH Set Piece xG For (1)

Again the Blades are stacking up well here, ranking 2nd in expected goals created from set plays.

Lastly, just for further illustration, we want to know how the Blades shape up when looking at who’s the best at creating high quality chances on average from set plays, done by dividing the Total Set Piece xG by the Total Set piece chances created.

DASH xG per Set Play Chance (1)

I suspected this might be the case having watched A LOT of Sheffield United set piece video over the last couple of days (oh, trust me, you’ll be hearing more on this). Of the chances that the Blades have created, the average quality of them is higher than the rest of the league and reflects the thesis that they know how to create a good chance from a set piece.

*Disclaimer: Take all these numbers with a pinch of salt. The season is fairly young and the number of chances fairly small, so some of this may be down to accident rather than design. But there’s enough to go on to tell a story so lets do just that*

Juuuuuust before we move on to the good part, we want to know which players have been the most dangerous outlet for Sheffield United. We’re going to be focusing on one guy and here’s the reason why:


Player Set Piece xG


Meet Jack O’Connell. Or Jack O’Cornerll as you may as well start calling him. I stopped short of titling this piece “The Jack O’Cornerll Story” because there’s plenty of other facets to Sheffield United’s set plays that make them so effective, not just O’Connell. But, the point is, I could well have done. The League leader in xG’s from set pieces, the boy is a set-piece magnet/pain in the backside for defences as we’re about to see.


Jack O'Connell celebrates scoring his sixth goal of the season
Jack O’Connell – Coming soon to a far post near you.


12 chances may seem like a low number but the data will only account for occasions when O’Connell has got a shot off (or has come very close to getting one off as we do collect that data too). It won’t include times when he’s played knock down’s for other players, or has made an excellent run but hasn’t been rewarded with a quality of delivery that means he’s able to get an attempt on goal.

But as any Real Football Man™ will tell you, football isn’t played on spreadsheets, it’s played on the pitch. So your reward for making it this far is that you now get to watch more video of what Sheffield United have come up with this season and why they’re one of the most dangerous teams in the Championship from these situations.


Part 3: The Video


So for this section we’re going to look at Corners and Free Kicks separately and look at the trends for each to see if we can pick up on what Sheffield United are doing that’s generating their set piece threat. Corners first.


I should point out now that I’m using data up to 20th November as that matches the data I have available for the Expected Goals graphics above – so Sheffield United have played 17 games in the dataset I have available. They’ve had 114 corners in this time and, because I’m too good to you, dear Reader, I’ve watched every single one of these in video and collected some basic information about the delivery of the corners to try and break down what Sheffield United are trying to do and discover any trends.

To give you some initial primers on what you’re about to watch:

-Sheffield United have 2 main corner takers: John Fleck (49 taken) and Paul Coutts (40 taken).

-70% of their corners are in-swinging – a clear strategic decision.

– Of their 114 corners, 21 have directly led to a shot (18%)  but with several others going close to creating dangerous situations, as you will see.

-Their split between different Areas of Delivery is fairly even: Near Post (24% of deliveries), Far Post (32%), Centre (area between the goal posts – 21%) and Short corner (23%)

-However, Far Post Corners account for 61% of their total corner chances, and 54% of their xG created from corners. It’s clear that Far Post corners are their strength so we’re going to look at those particularly closely. As you’ll see with the upcoming analysis, The Blades are reeeeally good at creating far post opportunities.


The Headline Routine –  The Bear Hug Block


I’m just going to dive in head first here and start off with my favourite corner hack I’ve seen possibly ever? Not because of the great chance created, but because of how it’s created. In their recent fixture vs QPR, United manage to create a humongous space at the far post and there’s a few things to break down here as to how they’ve managed to do it – it might require you watch the routine 10+ times but stay with me, it’s worth it when you can finally see all the moving parts and get a clear picture of what Wilder and Knill were aiming for on the training pitch.


I’ll link to the video for those who want a clearer view. Click here.

  1. For starters, there’s an option for the short corner which drags two QPR bodies out of the box, leaving a 6v5 in QPR’s favour in the penalty area.
  2. Before the ball is played in, watch #6 Chris Basham in the far-centre of the 6 yard box. His run drags his marker towards the near post and away from the far post.
  3. Now, by the ‘keeper, watch Clayton Donaldson holding his marker down, preventing his marker from covering the far post delivery.
  4. One of 3 players starting near the penalty spot, watch Cameron Carter-Vickers make a darting run to the near post to take his marker with him.

Now we know how the space at the far post is created. But how is it expolited?

  1. Cast your attention to the gathering on the penalty spot at the start of the delivery. This is where Jack O’Connell and partner-in-set-piece-menace Leon Clarke start, with Carter-Vickers.
  2. As soon as Coutts, taking the corner, drops his arm, just watch Clarke. He grabs O’Connell’s marker into a bear hug leaving the marker no chance of tracking O’Connell.


Voila. It’s so damn smart, but somehow O’Connell fails to hit the target. They even tried it again in the same game a few minutes later with O’Connell and Clarke swapping roles. This time O’Connell’s marker is wise to the routine and follows the ball whereas Clarke’s marker manages to follow him literally by grabbing a handful of his shirt and clinging on for dear life.

giphy (1)

They’d tried this one in the previous fixture vs Leeds too, though the execution was let down by a poor delivery from Mark Duffy this time. But O’Connell was there and free at the far post again and it’s hard to imagine him not getting a goal from this exact method at some point during the season should teams not wise up to it.


giphy-downsized-large (2)


The Trends


So that was the headline routine which is by far their most dangerous. There’s two main trends I’ve observed from Sheffield United’s other corner’s and how they look to create the space to attack.

1) Blocking.

In case I haven’t made it clear enough, O’Connell is Sheffield United’s biggest set piece threat and that’s very much intentional. Most of their routines are set up to get him on the end of them as seen above and in further examples below. This video is from their match vs Barnsley and, although the video isn’t ideal to show it, you can still see how blocking has created the chance for O’Connell here. Blocking appears to be Sheffield United’s main strategy of creating chances vs man-marking set ups.

  1. O’Connell is the player near the edge of the box at the start of the video, with Jake Wright the closest Sheffield United player to him. Both are clearly marked by Barnsley players.
  2. Whilst the video is zoomed in on John Fleck taking the corner, Wright steps across O’Connell’s marker to delay his run by that fraction of a second needed to create enough space for O’Connell to win the header and have a decent attempt on goal. You can just about see this as the camera reverts back to the standard TV angle.

giphy (2)


And now a slightly different version of the routine here but that still reinforces the point, vs Hull.

For starters, this time it’s a near-post run. Keep your eye on the bottom right of the video as Duffy prepares to take the corner. Carter-Vickers is clearly watching and waiting for O’Connell to make his run before making that trademark step across the defender. Football is a game of fine margins and what finer margin than half a second gained on your defender which allows a free header at goal.

giphy-downsized-large (6)

2) Using runners to create space at the far post.

It’s a point I mentioned earlier, Sheffield United are great at using runners to create space for O’Connell to attack. In this one, vs Ipswich, Sheffield United start off with 5 men in the penalty area – 3 in the 6 yard box, 2 in formation near the penalty spot. Starting from the 6 yard box, Leon Clarke and Chris Basham make runs towards the near post taking 4 Ipswich defenders with them.

Thanks to these runs, this leaves O’Connell, starting at the top of the penalty area, with a one on one in which he is always likely to win.

giphy-downsized-large (4)

All the examples we’ve seen so far have been broadly man-marking set ups, so how do they fare against zonal marking?

3) Zonal Marking

I couldn’t find too many clips to actually give this question a good answer, but this vs Norwich is probably the best example.

Norwich line up with a 7 man defence on the edge of the 6 yard area, also placing 1 man on the far post.

Sheffield United’s answer to this one is simple (and heartwarmingly predictable now): Block the far side defender and allow Jack O’Connell a free header of the ball. You can see Jake Wright get into position to block Cameron Jerome (#10) and make sure Jerome isn’t able to make any movement towards the ball.

giphy-downsized-large (5)

That just about covers all my observations on the Blades’ corners. But, as you saw at the start of the piece, Wilder & Knill are savvy at free kick set ups too – so what about those?


Wide Free Kicks

I’ve defined wide free kicks as any dead ball taken from an area outside the width of the penalty area. I’m also going to break these up further into, for want of better phrases, “Deep” Wide Free Kicks and “Shallow” Wide Free Kicks. Deep Wide FK’s are free kicks taken before the 18 yard line, with Shallow Wide FK’s taken beyond the 18 yard line. This may seem odd but there’s a reason why I’ve made that distinction which we’ll discuss shortly. Let’s start with Shallow Wide Free Kicks.

Shallow Wide Free Kick’s

I’ll whizz through these in order to get to the Direct Free Kicks where there’s a bit more action to speak of, but this piece is all about Sheffield United’s set piece trends and one thing I’ve noticed is the differentiation between these Shallow WFK’s and Deep WFK’s. Shallow WFK’s are almost always taken with an in-swing, much like their corners are. This seems smart as, with less of a gap between the defensive line and the goalkeeper, there is little space for any attackers to run in to, so an in-swinging free kick makes up for the lack of running space by allowing the striker to use the movement of the ball to guide it towards goal rather than trying to change the direction of the ball like they would have to if the free kick was out-swinging. By the same token, it’s slightly harder for defenders as they have to be more precise about any clearances they attempt with the ball moving towards their goal rather than away from it.

Two examples are this vs Cardiff:

giphy (3).gif

And this vs Middlesbrough:

giphy (4)


Deep Wide Free Kicks

On the contrary to what I wrote for Shallow WFK’s, Sheffield United show a preference for out-swinging free kicks when taking from deeper wide positions. With these, there’s a large space between the defensive line and the goalkeeper so the attacking players will now have more room in which to attack the ball. With an out-swing, this leaves little chance of the goalkeeper coming to intercept the ball which, if executed correctly, leaves the Sheffield United attacker in a one-on-one duel with his defender.

Leon Clarke showed a good execution of a typical Sheffield United Deep Wide Free Kick vs Wolves, sticking to his man and using the pace of the ball to head it back across goal:

giphy (5)


This next one is slightly different as it looks more like it’s just down to the improvisation and excellent communication of Fleck, delivering, and Billy Sharp, receiving, but my hunch is that the look they share between them is an indication that this was pre-meditated. Just watch how Sharp appears to be jogging back into position but gets Fleck’s attention and they share a look before Sharp spins off the defence.

giphy (6)

We’re nearly done, just one more aspect of Sheffield United’s set piece play that we need to look at: free kicks from (typically) Direct situations.


Direct Free Kicks

It’s only fair that we give those two crafty free kick routines that were seen at the beginning of the piece the once over in the same way we’ve looked at every other set piece situation. Particularly as The Blades have actually attempted both routines this season, showing they’re very much still a part of the playbook.

Now I can only speculate but it seems Wilder has a bet on O’Connell to be Championship top scorer because he really does seem intent on having the man on the receiving end of every set piece. This is vs Reading.

giphy (7)

I’ve said this already but I really do love this routine simply because when it works, it turns a poor goal-scoring chance into a great goal-scoring chance. This one didn’t come off quite as well because Chris Gunter  reads the situation and is able to get across to block despite Mo Barrow’s questionable decision to just let O’Connell have the freedom of Bramall Lane. I’m actually going to break the routine down using the successful version seen earlier as it’s much cleaner and easier to break down the moving parts.


WILDER Scunthorpe

I’m aware this is like a potato-print painter trying to describe the works of Van Gogh, but this potato-printer has studied the Van Gogh painting enough times to know what’s going on.

-First up, make a mental note of goalscorer Chris Basham’s starting position, stood as part of the wall.

-Next, examine the role of the player who first runs over the ball. This is John Fleck – without this run the goal couldn’t happen. What he does is drag the only Scunthorpe defender who *might* just track Basham’s run away from the wall, thus taking him away from Basham.

-The wall itself is completely focused on blocking the expected shot, and are then caught unaware when the ball is passed to you-know-who  Jack O’Connell.

-Basham has already pulled away from the wall by this time and the first time pass from O’Connell leaves Basham with the relatively simple task of finishing past the keeper.

I mean it’s just so good, isn’t it?

And now for the other routine, seen here in action this season vs Nottingham Forest:

giphy (8)

No goal this time and probably not as pretty as the previous masterpiece but, as you can see, a cutback is arguably a more favourable position to be than taking a cross from the free kick starting point, thus making it a +EV move. Even though it didn’t come off, the point of why Wilder & Knill dream up these routines is an important one which I’ll try and summarise below.


Closing Thoughts


What you want to try to do with all set pieces, through any method, is to create the optimum possible goal-scoring opportunity from the situation.


I think we can all see now that that’s exactly what Chris Wilder & Alan Knill are doing.



Twitter: @olivermpw_


If you enjoyed this article and want to see more coverage of set pieces and routines in particular then I implore/urge/demand you check out Stuart Reid’s work (@From_the_wing). His work on set-pieces is largely what inspired me to churn this piece out and given that he currently works with professional clubs on their set piece execution, it’s best you read all while you can before he signs an NDA and stops sharing the good work with us.



This article was written with the aid of StrataData, which is property of Stratagem Technologies. StrataData powers the StrataBet Sports Trading Platform, in addition to StrataBet Premium Recommendations.

League One: A Data-Driven Round Up

I’ve been meaning to get this written up for at least 3-4 weeks now but time has been scarce. On the bright side though, this means we’ve now got a bigger dataset to look in to and a more rounded picture of how the teams in League One have been performing.

The first thing to note before we get stuck in: the data used in the article is correct prior to last weekend’s games. So, within this dataset, the majority of teams have played 12 matches instead of the 14 they’ve actually played as of last night.

Secondly – and the essence of this piece – is that the data used in this piece is courtesy of Stratagem Technologies. As of this season, Stratagem have started collecting detailed chance data for League One which, thanks to their generosity, means we can now use that data to assess team and player performance from a Chance Quality/Expected Goals point of view – the under-the-hood, driving forces that allow us to make judgements on actual performance levels rather than just results.

As always, just in case anyone reading this isn’t familiar with what Expected Goals represents, I’ll paste an explanation from a previous article of mine below. If you’re comfortable with the concept, feel free to skip the next paragraph.

Expected Goals is simply a method used to quantify the quality of chances created and conceded by a team throughout a game. It is calculated by taking a shot and looking at historical data (collected by companies such as my employer, Stratagem) to calculate the conversion percentage of shots from the past that had the same characteristics as the new shot. The basic theory is that 1) the closer the shot is to goal, the more likely it’ll go in, 2) a shot from a central location is more dangerous than a shot from a wide location, and 3) shots with feet are more dangerous than headers from the same distance. As an example, imagine Harry Kane has a header on goal from just outside the 6 yard box following a cross from Danny Rose. You’d look back at all headers from just outside the 6 yard box following a cross, to find it has a conversion percentage of 15%*. This would give Harry Kane’s header an Expected Goal value of 0.15. If you’d like to read more about why Expected Goals is useful information for teams and players, I recommend giving this by @OneShortCorner a read as it explains in simple terms what xG’s useful for and how to interpret it.

*I pulled this number out of thin air.

No hanging around though, let’s get going…




Overall Team Performance


You may or may not be familiar with the saying occasionally heard in football circles: “The League table tells lies.” It’s true. Sometimes good teams lose matches. Sometimes bad teams win matches. Sometimes a team will create chance after chance and somehow fail to score, going on to lose the game. Sometimes teams will be under siege in their own half for 90 minutes but score from a lucky, deflected goal to claim a win. This happens every single week in football and so it can be helpful to look past the scoreline to see how a team has performed on a chance creation and prevention basis. This is what we’ve been doing at Stratagem for League One so lets look at how the Expected Goals Difference table looks – again this was after Matchday 12.

DASH GD Performance
Green Lines = Expected Goal Difference. Black Diamonds = Actual Goal Difference


Some parts of this resemble the actual league table – Wigan have been clearly the best team in the division so far, Gillingham clearly the worst. We’ll drill down into what’s gone right & wrong for these two teams later in the piece but first of all, it’s more interesting to look at the outliers rather than just saying what many of you will already know about Wigan and Gillingham – “Good team is good. Bad team is bad.”

Anyone else have AFC Wimbledon and Doncaster as top 6 performers so far? Me neither. The Wombles in particular have a clear disparity between their Expected Goal (xG) Difference (+3.85) and their Actual Goal Difference (-9) which has been driven by under-performance at both ends of the pitch. Based on our Chance Model, their “xG For” total at this stage is 13.51, versus 5 goals scored, and their “xG Against” total is 9.66, versus 14 goals conceded. No matter how bad the Wombles’ finishing or goalkeeping has been which has led to this difference, in the longer term I think fans can rest assured that results will begin to turn and a relegation battle *should* be comfortably avoided if they continue to keep performing as they have been.

Next up in the spotlight; League One surprise package Shrewsbury. A team who struggled against relegation last season and tipped for a similar season this time around, they are now top of the league and are still unbeaten. Quite a number of people are claiming that they don’t expect this to last and they may be correct, the Shrews perhaps lack the squad depth of other competitors in the upper echelons of League One which may count against them as the season goes on but, as the above table shows, so far Shrewsbury have been genuinely good. There’s no luck here, they’ve got the 3rd best xG difference in the league which is enough to put them into the promotion equation and, as we’ll see further into the piece, there may be a reason why they’ve been able to record such consistent results to place them 1st in the table rather than the 3rd place that the Expected Goal Difference table has them…

Now though, let’s see how the teams’ defensive and attacking performances look against one another to draw further conclusions:


Attacking & Defensive Output


DASH L1 xG Matrix

To read this graph:

-Teams towards the top have a bad defence. Teams towards the bottom have a good defence

-Teams towards the right have a good attack. Teams towards the left have a bad attack.


Some quick takes on what we can see here:

Wigan have both the 2nd best attack and the 2nd best defence in the division. No other team is able to put up such illustrious numbers at both ends of the pitch reflected in the fact that they are out there on their own in the bottom-right of the graph.

Rotherham have the best attack in the division, but it’s matched with a mid-table defence.

Bristol Rovers and Peterborough have top 6 attacks but also have bottom 6 defences.

AFC Wimbledon have the division’s best defence, but it’s matched with a bottom 6 attack.

Gillingham and Northampton have bottom 4 defences and bottom 4 attacks. A recipe for relegation unless performances can turn around.

Oldham  and Plymouth have bottom 4 defences but their attacking output is not as bad as their other relegation rivals, posting attacking numbers more consistent with mid-table, but still below average.

This is reasonable initial insight, but let’s break this down further by looking at what’s powering each teams’ defensive performance and attacking performance.


Defensive Performance


Taking a deeper dive into the defensive numbers of the teams, we can look at the number of chances conceded per game versus the average xG value/quality of each shot that each team is giving up. This is so we can compare which teams concede lots of shots versus few shots and which teams concede low quality chances versus high quality chances (on average).


DASH Defence Viz

To read this graph:

-Teams towards the top concede lots of shots per game. Teams towards the bottom concede few shots per game.

-Teams towards the right concede a high chance quality on average. Teams towards the left concede a low chance quality on average.

Let’s start by acknowledging the best defensive teams in the League as shown in the “Low Volume, Low Quality” quadrant – AFC Wimbledon, Shrewsbury, Doncaster, and Wigan.

AFC Wimbledon are showing an elite defensive performance which is clearly being driven by two factors. One, is that they concede the lowest average chance quality in the whole league, i.e, Wimbledon are great at preventing teams from creating high-quality chances against them and are great at forcing teams to instead take low-quality shots – a very valuable trait.

The idea behind this is a maths-y one based on variance – the long and short of it is that, defensively, it’s better to concede a lot of low-quality shots than a few high-quality shots (and, conversely, offensively it’s better to take a few high-quality shots than a lot of low-quality shots) as you’re increasing the chances of benefiting from a positive swing of variance and decreasing the chances of suffering from a negative swing in variance. If you want to understand more about the concept, read this.

Better than conceding a lot of low-quality shots though is to only concede a few of them: hello again Wimbledon and your 4th-fewest shots conceded. George Long’s goal isn’t even being peppered with these fairly poor attempts at goal, he’s receiving a light sprinkling of not-very-threatening attempts. Despite Wimbledon having conceded 14 goals from the opening 12 games, if they continue to defend as they have done so far then they should soon start picking up results and clean sheets.

Wigan are limiting their opponents ability to get shots off against them at a league-best rate, conceding a meagre 7.6 chances a game. What we can also see is that they’re also strangling the quality of chance their opponents are able to take by having the 7th best xG p/shot against. It’s commendable enough to concede so few shots but to limit the quality on them as well is a potent clean-sheet cocktail and a big reason why they’d only conceded 7 goals in the 12 league games played at this point.

I promised we’d continue to examine why Shrewsbury have started so well, and you can see they are placed very closely with Wimbledon as a team that also concedes very few attempts on goal, but also are 2nd best in the league at limiting the quality of these attempts. Their defensive performance has been really good so far – I’ve watched them twice now this season whilst working for Strata and (quick scouting report) my observation is that the primary reason that teams are really struggling to break them down is because of the immense defensive work rate of the midfield 5 of their 4-5-1. The wide men, commonly Shaun Whalley and Alex Rodman, are excellent at tracking back to help their full backs whilst in the middle, Jon Nolan and Abu Ogogo aggresively press the ball every time it comes into the middle third and aid Ben Godfrey in blowing up everything that comes at them centrally. Nolan has been the standout performer for his attacking as well as defensive contribution and is disproving the quiet suspicion I had that he was signed just because he’s an uncanny double for Shrew-of-old and current Brentford player Ryan Woods.



Moving swiftly on though and somewhat alerting (to me at least) is to see two teams who harboured realistic play-off ambitions at the start of the season currently in the “bad defence” quadrant in the top right. Plymouth, Oldham, Northampton and Gillingham are all teams you’d expect to see there and, being current relegation candidates, would probably be the first teams you’d guess at having poor defences. Somehow though, Bristol Rovers and Peterborough are managing to concede the volume and quality of chances at a near-equivalent rate to the relegation elect, something that will hinder each teams’ respective promotion pushes in what seem to be “we’ll score more than you” strategies. This has to be done properly though by having an outstanding attack capable of consistently outscoring such a leaky defence and there’s one team who are showing these two how it’s done in this regard which we shall look at next…


Attacking Performance


So here’s the same graph but this time for the attacking output of the teams – the average amount of chances created per game alongside the average xG value per chance created.

DASH Attack Viz (1)

To read this graph:

-Teams towards the top are taking a high volume of shots per game. Teams towards the bottom are taking a low volume of shots per game.

-Teams towards the right are taking a high-quality shot on average. Teams towards the left are taking a low-quality shot on average.

We’ll quickly go back to Shrewsbury because their attack is interesting. We’ve already established how well they’re performing defensively – conceding low-quality chances and a low volume of them. Well, in attack they create the 5th-fewest chances per game, which, pretty bad right? They create roughly the same amount of chances per game as Gillingham?

Correct, but there’s a difference. Shrewsbury’s chances have an xG p/shot value nearly double that of Gillingham’s which is why they’re able to make a low shot-volume work into a successful attack. Their xG per shot is 0.16 which equates to the average quality of shot they take being a 1-in-6 shot. It’s the best in the league and means that despite their low shot volume, it’s irrelevant as they’re taking a shot of league-best chance quality when they do decide to pull the trigger. To use the dice metaphor that’s been used before: Shrewsbury are rolling a 6 sided dice when they shoot, and are only allowing their opponents to roll a 10-sided dice. By doing this they are stacking the odds in their favour and once you know this information, it becomes less surprising that they continue to rack up the results and are currently unbeaten.

It’s quite clear though that Rotherham are the best attacking team in the division. Out there on their own at the top-right of the graph – they pummel teams right in the penalty area by taking a lot of shots of a very high quality. This is very hard to do. As you can see, the class team in the division – Wigan – are able to match them for volume but can’t match the quality of shot. Another close competitor – Shrewsbury – are able to match the quality of shot, but can’t match the volume. So it’s genuinely impressive that Rotherham have such a high volume, high quality output but, as we’ve seen earlier, they’ve sacrificed some defensive stability in order to do this. Combining a mid-table defence with a league-best attack isn’t the worst strategy in the world though and it’s perfectly possible that their attack could power them all the way to promotion – they don’t need a high-performing defence when the attack is so good and should consistently outscore the opposition.

Right now Gillingham and Northampton look pretty doomed with their current attacking output. They’re failing to create chances and can’t even claim that their rare opportunities are good ones.


Further Illustrations:


I thought it’d be helpful to use a different tool to visualise what a good attack, Rotherham’s, looks like against a bad attack, Northampton’s. This is league-best vs league-worst. I’ve created a Shot Dashboard with the Strata dataset which displays the shot location, player, body part, and outcome of every chance recorded by every team in the division and we can filiter it by team to gain further insight.

First, Rotherham:League One Shots Dashboard

I’ve highlighted all the shots in the penalty area in between the width of the posts, christened “The Danger Zone” as this is the most dangerous position to take shots from – Rotherham have had 75 Danger Zone shots.

And now, Northampton:League One Shots Dashboard (1)

Northampton’s danger zone is clearly more sparse having taken a meagre 35 shots from this same area – less than half of what Rotherham have managed.

One final quirk I wanted to mention. As I’m going to make the Dashboard available for public use, I thought it’d be useful to include an example of what you can look at and the interesting discoveries and quirks that can be made when you have a play around with it by filtering by Team, Player, or Outcome of the chance. Below I’ve filtered it to show only Blackpool’s shots, and further filtered it to show only their goals.

This is Blackpool’s goals this season.

League One Shots Dashboard (1)

They are the only team in the league to have scored more goals from outside the box than inside. I’d be very surprised if there’s another team in the country to have done this by this stage of the season.

If you want to look at this yourself, you can view the Dashboard here. You can filter the map by Team, Player, the Body Part used to take the shot with, and the Outcome of the chance.

Also, if you want to look more closely at the graphs used in this piece, you can do so by clicking on this link.

I think that takes care of business on what we can look at in League One from a team perspective, if you enjoyed this then keep your eyes peeled for an upcoming Player Analysis piece. I’m always happy to engage in further discussion so if you’ve any questions/thoughts/criticisms about anything you’ve read, please do feel free to contact me either on Twitter (@olivermpw_) or by leaving a comment on here and I’ll get back to you. Thanks for reading.

This article was written with the aid of StrataData, which is property of Stratagem Technologies. StrataData powers the StrataBet Sports Trading Platform, in addition to StrataBet Premium Recommendations.

Quantifying Luton’s Attacking and Defensive Performance (so far)


“Never too high, never too low.” – a line that will be fondly familiar to Luton fans, often preached by John Still during his spell at the Luton helm. 8 games in to #OperationPissTheLeague this 17/18 season, we’ve already experienced the highs of an 8-2 victory,  the Marek Stech injury-time penalty save at Mansfield to rescue a point, and the 98th minute winner at Wycombe. Alongside that, we’ve also endured the lows of conceding an injury-time winner to Barnet (as well as the overall performance that day) and being down to 10 men after half an hour against Swindon who promptly played us off the park for the remaining 60 minutes. Those moments thrown together and added to the results so far (currently sitting 4th in League Two on 14 points) and the general feeling among fans seems to be one of  hitting-but-not-exceeding expectations. It could be worse, it could be better. The best is, hopefully, yet to come.

The purpose of this piece is to apply a bit of analysis to the season and get under the hood of the performances Luton have been putting in. Hopefully you’ll have read my previous two posts on this blog and will therefore have a feel for what’s coming up in this piece in terms of the analytical concepts I’ll be applying to Luton based on the data I’ve been collecting this season. If you’re familiar with Expected Goals then feel free to skip the next paragraph and move on to the main course. If not, then allow me to quickly explain the concept:

Expected Goals is simply a method used to quantify the quality of chances created and conceded by a team throughout a game. It is calculated by taking a shot and looking at historical data (collected by companies such as my employer, Stratagem) to calculate the conversion percentage of shots from the past that had the same characteristics as the new shot. The basic theory is that 1) the closer the shot is to goal, the more likely it’ll go in, 2) a shot from a central location is more dangerous than a shot from a wide location, and 3) shots with feet are more dangerous than headers from the same distance. As an example, imagine Harry Kane has a header on goal from just outside the 6 yard box following a cross from Danny Rose. You’d look back at all headers from just outside the 6 yard box following a cross, to find it has a conversion percentage of 15%*. This would give Harry Kane’s header an Expected Goal value of 0.15. If you’d like to read more about why Expected Goals is useful information for teams and players, I recommend giving this by @OneShortCorner a read as it explains in simple terms what xG’s useful for and how to interpret it.

*I pulled this number out of thin air.

On we go…


The Team


Part 1: Expected Goals and Expected Points




In the first section of this piece, I want to talk about the 8 matches Luton have played so far and the underlying performances the team has been putting in. What we have here is a table of Luton’s results so far. The bold, black number represents the goals scored by each side in the match, but the number I hope to be of most interest is the one underneath in orange, italic font. These represent the Expected Goal (xG) scores by each side in each game, as per my data (I’ve already written about the 8-2 Yeovil game here).

These numbers can help to tell you a little story about what happened in each match, and draw some early conclusions prior to doing more detailed analysis. For example, the Barnet game was very nearly a non-event, Colchester at home we were comfortable and deserved winners, and Lincoln was probably a fair draw. I don’t really want to go too much into these though as, rather than looking at individual match performance, I’d rather look at the overall performance over the opening 8 games as I think there’s more insight to be gained by doing so.

We’ll come onto that shortly, but first I want to establish another metric which was touched on briefly in the “8-2 Yeovil” piece –  Expected Points. Expected Points will tell us how many points Luton deserved to pick up from each match based on the chances created by both sides and is another good way of using xG values to illustrate whether Luton’s results have been in line with performances or have they been getting lucky/unlucky with their results so far. Expected Points are calculated by simulating the shots taken by each side in a game thousands of times, leaving us with the percentage of times we could expect a team to win, lose, or draw a particular match based on the xG scores by each side. I’ll use the example you’ll have seen before to recap – the Yeovil match where the xG scores were Luton 3.07, Yeovil 1.48. We include Yeovil’s penalty (xG value of .78) in the simulation even though you’ll notice it is listed as “+1pen” in the match table – I’ll explain why this is later – in this instance it’s included as it was a shot that contributed towards Yeovil’s likelihood of scoring during the game and therefore impacted Yeovil’s chances of gaining a result.

The results from those simulations were as follows:

Luton Win (74.72%),  Draw (15.77%), Yeovil (9.51%)

We calculate Luton’s Expected Points from the game simply by multiplying Luton’s win percentage by 3 (the amount of points Luton would receive for winning the game) and multiplying Luton’s draw percentage by 1 (the amount of points Luton would receive for drawing the game) and add the two together, as follows:

(0.7472*3)+(0.1577*1) = 2.4

So, Luton gain an Expected Points score of 2.4 for the match. This doesn’t tell us that much on its own, but over the course of a season and a period of games this will have more value, as we can use it to see whether Luton have been getting the results their performances deserved, as mentioned before. This piece is all about the season so far so let’s take a look at the Expected Points scores for the other matches:

xP Table

I appreciate this is boringly similar to the xG table above but I don’t feel the individual numbers are that important. I want to instead look at how Expected Points compare with the Actual Points gained so far and see where we’re at:

Actual Points (8 games): 14

Expected Points (8 games): 13.36

So, a near-perfect hit which, in simple terms, means we’ve pretty much gotten what we’ve deserved for the performances we’ve put in. The slight exception is the Barnet game, where there is definitely an argument to be had that we were unlucky to lose the game (though an equally strong argument that we didn’t deserve to win the game!) so no one had any complaints when Barnet’s Jack Taylor had the temerity to rudely awake everyone from their afternoon nap by curling home inside the far post from 20 yards for a 92nd minute winner.

This is actually a great case for why we track Expected Points though – this stuff *should* even itself out over the season. For every match we lose where we “deserved” at least a point, there’ll be a match we win where we could consider ourselves a little fortunate to do so.

Part 2: Under The Hood Performances


Let’s get more stuck in to the numbers that power the observations made so far – Luton’s Expected Goals totals. Here are three tables:

-First, the sum total of all of Luton’s Expected Goals and the sum total of Luton’s Opponents Expected goals, not including penalties.**

xG Total


-Second, the Expected Goals totals averaged over 8 games.

xG Per Game


-Third, the total number of shots, shots on target (SOT) and the average xG value per shot as recorded in my dataset.

xG Shot Stats


Conclusions: These are pretty good. It’s only 8 games (very small sample) but, as a team that’s harbouring promotion ambitions, it goes without saying that you want to see your team creating better quality chances more often than your opponents and that’s exactly what Luton have done so far. This is displayed by the superior difference in xG totals so far, but also in the xG per Shot statistic. It’s fairly self explanatory but, for clarity, it’s the average xG value of the shots taken by Luton and their opponents calculated by dividing the xG Sum Total by the Total number of shots. This is another feather in Luton’s cap as what it tells us is that Luton are taking a good quality of shot when they do decide to pull the trigger, whilst limiting their opponents to taking shots of lesser quality.

I quite like the metaphor Ted Knutson used in his piece on Brentford’s start to the season when he compared a team’s xG per shot to rolling a die. Looking at it in this way, Luton are rolling an ~8 sided die every time they shoot, whereas they’re currently forcing their opponents to roll an ~11 sided die. This is to their advantage and is even more favourable when we can see that Luton are also shooting/rolling that 8-sided die more often than their opposition are shooting/rolling their 11-sided die in their games so far. Given we’ve also had a tough schedule with away games at Mansfield, Lincoln, and Wycombe, games where even the most optimistic fan would probably not expect Luton to dominate in shot quality and quantity, then this is not bad at all. So early signs are encouraging and it’ll be interesting to see how these averages hold out over a larger sample size and a few more games- certainly if we are to maintain these standards throughout the season, we should go close but my gut feeling suggests these numbers may need improving on slightly at both the attacking and defensive ends of the pitch if we’re to really push on into league-winning form.

**The reason penalties are excluded from these totals is that creating quality chances and preventing your opponents from creating quality chances is a repeatable skill – whereas winning penalties is not. And that’s ultimately what we’re trying to track here, a gauge on how Luton are likely to perform going forward based on things we know to be repeatable**


The Players


Town defender Jack Stacey

Part 3: Player xG


It goes without saying that a team’s expected goals total is made up of each of it’s players own personal contribution to that total so that’s exactly what we’re going to look at next. Again I must stress that 8 games is a small sample size with very few players completing more than 5 games worth of minutes so far this season – these will be much more interesting and insightful once the dataset has beefed up a bit. I’ve filtered out players that have played less than 200 minutes so far this season from these lovely graphs below because it is absolutely, certainly too early to draw any kind of conclusions about them from a statistical point of view.

First up, let’s take a look at the sum totals for each of the players so far:


xG Totals


Let’s start with the obvious: Danny Hylton and James Collins have been getting on the end of Luton’s best chances overwhelmingly so compared to their team mates. It’s no big problem and if anything is quite intuitive to be relying on your strikers to be getting on the end of your best chances, so this is fine. What’s interesting is that Hylton’s played ~100 minutes less than Collins and is already ahead of his striking colleague in xG, but we’ll go into this more in a paragraph or two.

The 2nd thing that should be immediately obvious, to Luton fans at the very least, is the player nicely settled in at number 5 on this list and amongst Andy Shinnie, Olly Lee, Pelly-Ruddock Mpanzu and Luke Berry – players who are more-readily considered to be the supporting cast in an attacking sense. Yes, Dan Potts has so far contributed the 5th-highest amount to Luton’s xG total this season. This was something that I noticed when collecting this data after each match, that Potts was getting on the end of an unusually large amount of set pieces, certainly more than conventional wisdom would tell you he should be getting on – I can’t be the only one who, before the start of this season, wouldn’t have put Potts up there with the biggest threats from set pieces in the team. It’s credit to him though and definitely something to keep an eye on, though it must be stressed that nearly half of his current 0.88 xG total came from his goal against Colchester, by far the best chance he’s gotten on the end of to date. The rest of his chances certainly haven’t been as clear-cut but it’s undoubtedly a positive that he’s been posing any kind of threat in the opposition penalty area, especially from set pieces. Fingers crossed he can add to his goal tally before teams start marking him more tightly.

One of the problems with looking at xG totals is that it’s unfairly weighted towards players who have played more minutes – naturally they’ve had more time on the pitch to get more scoring opportunities. We want to see who’s contributing the most for their time on the pitch and we do this by adjusting the data into a “per 90 minutes” number i.e, what the players average contribution would be for every 90 minutes they spend on the pitch. It levels the playing field for those players who haven’t played as many minutes as some of their teammates. Feast your eyes:




Sadly Elliot Lee and his 1.3xG/90 miss out on this one on the basis he’s played a meagre 30 minutes of football this season (1 shot, 1 goal is a sterling contribution for half an hours play, though). Let’s concentrate on what we do have, and Hylton and Collins’ numbers continue to be encouraging. Hylton’s currently taken 12 shots from open play giving him an xG p/shot of 0.24. He’s essentially averaging a couple of 1-in-4 shots every game so far which is decent enough and should see him able to add to his current goal tally of 1 on a regular basis.

James Collins is the more interesting player for me to talk about right now though. He was considered to be a very good finisher before he came to Luton and has certainly added weight to that argument since he’s been here. However, 11 shots / 2.65xG / 0.38xGp90 doesn’t really scream 6 goals to me, which he has scored so far. We can look at the likelihood of Collins scoring 6 goals from the shots he’s taken using Danny Page‘s Longterm Expected Goals Simulator. See below:

James Collins

The Simulator believes Collins should more likely have scored 2 or 3 goals from the chances that have fallen to him so far, with it actually being slightly more likely that he would’ve scored 0 goals than 6! This is far from a criticism of Collins as it shows he’s finished his chances very well, but the point is that we cannot expect him to keep scoring at the same rate if his (perfectly good) xG/90 numbers continue as they are. As you’ll be tiring of hearing me say now, 8 games is a small sample and Collins is far from the first player to experience a hot run of finishing. To put it into context, if Collins continues to receive the chances he’s currently receiving at the same rate as he’s so far received them, then you’d be pretty confident that he could be getting 15-20 goals in a season which is exactly what you want from him. All is well.

Just for further illustration, I’ve giffed up a couple of his more impressive finishes that came from what my model terms to be low-quality chances: his hat-trick goal vs Yeovil and his beauty against Colchester.


giphygiphy (1)


Part 4: Player xA


The last section of this piece will focus on the creative forces of the side and for that I’ll need to introduce the Expected Assists (xA) metric. Every time a shot is recorded along with it’s Expected Goal value, I’ve been tracking the player making the assist (Primary Assist) and the player making the pass to the Primary assister (Secondary Assist), with each player credited a value for their part in creating the chance. Rather than just saying how many Key Passes (passes before the shot) each player has made, we’re assigning a quality value to each of these passes. In the same way not all shots are equal, not all shot assists are equal either. Now, as with the Expected Goals model, I can’t/won’t go into how exactly the values are credited to each of these players as it’s not dissimilar to the methods used at Stratagem, but let’s not let that get in the way of more data-driven insight! I present to you the xA totals:


xA Totals


Would you just look at that. TWO defenders in the top-two places, no less that THREE defenders in the top 4. Let’s start our analysis at the top of the pile.

Jack Stacey is a player I’m really growing to like and, with each passing performance, I’m becoming more and more convinced that he must run to and from matches like a young schoolboy – his engine hasn’t once seemed to be exhausted by his incessant patrolling of the right flank for 90 minutes every game. Incidentally, this fact hasn’t been lost on Luton fans and is providing one of the big talking points amongst the fan-base right now as we currently have a home-grown, England U20 international (an extremely rare commodity at League Two level) right-back also in the squad in the shape of James Justin. The fact that there is even a debate as to whether Justin should come back into the side when fit again shows how well Stacey has done – most fans, in particular Luton’s, want to see home-grown players in the starting XI and especially one whom the club did very well to keep hold of in the summer amid interest from higher up the English football pyramid. Stacey, however, must be giving Nathan Jones an almighty headache in this position. His attacking output has been excellent so far as he’s always offering an option on the right flank, particularly necessary because of Jones’ formation of choice – the narrow 4-4-2 diamond – and it’s showing up in the data that his final ball isn’t too bad either.

Alan Sheehan is another weapon in this team as his set-piece deliveries are up there with the best in this division (as mentioned earlier, Dan Potts has gobbled up a lot of those quality Sheehan deliveries from corners). And this is all from a centre-back. It’s fair to say that if he was 3 inches taller and had a higher top speed, he’d have had a much more sustained period at a higher level of football and would almost definitely still be playing there now and, despite his suggested physical limitations at this level (where coming across an extremely quick or extremely strong striker is an almost-weekly occurence), he is actually a fairly important cog in creating further goalscoring opportunities for a team that is posting pretty good defensive numbers as it is with him in it.

Again though, we know the totals are slightly slanted in Stacey and Sheehan’s favour as, collectively, they’ve missed a grand total of 0 minutes this season. Let’s look at the p90 numbers:




So there you go then, a level playing field and Stacey – the right back – is still our biggest creative contributor and shows how he is excelling in the demands placed on him in that right back position of the 4-4-2 diamond, with Andrew Shinnie the “tip” of that diamond and largely expected to be the largest creative force in the team, just behind him. In my opinion, it’s definitely a good sign that there’s no outstanding creator the team is reliant on, if one of these players was to get injured then their creative output shouldn’t be too sorely missed with it spread so widely amongst the team.

We’re nearing the end now but here’s one last graphic to sum up everything that’s been said above in the Player section:


Player xG_90 vs xA_90


There’s no new insight to gain here – players towards the top of the graph have been the greater creators so far, players towards the right of the graph have been the greater goal-threats so far, with the + marking you see embedded on the graph the average for both. So players above the line are above-average creators in the team, players to the right of the line are the above-average goal-threats. This is decent viewing at this stage, but will only becoming more valuable once the sample size has grown and players have played more minutes, drops or improvements in form have occured, and we can more confidently say that this is a players average contribution to the team.


Any readers who are in slight doubt of the use of expected goals and what it means – the video below should help reinforce the point that no chance is ever a 100%, nailed-on, my-gran-could-have-scored-that, certainty.  It makes sense to reward teams for creating chances that are as close to 100% in probability as possible even when the chance is missed, and that’s what Expected Goals does. I genuinely am grateful if you’ve made it this far and I’d be glad to listen to any feedback or questions you may have regarding anything you have read in this piece, even if you just want to open up a discussion about something you’ve read above, I’m all ears! Leave a comment or find me on twitter at @olivermpw_. Thanks for reading.





To calculate Expected Points, I’ve once again been using Danny Page‘s excellent Match Expected Goal Simulator.

A story of how Luton have already achieved 1/3rd of a Leicester this season.

Before we get started, I thought it’d be best to make absolutely sure that anyone reading is up to speed with the concepts mentioned previously and in this forthcoming piece of writing. I’m not sure the best use of the blog is to provide yet another explanation of Expected Goals (xG) and its uses; other people have already done so in a far more articulate and interesting way than I would manage. If you want to take 5 minutes just to increase your understanding, then I’d highly recommend OneShortCorner‘s set of posts that is essentially Football Analytics for Dummies, his 4th piece in the series being the one that covers xG. For a deeper dive into what xG actually tells us and how to interpret it, this piece by Danny Page (more from him later) is by far the best post I’ve read on explaining what an xG number actually means. Once you’re feeling comfortable with what we’re talking about here, please read on…

In my debut post on this blog, I spoke about the project I’ll be running this season; self-collecting xG numbers for every Luton Town league match this season. The plan is to write about the findings occasionally when I have an interesting idea or when there’s an interesting match to write about. It’s important to note now before we dig in to those collected numbers – if you were hoping to read a full methodology of how I collect my data and run my xG model, then I’m sorry to disappoint you but this is secret sauce. I’m collecting the data in a very similar way to how I would in my work for StrataBet so to reveal anything about how these numbers are produced would be infringing on what is really StrataBet’s intellectual property and the essence of their business. Needless to say, it will have to remain under wraps as I like my job there and would like to keep it.

Enough waffling, I present you the pièce de résistance of what this blog is for: the numbers. Luton have so far played two games in League Two – Yeovil (H) and Barnet (A). I was initially going to write about both matches in this piece, but the longer it went on the more obvious it became that I should be focusing squarely on the opening day match against Yeovil which you may or may not be aware finished in an 8-2 victory for Luton, a typically slow start to the season. Getting stuck in straight away, this is actually a perfect case study for what xG can be useful for – intuitively have you ever watched a game, including Luton vs Yeovil (if you haven’t, here’s the goals which are worth watching just for Alan McCormack’s thunderb*****d), and felt that the final score should’ve been 8-2? It goes without saying that this is a freak result, so based on the chances created by both sides, what would be the likelihood of that occurrence? To answer that question, we need to sum up all of the xG numbers for each individual chance from the game and it looks a little something like this:


xG Chart
It may surprise you to learn that I’m somewhat new to dataviz.

Note: Yeovil’s total includes a penalty, which accounts for 0.78 of their xG total as they get converted ~78% of the time. Their Open Play xG was 0.7.

Now we have the numbers, what can we use them to tell us? For that we need to refer back to Danny Page and his article mentioned at the beginning of this piece. In the article, he states:

 “In my opinion, Win Percentage would be the most reasonable determination if you’re tweeting out expected goal scores. If you’re including a picture in your report, graphing the goal difference will show the variance in possible results, and allows you to display the probability of each result.”

Sound advice indeed, so using his Match Expected Goals Simulator, we can show what the Result Percentage would’ve been for both sides, the Points Per Game both sides would typically win based on the game, the probabilities of each Goal Difference occurring, and the likelihood of each side scoring a certain number of goals.


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Team A = Luton(Red) . Team B = Yeovil(Blue)

Some explanation:

Result Percentage is calculated from simulating the game 10,000 times, with each result grouped together and then expressed as a percentage. Luton won 74.72% of the sims.

Points Per Game is calculated by multiplying the Win Percentage by 3 (the points available for a win), multiplying the Draw Percentage by 1 (the points available for a draw) and adding them together.

(Win % * 3) + (Draw %) = PPG

In this case, (3*0.7472) + 0.1577 = 2.399

This is something I’ll be keeping track of throughout the season, and plan to chart Luton’s actual points won against their expected Points further into the season to gauge whether they’ve been picking up the results they “should” have.

-Goals Scored. Ideally you’d be able to see the exact percentages for each unit, because then you’d be able to see that there was just a 0.17% chance that Luton would score 8 goals, based on the chances they created. The best way to articulate why it was so unlikely is to watch the goals and look at Olly Lee’s goal (00:16), Alan McCormack’s goal (00:35), and James Collins’ hat-trick goal (01:38). Pause the game just as they’re taking the shot, and think of how many times you’d estimate a shot from those positions would result in a goal? Would it be 1 in 5? 1 in 10? 1 in 20? As it happens, in this instance Luton scored 3 goals from these chances as a result of some excellent finishing. xG doesn’t measure finishing skill however, it measures Chance Creation and based on those chances it is extremely unlikely that Luton should have scored 3 times from them which obviously contributes to the low probability that Luton would, in fact, score 8.

Goal Difference quite clearly shows a lot of colour for “-minus” goal differences, i.e Luton wins. For me, I think the main takeaway is that there was a 51.11% chance Luton would win by 2 goals or more, a better-than-coinflip chance.

If you’ve made it this far, hopefully your patience will be rewarded because I think the most exciting takeaway is yet to come. Thanks to the above Goals Scored feature on Danny Page’s Expected Goals Simulator, we now have percentage probabilities for the likelihood that Yeovil would score exactly 2 goals, and for the likelihood that Luton would score exactly 8 goals.

So what?

So we can calculate what the chances are the game would’ve finished as an 8-2 win for Luton!

The % chance of Yeovil scoring exactly 2 goals was 37.49%

The % chance of Luton scoring exactly 8 goals was 0.17%

Multiply these two together would give you a 0.064% chance of the match finishing 8-2 or a 1569/1 shot (or just under 1/3rd of a Leicester).

Thanks for reading and constructive feedback is definitely welcome – feel free to hit me up on Twitter or in the comments.

Introduction to: Luton Town FC & Advanced Stats

I must be the 30,00th person to add their voice to the football blogging rat race, but the aim of this endeavour is to hopefully provide something different to what is currently out there. A quick story to help illustrate what to expect from this page and the motivation behind starting it…

In my current job role at StrataBet, I watch matches from a variety of leagues worldwide and collect data for their database, most of which revolves around the chances created by each team. This data is used to generate ratings for each league StrataBet covers and to inform trading decisions.

Using these skills, I’m going to be collecting similar data on all matches played this season by my supported team, Luton Town, and will be posting statistical insights drawn from this data for both teams in each match. This is a personal project and is not affiliated with StrataBet so it is not to be seen as official content from them – I’ve wanted to see more depth to the data available for League Two and Luton for a while now rather than just shot or shot on target numbers so this is merely something to bridge that gap, posting content that I would want to see from other sources if it were possible.

Statistical insight you say?…

Yep, so if you’re reading and you’re not too familiar with the current in-vogue metrics, then you might want to buff up on Expected Goals (xG) and Expected Assists (xA), one of which made its debut on Match of the Day this weekend. With each future post on here I’ll provide in-depth explanations of any metric or idea used with the data, but to briefly explain: Expected Goals is a measurement of Chance Quality, Expected Assists is a measurement of Creation Quality. Using this data should provide reasonable insight into how Luton have done against their League Two opponents and which players have been particularly good (or bad) contributors to that, in an attacking sense.

Right now I’m not too sure how often content will come out, and whether it will be in tweet or blog form. I have a couple of ideas of what to produce with the data once the season is a few matches old and there is some depth to the data so keep your eyes peeled on here and on my Twitter account for any announcements (strong word) about upcoming posts.

Thanks for reading and fingers crossed I’ll see you here again next time…